# document

id: 41b7a493289b275a8d6cf08a8080c197
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 7742
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"mean precipitation amount (medium confidence). It is very likely that \r\nrainfall variability related to the El Nino-Southern Oscillation will be \r\namplified by the end of the 21st century. Sub-seasonal precipitation \r\nvariability is also projected to increase, with fewer rainy days but \r\nincreased daily mean precipitation intensity over many land regions \r\n(high confidence). Precipitation extremes will increase in almost all \r\nregions (high confidence), even where seasonal mean precipitation is \r\nprojected to decrease (medium confidence). There is high confidence\r\nthat heavy precipitation events associated with both tropical and \r\nextratropical cyclones will intensify. {4.5.1.4, 4.5.3.2, 8.2.3.2, 8.4.1, \r\n8.4.2, 8.5.2, 11.7.1.5}"


id: d4c94644662c832f66bcbdf0722982d
created_at: 2023-03-16 14:00:45
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vector_id: 31006
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"Southern Hemisphere storm tracks and associated precipitation \r\nhave shifted polewards since the 1970s, especially in the austral \r\nsummer and autumn (high confidence). It is very likely that these \r\nchanges are associated with a positive trend in the Southern Annular \r\nMode, related to both stratospheric ozone depletion and greenhouse \r\ngas increases. There is medium confidence that the recent observed \r\nexpansion of the Hadley circulation was caused by greenhouse gas \r\nforcing, especially in the Southern Hemisphere, but there is only low \r\nconfidence in how it influences the drying of subtropical land areas. \r\n{8.2.2, 8.3.2, 3.3.3}"


id: 7080c1276cc1b085f3765a623bb90231
created_at: 2023-03-16 14:00:45
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"There are contrasting projections in monsoon precipitation, \r\nwith increases in more regions than decreases (medium \r\nconfidence). Summer monsoon precipitation is projected to increase \r\nfor the South, South East and East Asian monsoon domains, while \r\nNorth American monsoon precipitation is projected to decrease \r\n(medium confidence). West African monsoon precipitation is \r\nprojected to increase over the Central Sahel and decrease over the \r\nfar western Sahel (medium confidence). There is low confidence in \r\nprojected precipitation changes in the South American and Australian \r\nmonsoons (for both magnitude and sign). There is high confidence\r\nthat the monsoon season will be delayed in North and South \r\nAmerica and medium confidence that it will be delayed in the Sahel. \r\n{8.2.2, 8.4.2.4}"


id: c7502871359638c4f900935a8b0c6883
created_at: 2023-03-16 14:00:45
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content_type: text
index: climate_gpt_only_giec
vector_id: 28948
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"Precipitation associated with extratropical storms and \r\natmospheric rivers will increase in the future in most regions \r\n(high confidence). A  continued poleward shift of storm tracks in \r\nthe Southern Hemisphere (likely) and the North Pacific (medium \r\nconfidence) will lead to similar shifts in annual or seasonal \r\nprecipitation. There is low confidence in projections of blocking and \r\nstationary waves and therefore their influence on precipitation for \r\nalmost all regions. {8.4.2}"


id: ca34705d958afab74b817a0d114729ed
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 29370
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"The seasonality of precipitation, water availability and \r\nstreamflow will increase with global warming over the \r\nAmazon (medium confidence) and in the subtropics, especially \r\nin the Mediterranean and southern Africa (high confidence).\r\nThe annual contrast between the wettest and driest month of the \r\nyear is likely to increase by 3-5% per 1degC in most monsoon regions \r\nin terms of precipitation, precipitation minus evaporation, and runoff \r\n(medium confidence). There is high confidence in an earlier onset in \r\nspring snowmelt, with higher peak flows at the expense of summer \r\nflows in snow-dominated regions globally, but medium confidence\r\nthat reduced snow volume in lower-latitude regions will reduce \r\nrunoff from snowmelt. {8.2.2, Box 8.2, 8.4.1.7, 8.4.2.4}"


id: fac1e372b4b41ac4fd8cd0a9893721fa
created_at: 2023-03-16 14:00:45
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vector_id: 36972
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"Increased evapotranspiration due to growing atmospheric \r\nwater demand will decrease soil moisture over the \r\nMediterranean, south-western North America, southern Africa, \r\nsouth-western South America, and south-western Australia \r\n(high confidence). In the Mediterranean, south-western South \r\nAmerica, and western North America, future aridification will far \r\nexceed the magnitude of change seen in the last millennium (high \r\nconfidence). Some tropical regions are also projected to experience \r\nincreased aridity, including the Amazon basin and Central America \r\n(high confidence). {8.4.1}"


id: 1ef7dc57f6c33776a2401b842dd3422c
created_at: 2023-03-16 14:00:45
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vector_id: 2311
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"Water cycle variability and extremes are projected to increase \r\nfaster than average changes in most regions of the world and \r\nunder all emissions scenarios (high confidence). In the tropics \r\nand in the extratropics of both hemispheres during summer/warm \r\nseason, interannual variability of precipitation and runoff over land \r\nis projected to increase at a  faster rate than changes in seasonal "


id: 1d30eee5442174c3b6fbdb4e3d6a9e22
created_at: 2023-03-16 14:00:45
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"Representation of key physical processes has improved in \r\nglobal climate models, but they are still limited in their ability \r\nto simulate all aspects of the present-day water cycle and to \r\nagree on future changes (high confidence). Climate change \r\nstudies benefit from sampling the full distribution of model "


id: 6ce79e64553ecf07e40e6fc08b03e374
created_at: 2023-03-16 14:00:45
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"(SRM) techniques are implemented rapidly or terminated abruptly. \r\nThe impact of SRM is spatially heterogeneous (high confidence), will \r\nnot fully mitigate the greenhouse gas-forced water cycle changes \r\n(medium confidence), and can affect different regions in potentially \r\ndisruptive ways (low confidence). {8.6.3}"


id: 4e1396d32185ca078a954b19e627a42c
created_at: 2023-03-16 14:00:45
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"outputs when considering future projections at regional \r\nscales. Increasing horizontal resolution in global climate models \r\nimproves the representation of small-scale features and the statistics \r\nof daily precipitation (high confidence). High-resolution climate and \r\nhydrological models provide a better representation of land surfaces, \r\nincluding topography, vegetation and land-use change, which \r\nimprove the accuracy of simulations of regional changes in the water \r\ncycle (high confidence). There is high confidence in the potential \r\nadded value of regional climate models but only medium confidence\r\nthat this potential is currently realized. {8.5.1}"


id: b8c08d508863e16fb692f0824316dd26
created_at: 2023-03-16 14:00:45
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vector_id: 26589
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"Natural climate variability will continue to be a major source of \r\nuncertainty in near-term (2021-2040) water cycle projections \r\n(high confidence). Decadal predictions of water cycle  changes \r\nshould be considered with low confidence in most land areas \r\nbecause the internal variability of precipitation is difficult to predict \r\nand can offset or amplify the forced water cycle response. Water \r\ncycle changes that have already emerged from natural variability \r\nwill become more pronounced in the near term, but the occurrence \r\nof volcanic eruptions (either single large events or clustered smaller \r\nones) can alter the water cycle for several years, decreasing global \r\nmean land precipitation and altering monsoon circulation (high \r\nconfidence). {8.5.2, Cross-Chapter Box 4.1}"


id: 14423f00bbc9e80e4d2d6307cf54df72
created_at: 2023-03-16 14:00:45
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"Continued global warming will further amplify greenhouse \r\ngas-induced changes in large-scale atmospheric circulation \r\nand precipitation patterns (high confidence), but in some \r\ncases regional water cycle changes are not linearly related to \r\nglobal warming. Non-linear water cycle responses are explained by \r\nthe interaction of multiple drivers, feedbacks and time scales (high \r\nconfidence). Non-linear responses of regional runoff, groundwater \r\nrecharge and water scarcity highlight the limitations of simple \r\npattern-scaling techniques (medium confidence). Water resources fed \r\nby melting glaciers are particularly exposed to non-linear responses \r\n(high confidence). {8.5.3}"


id: 538a7ca11259b995d6e370b70611e959
created_at: 2023-03-16 14:00:45
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content:
"Solar radiation modification could drive abrupt changes in \r\nthe water cycle (high confidence). It is very likely that abrupt \r\nwater cycle changes will occur if solar radiation modification "


id: 502c204fcef96301027b16c682fb7c1
created_at: 2023-03-16 14:00:45
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vector_id: 10052
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"and the extraction of unconventional fossil fuels (Schewe et al., 2014; \r\nD'Odorico et al., 2018; Djehdian et al., 2019). These dependencies \r\nhave resulted in increasing competition for water between the food \r\nand energy sectors. Pressures on this 'food-energy-water nexus' are \r\nfurther compounded by increasing globalization, which can transfer \r\nlarge-scale water demands to other regions of the world, raising \r\nserious concerns about local food and water security in regions that \r\nare highly dependent on agricultural exports or imports (D'Odorico \r\net al., 2018)."


id: 7367c9a2a235cc3d82331f00eb316677
created_at: 2023-03-16 14:00:45
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content:
"Currently, around four billion people live under conditions of severe \r\nfreshwater scarcity for at least one month of the year, with half \r\na  billion people in the world facing severe water scarcity all year \r\nround (Mekonnen and Hoekstra, 2016). The AR5 WGII reported that \r\napproximately 80% of the world's population already suffers from \r\nhigh levels of threat to water security (Jimenez Cisneros et al., 2014). \r\nGiven the vulnerability of the planet's freshwater resources and the \r\nrole of climate change in intensifying adverse impacts on human \r\nsocieties and ecosystems (Hoegh-Guldberg et al., 2018; IPCC, 2018), \r\nthis chapter evaluates advances in the theoretical, observational and \r\nmodel based understanding of the global water cycle made since AR5 \r\n(IPCC, 2013) and AR6 Special Reports."


id: e71be16055a0d174fa64d452c836ca34
created_at: 2023-03-16 14:00:45
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"Water scarcity occurs when there are insufficient freshwater resources \r\nto meet water demands, although water problems may also arise \r\nfrom water quality issues or from economic and institutional barriers \r\n(AR6 WGII Chapter 4). This affects the preservation of environmental \r\nflows that ultimately influence ecosystem functioning and services \r\n(Schewe et al., 2014; Mekonnen and Hoekstra, 2016; Djehdian \r\net al., 2019). As such, water availability is a  major constraint on \r\nhuman society's ability to meet the future food and energy needs of \r\na growing population (D'Odorico et al., 2018). Water plays a key role \r\nin the production of energy, including hydro-electricity, bioenergy, "


id: bc205e922fcdcecfd61822d08eb86aed
created_at: 2023-03-16 14:00:45
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"As shown in Figure  8.1, the global water cycle is the continuous, \r\nnaturally occurring movement of water through the climate system \r\nfrom its liquid, solid and gaseous forms among reservoirs of the \r\nocean, atmosphere, cryosphere and land (Stocker et al., 2013). \r\nIn the atmosphere, water primarily occurs as a gas (water vapour), \r\nbut it is also present as ice and liquid water within clouds where \r\nit substantially affects Earth's energy balance (Sections  7.4.2.2 \r\nand 7.4.2.4). The water cycle primarily involves the evaporation1"


id: ba0a58ba47fc1588abee18f99c3b0629
created_at: 2023-03-16 14:00:45
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"and precipitation of moisture at the Earth's surface including \r\ntranspiration associated with biological processes. Water that falls on \r\nland as precipitation, supplying soil moisture, groundwater recharge, \r\nand river flows, was once evaporated from the ocean or sublimated \r\nfrom ice-covered regions before being transported through the \r\natmosphere as water vapour, or in some areas was generated over \r\nland through evapotranspiration (Gimeno et al., 2010; van der Ent \r\nand Savenije, 2013). In addition, the net flux of atmospheric and \r\ncontinental freshwater is a key driver of sea surface salinity, which in \r\nturn influences the density and circulation of the ocean (Chapter 9). "


id: b0365468fad890bf769f56596dcc477e
created_at: 2023-03-16 14:00:45
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"This section summarizes observed and projected water cycle changes \r\nreported in AR5 (IPCC, 2013) and in the recent IPCC Special Reports \r\non Global Warming of 1.5degC (SR1.5), the Ocean and Cryosphere in \r\na Changing Climate (SROCC), and Climate Change and Land (SRCCL). "


id: 28b173f259cdd2c8db0ef16d850516c4
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"This Report is the first IPCC assessment to include a chapter specifically \r\ndedicated to providing an integrated assessment of the global water \r\ncycle changes, by building on many chapters from previous reports. "


id: e024b91cc88d45c201db5b7bac35f81
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"medium confidence under the RCP8.5 scenario (Section 12.4.5.3). \r\nSoil moisture drying in the Mediterranean, south-west USA \r\nand southern African regions was considered likely, with high \r\nconfidence by the end of this century under the RCP8.5 scenario \r\n(Section  12.4.5.3). Projections for annual runoff included both \r\ndecreases and increases. Decreases in Northern Hemisphere snow \r\ncover were assessed as very likely with continued global warming \r\n(Section  12.4.6.2). As temperatures increase, snow accumulation \r\nwas projected to begin later in the year and melting to start earlier, \r\nwith related changes in snowmelt-driven river flows (FAQ 12.2 and \r\nSection 12.4.6.2 in AR5 WGI). In terms of the potential for abrupt \r\nchange in components of the water cycle, long-term droughts and \r\nmonsoonal circulation were identified as potentially undergoing \r\nrapid changes, but the assessment was reported with low \r\nconfidence (Sections 12.5.5.8.1 and 12.5.5.8.2, and Table 12.4)."


id: 2acbc816b68db6f567c93bbdef96151b
created_at: 2023-03-16 14:00:45
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"low-elevation snow cover is also projected to decrease, regardless \r\nof emissions scenario. Widespread permafrost thaw is projected to \r\ncontinue through this century and beyond. River runoff in snow- or \r\nglacier-fed basins is projected to increase in winter and to decrease in \r\nsummer (and in the annual mean) by 2100. In the oceans, the Atlantic \r\nMeridional Overturning Circulation (AMOC) will very likely weaken \r\nover the 21st century under all emissions scenarios (SROCC), with \r\npotential effects on atmospheric circulation and the water cycle at \r\nthe regional scale (see also Section 8.6)."


id: 84350322b2ef807247b9dfa3d10a1be2
created_at: 2023-03-16 14:00:45
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"The Special Report on the Ocean and Cryosphere in a  Changing \r\nClimate (SROCC) provides a comprehensive assessment of recent and \r\nprojected changes, specifically in snow and ice-covered areas that \r\nform a key component of the water cycle in high-elevation and high\u0002latitude areas. High mountain regions have experienced significant \r\nwarming since the early 20th century, resulting in reduced snowpack \r\non average (Marty et al., 2017), with glaciers retreating globally \r\nsince the mid-20th century (Marzeion et al., 2018; Zemp et al., 2019). \r\nGlacier shrinkage and snow cover changes have led to changes \r\n(both increases and decreases) in streamflow in many mountain \r\nregions in recent decades (Milner et al., 2017). Permafrost regions \r\nhave undergone degradation and ground-ice loss due to recent \r\nwarming (Lu et al., 2017). Glacier mass loss is projected to continue \r\nthrough the 21st century under all scenarios. In high mountain areas, "


id: 248523a04546ac471954ee68421ad56f
created_at: 2023-03-16 14:00:45
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"This chapter assesses water cycle changes and considers climate \r\nchange from the perspective of its effects on water availability \r\n(including streamflow and soil moisture, snow mass and glaciers, \r\ngroundwater, wetlands and lakes) rather than only precipitation. \r\nThe chapter highlights the sensitivity of the water cycle to multiple \r\ndrivers and the complexity of its responses, depending on regions, \r\nseasons and time scales. Anthropogenic drivers include not only \r\nemissions of GHGs but also different species of aerosols, land and \r\nwater management practices. Emphasis is placed on assessing the \r\nfull range of projections, including 'low likelihood, high impact' \r\nclimate trajectories such as the potential for abrupt changes in the \r\nwater cycle."


id: 85580c5ae677b1469daa0cd7827d310b
created_at: 2023-03-16 14:00:45
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"high-impact scenarios are also assessed, especially the potential \r\nfor abrupt climate change (Section 8.6). Final remarks about future \r\nstudies on water cycle changes (Section 8.7) are also provided, and \r\nthe chapter addresses three frequently asked questions (FAQs) on the \r\nwater cycle's sensitivity to land use change (FAQ 8.1), the projected \r\noccurrence and severity of floods (FAQ 8.2) and droughts (FAQ 8.3) at \r\nthe global scale. This chapter outline is summarized with a schematic \r\n(Figure  8.2) which also provides a  quick guide to the main topics \r\naddressed across the different sections."


id: 7c23feef878114ed0888ac8c2bce5855
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"on regional water cycle changes can be found in Chapters 10 to 12 \r\nand in the Atlas. The reader is also referred to the interactive Atlas \r\nfor a  more detailed assessment of the range of model biases and \r\nresponses at the regional scale. Beyond WGI, water is also a major \r\ntopic for both adaptation and mitigation policies so has strong \r\nconnections with both WGII and WGIII. Assessment of hydrological \r\nimpacts at basin and catchment scales, including a broader discussion \r\non adaptation and vulnerability, potential threats to water security, \r\nsocietal responses, improving resilience in water systems and related \r\ncase studies is provided in WGII (Chapter 4)."


id: 1a0552451c2053907679a8a8206b6aa1
created_at: 2023-03-16 14:00:45
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"as the climate warms (Pendergrass and Hartmann, 2014b; Doll et al., \r\n2018). Future water availability is also determined by changes in \r\nevaporation, which is driven by a general increase in the atmospheric \r\nevaporative demand (Scheff and Frierson, 2014) and modulated by \r\nvegetation controls on evaporative losses (Milly and Dunne, 2016; \r\nLemordant et al., 2018; Vicente-Serrano et al., 2020). At regional \r\nscales, water cycle changes result from the interplay between \r\nmultiple potential drivers (CO2, aerosols, land use change and human \r\nwater use; Section 8.2.3). This section assesses advances in physical \r\nunderstanding of global to regional drivers of water cycle changes."


id: c102464f45d836963fd9beb1ccbd32d3
created_at: 2023-03-16 14:00:45
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"The Clausius-Clapeyron equation determines that low-altitude \r\nspecific humidity increases by about 7% degC-1 of warming, assuming \r\nthat relative humidity remains constant, which is approximately \r\ntrue at a  global scale but not necessarily valid regionally. It is \r\nvery likely that near surface specific humidity has increased since \r\nthe 1970s (Section  2.3.1) and total atmospheric water vapour \r\ncontent (precipitable water) is very likely to increase at close to \r\na thermodynamic rate on average globally with continued warming. \r\nDifferent radiative forcing mechanisms lead to some variation in \r\nthe global mean thermodynamic response by altering the relative "


id: bcba91a3efe12cc480f94cddd5433fce
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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"It is well understood that global precipitation and evaporation \r\nchanges are determined by Earth's energy balance (Section 8.2.1). \r\nAt regional scales smaller than about 4000 km, water cycle changes \r\nbecome dominated by the transport of moisture (Dagan et al., \r\n2019a; Jakob et al., 2019; Dagan and Stier, 2020), which depend \r\non both thermodynamic and dynamical processes (Section  8.2.2). \r\nThe constraints of energy budgets at global scales and moisture \r\nbudgets at regional scales cause key water cycle characteristics \r\nsuch as precipitation intensity, duration and intermittence to alter "


id: e4f84b1379f1931a46e189e2e2900a25
created_at: 2023-03-16 14:00:45
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"humidity distribution: the rate of global precipitable water increase \r\nwith global surface temperature ranges2 from 6.4 +- 1.5% degC-1 for \r\nsulphate aerosol-induced changes to 9.8 +-  3.3%  degC-1 for black \r\ncarbon-induced changes based on idealized modelling (Hodnebrog \r\net al., 2019b). Specific humidity increases at a  lower rate over \r\nland due to decreasing relative humidity (Collins et al., 2013) \r\nas corroborated by observations and simple models (Byrne and \r\nO'Gorman, 2018). Prevalent increases in atmospheric water vapour \r\ndrive powerful amplifying feedbacks (Section  7.4.2.2), intensify \r\natmospheric moisture transport and heavy precipitation events \r\n(Section  8.2.3.2), and alter the surface and atmospheric energy \r\nbalance, thereby influencing global evaporation and precipitation \r\nchanges (Figure 8.3)."


id: ef67654542b4adbbdeed83a04af55567
created_at: 2023-03-16 14:00:45
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"controlled by thermal deepening of the troposphere (Jeevanjee and \r\nRomps, 2018) and limited by surface evaporation and consequent \r\natmospheric latent heat release and warming (Webb et al., 2018). \r\nClimate feedbacks (e.g., temperature lapse rate and clouds) that vary \r\nacross models (Sections 7.4 and 3.8.2) also modulate the magnitude \r\nof e (O'Gorman et al., 2012; Flaschner et al., 2016; T.B. Richardson \r\net al., 2018a). Uncertainty in e  across CMIP5 models relating to \r\ndeficiencies in representing low-altitude cloud feedbacks (Watanabe \r\net al., 2018) and absorption of shortwave radiation by atmospheric \r\nwater vapour (DeAngelis et al., 2015) do not apply well to CMIP6 \r\nsimulations, the latter improvement explained by more accurate \r\nradiative transfer modelling (Pendergrass, 2020b)."


id: f9e7fa750be4f336aa5d2fc1aa5943a2
created_at: 2023-03-16 14:00:45
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"Hydrological sensitivity (e) is defined as the linear change in \r\nglobal mean precipitation with global surface air temperature \r\n(GSAT) once rapid adjustments of the hydrological cycle to radiative \r\nforcings have occurred (Figure 8.3a). There is robust understanding \r\nand high agreement across idealized CO2 forcing CMIP5 and CMIP6 \r\nexperiments (Flaschner et al., 2016; Samset et al., 2018b; Pendergrass, \r\n2020b) that e  = 2.1-3.1%  degC-1 (Figure  8.4). The magnitude of \r\ne depends primarily on atmospheric net radiative cooling which is "


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vector_id: 17750
content:
"The fast and slow precipitation responses over global land combine \r\non average during transient climate change (Figure  8.3d). This \r\nexplains a  consistent land and ocean mean precipitation increase \r\nin projections (Table 4.3) but this is determined by a complex and \r\nmodel-dependent evolution of continental water cycle changes over \r\nspace and time."


id: 538ee6fde32b17921e58a25a6a0d3033
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 10614
content:
"Increases in global precipitation over time, as the climate warms, are \r\npartly offset by the overall cooling effects of anthropogenic aerosol \r\nand by rapid atmospheric adjustments to increases in GHGs and \r\nabsorbing aerosol. This explains why multi-decadal trends in global \r\nprecipitation responses in the satellite era (Adler et al., 2017; Allan \r\net al., 2020) are small and difficult to interpret given observational \r\nuncertainty, internal variability and volcanic forcings. The delayed \r\nwarming effect of rising CO2 concentration, combined with declining \r\naerosol cooling, are expected to increase the importance of the slow \r\ntemperature-related effects on the energy budget relative to the \r\nmore rapid direct radiative forcing effects as transient climate change \r\nprogresses (Shine et al., 2015; Salzmann, 2016; Myhre et al., 2018b). "


id: d2d057bf149fa4da3d9aed65eb27283e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 30687
content:
"A warming climate drives increases in atmospheric moisture and \r\nhorizontal moisture transport from the divergent to the convergent \r\nportions of the atmospheric circulation (including storm systems, \r\nthe tropical rain belt and monsoons) that on average amplifies \r\nexisting precipitation minus evaporation (P-E) patterns (Held and \r\nSoden, 2006). Increased latent heat transports in high latitudes \r\nalso contribute to polar amplification of warming (Section 7.4.4.1). \r\nAlthough convergent parts of the atmospheric circulation are \r\nexpected to become wetter (in terms of increasing P-E) and net \r\nevaporative regions drier (increasing E-P) these regions are not \r\ngeographically and seasonally fixed and their location and timing "


id: b9a43a098c9e95e0cfdb51aa81a9fedf
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 26747
content:
"layer adjustments and ocean heat uptake playing a  secondary \r\nrole, based on idealized modelling (Siler et al., 2019). Increased \r\nevaporation from warmer oceans and lakes is exacerbated by the \r\nloss of surface ice in some regions (Bintanja and Selten, 2014; Laine \r\net al., 2014; W. Wang et al., 2018; Sharma et al., 2019; Woolway \r\net al., 2020). This can generate a  more local moisture source for \r\nprecipitation, for example in north-west Greenland during non\u0002summer months since the 1980s (Nusbaumer et al., 2019), though \r\nmoisture transport changes can counteract this effect (Nygard \r\net al., 2020). Ocean stratification due to heating of the upper layers \r\nthrough radiative forcing has been identified as a mechanism that \r\nfurther amplifies surface salinity patterns beyond the responses \r\ndriven by water cycle changes alone (Zika et al., 2018). "


id: d9f914eef2fef16cc4e7743b0dceaeee
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 31816
content:
"are expected to alter (Section  8.2.2.2). Atmospheric and ocean \r\ncirculation changes overall decrease the amplification of P-E \r\nand salinity patterns. Paleoclimate evidence confirms that during \r\nthe LGM zonal mean changes were roughly in agreement with \r\nthermodynamic expectations (G. Li et al., 2013). However regional \r\nchanges can be dominated by dynamics, including responses to the \r\nlarge Northern Hemisphere (NH) ice sheets (DiNezio and Tierney, \r\n2013; T.  Bhattacharya et al., 2017; Scheff et al., 2017; D'Agostino \r\net al., 2019; Lowry and Morrill, 2019) such that altered P-E patterns \r\nare not well described by thermodynamic drivers (Oster et al., 2015; \r\nLora, 2018; Morrill et al., 2018)."


id: e04e118fb00ae6e333d06c84c83ec469
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 32787
content:
"The strong physical basis for regionally and seasonally dependent \r\nresponses of P-E and the expectation for an increasing contrast \r\nbetween wet and dry seasons and weather regimes is supported \r\nby high agreement across multiple observational and CMIP5/CMIP6 \r\nmodelling studies (Liu and Allan, 2013; Kumar et al., 2015; Polson \r\nand Hegerl, 2017; Ficklin et al., 2019; Deng et al., 2020; Schurer \r\net al., 2020). Increased moisture transports into storm systems, \r\nmonsoons and high latitudes increase the intensity of wet events \r\n(Section  8.2.3.2), while stronger atmospheric evaporative demand \r\nwith warming (Scheff and Frierson, 2014; Vicente-Serrano et al., \r\n2018; Cook et al., 2019) is an important mechanism for intensifying \r\ndry events (Section  8.2.3.3) and decreasing soil moisture over "


id: 99380093d98aebe4b37f34841ee0cae4
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 21619
content:
"There is robust evidence and high agreement across thermodynamics, \r\ndetailed modelling and observations that amplification of P-E \r\npatterns occurs over the oceans (Figure  8.5a) with an associated \r\n'fresh gets fresher, salty gets saltier' signature in ocean salinity \r\n(Sections  2.3.3.2 and 3.5.2). This amplification is moderated by \r\nproportionally larger increases in subtropical ocean evaporation \r\nand weakening of the tropical circulation (Section  8.2.2.2), an \r\nexpectation supported by observations (Skliris et al., 2016) and \r\nprocess understanding (Yang and Roderick, 2019). Thermodynamics \r\nexplain a smaller low latitude evaporation increase (1% degC-1) than in \r\nhigh latitudes (5% degC-1) with changes in surface radiation, boundary "


id: 484b31a7f9295eb085606b191d9c25b2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 8744
content:
"many subtropical land regions. However, aridification is modulated \r\nregionally by poleward migration of the subtropical dry zones and \r\nan increasing land-ocean temperature contrast that drives declining \r\nrelative humidity (Section 8.2.2.2)."


id: 87449a0fe47f76eeed3ba8fadbc7fd50
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 18818
content:
"To summarize, increased moisture transport from evaporative oceans \r\nto high precipitation regions of the atmospheric circulation will drive \r\namplified P-E and salinity patterns over the ocean (high confidence) \r\nwhile more complex regional changes are expected over land. \r\nGreater warming over land than ocean alters atmospheric circulation \r\npatterns and on average reduces continental near-surface relative \r\nhumidity which along with vegetation feedbacks can contribute to \r\nregional decreases in precipitation (high confidence). Based on an \r\nimproved understanding of thermodynamic drivers since AR5 and \r\nmultiple lines of evidence, there is high confidence that very wet or \r\ndry seasons and weather patterns will intensify in a warming climate \r\nsuch that wet spells become wetter and dry spells drier."


id: 625b20900064d20945280db2109a5df
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13036
content:
"Model simulations show a stronger Pacific Walker circulation during \r\nthe LGM in response to a cooler climate (consistent with an expected \r\nweakening in a warmer climate), but a weaker Indian Ocean east-\r\nwest circulation in response to the exposure of the Sunda and Sahul \r\nshelves due to lowered sea level (DiNezio et al., 2011). The latter \r\neffect is detectable in proxies for hydroclimate, as well as salinity and \r\nsea surface temperature (DiNezio and Tierney, 2013; DiNezio et al., \r\n2018). More relevant to future warming is the mid-Pliocene period \r\n(3 million years ago), the last time the Earth experienced CO2 levels \r\ncomparable to present (see Cross-Chapter Box  2.4). Sea surface \r\ntemperature (SST) reconstructions show a weakening of the Pacific \r\nzonal gradient and a  pattern of warmth consistent with a  weaker \r\nWalker cycle response (Corvec and Fletcher, 2017; Tierney et al., 2019; "


id: 2bfeaeb50d2bdaa0129c6fcf6c63343e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 4351
content:
"Responses of the large-scale atmospheric circulation to a  warming \r\nclimate are not as well understood as thermodynamic drivers \r\n(Shepherd, 2014). The AR5 identified robust features including \r\na  weakening and broadening of tropical circulation with poleward \r\nmovement of tropical dry zones and mid-latitude jets (Collins et al., "


id: 764e915b6c44a12c78f7ba2ca14a1280
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 16205
content:
"(Section 8.4.2.1) with limited evidence of distinct regional responses \r\nto GHG forcing including a northward shift over eastern Africa and the \r\nIndian Ocean and a southward shift in the eastern Pacific and Atlantic \r\noceans (Mamalakis et al., 2021). Paleoclimate evidence highlights the \r\ndistinct regional ITCZ responses to hemispheric asymmetry in volcanic \r\nand orbital forcing (McGee et al., 2014; Boos and Korty, 2016; Colose \r\net al., 2016; Denniston et al., 2016; PAGES Hydro2K Consortium, 2017; \r\nSingarayer et al., 2017; Atwood et al., 2020) and rapid (>1deg latitude \r\nover decades) shifts in the ITCZ and regional monsoons in response to \r\nAMOC collapse cannot be ruled out (Sections 8.6.1.1 and 5.1.3)."


id: 8627b967e1ffd4940c3da3f4a5a7e8da
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 18649
content:
"McClymont et al., 2020). Although the Pliocene SST pattern and wet \r\nsubtropics contrast with present conditions (Burls and Fedorov, \r\n2017), the paleoclimate record strengthens evidence that a warmer \r\nclimate is associated with a weaker Walker circulation (Cross-Chapter \r\nBox 2.4; Section 3.3.3)."


id: ddf91f538dcbe50f9f5a3afe4a5b0527
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 32423
content:
"Since AR5, weakening of the tropical circulation has been explained \r\nas a  rapid response to increasing CO2 concentrations and slower \r\nresponse to warming and evolving SST patterns (He and Soden, 2017; \r\nXia and Huang, 2017; Shaw and Tan, 2018; Chemke and Polvani, 2020). \r\nLarge-scale tropical circulation weakens by 3-4% in a rapid response \r\nto a quadrupling of CO2 concentrations (Plesca et al., 2018), which \r\nsuppresses tropospheric radiative cooling, particularly in subtropical \r\nocean subsidence regions (Bony et al., 2013; Merlis, 2015; Richardson \r\net al., 2016). The resulting increased atmospheric stability explains \r\nthe rapid weakening of the Walker circulation (Wills et al., 2017) \r\nand Northern Hemisphere Hadley Cell (Chemke and Polvani, 2020). \r\nSubsequent surface warming contributes up to a  12% slowing of \r\ncirculation for a uniform 4degC SST increase, driven by thermodynamic \r\ndecreases in temperature lapse rate (Plesca et al., 2018)."


id: 1da18d9c3459a80861ecd8945c7f6c85
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 2102
content:
"surface and subsurface, including cryosphere and biosphere \r\ninteractions and the direct impacts of human activities."


id: 5515b1f7c492dcc2d41e3f608ae61661
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 10847
content:
"weaker Northern Hemisphere expansion in response to GHG forcing \r\nis modulated by tropospheric ozone and aerosol forcing, particularly \r\nblack carbon (Davis et al., 2016; Grise et al., 2019; Watt-Meyer \r\net al., 2019; Zhao et al., 2020). However, internal variability is found \r\nto dominate observed responses in the NH, precluding attribution to \r\nradiative forcing (D'Agostino et al., 2020a). Paleoclimate evidence \r\nof poleward expansion and weakening of westerly winds in both \r\nhemispheres in the warmer Pliocene is linked to reduced equator-to\u0002pole thermal gradients and ice volume (Abell et al., 2021)."


id: 660796ab2b0f8ca96f80a9930d44a335
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13640
content:
"Reductions in snow, freshwater ice and permafrost affect terrestrial \r\nhydrology. Permafrost degradation reduces soil ice and alters the \r\nextent of thermokarst lake coverage (Section  9.5.2; M.  Meredith "


id: efc096da9bc0b6f70b0c0036911e0c4e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 35224
content:
"Processes operating at local scales are capable of substantially \r\nmodifying the regional water cycle. This section assesses the \r\ndevelopment in understanding of processes affecting the atmosphere, "


id: 46457e6f2e31b7689521e94125b40bcb
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 8443
content:
"et al., 2019). A lag between current climate change and permafrost \r\ndegradation is expected, given the slow response rates in frozen \r\nground and the fact that snow cover insulates soil from sensible heat \r\nexchanges with the air above (Hoegh-Guldberg et al., 2018; Garcia\u0002Garcia et al., 2019; Soong et al., 2020). Post-wildfire areas are also \r\nlinked with permafrost degradation in the Arctic based on satellite \r\nobservations (Yanagiya and Furuya, 2020). An increase in spring \r\nrainfall can increase heat advection by infiltration, exacerbating \r\npermafrost thaw and leading to increased methane emissions \r\n(Section  5.4.7; Neumann et al., 2019). Increased heat transport \r\nby Arctic rivers can also contribute to earlier sea ice melt (Park \r\net al., 2020)."


id: ff51f23059a03de87c31a45b38f62dc2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 37717
content:
"In summary, it is virtually certain that warming will cause a loss of \r\nfrozen water stores, except in areas where temperatures remain \r\nbelow 0degC for most of the year. There is high confidence that warming \r\nand reduced snow volume drives an earlier snowmelt, leading to \r\nseasonally dependent changes in streamflow. There is medium \r\nconfidence that weaker sunlight earlier in the season can reduce \r\nthe rate of snowmelt. Melting of snowpack or glaciers can increase \r\nstreamflow in high-latitude and high-altitude catchments until \r\nfrozen water reserves are depleted (high confidence). There is high \r\nconfidence that warm, moist airflows and associated precipitation \r\ndominate glacier mass balance in some regions (New Zealand, \r\nGreenland, Antarctica)."


id: aea8ba74db6d6428dc23454c35fc0426
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 25008
content:
"Since AR5, advances in understanding the expected changes in \r\nintense rainfall at the sub-daily time scale (Section 11.4, Figure 8.4) \r\nare provided by idealized or high resolution model experiments and \r\nobservations (Westra et al., 2014; Fowler et al., 2021). There is robust "


id: 84c3ec490eccda6bcd93cc872c6e513c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 18418
content:
"depends on the moisture-convergence regime (Welty et al., 2020). Only \r\nhigh-resolution convection-permitting models can capture the sub-grid \r\nscale mechanisms for convective initiation (C.M. Taylor et al., 2013; \r\nH. Moon et al., 2019). There is medium evidence that greater tropical \r\ncyclone rainfall totals can be caused by dynamical feedbacks (Chauvin \r\net al., 2017) and slower propagation speed as tropical circulation \r\nweakens (Kossin, 2018). These processes amplify the thermodynamic \r\nintensification of rainfall (Section 11.7.1.2), yet observational support \r\nis weak (Chan, 2019; Lanzante, 2019; I.J. Moon et al., 2019; Knutson \r\net al., 2020). Slower decay following landfall, explained by larger stores \r\nof heat and moisture at higher SSTs, can also amplify rainfall amount \r\nbased on observations and modelling (Li and Chakraborty, 2020). \r\nRainfall intensity from the outer rain bands of tropical cyclones is also \r\nincreased by aerosol-cloud interactions (Box 8.1)."


id: 71d7732bba98394fa7d765a8860ba319
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 15539
content:
"et al., 2018). More intense but less frequent storms (Kendon et al., \r\n2019) favour focused groundwater recharge through leakage from \r\nsurface waters (R.G. Taylor et al., 2013a; Cuthbert et al., 2019a) and \r\nrunoff and flash flooding where the percolation capacity of the soil is \r\nexceeded (Yin et al., 2018). "


id: 956dc6136904b58f15625092c34fded3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 21008
content:
"Increased severity of flooding on larger, more slowly-responding rivers \r\nis expected as precipitation accumulations increase during persistent \r\nwet events over a season. This can occur where atmospheric blocking \r\npatterns repeatedly steer extratropical cyclones across large river \r\ncatchments, as identified for NH mid-latitudes and Asia (Takahashi \r\net al., 2015; Pfleiderer et al., 2018; Zhou et al., 2018; Bloschl et al., \r\n2019; Lenggenhager et al., 2019; Nikumbh et al., 2019; Zanardo et al., \r\n2019), although groundwater flooding and antecedent conditions \r\nincluding soil moisture and snowmelt also play a  role (Muchan \r\net al., 2015; Berghuijs et al., 2019). Increased atmospheric moisture \r\namplifies the severity of these events when they occur in a warmer \r\nclimate, yet drivers of change in the occurrence of blocking patterns, \r\nstationary waves and jet stream position are not well understood \r\n(Section 8.2.2.2 and Cross-Chapter Box 10.1). "


id: 7e948aa1dcf82e6ce4d715158d54a48
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 17479
content:
"Vegetation is a crucial interface between subsurface water storage \r\n(in soil moisture and groundwater) and the atmosphere. Plants \r\nalter evapotranspiration and the surface energy balance, and \r\nthus can have a  large influence on regional aridity (Lemordant \r\net al., 2018). SRCCL concluded there is high confidence that higher \r\natmospheric CO2 increases the ratio of plant CO2 uptake to water \r\nloss (water-use efficiency; WUE) through the combined enhancement \r\nof photosynthesis and stomatal regulation (Section 5.4.1; De Kauwe \r\net al., 2013; C.D. Jones et al., 2013; Deryng et al., 2016; Swann et al., "


id: 8c49286f5e68fad9d5d71d9479bd6714
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 19579
content:
"2016; Cheng et al., 2017; Knauer et al., 2017; Peters et al., 2018; \r\nGuerrieri et al., 2019). Modelling studies suggest that increasing \r\nWUE can partly counteract water losses from increased evaporative \r\ndemand in a warmer atmosphere, potentially mitigating aridification \r\n(Milly and Dunne, 2016; Bonfils et al., 2017; Cook et al., 2018; Y. Yang \r\net al., 2018). However, observational studies suggest that this effect \r\nmay be counter-balanced by the increase in plant growth in response \r\nto elevated CO2, which results in increased water consumption \r\n(De Kauwe et al., 2013; Donohue et al., 2013; Ukkola et al., 2016b; "


id: 2d0652759a24e224e6d0192adcf0da94
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 4517
content:
"Figure 8.6 | Climatic drivers of drought, effects on water availability, and impacts. Plus and minus signs denote the direction of change that drivers have on factors \r\nsuch as snowpack, evapotranspiration, soil moisture, and water storage. The three main types of drought are listed, along with some possible environmental and socio-economic \r\nimpacts of drought (bottom). "


id: e1c487a438fd36ab0441e747100e776
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 33015
content:
"Yang et al., 2016; Guerrieri et al., 2019; Mankin et al., 2019; A. Singh \r\net al., 2020). In semi-arid regions, increased plant water consumption \r\ncan reduce streamflow and exacerbate aridification (Ukkola et al., \r\n2016b; Mankin et al., 2019; A.  Singh et al., 2020). Thus, there is \r\nlow confidence that increased WUE in plants can counterbalance \r\nincreased evaporative demand (Cross-Chapter Box 5.1)."


id: 78894d26c7444df591deabbe98938f9e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 16524
content:
"In summary, there is high confidence that a warming climate drives \r\nan increase in atmospheric evaporative demand, decreasing available \r\nsoil moisture. There is high confidence  that higher atmospheric \r\nCO2 increases plant water-use efficiency, but low confidence that \r\nthis physiological effect can counterbalance water losses. Since \r\ndrought can be defined in a number of ways, there are potentially \r\ndifferent responses under a warming climate depending on drought \r\ntype. Beyond a lack of precipitation, changes in evapotranspiration \r\nare critical components of drought, because these can lead to soil \r\nmoisture declines (high confidence). Under very dry soil conditions, \r\nevapotranspiration becomes restricted and plants experience water \r\nstress in response to increased atmospheric demand (medium \r\nconfidence). Human activities and decision-making have a  critical \r\nimpact on drought severity (high confidence)."


id: d5ee432f4794ff83420cf7c007dd916f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 31173
content:
"Drought severity also depends on human activities and decision\u0002making (AghaKouchak et al., 2015; Van Loon et al., 2016; Pendergrass "


id: e88d700014068b708b6cdad9381f38ab
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 34094
content:
"In summary, there is high confidence that land-use change and \r\nwater extraction for irrigation drive local, regional and remote \r\nresponses in the water cycle. Large-scale deforestation is likely to \r\ndecrease precipitation over the deforested regions but there is low \r\nconfidence in the effects of limited deforestation. There is medium \r\nconfidence that deforestation drives increased streamflow relative to \r\nthe responses caused by climate change. Urbanization can increase \r\nlocal precipitation (medium confidence) and resulting runoff intensity \r\n(high confidence). A warming climate combined with direct human \r\ndemand for water is expected to deplete groundwater resources in \r\ndry regions (high confidence)."


id: 5b282b6f36769bc1de24b7290f4faaf9
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 11850
content:
"Aerosols affect precipitation in two major pathways, by altering the shortwave and longwave radiation and influencing cloud \r\nmicrophysical properties."


id: 7224ae3be5acff06ea977fff759501f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 15586
content:
"Aerosols scatter and absorb solar radiation which reduces the energy available for surface evaporation and subsequent precipitation. \r\nIn addition, cooling is incurred by the radiation that is reflected back to space directly by the aerosols and indirectly by the aerosol \r\neffect on cloud brightening. Northern Hemisphere (NH) station data indicate decreasing precipitation trends during the 1950s to the \r\n1980s, which have since partially recovered (Wild, 2012; Bonfils et al., 2020). These changes are attributable with high confidence\r\nto anthropogenic aerosol emissions from North America and Europe causing dimming through reduced surface solar radiation. "


id: 4c99fce119085e862abb3fe252ad9738
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 9476
content:
"This peaked during the late-1970s and partially recovered thereafter following improved air quality regulations (Section  6.2.1; \r\nBox 8.1, Figure 1)."


id: e1d384865858eba95354127774430b56
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 33026
content:
"Absorption of solar radiation by anthropogenic aerosols such as black carbon warms the lower troposphere and increases moist \r\nstatic energy, but also results in larger convection inhibition that suppresses light rainfall (Box 8.1, Figure 2; Y. Wang et al., 2013). \r\nRelease of aerosol-induced instability, often triggered by topographical barriers, produces intense rainfall, flooding (Fan et al., 2015; "


id: f53e5368bc43ad526cf6f1f6d625295c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 36100
content:
"Lee et al., 2016) and severe convective storms (medium confidence) (Saide et al., 2015). In particular, aerosols induce intense convection \r\nat the Himalaya foothills during the pre-monsoon season, which generates a  regional convergence there (medium confidence).\r\nThis mechanism is termed the 'elevated heat pump hypothesis' (Lau and Kim, 2006; D'Errico et al., 2015)."


id: 7daab3310204c971dc5ebae75521526b
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 17346
content:
"(Abbott and Cronin, 2021). In addition, delaying rain initiation until greater altitudes are reached transports more cloud water above \r\nthe 0degC altitude and leads to additional release of latent heat of freezing and/or vapour deposition, which in combination with the \r\nadded latent heat of condensation enhances the cloud updrafts (Fan et al., 2018). The stronger updrafts invigorate mixed-phase \r\nprecipitation and the resultant hail and cloud electrification (Rosenfeld et al., 2008; Thornton et al., 2017). This includes the outer \r\nconvective rainbands of tropical cyclones. There is medium confidence that air pollution enhances flood hazard associated with the \r\nouter rain bands at the expense of the inner rain bands (Wang et al., 2014; C. Zhao et al., 2018; Souri et al., 2020)."


id: eb622fe0dc358193a715f886ab41991d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 34528
content:
"The aerosol effect on invigoration and rainfall from deep convective clouds peaks at moderate levels (aerosol optical depth of 0.2 to 0.3), \r\nbut reverses into suppression with more aerosols (H. Liu et al., 2019). More generally, the microphysical aerosol-related processes \r\noften compensate or buffer each other (Stevens and Feingold, 2009). For example, suppressed rain by slowing drop coalescence \r\nenhances mixed-phase precipitation. Therefore, despite the potentially large aerosol influence on the precipitation forming processes, \r\nthe net outcome of aerosol microphysical effects on precipitation amount has generally low confidence, especially when evaluated \r\nwith respect to the background of high natural variability in precipitation (Tao et al., 2012)."


id: 6cb22675f888fe757d93a53dd686048c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 14717
content:
"The human influence on the global water cycle is often summarized \r\nas an intensification (Huntington, 2006; DeAngelis et al., 2015; \r\nW. Zhang et al., 2019b) or an overall strengthening which has been \r\nobserved since at least 1980 (high confidence) (see Chapter 2). There \r\nis, however, no unique definition of the global water cycle intensity \r\n(Trenberth, 2011; Ficklin et al., 2019; Sprenger et al., 2019). One \r\nsimple metric is the global and annual mean amount of precipitation. \r\nAlthough an increase in global precipitation is consistent with \r\nphysical expectations (Section 8.2.1), it has not yet been detected and \r\nattributed to human activities given large observational uncertainties \r\nand low signal-to-noise ratio (Section  3.3.2.2). Other metrics are \r\nmore suitable to detect and attribute changes in the global water \r\ncycle, including the likely increase in global land precipitation since \r\n1950 (Section  2.3.1.4) which is likely due to a  human influence \r\n(Section 3.3.2.3)."


id: 135645829aabf90ca5614a72da589217
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 554
content:
"The flux of freshwater between the ocean and atmosphere is \r\ndetermined by the difference between precipitation and evaporation \r\n(P-E). Evaporation is measured in very few locations across the \r\nglobal ocean, so that directly assessing P-E over the ocean is very \r\nchallenging and relies on indirect reanalysis estimates (Robertson \r\net al., 2020). The AR5 presented robust evidence of an amplified\r\noceanic pattern in P-E since the 1960s from both regional and \r\nglobal surface and subsurface salinity measurements and reanalyses. "


id: 5738dd81b43da4b44aff5c5b5b5ade40
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 11210
content:
"This section provides a process-based evaluation and a comprehensive \r\nassessment of observed water cycle changes by integrating multiple \r\nlines of evidence including paleoclimate data, historical datasets, \r\ntheoretical understanding (Section 8.2) and model simulations."


id: e5c1d14da223d07d27bf206ce056472e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 33652
content:
"This  pattern is consistent with our theoretical understanding of \r\nhuman-induced changes in the water cycle, leading to the conclusion \r\nthat these changes are very likely the result of anthropogenic forcings \r\n(Section 9.2.2.2). "


id: a2639d183a17f8298a3f4fcc5daab53d
created_at: 2023-03-16 14:00:45
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vector_id: 23110
content:
"In contrast, AR5 did not provide a  conclusive assessment of \r\nobserved changes in P-E over land. Continental P-E estimated \r\nfrom reanalyses and data-driven land surface models indicate that \r\ninterannual variations are linked to ENSO (Robertson et al., 2014, \r\n2020). Increasing trends in P-E since 1979 based on land models are \r\nnot statistically significant. Observations and models show evidence \r\nthat P-E increases in the wet parts and decreases in the dry parts \r\nof tropical circulation systems, which shift in location seasonally \r\nand from year to year, with increases in seasonality since 1979 (see \r\nBox 8.2; Chou et al., 2013; Liu and Allan, 2013; Fu and Feng, 2014)."


id: d08ae9803b6a007ec358388591a6ba70
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 30335
content:
"In summary, a low signal-to-noise ratio, observational uncertainties \r\nand current data assimilation techniques limit the assessment of \r\nrecent global trends in P-E over both land and ocean. It is likely\r\nthat the global land P-E variations observed since the late 1970s \r\nwere dominated by internal variability, mostly linked to ENSO \r\nteleconnections (medium confidence). In contrast, the attribution of \r\nchanges in sea surface salinity (Section 3.5.2.2) suggests that it is \r\nextremely likely that human influence has contributed to the regional \r\nchanges in P-E observed over the global ocean since the mid\u000220th century."


id: 8645837f6cb8634c83c9268ca5097d6a
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 18667
content:
"The AR5 presented evidence of increases in global near-surface and \r\ntropospheric specific humidity since the 1970s but with medium \r\nconfidence of a  slowing of near-surface moistening trends over \r\nland associated with reduced relative humidity since the late 1990s. \r\nAccording to AR5, radiosonde, Global Positioning System (GPS) and \r\nsatellite observations of tropospheric water vapour indicate very likely\r\nincreases at near global scales since the 1970s occurring at a rate that \r\nis generally consistent with the Clausius-Clapeyron relation (about \r\n7%  degC-1 at low altitudes) and the observed atmospheric warming \r\n(Hartmann et al., 2013). "


id: 3d51cb6795ecc26d57a21d2132cb4830
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 7006
content:
"precipitation over wet tropical land areas (Gimeno et al., 2020) and to \r\nmore extreme and persistent wet and dry weather events (Konapala \r\net al., 2020) in many regions worldwide. "


id: 22d49c106683409e4d6acfe90475d0aa
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 2931
content:
"activities, but are consistent with the heating effect of increasing CO2\r\nlevels on the distribution of daily precipitation rates (Section 8.2.3.2) \r\nand with a  distinct overall intensification of heavy precipitation \r\nevents found in both observations and CMIP5 models, though with \r\nan underestimated magnitude (Fischer and Knutti, 2014). Beyond \r\namplified precipitation extremes (Section  11.4.2), CMIP5 models \r\nalso indicate that anthropogenic forcings have increased temporal \r\nvariability of annual precipitation amount over land from 1950 to \r\n2005, which is most pronounced in annual mean daily precipitation \r\nintensity (Konapala et al., 2017). "


id: ddfc990b94111e6788f31e3de527b3dc
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 32426
content:
"In summary, there is high confidence that human-caused global \r\nwarming has led to an overall increase in water vapour and moisture \r\ntransport throughout the troposphere, at least since the mid-1990s. \r\nIn particular, there is high confidence that moisture transport into the \r\nArctic has increased but only medium confidence in the attribution \r\nof such a trend to a human influence. There is medium confidence\r\nthat human influence has contributed to a decrease in near-surface \r\nrelative humidity over the Northern Hemisphere mid-latitude \r\ncontinents during summer (see also Sections 2.3.1.3 and 3.3.2.3)."


id: 6347c0dca57ca4a3ecbeeedeeba76353
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13188
content:
"Anthropogenic aerosols can alter precipitation intensities \r\nboth through radiative and microphysical effects (Box  8.1 and \r\nSection  8.5.1.1.2). Precipitation suppression through aerosol \r\nmicrophysical effects has been observed in shallow cloud regimes \r\nover South America and the south-eastern Atlantic, associated \r\nwith local biomass burning (Andreae et al., 2004; Costantino and \r\nBreon, 2010), and in industrial regions in Australia (Rosenfeld, \r\n2000; Hewson et al., 2013; Heinzeller et al., 2016). In contrast, \r\nprecipitation intensification through aerosol microphysical effects \r\nin deep convective clouds is seen in many regions such as the \r\nAmazon, southern USA, India, and Korea. This is associated with \r\nanthropogenic aerosols from cities (Hewson et al., 2013; Fan et al., \r\n2018; S.S. Lee et al., 2018; Sarangi et al., 2018)."


id: fe5e4256c5eb5c0aeff4d6ab10982a76
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 37557
content:
"This section assesses observed changes in precipitation at global \r\nand regional scales. Note that changes in precipitation seasonality \r\nare assessed in Box  8.2 and that changes in regional monsoons \r\nare assessed in section  8.3.2.4 where observed changes in both \r\ncirculation and rainfall are considered. Further assessment of regional \r\nchanges in precipitation is presented in Chapters 10, 12 and Atlas, \r\nwhile extreme precipitation is presented in Chapter 11."


id: b7b6cf5dcc4aa178fd2168b6e9f7ba4e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 26437
content:
"Over the African continent, there are distinct precipitation trends \r\nobserved in multiple datasets since the 1980s (Figure 8.7; Maidment \r\net al., 2015; P. Nguyen et al., 2018). Increases in intense convective \r\nstorms affecting the Sahel have been attributed to increased \r\nland-ocean temperature gradients (Taylor et al., 2017), enhanced \r\nby intense heating of the Sahara (Dong and Sutton, 2015) rather \r\nthan thermodynamics (Section  8.2.2). Changes in Sahel rainfall, \r\nwith reduced precipitation amounts from the 1960s to the 1980s \r\nand a  subsequent recovery, are assessed in Sections  8.3.2.4.3 \r\nand 10.4.2.1. In eastern Africa, decreasing precipitation amount \r\n(-2 to -7 % per decade for 1983-2010) was reported for the March \r\nto May 'long rains' season (Lyon and Dewitt, 2012; Viste et al., 2013; \r\nLiebmann et al., 2014; Maidment et al., 2015; Rowell et al., 2015) \r\nand evidence of a  recovery since, with internal variability playing "


id: 54e64408acebe8f8f14ec6e89b15ad30
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 10813
content:
"Global and regional changes in precipitation frequency and intensity \r\nhave been observed over recent decades. An analysis of 1875 rain \r\ngauge records worldwide over the period 1961-2018 indicates that \r\nthere has been a general increase in the probability of precipitation \r\nexceeding 50  mm  day-1, mostly due to an overall boost in rain \r\nintensity (Benestad et al., 2019). Such changes in precipitation \r\nintensity and frequency have not been formally attributed to human "


id: a34a49617af7d21449c2f108fb573f64
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 23255
content:
"a large role in these decadal changes (Wainwright et al., 2019). In \r\ncontrast, the second 'short rains' season in eastern Africa (October to \r\nDecember) does not exhibit significant precipitation trends (Rowell \r\net al., 2015). Increases in annual southern African rainfall of 6-7% \r\nper decade during 1983-2010 are linked with the Pacific Decadal \r\nOscillation (PDO; Maidment et al., 2015)."


id: 411f2e848ead36b527b27675ff8a19b1
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 7635
content:
"Section  8.3.1.6 assesses changes in precipitation over the \r\nMediterranean region and its connection with drought and aridity."


id: 19dda7e5456efb32117895a3ea5bd50
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 1538
content:
"Rainfall increases have been observed over northern Australia since \r\nthe 1950s, with most of the increases occurring in the north-west \r\n(Dey et al., 2019a, b; Dai, 2021) and decreases observed in the north\u0002east (J. Li et al., 2012) since the 1970s. In contrast, there has been \r\na  decline in rainfall over southern Australia related to changes in \r\nthe intensification and position of the subtropical ridge (CSIRO and \r\nBoM, 2015) and anthropogenic effects (Knutson and Zeng, 2018). \r\nThe drying trend over south-west Australia is most pronounced \r\nduring May to July, where rainfall has declined by 20% below the \r\n1900-1969 average since 1970 and by about 28% since 2000 (BoM \r\nand CSIRO, 2020). "


id: e7cdd203417c05e4144571697cac8fac
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 33965
content:
"Snowfall is an important component of precipitation in high-latitude \r\nand mountain watersheds. Reanalysis data indicate significant \r\nreductions in annual mean potential snowfall areas over NH land by \r\n0.52 million km2 per decade, with the largest decline over the Alps, \r\nwith snow water equivalent reductions of about 20 mm per decade \r\n(Tamang et al., 2020). In the Tibetan Plateau, region-wide winter \r\nsnowfall has increased but summer snowfall has decreased during \r\nthe 1960-2014 period (Deng et al., 2017). State-of-the-art model \r\nsimulations indicate reduced mean annual snowfall in the Arctic, \r\ndespite the strong precipitation increase, mainly in summer and \r\nautum, when temperatures are close to the melting point (Bintanja \r\nand Andry, 2017). "


id: dea1d5cc1ee39c49b3bb18ec6d6ac6ed
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 32524
content:
"line with similar studies that focused on the 1981-2012 (Y. Zhang \r\net al., 2016) and 1982-2013 (K. Zhang et al., 2015) periods. Zeng \r\net al. (2018) determined that the 8% global increase in satellite\u0002observed leaf area index between the 1980s and the 2010s may \r\nexplain an increase in evapotranspiration of 12.0 +-  2.4  mm yr-1\r\n(about 55 +-  25% of the total observed increase). Forzieri et al. \r\n(2020) estimated that the recent increase in leaf area index led to \r\n3.66+-0.45 W m-2 in latent heat flux (about 51 +- 6 mm yr-1) and \r\nthat the sensitivity of energy fluxes to leaf area index increased by \r\nabout 20% over the 1982-2016 period. Overall, there is medium \r\nconfidence that greening has contributed to the global increase in \r\nevapotranspiration since the 1980s."


id: 537204f95a19e46466b4fc765a01e786
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 10601
content:
"An increasing number of studies have identified signals of attribution \r\nin the recent observed trends in evapotranspiration. Douville \r\net al. (2013) found that the post-1960 rise in evapotranspiration in \r\nboth the mid-latitudes and northern high latitudes was related to \r\nanthropogenic radiative forcing. An analysis of CMIP5 simulations \r\nsuggests that anthropogenic forcing accounts for a  large fraction \r\nof the global mean evapotranspiration trend from 1982 to 2010 \r\n(Dong and Dai, 2017). Padron et al. (2020) determined that \r\nincreases in evapotranspiration were responsible for the majority \r\nof the anthropogenic pattern in dry-season water availability that \r\ndominates global trends since 1984. These findings are further \r\nsupported by CMIP6 model results (Figure  8.8) that show that \r\nthe recent summer increase in evapotranspiration in the northern \r\nmid- and high latitudes is due to GHG forcing and decreasing \r\nanthropogenic aerosol emissions over Europe. "


id: 90e5aad13ec0b09138e2f44eae67a488
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 20342
content:
"In summary, there is high confidence that terrestrial evapotranspiration \r\nhas increased since the 1980s. There is medium confidence that \r\nthis trend is driven by both increasing atmospheric water demand \r\nand vegetation greening, and high confidence that it can be partly \r\nattributed to anthropogenic forcing. There is low confidence about \r\nthe extent to which increases in plant water use efficiency have \r\ninfluenced observed changes in evapotranspiration. "


id: d732627fda3233aaa3fcba35784a645d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 31371
content:
"Since AR5, the predominant contribution of transpiration to the \r\nobserved trends in terrestrial evapotranspiration has been revisited \r\nand confirmed (Good et al., 2015; Wei et al., 2017). Using satellite \r\nand ecosystem models, Zhu et al. (2016) found a positive trend in \r\nleaf area index during 1982-2009, indicating that greening could \r\ncontribute to the observed positive trend of evapotranspiration, in "


id: 2e3d4bd047888fb945feb6d2df06b010
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 4712
content:
"studies of changes in the timing of streamflow in snow-influenced \r\nbasins continue to support a  prominent influence from warming \r\n(Kang et al., 2016; Dudley et al., 2017; Kam et al., 2018). Global \r\nland runoff variations correlate significantly with ENSO variability \r\n(Miralles et al., 2014b; Schubert et al., 2016)."


id: 72ffead5395418438306ecb6a1658a8a
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 15705
content:
"Observed changes in flooding are assessed in Section  11.5.2 and \r\nare summarized as follows. For changes in the magnitude of peak \r\nflow, recent studies show strong spatial heterogeneity in the sign, \r\nsize and significance of trends. For changes in timing of peak flows, \r\nrecent studies further support observed changes in snowmelt-driven \r\nrivers. Observed changes in runoff and flood magnitude cannot be \r\nexplained by precipitation changes alone given the possible season\u0002and region-dependent decreases in antecedent soil moisture and \r\nsnowmelt, which can partly offset the increase in precipitation \r\nintensity (Sharma et al., 2018), or the expected effect of urbanization \r\nand deforestation which can, on the contrary, amplify the runoff \r\nresponse (Chen et al., 2017; Abbott et al., 2019; Cavalcante et al., \r\n2019). Simulations of mean and extreme river flows are consistent \r\nwith the observations only when anthropogenic radiative forcing is \r\nconsidered (Gudmundsson et al., 2021). "


id: 3842dc708905bf55411de85958151a5
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 6225
content:
"In summary, the assessment of observed trends in the magnitude \r\nof runoff, streamflow, and flooding remains challenging, due to the \r\nspatial heterogeneity of the signal and to multiple drivers. There is, \r\nhowever, high confidence that the amount and seasonality of peak \r\nflows have changed in snowmelt-driven rivers due to warming. There \r\nis also high confidence that land-use change, water management \r\nand water withdrawals have altered the amount, seasonality, \r\nand variability of river discharge, especially in small and human\u0002dominated catchments. "


id: 29aa195706e9604d7818f7f0d44c4449
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3990
content:
"The AR5 reported low confidence that changes in drought since the \r\nmid-20th century could be attributed to human influence, owing to \r\nobservational uncertainties and difficulties in distinguishing decadal\u0002scale variability from long-term trends. Changes in soil moisture, \r\na metric of aridity, were not assessed thoroughly in AR5. Since AR5, \r\nnew satellite products, land surface reanalyses, and land surface \r\nmodels have been used to document recent changes in soil moisture \r\nat the global scale. The science of detection and attribution has also \r\nprogressed considerably (Trenberth et al., 2015; Easterling et al., \r\n2016; Stott et al., 2016). Attribution efforts have further benefited \r\nfrom the increased use of paleoclimate information, which provides \r\nan important constraint on natural variability that is insufficiently \r\nsampled by short observational record (Cook et al., 2018; Kageyama \r\net al., 2018)."


id: f88c21485cda8b1b48ec31447062a29f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 36614
content:
"Several studies have identified a  persistent 'fingerprint' of \r\nanthropogenic forcing in global trends in aridity spanning the last \r\n120 years. Using a  combination of tree ring data, CMIP5 model \r\nsimulations, and reanalysis products, Marvel et al. (2019) determined \r\nthat the dominant trend in aridity since 1900, characterized by \r\ndrying in North and Central America and the Mediterranean, is \r\ndetectable and attributable to external forcing from 1900 to 1949. \r\nThis trend weakens from 1950 to 1975, possibly due to aerosol "


id: bbcc70e6b79c4a3f5231be87896f688
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 27102
content:
"Some studies have suggested that dam construction and water \r\nwithdrawals can be the dominant drivers in observed trends in \r\nstreamflow amount (Wada et al., 2013). Regionally, land-use and \r\nland cover changes have been identified as important factors for \r\nstreamflow (H.  Chen et al., 2020). The impact of surface dimming \r\nfrom aerosol emissions on evaporation was identified as a discernible \r\ninfluence in NH streamflows (Gedney et al., 2014). While changes \r\nin annual mean streamflow present a  complicated picture, recent "


id: ef5ed7b16d2796888437032e1cadaad8
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vector_id: 35139
content:
"accounted for 8-27% of these soil moisture deficits. Robeson (2015) \r\nestimated that the California drought was a 1-in-10,000 year event. \r\nTree ring reconstructions indicate that prolonged megadroughts \r\nhave occurred in the western USA throughout the last 1200 years \r\n(Cook et al., 2004, 2010; B.I. Cook et al., 2015), forced by internal \r\nvariability (Coats et al., 2016; Cook et al., 2016b). However, Williams \r\net al. (2020) determined that 2000-2018 drought across the south\u0002western USA was the second driest 19-year period since 800 CE, and \r\nattributed nearly half the magnitude of this event to anthropogenic \r\nforcing (see also Section  10.4.2.3). Evidence for human signals in \r\ndrought can also be found in western North American streamflow \r\nrecords, as noted above in Section 8.3.1.5. There is high confidence\r\nthat anthropogenic forcing has contributed to recent droughts and \r\ndrying trends in western North America."


id: 1332f957af45cda437eff3bf19f818c7
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 532
content:
"Large areas of east-central Asia experienced drying in the early 2000s \r\nas a result of warmer temperatures, lower humidity, and declining \r\nsoil moisture (Wei and Wang, 2013; Z. Li et al., 2017; Hessl et al., \r\n2018). Paleoclimate data from the Mongolian plateau suggest that \r\nthis recent central Asian drought exceeds the 900-year return interval, \r\nbut is not unprecedented in the last 2060 years (Hessl et al., 2018). \r\nThere is low confidence due to limited evidence that recent droughts \r\nin central Asia can be attributed to anthropogenic forcing."


id: f9ed3b7e064d001995062d72b21923f6
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 36830
content:
"On a regional scale, the robustness of trend attribution for drought \r\nand aridity varies widely. Key trends and their attributions are \r\nsummarized here, while a complete regional assessment of observed \r\ntrends in drought and aridity is in Chapter 11 (Sections 11.6.2, 12.3.2 \r\nand 12.4)."


id: 458d7d7aa32a07183d515a00f6a08b1c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 8351
content:
"In the western USA, anthropogenic warming is amplifying drought \r\nand aridity by increasing evaporative demand and water loss to the \r\natmosphere (Weiss et al., 2009; Overpeck, 2013; Cook et al., 2014; \r\nGriffin and Anchukaitis, 2014; Williams et al., 2020). For the California \r\ndrought between 2012-2014, Griffin and Anchukaitis (2014) \r\nused paleoclimate reconstructions to determine that while rainfall \r\ndeficits were not unprecedented, record-high temperatures drove an \r\nexceptional decline in soil moisture relative to the last millennium. \r\nWilliams et al. (2015) concluded that anthropogenic warming "


id: 84ea8ded67916ef17c493290763e727
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 18433
content:
"Both central and north-eastern Africa have experienced a  decline \r\nin rainfall since about 1980 (high confidence) (Lyon and Dewitt, \r\n2012; Lyon, 2014; Hua et al., 2016; Nicholson, 2017). In Central \r\nAfrica, the decline has been attributed to atmospheric responses to \r\nIndo-Pacific sea surface temperature variability (Hua et al., 2018). \r\nIn north-eastern Africa, droughts have become longer and more "


id: c8a3e26eff26bf97251d9c838451b084
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 29126
content:
"In summary, it is very likely that anthropogenic factors have \r\ninfluenced global trends in aridity, mainly through competing \r\nchanges in evapotranspiration and/or atmospheric evaporative \r\ndemand due to anthropogenic emissions of GHG and aerosols. There \r\nis high confidence that the frequency and the severity of droughts has \r\nincreased over the last decades in the Mediterranean, western North \r\nAmerica, and south-western Australia and that this can be attributed \r\nto anthropogenic warming. There is medium confidence that recent \r\ndrying and severe droughts in southern Africa and south-western \r\nSouth America can be attributed to human influence. In some regions \r\nof western North America and the Mediterranean, paleoclimate \r\nevidence suggests that recent warming has resulted in droughts that \r\nare of similar or greater intensity than those reconstructed over the \r\nlast millennium (medium confidence)."


id: f4748569547ee26df4f959ca92e7f8f4
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 35961
content:
"Several subtropical, semi-arid regions in the Southern Hemisphere \r\nhave experienced long-term drying trends in the late 20th century. \r\nSouth-western South America (central Chile) experienced a  multi\u0002decadal decline in precipitation and streamflow culminating in \r\na  post-2010 megadrought that has been partly attributed to \r\nanthropogenic GHG emissions and ozone depletion (Boisier et al., \r\n2016, 2018; Saurral et al., 2017; Knutson and Zeng, 2018; Seager \r\net al., 2019b; Garreaud et al., 2020). There is medium confidence that \r\ndrying in central Chile can be attributed to human influence. The tree\u0002ring paleoclimate record demonstrates that the mid-century increase \r\nin exteme drought events in southern South America is unusual in \r\nthe context of the last 600 years, suggesting an emerging influence \r\nof anthropogenic forcing (Morales et al., 2020). "


id: c092d577fc7b59f51a9eedcf11fe9dca
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 27859
content:
"There has been a 20% decrease in winter (May to July) rainfall in \r\nsouth-western Australia since 1970, with the decline increasing to \r\naround 28% since 2000 (Delworth and Zeng, 2014; BoM and CSIRO, \r\n2020). There has also been a  significant increase in the average \r\nintensity of seasonal droughts in the region since 1911in response \r\nto both lower precipitation and increased atmospheric evaporative \r\ndemand (Gallant et al., 2013). Several studies attribute the \r\nprecipitation declines in south-western Australia to anthropogenic \r\nchanges in GHG and ozone (Delworth and Zeng, 2014; Knutson \r\nand Zeng, 2018; Seager et al., 2019b). There is high confidence that \r\nthe observed drying in south-western Australia can be attributed to \r\nanthropogenic forcing. "


id: 220a0c26083dedb5b33621c199fc7faa
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 2802
content:
"In south-eastern Australia, the average length of droughts have \r\nincreased significantly, lasting between 10 and 69% longer than \r\ndroughts during the first half of the 20th century (Gallant et al., \r\n2013). Paleoclimate reconstructions indicate a  97.1% probability \r\nthat the decadal rainfall anomaly recorded during the 1997-2009 "


id: 97e557f5035f3f633f312c9b54544940
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 21416
content:
"2000 and 2018 are -19.0 +- 2.5 Gt yr-1 (Shean et al., 2020). The most \r\nnegative changes were found in Nyainqentanglha with -4.0 +- 1.5 \r\nGt yr-1, while glaciers in Kunlun, northern Tibetan Plateau, slightly \r\ngained mass at 1.4 +- 0.8 Gt yr-1."


id: 37278edcaa3eec0b5f7cdc3d39073ab0
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 6064
content:
"There is some evidence that an increase of precipitation over high \r\nmountains can offset glacier ablation (melt; Farinotti et al., 2020). \r\nHowever, this process has only been described from the Karakoram \r\nregion in the north-western Himalaya, where it is thought to be \r\npartly responsible to the advances of glacier changes in the last two \r\ndecades, referred to as the 'Karakoram Anomaly' (Farinotti et al., \r\n2020). In the Himalaya, Maurer et al. (2019) observed faster ice \r\nloss during 2000-2016 (7.5 +- 2.3 Gt yr-1) compared to 1975-2000 \r\n(-3.9  +-  2.2 Gt yr-1). In the Southern Hemisphere, the rate of \r\nglacier mass lost in South America is estimated at 19.4 +- 0.6 Gt \r\nyr-1 based on surface elevation changes over 2000-2011, which \r\ninclude the North and South Patagonian Icefields of South America \r\n(Braun et al., 2019), and at -22.9 +- 5.9 Gt yr-1 over 2000-2018 \r\n(Dussaillant et al., 2019)."


id: e8bed05e1e1549489ceb1043e8f40b9e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 34132
content:
"In summary, human-induced global warming has been the primary \r\ndriver of a  global glacier recession since the early 20th century \r\n(high confidence). Most glaciers have lost mass more rapidly since \r\nthe 1960s and in an unprecedented way over the last decade, \r\nthereby contributing to increased glacier runoff, especially from \r\nlarger glaciers until a maximum is reached, which tends to occur \r\nlater in basins with larger glaciers and higher ice-cover fractions \r\n(high confidence)."


id: 2a43b799a78ad290cfc0b1d5df1a2ca9
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 4076
content:
"In summary, a  decline in the spring NH snow cover extent, snow \r\ndepth and duration has been observed since the late 1960s and has \r\nbeen attributed to human influence (high confidence). Depending \r\non the region and season, there is low-to-medium confidence in the \r\nmain drivers of snow cover changes, although various regions exhibit \r\na  shortening of the snow cover season which is consistent with \r\nglobal warming. A more detailed assessment of observed changes in \r\nseasonal snow cover is provided in Section 9.5.3."


id: 6711ca5b6cf3ba2bc2ec799dda4e3b0
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13804
content:
"Wetlands and lakes affect the climate through their impact on carbon \r\nand methane budgets (Section 5.2.2; e.g., Saunois et al., 2016; Zhan \r\net al., 2019) and on surface heat fluxes, with coupled weather and \r\nclimate effects (e.g., Zhan et al., 2019). Although these features are \r\nalso affected by human activities and by climate change, AR5 did not \r\nspecifically report on wetlands and lakes."


id: a91dfca1e674cc207bd461bfbef1a0e3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 24135
content:
"Inventories of surface water bodies are not systematically produced \r\nat national or regional levels. However, assessments are undertaken \r\nat the global scale (Ramsar Convention on Wetlands, 2018). Merging \r\nobservations from multiple satellite sensors makes it possible to \r\ndetect surface water even under vegetation and clouds over about \r\n25 years, but with low spatial resolution (Prigent et al., 2016). \r\nMost recent multi-satellite products from visible, infrared, and \r\nmicrowave measurements, estimate a surface water area of about \r\n12 to 14 million km2 (including permanent and transitory surfaces, \r\ne.g., Aires et al., 2018; Davidson et al., 2018), which is much higher \r\nthan those provided by optical imagery (about 3  million km2). \r\nInventories show a strong decrease in natural surface water of about \r\n0.8% yr-1 in total from 1970 to the present (Ramsar Convention \r\non Wetlands, 2018) but the sites are not evenly distributed. Multi-"


id: f185e25241220a077f6f8dada22e5f94
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 35501
content:
"Observations show a  rapid recent decrease of spring SCE in NH, \r\nmostly in Eurasia and North America, closely linked to temperature \r\nchange, for example, March to April SCE is decreasing at 3.4% +- 1.1 \r\n% per decade (1979-2005; Brown and Robinson, 2011; Hernandez\u0002Henriquez et al., 2015). An overall increasing annual trend of the \r\nNH SCE since the late 1980s has been observed, in contrast to \r\ndecreasing trends over 1960s to 1980s that are dominated by the "


id: ef4af7cc3f2bdfc7e1a59e54767e529a
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 35125
content:
"satellite estimates show a  strong interannual variability in surface \r\nwater extent over the period 1992-2015 with no clear long-term \r\ntrend (Prigent et al., 2020). "


id: f33b7836272dddaa3d2310900aeea626
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 35779
content:
"limited ability of global climate models to represent key controls \r\non regional rainfall variability like ENSO (Technical Annex VI and \r\nSection 3.7.3; R. Chen et al., 2020) may also underestimate observed \r\nrecharge from such events that are of particular importance in \r\ndrylands (R.G. Taylor et al., 2013b; Cuthbert et al., 2019b). Numerical \r\nrepresentations of the impact of precipitation intensification on \r\ngroundwater recharge in large-scale models remain constrained by \r\nthe challenges of including key recharge pathways that consider \r\npreferential flowpaths in soils (Beven, 2018) and focused recharge \r\nthrough leakage from surface waters (Doll et al., 2014)."


id: 13035da18a627c02a516d495775d3955
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 500
content:
"Human-made water bodies represent approximately 10% of the \r\ntotal continental water surfaces (Figure 8.1; Ramsar Convention on \r\nWetlands, 2018) and consist mainly of reservoirs and rice paddies. \r\nHigh resolution optical imagery over the period 1984-2015 \r\n(Donchyts et al., 2016; Pekel et al., 2016) shows a net increase of \r\nabout 0.1 million km2 in artifical water surfaces, mainly due to the \r\nconstruction of reservoirs. Surfaces of rice paddies are also increasing, \r\nespecially in South East Asia (Davidson et al., 2018). "


id: 1a74a9d06351c3eaacabf5fd58a4372d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 1642
content:
"In summary, there is high confidence that the extent of human-made \r\nsurface water has increased over the 20th and early 21st centuries. \r\nIn contrast, due to low agreement in the observational records at the \r\nglobal scale, there is only low confidence in the observed decline of \r\nthe natural surface water extent in recent years (see also SRCCL)."


id: 4961f1295cf1c379d9790e2ada208179
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 8930
content:
"As the world's most widespread store of freshwater (R.G.  Taylor \r\net al., 2013a), groundwater is estimated to supply between a quarter \r\nand a third of the world's annual freshwater withdrawals to meet \r\nagricultural, industrial and domestic demands (Doll et al., 2012; Wada \r\net al., 2014; Hanasaki et al., 2018)."


id: 9f2b2dbeb7f87afbd5d4f8e5bc98069c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 22578
content:
"Attribution of changes in groundwater storage, observed locally \r\nthrough piezometry (Figure  8.10; R.G.  Taylor et al., 2013a) or \r\nestimated from GRACE satellite measurements (Rodell et al., 2018) at \r\nregional scales (>100,000 km2), is often complicated by non-climate \r\ninfluences that include land-use change (Favreau et al., 2009) and \r\nhuman withdrawals (Bierkens and Wada, 2019). "


id: 180aa46aca8e81bac637bd5367806ffa
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 1276
content:
"Quantification of changes in groundwater storage from GRACE is \r\ncurrently constrained by uncertainty in the estimation of changes \r\nin other terrestrial water stores using uncalibrated, global-scale \r\nLand Surface Models (Doll et al., 2014; Scanlon et al., 2018) and \r\nthe limited duration of the period of GRACE observations (2002 to \r\n2016). Centennial-scale piezometry in north-west India reveals that \r\nrecent groundwater depletion traced by GRACE (Rodell et al., 2009; \r\nChen et al., 2014), follows more than a  century of groundwater \r\naccumulation through canal leakage (MacDonald et al., 2016). \r\nFurther, groundwater depletion is often localized occurring below the \r\nfootprint (200,000 km2) of GRACE, as has been well demonstrated by \r\ndetailed modelling studies in the California Central Valley (Scanlon \r\net al., 2012) and North China Plain (Cao et al., 2016)."


id: d461e67cd5c5d46da10512eb85d6020
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 30934
content:
"Climate variability and drought affect groundwater depletion \r\nmainly due to amplified groundwater withdrawals. For instance, the \r\ndepletion rate in Central Valley aquifer in the USA from 2006 to 2010 \r\nis estimated to range from 6 to 8 km3 yr-1 using GRACE data (Scanlon \r\net al., 2012). In India, Asoka et al. (2017) show contrasting trends in \r\ngroundwater storage in the north (declining at 2 cm yr-1) and south \r\n(increasing at 1-2 cm yr-1) that is explained by variations in human \r\nwithdrawals and precipitation linked to Indian Ocean sea surface \r\ntemperature variability."


id: db17b2699c19531e8b88c04aac6ddaf2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 31983
content:
"The overall underestimation of precipitation intensities in global \r\nclimate models (Wehner et al., 2010, 2020; Goswami and Goswami, \r\n2017) and of their sensitivity to warming temperatures (Borodina \r\net al., 2017) may lead to underestimates of their recharging effect \r\non groundwater (Mileham et al., 2009; Cuthbert et al., 2019b). The "


id: b3b216095ea6885582b633fece7fdaf1
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 25786
content:
"et al. (2019) in the Ganges-Brahmaputra-Megna basin, may be more \r\nseverely and widely affected by changes in upstream river discharge. \r\nThey argue further that saltwater inundation from storm surges will \r\nhave the greatest localized effects."


id: efbcdc18017f514ff72509f9364e0fce
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 35220
content:
"recharge (Tague and Grant, 2009). Aquifers in mountain valleys \r\nshow shifts in the timing and magnitude of: (i) peak groundwater \r\nlevels due to an earlier spring melt; and (ii) low groundwater levels \r\nassociated with lower baseflow periods (Allen et al., 2010; Dierauer \r\net al., 2018; Hayashi, 2020). The effects of receding alpine glaciers on \r\ngroundwater systems are not well understood but long-term loss of \r\nglacier storage is estimated to reduce summer baseflow (Gremaud \r\net al., 2009). In permafrost regions, coupling between surface water \r\nand groundwater systems may be particularly enhanced by warming \r\n(Lamontagne-Halle et al., 2018; Lemieux et al., 2020). In areas of \r\nseasonal or perennial ground frost, increased recharge is expected \r\ndespite a  decrease in absolute snow volume (Okkonen and Klove, \r\n2011; Walvoord and Kurylyk, 2016)."


id: ac89e855ee1df37f8e7f079ed6b02f05
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 24688
content:
"In summary, there is medium confidence that increased precipitation \r\nintensities, partly due to human influence, have enhanced groundwater \r\nrecharge, most notably in the tropics. There is high confidence that \r\ngroundwater depletion has occurred since at least the start of the \r\n21st century as a  consequence of groundwater withdrawals for \r\nirrigation in some of the world's most productive agricultural areas \r\nin drylands (e.g., southern High Plains and California Central Valley in \r\nthe USA, the North China Plain, north-west India)."


id: da7900c5dde9036491bb1220db29c7ad
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 31900
content:
"Coastal aquifers are the interface between the oceanic and terrestrial \r\nhydrological systems. Global sea level rise (SLR) causes interfaces \r\nbetween freshwater and saline-water to move inland. The extent \r\nof seawater intrusion into coastal aquifers depends on a variety of \r\nfactors including coastal topography, recharge, and groundwater \r\nabstraction from coastal aquifers (Comte et al., 2016). Modelling \r\nresults suggest that the impact of SLR on seawater intrusion is \r\nnegligible compared to that of groundwater abstraction (Ferguson \r\nand Gleeson, 2012; Yu and Michael, 2019). Coastal aquifers under \r\nvery low hydraulic gradients, such as the Asian mega-deltas, are \r\ntheoretically sensitive to SLR but, according to evidence from Akter "


id: ec7bd344dc30eb5eced9b55f4a8f76c8
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 34689
content:
"Observed changes in large-scale circulation indicators (Cross-Chapter \r\nBox 2.2) are assessed in Chapters 2 and 3 (Sections 2.3.1.4 and 3.3.3). \r\nIn this chaper we focus on the influence of regional scale teleconnection \r\nvariabililty on the water cycle and the attribution of these circulation \r\nchanges. While observed changes in modes of variability are assessed \r\nin Chapters 2 and 4 (Sections 2.4 and 4.3.3), here focus on hydrological \r\nteleconnections of relevance to the water cycle."


id: 693802339abaaefeef51ff4ad6902815
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 14144
content:
"2014; Bronnimann et al., 2015). However, CMIP5 and CMIP6 models still \r\nexhibit strong biases in representing the ITCZ, such as the simulation \r\nof a double ITCZ (Oueslati and Bellon, 2015; Adam et al., 2018; Tian \r\nand Dong, 2020). The impacts of aerosols and volcanic activity on the \r\nposition of the ITCZ have been investigated but changes are difficult to \r\ncharacterize from observations (Section 6.3.3.2; Friedman et al., 2013; \r\nJ.M. Haywood et al., 2013; Iles and Hegerl, 2014; Colose et al., 2016; \r\nChung and Soden, 2017). Such systematic shifts of the ITCZ can have \r\nimportant regional impacts like changes in precipitation (Figure 8.9)."


id: ae1a3aef833f9df43038dc6dd20752b1
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 24928
content:
"In summary, there is medium confidence that the tropical rain belts \r\nover the oceans have been narrowing and strengthening in recent \r\ndecades, leading to increased precipitation in the ITCZ core region \r\n(Section 8.2.2.2). Decreasing precipitation trends in the NH during \r\nthe 1950s-1980s have been attributed to anthropogenic aerosol \r\nemissions from North America and Europe (high confidence)."


id: 4d41e55c1468fa6b264f280101fbf5ae
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 9586
content:
"The AR5 reported low confidence in trends in the strength of the \r\nHadley circulation (HC) due to uncertainties in reanalyses but high \r\nconfidence on the widening of the tropical belt since 1979. In AR6, \r\nChapter  2  (Section  2.3.1.4.1) states that the HC has very likely\r\nwidened and strengthened since at least the 1980s, mostly in the NH \r\n(medium confidence). "


id: 58c59deaed0dfd504435bf99e06086f2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 11460
content:
"ITCZ trends seen in satellites, precipitation measurements and \r\nreanalysis data are further supported by ocean surface-salinity \r\nobservations. Long-term salinity observations show a  freshening in \r\nthe cores of the Atlantic and Pacific ITCZs and increased salinity on \r\nthe ITCZ margins (Durack and Wijffels, 2010; Durack et al., 2012; \r\nTerray et al., 2012; Skliris et al., 2014). By investigating simultaneous \r\nchanges in precipitation, temperature and continental aridity in CMIP5 \r\nhistorical simulations, Bonfils et al. (2020) found a secondary signal \r\n(Figure 8.9, right column) characterized by a robust inter-hemispheric \r\ntemperature contrast (Section 3.3.1.1), a latitudinal shift in the ITCZ \r\n(in accordance with the theory of cross-equatorial energy transport; \r\nSection 8.2.2.2), and changes in aridity in the Sahel (Section 8.3.1.6). \r\nThese forced changes are statistically detectable in reanalyses datasets \r\nover the 1950-2014 period at the 95% confidence level."


id: a983dcf325b430068f0ba719e4dd54ca
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 24203
content:
"In the Southern Hemisphere (SH), the HC expansion has \r\nbeen  associated with both the intensification and poleward shift \r\nof the subtropical high pressure belt (Nguyen et al., 2015), with \r\nconsequences for precipitation amount over Africa, Australia, \r\nSouth  America, and subtropical Pacific islands (Cai et al., 2012; \r\nGrose et al., 2015; Nguyen et al., 2015; Sharmila and Walsh, 2018; \r\nMcGree et al., 2019). The subtropical ridge in Australia has intensified \r\nsignificantly since 1970, with marked declines observed in April to \r\nOctober rainfall across south-eastern and south-western Australia \r\n(Timbal and Drosdowsky, 2013). "


id: 6442bea67320ee010f61bd39af969c89
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13344
content:
"The causes of the observed strengthening of the WC during 1980-2014 \r\nare not well understood due to competing influences from individual \r\nexternal forcings and since this strengthening is outside the range \r\nof variability simulated in coupled models (medium confidence), as \r\nassessed in Chapter 3 (Section 3.3.3.1). Recent strengthening in the WC \r\nhas been linked with internal variability (Chung et al., 2019), although \r\none study argues that it could be a  response forced by GHG that \r\nmodels do not capture because of common sea surface temperature \r\n(SST) biases in the equatorial Pacific (Seager et al., 2019a). It could \r\nbe also related to an interbasin thermostat mechanism whereby \r\nthe human-induced Indian Ocean warming emerged earlier than in \r\nthe tropical Pacific (L.  Zhang et al., 2018) and induced a  transient \r\nstrengthening of the zonal sea level pressure gradient and easterly \r\ntrades in the tropical Pacific (L. Zhang et al., 2019)."


id: 7e6e0f7d69e090a2c09e34b5dcb8294d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 17457
content:
"associated with hydroclimate variations than the subtropical ridge \r\n(Staten et al., 2019). Poleward expansion of the tropical belt strongly \r\ncontributes to precipitation decline in the poleward edge of the \r\nsubtropics (Cai et al., 2012; Scheff and Frierson, 2012; Timbal and \r\nDrosdowsky, 2013; He and Soden, 2017; H.  Nguyen et al., 2018; \r\nTang et al., 2018), although recent modelling evidence suggests \r\nthat subtropical precipitation declines are a response to direct CO2\r\nradiative forcing mainly over ocean, irrespective of the HC expansion \r\n(He and Soden, 2017). Both reanalyses datasets and climate model \r\nsimulations suggest that the HC expansion is not associated with \r\nwidespread, zonally symmetric subtropical drying over land (Schmidt \r\nand Grise, 2017). "


id: 984add541ea82cf55b8f0dc30a7ac6ae
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 21473
content:
"The weakening of the PWC observed during most of the 20th \r\ncentury is associated with reductions in land rainfall over the \r\nMaritime Continent during 1950-1999 (Tokinaga et al., 2012; \r\nYoden et al., 2017). In contrast, the recent strengthening of the WC \r\nhas been associated with an intensification of extreme flooding \r\n(Barichivich et al., 2018) and an increased frequency of wet days \r\n(J.C.  Espinoza et al., 2016, 2018) over the north-western Amazon, \r\nincreased precipitation in South America (Yim et al., 2017), reduced \r\nprecipitation over eastern Africa (Williams and Funk, 2011; Lyon and \r\nDewitt, 2012), and increased rainfall in southern Africa (Maidment \r\net al., 2015). Internal variability has been shown to have a dominant \r\nrole in the recent strengthening of the WC (Chung et al., 2019)."


id: 5e7acee97325ea9202feb9cffeffe1a1
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 12402
content:
"In summary, there is high confidence that changes in the WC are \r\nassociated with changes in the water cycle over regions like the \r\nMaritime Continent, South America and Africa. It is very likely\r\nthat the WC has strengthened in the Pacific since the 1980s, with \r\nmedium confidence that this strengthening is within the range of \r\ninternal variability. "


id: 7f1dfce29396224f2820059e5e11eb31
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 17550
content:
"In summary, it is very likely that the recent HC expansion was \r\nassociated with poleward shifts of tropical cyclone tracks over the \r\nwestern North Pacific Ocean since the 1940s, and of extratropical \r\nstorm tracks in the SH since the 1970s. Changes to the HC in the \r\nNH may have contributed to subtropical drying and a  poleward \r\nexpansion of aridity during the boreal summer, but there is \r\nlow confidence due to limited evidence. GHG increases and \r\nstratospheric ozone depletion have contributed to expansion of the \r\nzonal mean HC in the SH since around 1970, while the expansion \r\nof the NH  HC has not exceeded the range of internal variability \r\n(medium confidence)."


id: 162dc39f67eade7f8e84066a057ff1ec
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 1012
content:
"The AR5 reported low confidence in the attribution of changes in \r\nmonsoons to human influence, although a  detailed attribution \r\nassessment of the observed changes in the regional monsoons was \r\nnot presented. "


id: 28ad0504b3937b1bd0884f2ca61c5111
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3827
content:
"The AR5 concluded that the long-term weakening of the Pacific Walker \r\ncirculation (WC) from the late 19th century to the 1990s has been \r\nlargely offset by a  recent strengthening (high confidence), though \r\nwith low confidence in trends of the WC strength due to reanalysis \r\nuncertainties and large natural variability. The observed trends in the \r\nWC since 1980 are consistent with a very likely WC strengthening in \r\nthe Pacific, similar to a  La Nina pattern, with medium confidence\r\nin  the magnitude of these changes due to differences between \r\nsatellite observations and reanalyses. "


id: 1558f7fb5630099013c1f21f66039cdf
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 878
content:
"are discussed further in Section  10.4.2, from the perspective of \r\nclimate change attribution and in Section 10.6.3, from the viewpoint \r\nof constructing regional climate messages."


id: 635d94ada99253480bf03406cdc68e08
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13207
content:
"In summary, there is high confidence in observational evidence for \r\na weakening of the SAsiaM in the second half of the 20th century. \r\nResults from climate models indicate that anthropogenic aerosol \r\nforcing has dominated the recent decrease in summer monsoon \r\nprecipitation, as opposed to the expected intensification due to GHG \r\nforcing (high confidence). On paleoclimate time scales, the SAsiaM \r\nstrengthened in response to enhanced summer warming in the NH \r\nduring the early-to-mid Holocene, while it weakened during cold \r\nintervals (high confidence). These changes are tightly linked to orbital \r\nforcing and changes in high-latitude climate (medium confidence)."


id: 2778249abff975c3c844baae6217e11e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3612
content:
"The AR5 reported low confidence in the observed weakening of the \r\nEast Asian monsoon (EAsiaM) since the mid-20th century. Since \r\nAR5, there has been improved understanding of changes in the \r\nEAsiaM, based on paleoclimatic evidence, instrumental observations \r\nand climate modeling simulations. Rainfall reconstructions from \r\nthe Loess Plateau in China indicate that the northern extent of the \r\nmonsoon rain belts migrated at least 300 km to the north-west from \r\nthe LGM to the mid-Holocene (Yang et al., 2015). Similarly, Pliocene "


id: 22a38b4237d4a20f6b89915e50cd6762
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 2904
content:
"reconstructions indicate stronger intensity of the EAsiaM with a more \r\nnorthward penetration of the monsoon rain belt (S.  Yang et al., \r\n2018a). EAsiaM variability has been related to Atlantic Meridional \r\nOverturning Circulation (AMOC) dynamics, especially during the last \r\nglacial period, but whether the relationship is negative or positive \r\nremains uncertain (Sun et al., 2012; Cheung et al., 2018; Kang \r\net al., 2018)."


id: 8e51cd3031de330a84a25f1268d658d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 19917
content:
"since the 1950s, but there is low confidence in the magnitude of the \r\nanthropogenic influence. The transition towards a positive PDV phase \r\nhas been one of the main drivers of the EAsiaM weakening since the \r\n1970s (high confidence)."


id: 2430ca58f261a4c208e71e651a1f4fc0
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3140
content:
"Since AR5, there has been improved understanding of the West \r\nAfrican monsoon (WAfriM) response to natural and anthropogenic \r\nforcing. On paleoclimate time scales, enhanced summer insolation in \r\nthe Northern Hemisphere (NH) intensified the WAfriM precipitation \r\nduring the early-to-mid Holocene (high confidence), as seen in rainfall \r\nproxy records and climate model simulations (Masson-Delmotte \r\net al., 2013; Mohtadi et al., 2016; Braconnot et al., 2019). Despite \r\nimprovements in model simulations of the present-day monsoons, \r\nCMIP5 and CMIP6 models underestimate mid-Holocene changes \r\nin the amount and spatial extent of the WAfriM precipitation \r\n(Section 3.3.3.2; Brierley et al., 2020). "


id: 8c2e7ff4f4b21a3c823267ec85fbadcc
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 19560
content:
"Long-term precipitation observations from China indicate a trend of \r\ndrying in the north and wetting in the central-eastern China along \r\nthe Yangtze river valley since the 1950s (Qian and Zhou, 2014; Zhou \r\net al., 2017b; Day et al., 2018), with a weakened EAsiaM low-level \r\ncirculation that penetrates less far into northern China, increased \r\nsurface pressure over north-east China and southward shift of the \r\njet stream (Song et al., 2014). The southward shift and enhancement \r\nof the jet stream explains the increase of rainfall especially from the \r\nMeiyu front (Day et al., 2018) at the expense of drying over north\u0002east China. "


id: 78e6d63a7b7130bf00e1a345e94eecb7
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 16575
content:
"Anthropogenic factors such as GHGs and aerosols had an influence \r\non the EAsiaM changes (Figure 8.11; T. Wang et al., 2013; Song et al., \r\n2014; Xie et al., 2016; Chen and Sun, 2017; Ma et al., 2017; L. Zhang \r\net al., 2017; Day et al., 2018; Tian et al., 2018). Increased precipitation \r\nin the southern region has been linked to increased moisture flux \r\nconvergence driven by GHG forcing while changes in anthropogenic \r\naerosols have weakened the EAsiaM and reduced precipitation in \r\nthe northern regions (Tian et al., 2018). Aerosol-induced cooling, \r\nassociated atmospheric circulation changes and sea surface \r\ntemperature (SST) feedbacks weaken the EAsiaM and favour the \r\nobserved dry-north and wet-south pattern of rainfall anomalies \r\n(T. Wang et al., 2013; Song et al., 2014; L. Zhang et al., 2017; G. Chen \r\net al., 2018; X. Chen et al., 2018; Undorf et al., 2018b). "


id: 6583b8d9b5bea967e1886ca1f9f88af3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13547
content:
"Wetter conditions of the WAfriM prevailed later from the mid-to-late \r\n1990s, although the positive trend in precipitation started since the \r\nlate 1980s (see also Section 10.4.2.1) over the Sahel (high confidence) \r\nand in the Guinean coastal region (medium confidence), indicating \r\nthe geographical variation in the wetting recovery (Descroix et al., \r\n2015; Sanogo et al., 2015; Bodian et al., 2016; Nicholson et al., 2018). \r\nWhile the interannual and decadal variability of annual rainfall is not \r\nhomogeneous over the entire Sahel, the rainfall recovery was stronger \r\nin the east than in the west of the region (Section 10.4.2.1; Nicholson \r\net al., 2018). A  shift in the seasonality of the Sahelian rainfall, \r\nincluding delayed cessation has also been reported (Section 10.4.2.1; \r\nNicholson, 2013; Dunning et al., 2018). "


id: 11b9bdfee7d98f25cf9ca70bb8a60851
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 282
content:
"In the Sahel region, the emergence of this new rainfall regime is \r\nreflected in increased number of heavy and extreme events, compared \r\nto the 1970s-1980s, still not exceeding the values registered in the \r\n1950s to 1960s (Descroix et al., 2013, 2015; Panthou et al., 2014, \r\n2018; Sanogo et al., 2015), and in higher interannual variability \r\n(W. Zhang et al., 2017b; Akinsanola and Zhou, 2020) associated with "


id: d74d6e1d5b12e39d5ea9b32291383542
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 31390
content:
"In summary, there is strong evidence of a  stronger EAsiaM and \r\nnorthward migration of the rainbelt during warmer climates based \r\non paleoclimate reconstructions. There is high confidence that \r\nanthropogenic forcing has been influencing historical EAsiaM \r\nchanges with drying in the north and wetting in the south observed "


id: 933a5865d8d4cc40210464cf8215a3b9
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 20675
content:
"air associated with the Laurentide Ice Sheet (T. Bhattacharya et al., \r\n2017, 2018). The NAmerM strengthened until the mid-Holocene \r\nperiod, in response to ice-emsheet retreat and rising summer \r\ninsolation, but probably did not exceed the strength of the modern \r\nsystem (low confidence), as indicated by model simulations (Metcalfe \r\net al., 2015) and paleoclimatic reconstructions (Bhattacharya et al., \r\n2018). Paleoclimatic evidence from proxy datasets and mid-Pliocene \r\n(PlioMIP1) simulations suggest a wetter south-western USA during \r\nthat warmer period (A.M. Haywood et al., 2013; Pound et al., 2014; \r\nIbarra et al., 2018) but it is not clear whether this is due to increases \r\nof precipitation associated with the monsoon or occurring during the \r\nwinter season. "


id: 23f2f3aafdb45534756eb49db94c4f09
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3096
content:
"During 1948-2010, trends of boreal summer precipitation amount \r\nwere significantly positive over New Mexico and the core NAmerM \r\nregion, but significantly negative over south-western Mexico (Hoell \r\net al., 2016). In addition, diverse datasets like CRU, CHIRPS and GPCP \r\nshow significant decreases of precipitation in parts of the south\u0002western USA and north-western Mexico, including the NAmerM \r\nregion (Cavazos et al., 2020; Ashfaq et al., 2021). Other studies \r\nsuggest a  strengthening of the NAmerM upper level anticyclone \r\nsince the mid-1970s, with a more frequent northward location (Diem \r\net al., 2013). Between 1910-2010, the number of precipitation \r\nevents increased across the northern Chihuahuan desert, within \r\nthe NAmerM domain, despite a  decrease in their magnitude, and \r\nthe length of extreme dry and wet periods also increased (Petrie \r\net al., 2014). "


id: 5c50d2c528666d4500066232dcbf0dba
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 12037
content:
"In summary, most regions of West Africa experienced a wet period \r\nin the mid-20th century followed by a very dry period in the 1970s \r\nand 1980s that is attributed to aerosol cooling of the NH (high \r\nconfidence). Recent estimates provide evidence of a WAfriM recovery \r\nfrom the mid-to-late 1990s, with more intense extreme events partly \r\ndue to the combined effects of increasing GHG and decreasing \r\nanthropogenic aerosols over Europe and North America (high \r\nconfidence). On paleoclimate time scales, there is high confidence\r\nthat the WAfriM strengthened during the early-to-mid Holocene \r\nin response to orbitally-forced enhancement of summer warming \r\nin the NH."


id: d1e4b4496feca617be1c384f7a33a09b
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 30546
content:
"Analyses from a 50-km resolution GCM indicate that the NAmerM \r\nresponse to CO2 is very sensitive to SST biases, showing reductions \r\nin summer NAmerM precipitation with increased CO2 when the SST \r\nbiases are small (Pascale et al., 2017) in contrast to CMIP5 models \r\n(Cook and Seager, 2013; Maloney et al., 2014; Torres-Alavez et al., \r\n2014; Hoell et al., 2016). The NAmerM has been shown to be also \r\nsensitive to sulphur dioxide (SO2) emissions (Garcia-Martinez \r\net al., 2020). "


id: ad444606a3300d3476c1640cfd1cc78d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 24802
content:
"Since AR5, there have been updates on the observed long-term \r\nvariations and changes in the North American monsoon (NAmerM). \r\nDuring the Last Glacial Maximum (LGM; 21,000-19,000 years ago), \r\nthe NAmerM was substantially weaker due to cold, dry mid-latitude "


id: 7914bca303fd5e38eec8bf389d2ff967
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 16604
content:
"In summary, both paleoclimate evidence and observations indicate \r\nan intensification of the NAmerM in a  warmer climate (medium \r\nconfidence). The intensification recorded since about the 1970s has \r\nbeen partly driven by GHG emissions (medium confidence). "


id: d428bb1bf740f42bb9172a3b5a7f4081
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 30897
content:
"the domain considered for the SAmerM, confirming the occurrence \r\nof delayed onsets of the SAmerM since 1978 (Correa et al., 2021). \r\nCMIP5 simulations show trends toward delayed onsets of the \r\nSAmerM in association with anthropogenic forcing, although the \r\nsimulated trends underestimate the observed trends (Fu et al., 2013). \r\nTotal rainfall reductions are observed in the southern Amazon during \r\nSeptember-October-November after 1978 (Fu et al., 2013; Bonini \r\net al., 2014; Debortoli et al., 2015, 2016; Espinoza et al., 2019), \r\nconsistent with reductions in river discharge in the region (Molina\u0002Carpio et al., 2017; Espinoza et al., 2019; Heerspink et al., 2020)."


id: 75fa8f80b3c669966b678900c8ea431c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 16157
content:
"In summary, there is high confidence that the SAmerM onset has \r\nbeen delayed since the late 1970s. This is reproduced by CMIP5 \r\nsimulations that consider anthropogenic forcing. There is also \r\nhigh confidence that precipitation during the dry-to-wet transition \r\nseason has been reduced over the southern Amazon. Paleoclimate \r\nreconstructions and simulations suggest a weaker SAmerM during \r\nwarmer epochs such as the Mid-Holocene or the 900-1100 period, \r\nand stronger monsoon during colder epochs such as the LGM or the \r\n1400-1600 period (high confidence). "


id: c50b0b027f3daf3adf5bb8f6cc99f019
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 28580
content:
"Isotope records from caves in the central Peruvian Andes show \r\nthat the late Holocene (<3000 years ago) was characterized by \r\nmulti-decadal and centennial-scale periods of significant decline in \r\nintensity of the SAmerM (Bird et al., 2011a; Vuille et al., 2012). This \r\ncould be partly due to a reduction in the zonal SST gradient of the \r\nPacific Ocean, favouring El Nino-like conditions (Kanner et al., 2013). \r\nOther studies suggest increased SAmerM precipitation amount \r\nduring the Late Holocene, in association with the expansion of the \r\ntropical forest (Smith and Mayle, 2018). Well-dated equilibrium lines \r\nof glaciers during the deglaciation suggest that the AMOC enhances \r\nAtlantic moisture sources and precipitation amount increase over the \r\ntropical and southern Andes (Beniston et al., 2018). "


id: 90e31f4151d8c3ac501146324c2c250d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 20338
content:
"Since AR5, several studies have examined observed variability \r\nand changes in the Australian and Maritime Continent monsoon \r\n(AusMCM) using paleoclimate records, instrumental observations \r\nand modeling studies (Denniston et al., 2016; Zhang and Moise, \r\n2016). Paleoclimate reconstructions and modelling indicate that \r\nthe Indo-Australian monsoon may vary in or out of phase with the \r\nEAsiaM, depending on whether there is a meridional displacement or \r\nexpansion of the tropical rainfall belt (Ayliffe et al., 2013; Denniston \r\net al., 2016). For instance, mid-Holocene simulations suggest that the \r\nAusMCM weakens and contracts due to a decreased net energy input \r\nand a weaker dynamic component (D'Agostino et al., 2020b). "


id: 2844fe3a852ec2152a6d18e301062167
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3743
content:
"Observations during 1979-2014 suggest that poleward shifts in the \r\nSouth Atlantic Convergence Zone (SACZ) noted in recent decades \r\n(Talento and Barreiro, 2018; Zilli et al., 2019), are associated with \r\nprecipitation amount decrease along the equatorward margin and \r\nincrease along the poleward margin of the convergenze zone (Zilli \r\net al., 2019). Several observational studies identified delayed onsets of \r\nthe SAmerM after 1978 related to longer dry seasons in the southern \r\nAmazon (Fu et al., 2013; Yin et al., 2014; Arias et al., 2015; Debortoli \r\net al., 2015; Arvor et al., 2017; Giraldez et al., 2020; Haghtalab et al., \r\n2020; Correa et al., 2021). In contrast, other studies indicate a trend \r\ntoward earlier onsets of the SAmerM (Jones and Carvalho, 2013). \r\nThese discrepancies are explained by the methodology used and "


id: fa007c69f47030259601ff8b841bd984
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 36847
content:
"Rainfall increases have been observed over northern Australia since \r\nthe 1950s, with most of the increases occurring in the north-west \r\n(Dey et al., 2019a, b; Dai, 2021) and decreases observed in the north-"


id: b7b2b4e6bc07657b00fd51bef86554cb
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 26433
content:
"east (J. Li et al., 2012) since the 1970s. There is also a trend towards \r\nmore intense convective rainfall from thunderstorms over northern \r\nAustralia (Dowdy, 2020). There is no consensus on the cause of the \r\nobserved Australian monsoon rainfall trends, with some studies \r\nsuggesting changes are due to altered circulation driving increased \r\nmoisture transport or increased frequency of the wettest synoptic \r\nregimes (Catto et al., 2012; Clark et al., 2018). Other studies find \r\nthat model simulations that include anthopogenic aerosols (Rotstayn \r\net al., 2012; Dey et al., 2019a) are better able to capture observed \r\nAustralian monsoon rainfall trends than simulations with natural or \r\nGHG forcing only (Knutson and Zeng, 2018). "


id: 7addb9339627e067d331733c568b4252
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 16923
content:
"is greater than what would be expected solely from changes in US \r\nlandfall frequency, suggesting the increasing role of TCs have in \r\ncausing heavy rainfall events (Kunkel et al., 2010). For example, there \r\nis evidence for an anthropogenic contribution to the extreme rainfall \r\nof Hurricane Harvey in 2017 (Emanuel, 2017; Risser and Wehner, \r\n2017; van Oldenborgh et al., 2017; Trenberth et al., 2018; S.-Y.S. Wang \r\net al., 2018). "


id: 2dec65e1e389bf6f16ca248ab352655
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 4663
content:
"While TCs cause extreme local rainfall and flooding, they can be also \r\nan important contributor to annual precipitation and regional fresh \r\nwater resources (Hristova-Veleva et al., 2020). Transport of moisture \r\nby TCs is an important contributor for precipitation over the coastal \r\nareas of East Asia mostly from July through October, with the TC \r\nrainfall accounting for nearly 10% to 30% of the total rainfall in \r\nthe region (L. Guo et al., 2017). Local TC rainfall totals depend on \r\nrain-rate and translation speed (the speed of TC movement along \r\nthe storm track) with slow TCs such as Hurricane Harvey (2017), \r\nproviding a clear example of the effect of slow translation speed on \r\nlocal rainfall accumulation, with urbanization exacerbating the storm \r\ntotal rainfall and flooding (Section 11.7.1; W. Zhang et al., 2018). "


id: 951992a359ef6450528cc1195675e91f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 20963
content:
"The Maritime Continent (MC) experiences the influence of both the \r\nAsian and the Australian monsoons, with rainfall peaking during \r\nboreal winter/austral summer (Robertson et al., 2011). Reductions in \r\nland rainfall and marine cloudiness over the MC and weakening of \r\nsurface moisture flux convergence have been observed in the period \r\n1950-1999 (Tokinaga et al., 2012; Yoden et al., 2017). These trends \r\nare indicative of a slowdown of the Walker Circulation, with positive \r\nsea level pressure trends over the MC and negative trends over \r\nthe central equatorial Pacific (Tokinaga et al., 2012). More recently \r\n(1981-2014), a trend of increasing annual rainfall over large areas \r\nof the MC has been identified (Hassim and Timbal, 2019). Given the \r\nlarge variability in MC rainfall on interannual time scales, the choice \r\nof time period may influence the calculated rainfall trend (Hassim \r\nand Timbal, 2019)."


id: 3aef28088172f5a215f7d6f3ddd7cdf7
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"In addition to evidence that rain-rates have increased, there is \r\nevidence that TC translation speed has slowed globally (Kossin, \r\n2018) thus amplifying thermodynamic intensification of rainfall \r\nand may be linked to anthropogenic forcing (Gutmann et al., 2018). \r\nThis is limited evidence however, so there is medium confidence of \r\na detectable change in TC translation speed over the US. Since the \r\n1900s, and there is low confidence for a  global signal because of \r\nlimited agreement among models and due to data heterogeneity. \r\nHowever, the slowdown is consistent with theoretical and modelling \r\nstudies that indicate a general weakening of the tropical circulation \r\nwith warming that reduces the speed of the TC system (Chauvin \r\net al., 2017), though there is limited observational evidence\r\n(Sections 8.2.3.5 and 11.7.1). "


id: 310f28cf24fbd6b3dc87721473303431
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 5142
content:
"During 1951-2007 daily rainfall extremes did not increase over \r\nthe MC, in contrast to the rest of South East Asia (Section 11.4.2; \r\nVillafuerte and Matsumoto, 2015). Rainfall extremes in Indonesia \r\nincreased in austral summer, as evidenced from station weather \r\nobservations for the period 1983-2012 (Supari et al., 2018). "


id: dacfc23735d4c3a7cf92daa8df9d0c3e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 31954
content:
"In summary, notable rainfall increases have been observed in parts of \r\nnorthern Australia since the 1970s, although there is low confidence\r\nin the human contribution to these changes. Rainfall changes have \r\nbeen observed over the MC region but there is low confidence in \r\nthe identification of trends because of large variability at interannual \r\ntime scales."


id: b09a9fdb2c81303c9d1b372fd4f540d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 25304
content:
"In summary, there is medium confidence of an observed increase in \r\nTC precipitation intensity in regions with sufficient data coverage \r\nRobust physical understanding (Section 8.2.3.2) and detailed singular \r\nevent attribution studies provide evidence that tropical cyclone \r\nrainfall has increased with a  warming climate (high confidence, \r\nSection 11.7.1.4)."


id: cecae82b638c6d11a04dcd98ed75a15e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 30070
content:
"The AR5 assessed low confidence in centennial changes in tropical \r\ncyclone (TC) activity globally, and in the attribution of observed \r\nchanges in TCs to anthropogenic forcing. Since AR5, there has been \r\nconsiderable progress in understanding the observed changes of TCs \r\nand an overall improved knowledge of the sensitivity of TCs to both \r\nGHG and aerosol forcing (Knutson et al., 2019; Sobel et al., 2019). "


id: 621bdc8537a330fa297487a252e90e90
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 12991
content:
"Stationary waves are planetary-scale waves that are approximately \r\nstable (stationary) in terms of geographic position, as opposed to \r\npropogating planetary waves, and are important both as part of the \r\nclimatological general circulation and seasonal and shorter-term \r\nanomalies. They are related to surface features including land-\r\nocean contrasts and major mountain ranges, as well as atmospheric \r\nfeatures including the jet stream, storm tracks, and blocking, which \r\nare considered separately in the following sections. While zonal mean \r\nchanges in P-E (precipitation minus evaporation) are dominated \r\nby thermodynamic effects (Section  8.2.2.1), changes in stationary \r\nwaves are of key importance in understanding zonal asymmetries \r\nin the water cycle response to global warming (Wills and Schneider, \r\n2015; Wills et al., 2019). The AR5 did not explicitly assess stationary "


id: 95587031f5ead984eb9c2e5964707816
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 20995
content:
"Although observational data limitations (Lau and Zhou, 2012) \r\ntend to limit detection of anthropogenic forced increases in TC \r\nprecipitation (Knutson et al., 2019), there is medium confidence that \r\nanthropogenic forcing has contributed to observed heavy rainfall \r\nevents over the USA associated with TCs (Kunkel et al., 2012) and \r\nother regions with sufficient data coverage (Section 11.7.1.2; Bindoff \r\net al., 2013). There has been increased frequency of TC heavy rainfall \r\nevents over several areas in the USA since the late 19th century that "


id: cca196cc659b3d93e3ac18d32bad7185
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 29732
content:
"Currently no consensus exists on observed trends in blocking during \r\n1979-2013. (Horton et al., 2015) identified increasing trends in \r\nanticyclonic circulation regimes based on geopotential height \r\nfields in the mid-troposphere, which may be partly related to the \r\ntropospheric warming itself and thus not represent real changes \r\nin the statistics of weather (Horton et al., 2015; Woollings et al., \r\n2018). Hanna et al. (2018) and (Davini and D'Andrea, 2020) reported \r\na  significant increase in the frequency of summer blocking over \r\nGreenland. A weakening of the zonal wind, eddy kinetic energy and \r\namplitude of Rossby waves in summer in the NH (Coumou et al., \r\n2015, Kornhuber et al., 2019) and an increased 'waviness' of the jet \r\nstream associated with Arctic warming (Francis and Vavrus, 2015; \r\nPfahl et al., 2015; Luo et al., 2019) have also been identified, which \r\nmay be linked to increased blocking. "


id: 59e13d95b0d25db98fbf9ad721649204
created_at: 2023-03-16 14:00:45
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vector_id: 11643
content:
"waves, but noted changes in related circulation features such as \r\na likely poleward shift of the Northern Hemisphere (NH) storm tracks \r\nand an increase in frequency and eastward shift in North Atlantic \r\nblocking anticyclones, although there was low confidence in the \r\nglobal assessment of blocking."


id: a6322c74776fb16a6071affa970b2235
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 23687
content:
"Since AR5, several studies have demonstrated a  link between \r\nstationary wave amplitude and wet and dry extremes in several \r\ndifferent regions of the NH (Liu et al., 2012; Coumou et al., 2014; \r\nScreen and Simmonds, 2014; Yuan et al., 2015) with changes in \r\nmoisture transport playing an important role (Yuan et al., 2015). \r\nA  'resonance mechanism' has been proposed for an increasing \r\namplitude of stationary waves (Petoukhov et al., 2013, 2016; Coumou \r\net al., 2014; Kornhuber et al., 2017) and several studies have linked \r\nincreasing amplitude of stationary waves to Arctic warming (Francis \r\nand Vavrus, 2012, 2015; Liu et al., 2012; Tang et al., 2014) as well \r\nas to global warming (Mann et al., 2017). However, other studies \r\nhave not identified an increase in stationary wave amplitude (Barnes, \r\n2013; Screen and Simmonds, 2013a, b). "


id: db6ac17a3a9e79912ebecd250662a7bb
created_at: 2023-03-16 14:00:45
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vector_id: 32035
content:
"There has been considerable work on linkages (teleconnections) \r\nbetween Arctic warming and the mid-latitude circulation (see also \r\nCross-Chapter Box 10.1). The limited amount of research on Southern \r\nHemisphere (SH) stationary waves suggests changes in high-latitude, \r\nmid-tropospheric stationary waves which influence Antarctic \r\nprecipitation (Turner et al., 2017) and changes in stratospheric \r\nstationary waves that are associated with ozone depletion rather than \r\nincreases in GHGs (L. Wang et al., 2013). The observed climatology \r\nof NH winter stationary waves is well-represented in the CMIP5 \r\nmulti-model mean (Wills et al., 2019) but individual models have \r\nimportant deficiencies in reproducing stationary wave variability (Lee \r\nand Black, 2013). In the SH, the observed climatology of stationary \r\nwaves in CMIP5 models has considerable bias in both phase and \r\namplitude (Garfinkel et al., 2020). A comprehensive assessment is not \r\nyet available for CMIP6 models."


id: 58cb84b67c07f317b52661d6e9213fe3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 11465
content:
"In summary, no robust trend in atmospheric blocking has been \r\ndetected in modern reanalyses and in CMIP6 historical simulations \r\n(medium confidence). The lack of trend is explained by strong \r\ninternal variability and/or the competing effects of low-level Arctic \r\namplification and upper-level tropical amplification of the equator\u0002to-pole temperature gradient (medium confidence)."


id: 93917810edcef5af399c0ab49695b735
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 20731
content:
"In summary, there is low confidence in strengthened winter stationary \r\nwave activity over the North Atlantic, associated with increased \r\npoleward moisture fluxes east of North America There is medium \r\nconfidence in a recent amplification of the NH stationary waves in \r\nsummer, but no formal attribution to anthropogenic climate change."


id: ab370b45071f300df704e72d73063c9d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"The AR5 indicated low confidence in long-term changes in the \r\nintensity of extratropical cyclones (ETC) over the 20th century derived \r\nfrom centennial reanalyses and storminess proxies based upon sea \r\nlevel pressure. This was confirmed by the SREX assessment that the \r\nmain Northern Hemisphere (NH) and Southern Hemisphere (SH) \r\nextratropical storm tracks likely experienced a poleward shift during \r\nthe last 50 years (Seneviratne et al., 2012) with low confidence, and \r\ninconsistencies within reanalysis datasets remain."


id: fb48e9026744a638dd9183aa2a681a52
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 37043
content:
"Atmospheric blocking refers to persistent, semi-stationary weather \r\npatterns characterized by a high-pressure (anticyclonic) anomaly that \r\ninterrupts the westerly flow in the mid-latitudes of both hemispheres. \r\nBy redirecting the pathways of mid-latitude cyclones, blocking can \r\naffect the water cycle and lead to negative precipitation anomalies \r\nin the region of the blocking anticyclone and positive anomalies in \r\nthe surrounding areas (Sousa et al., 2017). In this way, blocking can \r\nalso be associated with extreme events such as heavy precipitation \r\n(Lenggenhager et al., 2019), drought (Schubert et al., 2014) and \r\nheatwaves (Miralles et al., 2014a). The AR5 reported low confidence in \r\nglobal-scale changes in blocking, due to methodological differences \r\nbetween studies."


id: 3c353c3df6b8ce6cc61fffc78a95cd3d
created_at: 2023-03-16 14:00:45
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vector_id: 6836
content:
"Since AR5 there has been considerable progress in quantifying \r\nstorm track activity using multiple reanalysis products and different \r\nmethodologies (Hodges et al., 2011; Neu et al., 2013; Tilinina et al., \r\n2013; X.L. Wang et al., 2016). Over the NH increases in the total "


id: eb7b616cc414a25a5dab6030d7bebd04
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 34548
content:
"Figure 8.12 | Annual anomalies (with respect to the reference period 1979-2018) of the total number of extratropical cyclones (a, b) and of the number \r\nof deep cyclones (<980 hPa) (c, d) over the Northern (a, c) and the Southern (b, d) Hemispheres in different reanalyses (shown in colours in the legend).\r\nNote different vertical scales for panels (a, b) and (c, d). Thin lines indicate annual anomalies and bold lines indicate five-year running averages. (e, f) The number of reanalyses \r\n(out of five) simultaneously indicating statistically significant (90% level) linear trends of the same sign during 1979-2018 for JFM (January-February-March) over the Northern \r\nHemisphere (e) and over the Southern Hemisphere (f). Updated from Tilinina et al. (2013). Further details on data sources and processing are available in the chapter data table \r\n(Table 8.SM.1)."


id: b1d0b7f702e79d1267ac206394b8e440
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 25480
content:
"Central and South European precipitation anomalies. Over centennial \r\ntime scales, Gan and Wu (2014) reported an intensification of storm \r\ntracks in the poleward and downstream regions of the North Pacific \r\nand North Atlantic upper troposphere using the NOAA-CIRES-DOE \r\nTwentieth Century Reanalysis. Poleward migration of the SH storm \r\ntracks (Grise et al., 2014; X.L. Wang et al., 2016; Dowdy et al., 2019) \r\nwas identified during the austral summer and is closely associated \r\nwith cyclone-associated frontal activity (Solman and Orlanski, 2014, \r\n2016) and cloud cover (Bender et al., 2012; Norris et al., 2016)."


id: 1eb07bbcbf824101107acbb964750a57
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 2273
content:
"The representation of ETCs in both climate models and reanalyses \r\nis resolution-dependent, hence changes must be assessed with \r\ncaution (Section  3.3.3.3). In particular, CMIP5 models show \r\na  systematic underestimation of the intensity of ETCs (Zappa \r\net al., 2014), a  feature that is partially related to their relatively \r\ncoarse resolution or other possible deficiencies such as an excess \r\nof dissipation (Chang et al., 2013). The best representation of ETCs \r\nand their intensity in the  North Atlantic are provided by relatively \r\nhigh horizontal resolution CMIP5 models (Zappa et al., 2014). Using \r\na single high-resolution climate model, (Hawcroft et al., 2016) showed \r\nthat precipitation amount associated with ETCs was generally well \r\nsimulated, though with too much precipitation during the strongest \r\nECTs compared with observed estimations."


id: 56d1ea452804dbcb6e9dcd1946c22b69
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 11135
content:
"In summary, there is low confidence in recent changes in the total \r\nnumber of extratropical cyclones over both hemispheres. It is as likely \r\nas not that the number of deep cyclones over the NH has decreased \r\nafter 1979 and it is likely that the number of deep extratropical \r\ncyclones increased over the same period in the SH. It is likely that \r\nextratropical cyclone activity in the SH has intensified during austral \r\nsummer with no significant changes in austral winter. There is \r\nmedium confidence that boreal-winter storm tracks during the last \r\ndecades experienced poleward shifts over the NH and SH oceans. \r\nThere is low confidence of changes in extratropical cyclone activity \r\nprior 1979 due to inhomogeneities in the intrumental records and \r\nmodern reanalyses. "


id: d71ef64bb942ddef1661663b6ee1a8e4
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 31361
content:
"Analysis of storm track activity over longer periods suffers from \r\nuncertainties associated with changing data assimilation and \r\nobservations before and during the satellite era, resulting in in \r\nhomogeneities and discontinuities in centennial reanalyses (Krueger \r\net al., 2013; X.L. Wang et al., 2013, 2016; Chang and Yau, 2016; \r\nVarino et al., 2019). Feser et al. (2015) reviewed multiple storm track \r\nrecords for the Atlantic-European sector and demonstrated growing \r\nstorm activity north of 55degN from the 1970s to the mid-1990s with \r\ndeclining trend thereafter, sugesting strong inter-decadal variability \r\nin storm track activity. This was also confirmed by Krueger et al. \r\n(2019) from the analysis of geostrophic winds derived from sea level \r\npressure gradients. "


id: 40ab68926f8a98f772d38fc88d62b09a
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 7553
content:
"Poleward deflection of mostly oceanic winter storm tracks since \r\n1979 was reported in both the North Atlantic and North Pacific \r\n(Tilinina et al., 2013; J. Wang et al., 2017). This large-scale tendency \r\nhas regional variations and may be seasonally dependent. Wise and \r\nDannenberg (2017) reported a  southward shift in the east Pacific \r\nstorm track from the 1950s to mid-1980s followed by northward \r\ndeflection in the later decades. (King et al., 2019) reported an \r\nassociation of Atlantic storm track migrations with SSW events with "


id: a8ab339704f50d7ad3238c259083844d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 24067
content:
"Greenland and New Zealand (Bozkurt et al., 2018; Mattingly et al., \r\n2018; Little et al., 2019), contributing about 45-60% of total annual \r\nprecipitation in subtropical South America (Viale et al., 2018). They \r\nalso transport moisture from South America to the western and \r\ncentral South Atlantic, feeding the ARs that reach the west coast \r\nof South Africa (Ramos et al., 2019). However, the estimation of \r\nprecipitation rate from ARs can have large uncertainties, especially \r\nas ARs hit topographically complex coastal regions (Behrangi \r\net al., 2016), which can cause complexities in quantifying AR-related \r\nprecipitation."


id: 70c97f4ea4dc4ed30e3cfb0e4a585b4d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 15373
content:
"Analysis of observed trends in the characteristics of ARs has been \r\nlimited. Gershunov et al. (2017) and Sharma and Dery (2019) have \r\nshown a rising trend in land-falling AR activity over the west coast \r\nof North American since 1948. (Gonzales et al., 2019) have also \r\ndocumented a  seasonally-asymmetric warming of ARs affecting \r\nthe West Coast of the USA since 1980, which has hydrological \r\nimplications for the timing and magnitude of regional runoff. Longer\u0002term paleoclimate analysis of ARs is even more limited, although \r\nLora et al. (2017) reported that in the last glacial maximum, AR \r\nlandfalls over the North American west coast were shifted southward \r\ncompared to the present conditions. "


id: 83327f3a774d1303caf6ed3fc18e7ec3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 18167
content:
"In summary, it is likely that there was an increasing trend in the \r\nAR activity in the eastern North Pacific since the mid-20th century. \r\nHowever, there is low confidence in the magnitude of this trend \r\nand no formal attribution, although such an increase in activity is \r\nconsistent with the expected and observed increase in precipitable \r\nwater associated with human-induced global warming. "


id: 39857e118d89aa9454e55aadc5f24974
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 6424
content:
"Following on from the assessment in Chapters 2 and 3, this section \r\nconsiders changes in modes of variability at seasonal to interannual \r\ntime scales in terms of their implications on recent water cycle \r\nchanges. These modes are described in details in Technical Annex IV."


id: af63e643a886e3b5e6adc3870234381b
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 25108
content:
"The amplitude of the El  Nino-Southern Oscillation (ENSO; Section \r\nAIV.2.3) variability has increased since 1950 (Section 2.4.2) but there \r\nis no clear evidence of human influence (Sections 2.4.2 and 3.7.3). "


id: db59b1639bf27db1e50b370dee0b79b9
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 32021
content:
"ENSO influences precipitation and evaporation dynamics, river flow \r\nand flooding at a global scale (Figure 3.37; Ward et al., 2014, 2016; \r\nMartens et al., 2018). Reconstruction (1804-2005) of Thailand's \r\nChao Praya River peak season streamflow displays a  strong \r\ncorrelation with ENSO (Xu et al., 2019). Based on water storage \r\nestimates from 2002 to 2015, drought conditions over the Yangtze \r\nRiver basin followed La Nina events and flood conditions followed \r\nEl Nino events (Z. Zhang et al., 2015). Strong correlation between \r\nENSO and terrestrial water storage has been identified mostly in the \r\nsubtropics but with diverse intensities and time lags depending on \r\nthe region (Ni et al., 2018). The likelihood of increased/decreased \r\nflood hazard during ENSO events has a complex spatial pattern with \r\nlarge uncertainties (Emerton et al., 2017). "


id: c480e2c0d08c5e43b735752afedfe78c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 28491
content:
"Intraseasonal variability, like the Madden Julian Oscillation (MJO, \r\nSection AIV.2.8) and the Boreal Summer Intraseasonal Oscillation \r\n(BSISO), are highly relevant to the water cycle (Maloney and Hartmann, \r\n2000; Lee et al., 2013; Yoshida et al., 2014; Nakano et al., 2015). Since \r\nAR5, studies on MJO teleconnections within the tropics and from "


id: 1f2d455377286f756ba168521c2f716
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 2343
content:
"have been developed since its discovery, a better understanding of \r\nits dynamics is still needed (Jiang et al., 2020; Zhang et al., 2020). \r\nFurthermore, metrics based on dynamical processes are needed to \r\nassess model simulations of these events (Stechmann and Hottovy, \r\n2017; B.  Wang et al., 2018) as well as related teleconnections \r\n(J. Wang et al., 2020)."


id: 8502116eee24cdbff77ea9aa60beb29c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 18447
content:
"the tropics to higher latitudes have continued (Guan et al., 2012; \r\nMundhenk et al., 2018; Tseng et al., 2019; Aberson and Kaplan, \r\n2020; Finney et al., 2020b; Fowler and Pritchard, 2020; Fromang and \r\nRiviere, 2020). "


id: bf39fda4cbbb313f57e94b22ec9d290e
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 27638
content:
"The strength and frequency of the MJO have increased over the past \r\ncentury (medium confidence) (Oliver and Thompson, 2012; Maloney \r\net al., 2019; Cui et al., 2020) because of global warming (Arnold \r\net al., 2015; Carlson and Caballero, 2016; Wolding et al., 2017; \r\nMaloney et al., 2019). A 20th century reconstruction suggests a 13% \r\nincrease of the MJO amplitude (Oliver and Thompson, 2012), with \r\ndifferences in seasonal variability (Tao et al., 2015; Z. Wang et al., \r\n2020). However, up to half of changes recorded during the second \r\nhalf of the 20th century could be due to internal variability (Schubert \r\net al., 2013). Other observed changes in MJO characteristics include \r\na  decrease (by three to four days) in the residence time over the \r\nIndian Ocean but an increase (by five to six days) over the Indo\u0002Pacific and Maritime Continent sectors (Roxy et al., 2019). "


id: 508372635db7ba6c22e81bde247d7ec0
created_at: 2023-03-16 14:00:45
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content:
"In summary, multiple water cycle changes related to ENSO and IOD \r\nteleconnections have been observed across the 20th century (high \r\nconfidence), mostly dominated by interannual to multi-decadal \r\nvariations. The MJO amplitude has increased in the second half of \r\nthe 20th century partly because of anthropogenic global warming \r\n(medium confidence) altering regional precipitation signals."


id: 4f8b3e376c985e13695105e69053fe4b
created_at: 2023-03-16 14:00:45
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content:
"Consequences of these changes are increased rainfall over South \r\nEast Asia, northern Australia, south-west Africa and the Amazon, \r\nand drying over the west coast of the USA and Equador (Roxy et al., \r\n2019). During the austral summer, air-sea interactions and location \r\nof the MJO active phase are important to modulate the strength of \r\nthe rainfall response in the South Atlantic Convergence Zone (Shimizu \r\nand Ambrizzi, 2016; Alvarez et al., 2017), including its southward \r\nshift (Barreiro et al., 2019). In the austral winter, the intraseasonal \r\nvariability is mostly influential over regions of the Amazonian basin \r\n(Mayta et al., 2019). Some MJO phases are particularly effective in \r\nconjuction with tropical cyclones in enhancing westerly moisture \r\nfluxes towards East Africa (Finney et al., 2020b)."


id: 43cb490db642ebed23af75c0286e5b49
created_at: 2023-03-16 14:00:45
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content:
"with other large-scale modes of climate variability, like ENSO (Fogt \r\net al., 2011) and the Indian Ocean Dipole (Hoell et al., 2017a), are \r\nresponsible for fluctuations in southern African rainfall (Nash, 2017) \r\nand southern South America (Gergis and Henley, 2017). In May, the \r\nSAM can trigger a southern Indian Ocean Dipole SSTA favoring more \r\nor less precipitation over the Indian sub-continent and adjacent \r\nareas (Dou et al., 2017), also affecting subsequent summer monsoon \r\nin the South China Sea (T.  Liu et al., 2018). Over South America, \r\na positive SAM is associated with dry conditions (Holz et al., 2017) \r\ndue to reduced frontal and orographic precipitation and weakening \r\nof moisture convergence. Regions particularly affected include Chile \r\n(Boisier et al., 2018) and the rivers of central Patagonia (Rivera \r\net al., 2018). "


id: 6841afe71b7892dd64f90827bc3b46ec
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"As discussed in 8.3.1.1, the definition of global water cycle intensity \r\nvaries from the simple metric of increases in global mean precipitation \r\nto broader joint considerations of water vapour and its transport, \r\nprecipitation minus evaporation (P-E) rates and continental runoff \r\n(Figure 8.1). The AR5 determined that globally averaged precipitation \r\nis virtually certain to increase with temperature and that there is high \r\nconfidence that the contrast of annual mean precipitation between \r\ndry and wet regions and seasons will increase over most of the globe \r\nas temperatures and moisture transports increase (Collins et al., \r\n2013). The AR5 also highlighted that continued ocean warming for \r\na  few decades after GHG forcing stabilizes or begins to decrease \r\nwill also lead to further increases in global mean precipitation \r\nand evaporation."


id: 91e18937ace6dfe956bad0154a6593e3
created_at: 2023-03-16 14:00:45
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content:
"In summary, while the attribution of 20th century variations of \r\nthe NAM/NAO is still unclear, there is a  strong relationship with \r\nprecipitation changes over Europe and in the Mediterranean region \r\n(high confidence). SAM teleconnections are associated with changes \r\nin moisture transport and extend to South America, Australia and \r\nAntarctica (high confidence) with documented drying occurring as \r\na result of the very likely human-induced SAM trend toward its positive \r\nphase observed from the 1970s until the 1990s (Section 3.7.2)."


id: 452b034c32ee13ba367f2eef211bcae2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"We consider global and regional climate projections of the \r\nwater  cycle, assessing projected changes in each component of \r\nthe water cycle  (Section  8.4.1) and the global-scale and regional \r\nphenomena that directly impact it (Section 8.4.2). "


id: dfda0d1e004a4d1d391922f956139856
created_at: 2023-03-16 14:00:45
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content:
"CMIP6 climate models continue to project a  steady increase in \r\nglobal mean column-integrated water vapour by around 6-13% \r\nby 2041-2060 and 5-32% by 2081-2100, depending on scenario \r\n(Table  8.1). This is consistent with projected atmospheric warming \r\n(Section  4.5.1.2) and the Clausius-Clapeyron relationship \r\n(Section 8.2.1) where every degree Celsius of warming is associated \r\nwith an approximate 7% increase in atmospheric moisture in the lower \r\natmospheric layers where most of the water vapour is concentrated. \r\nThis increase sustains a positive feedback on anthropogenic global \r\nwarming (Section  7.4.2.2). In contrast, the response of clouds is "


id: 868a958a64514e2af287fed5bae8ef92
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 18708
content:
"much more spatially heterogeneous, microphysically complex, and \r\nmodel-dependent so that the projected cloud feedbacks remain a key \r\nuncertainty for constraining climate sensitivity (Section 7.4.2.4). "


id: 2036ec35aedc4ff7600bd6e357f8a7c3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 2512
content:
"CMIP6 models project an overall decrease in near-surface relative \r\nhumidity over land, although with some regional and seasonal \r\nvariations in their response (Figure 4.26). Regional changes in near\u0002surface humidity over land are dominated by thermodynamic processes \r\nand are primarily controlled by moisture transport from the warming \r\nocean (Chadwick et al., 2016a). Increases in specific humidity lower "


id: d35c19cf646111a9e054a5feef9cdb80
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 30776
content:
"than the thermodynamic rate are explained by greater warming over \r\nland than ocean and modulated by land-atmosphere feedbacks such \r\nas soil moisture and plant stomatal changes (Section 8.2.2.1; Berg \r\net al., 2017; Douville et al., 2020). This explains why climate models \r\ncontinue to project a  contrasting response of near-surface relative \r\nhumidity, with a  slight and possibly overestimated increase over \r\nthe oceans and a consistent but possibly underestimated decrease \r\nover land (Byrne and O'Gorman, 2016; Douville and Plazzotta, 2017; \r\nR. Zhang et al., 2018)."


id: ef665761c696440028b8d6516368ead3
created_at: 2023-03-16 14:00:45
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content:
"over most of the globe as temperatures increase (high confidence), \r\nbut with large regional variations. Precipitation over the high \r\nlatitudes, equatorial Pacific Ocean, mid-latitude wet regions, and \r\nmonsoon regions were assessed as likely to increase under the \r\nRCP8.5 scenario, and in many mid-latitude and subtropical dry \r\nregions as likely to decrease (AR5 Chapters 7, 12, and 14). Extreme \r\nprecipitation over most mid-latitude land areas and wet tropical \r\nregions was assessed as very likely to become more intense and \r\nmore frequent."


id: 278d636da4aaa3fb41578f83012b18cc
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3628
content:
"In summary, there is high confidence in continued increases in global \r\nmean column integrated water vapour and near-surface specific \r\nhumidity over land. There is medium confidence in region and season\u0002dependent decreases in near-surface relative humidity over land, due \r\nto the complex physical processes involved. In general, there will be \r\nincreases in moisture transport into storm systems, monsoons and \r\nhigh latitudes (medium confidence)."


id: a79957e4ea4cfe98748f714984b9a3bb
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 23876
content:
"This section assesses projected changes in precipitation at regional \r\nscales. Note that changes in precipitation seasonality are assessed \r\nin Box 8.2 and that changes in regional monsoons are assessed in \r\nSection 8.4.2.4, where both circulation and rainfall are considered. \r\nFurther assessments of regional projections of precipitation are \r\npresented in Chapters 10, 12 and the Atlas, while a comprehensive \r\nassessment of changes in precipitation extremes is provided in \r\nChapter 11."


id: 879a4309b3f6aa4997bdf8f28bc35e68
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content:
"annual mean rainfall is likely to decrease include southern Africa, \r\ncoastal West Africa, Amazonia, south-western Australia, Central \r\nAmerica, south-western South America, and the Mediterranean."


id: d4ebea1c79a407bb7e4f025b0a9a076
created_at: 2023-03-16 14:00:45
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content:
"The AR5 identified that high-latitude precipitation increase may lead \r\nto an increase in snowfall in the coldest regions and a decrease of \r\nsnowfall in warmer regions due to a decreased number of freezing \r\ndays. The fraction of precipitation falling as snow and the duration \r\nof snow cover was projected to decrease. Heavy snowfall events \r\nglobally are not expected to decrease significantly with warming \r\nas they occur close to the water freezing point, which will migrate \r\npoleward and in altitude (O'Gorman, 2014; Turner et al., 2019). There \r\nare only a  small number of studies evaluating the implications of \r\nthis mechanism in specific regions. A study for the north-eastern USA \r\nindicates smaller reductions for major snowfall events against the \r\nbroader decline in snowfall expected from thermodynamic effects \r\n(Bintanja and Andry, 2017). Arctic snowfall is projected to decrease \r\nas rainfall makes up more of the precipitation (Zarzycki, 2018). "


id: ded6e40035f7ffca1c2b57384be358ee
created_at: 2023-03-16 14:00:45
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content:
"Beyond annual or seasonal mean precipitation amounts, an implication \r\nof the parallel intensification of the global water cycle and of the \r\nincreased residence time of atmospheric water vapour (Section 8.2.1) \r\nis that the distribution of daily and sub-daily precipitation intensities \r\nwill experience significant changes (Pendergrass and Hartmann, \r\n2014b; Pendergrass et al., 2015; Bador et al., 2018; Douville and John, \r\n2021), with fewer but potentially stronger events (high confidence)"


id: 2af148fa81180d4c5c0ecf7abbf0e5a8
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 4183
content:
"(Section  4.3.3). CMIP6 projections show that in the long-term \r\nmore drier days but more intense single events of precipitation are \r\nexpected, regardless of scenario (Figure 8.15). Over almost all land \r\nregions, it is very likely that extreme precipitation will intensify at \r\na rate close to the 7% degC-1 of global warming, but with large spatial \r\ndifferences (Sections  11.4 and 8.2.3.2). The projected increase in \r\nprecipitable water is expected to lead to an increase in the highest "


id: 5188cff67efad03f856751c89fed7676
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"possible precipitation intensities and an increase in the probability \r\nof occurrence of extreme precipitation events on the global scale \r\n(Neelin et al., 2017), regardless of how annual-mean precipitation \r\nchanges (O'Gorman and Schneider, 2009; O'Gorman, 2015). The \r\nprojected increase in heavy precipitation intensity is also found for "


id: b6eafe0194578ade8e4b222893edc0ab
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"An increase in the number of dry days is also projected in several \r\nregions of the world (Polade et al., 2014; Berthou et al., 2019a), "


id: db81d5e548ab8be24e41f5a5f0023c5b
created_at: 2023-03-16 14:00:45
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vector_id: 32050
content:
"which can dominate the annual precipitation change at least \r\nin the subtropics (Polade et al., 2014; Douville and John, 2021). \r\nThese findings are supported by CMIP6 projections showing \r\na  widespread increase in daily mean precipitation intensity over \r\nland (Figure 8.15b,d,f) as well as an increase in the number of dry \r\ndays in the subtropics and over Amazonia and Central America \r\n(Figure 8.15a,b,c). Such changes in precipitation regimes, as well as \r\nthe general increase in the frequency and intensity of precipitation \r\nextremes (Section  11.4.5), contribute to an overall increase in \r\nprecipitation variability (Polade et al., 2014; Pendergrass et al., \r\n2017; Douville and John, 2021). This is also found in CMIP6 models, \r\nwhich show a stronger increase of interannual variability than in \r\nseasonal mean precipitation changes, apart from in the winter \r\nextratropics where both quantities increase at the same rate with \r\nincreasing global warming levels (Figure 8.16). "


id: e3915a95464e552f378c57c36ec3d693
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 33283
content:
"Large differences have been found across seven global precipitation datasets, with no region showing a  consistent, statistically \r\nsignificant, positive or negative trend over the last three decades (X. Tan et al., 2020). Regional studies suggest that observed changes \r\nin precipitation seasonality are neither uniform nor stable across the 20th century (X. Li et al., 2016; Mallakpour and Villarini, 2017; \r\nSahany et al., 2018; Deng et al., 2019). Since the 1980s, there is growing evidence that contrasts between wet and dry regimes, \r\nincluding seasonality, have increased (Liu and Allan, 2013; Polson et al., 2013; Murray-Tortarolo et al., 2016; Tapiador et al., 2016; \r\nGallego et al., 2017; Polson and Hegerl, 2017; Barkhordarian et al., 2018; Lan et al., 2019; Liang et al., 2020; Schurer et al., 2020). "


id: 306fc1c3c3ca8abad4b040dbe90d461a
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 5052
content:
"In northern high latitudes, a shorter snow season (X. Zeng et al., 2018) is mainly due to an earlier onset of spring snowmelt (Peng et al., \r\n2013) which has been attributed to anthropogenic climate change (Najafi et al., 2016). Changes in snow seasonality affect streamflow \r\nat the regional scale, with an earlier peak in spring and a possible decrease of low-level flow in summer (Berghuijs et al., 2014; Kang \r\net al., 2016; Dudley et al., 2017), while glacier shrinking can also alter the low-level flow in mountain catchments (Lutz et al., 2014; Milner "


id: feba1cd178b8dc6732dc18fa7c47eb46
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 37621
content:
"et al., 2017; Huss and Hock, 2018). This can be partly ameliorated by water management in regulated catchments (Arheimer et al., 2017), \r\nbut not in large river basins such as the Amazon which also shows an increased seasonality of discharge since 1979 (Liang et al., 2020)."


id: f87ee82c77de1f97439e36c4079baaa3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"Increasing aridity contrasts between wet and dry seasons over the late 20th century have been suggested (Kumar et al., 2015), with \r\na human-induced decrease of water availability during the dry season over Europe, western North America, northern Asia, southern \r\nSouth America, Australia and eastern Africa (Padron et al., 2020). Seasonal contrasts in microwave surface soil moisture measurements \r\nhave also increased over 1979-2016 (Pan et al., 2019). Terrestrial water storage variations derived from gravimetric measurements \r\nsince 2003 show a strong seasonality which is underestimated by global hydrological models (Scanlon et al., 2019) and whose multi\u0002decadal trends are difficult to interpret given the direct effect of enhanced water use (Rodell et al., 2018; Scanlon et al., 2018)."


id: f7777b8dde9aa457dbbf1d1e3dbab97b
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 36442
content:
"In summary, there is medium confidence that the annual range of precipitation has increased since the 1980s, at least in subtropical \r\nregions and over the Amazon. There is low confidence that this increase is due to human influence and that GHG forcing has already \r\naltered the timing or duration of wet seasons. There is high confidence that the human-induced retreat of the springtime snow cover \r\nand melting of glaciers have already contributed to changes in streamflow seasonality in high-latitude and low-elevation mountain \r\ncatchments, and medium confidence that human activities have also contributed to an increased seasonality of water availability, \r\nincluding a drier dry season, in the extratropics."


id: 424d57fe88c2d979b1f8788449257982
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 7832
content:
"The AR5 reported with high confidence that the contrast between wet and dry seasons will generally increase with global warming \r\nand that monsoon onset dates will likely become earlier or show little change, while monsoon retreat dates will likely be delayed, \r\nresulting in a lengthening of the wet season in many regions. "


id: c7e9621eabab7bb75b04615026b9496b
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 29033
content:
"In summary, the annual range of precipitation, water availability and streamflow will increase with global warming over subtropical \r\nregions and the Amazon (medium confidence), especially around the Mediterranean and across southern Africa (high confidence). The \r\ncontrast between the wettest and driest month of the year is likely to increase by 3-5% degC-1 with global warming in most monsoon \r\nregions, in terms of precipitation, water availability (P-E) and runoff (medium confidence). There is medium confidence that the \r\nmonsoon season could be delayed in a warmer climate in the Sahel. There is high confidence of earlier snowmelt. "


id: dd50d8bd246007fffeb6a2f02833a97a
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 32312
content:
"Analysis of CMIP5 models suggests that atmospheric evaporative \r\ndemand will increase over most areas of the world in high-emissions \r\nscenarios (virtually certain), mostly as a consequence of an increase \r\nin vapour pressure deficit (Scheff and Frierson, 2014, 2015; Greve \r\nand Seneviratne, 2015; Vicente-Serrano et al., 2020). CMIP5 models \r\nalso project an increase in evapotranspiration over most land areas \r\n(medium confidence) (Laine et al., 2014). However, regional changes "


id: 1e176ddc8dce8030add8fc9fd4292443
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 2172
content:
"Since AR5, there is a  growing body of evidence suggesting that \r\nfuture projections in evapotranspiration are driven by changes in \r\ntemperature and relative humidity (Laine et al., 2014; Pan et al., \r\n2015; Ukkola et al., 2016a), as well as precipitation patterns, as \r\nfound in AR5."


id: 2f56586e925c78c5eb56db6c3be1c91f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 4867
content:
"Figure 8.17 | Projected long-term relative changes in seasonal mean evapotranspiration. Global maps of projected relative changes (%) in seasonal mean of \r\nsurface evapotranspiration for December-January-February (DJF; left panels) and June-July-August (JJA; right panels) averaged across available CMIP6 models (number \r\nprovided at the top right of each panel) for SSP1.2-6 (a, b) SSP2-4.5 (c, d) and SSP5-8.5 (e, f) scenario respectively. All changes are estimated in 2081-2100 relative to \r\n1995-2014. Uncertainty is represented using the simple approach. No overlay indicates regions with high model agreement, where >=80% of models agree on sign of change; \r\ndiagonal lines indicate regions with low model agreement, where <80% of models agree on sign of change. For more information on the simple approach, please refer to the \r\nCross-Chapter Box Atlas.1. Further details on data sources and processing are available in the chapter data table (Table 8.SM.1)."


id: 84cd1f8107dc2c402bd14ab74526a140
created_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 18420
content:
"confidence that warming of 2degC would increase the fraction of global \r\narea affected by flood hazard relative to warming of 1.5degC. Projected \r\nclimate-driven changes to runoff, streamflow, and flooding will occur \r\nin the context of potential human-caused land-use and land-cover \r\nchanges, which can have a large influence on surface water (Sterling \r\net al., 2013) but which have considerable uncertainty in projections \r\n(Prestele et al., 2016)."


id: 5a1dde14eb2aa4aec345cd4854b28744
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vector_id: 11691
content:
"CMIP6 models project a  geographical pattern of changes in \r\nevapotranspiration similar to previous generation models \r\n(Figure  8.17), although the magnitude is generally larger than \r\nfound for CMIP5 projections (X. Liu et al., 2020). There is, however, \r\na strong seasonality in many regions, with a larger relative increase \r\nin the winter season of the Northern Hemisphere (NH) and smaller \r\nrelative changes in the summer (Figure  8.17). Evapotranspiration \r\nincreases in most land regions, except in areas that are projected to \r\nbecome moisture-limited (due to reduced precipitation and increased \r\nevaporative demand), such as the Mediterranean, South Africa, and \r\nthe Amazonian basin (medium confidence). The patterns of change \r\nincrease in magnitude from low to high-emissions SSP scenarios \r\n(medium confidence)."


id: bb049ce7b56ffff3f34207d7766f8691
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 26963
content:
"In summary, future projections indicate that anthropogenic \r\nforcings will drive an increase in global mean evaporation over \r\nmost oceanic areas (high confidence) (Figure  8.17), an increase \r\nin global atmospheric demand (virtually certain) and an increase \r\nin evapotranspiration over most land areas, with the exception of \r\nmoisture-limited regions (medium confidence). However, substantial \r\nuncertainties in projections of evapotranspiration, especially at \r\nseasonal and regional scales, remain (see also Section 8.2.3.3 and \r\nCross-Chapter Box 5.1)."


id: e4487429562574da4f0a312533a1d878
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 33393
content:
"Changes in streamflow vary regionally and increase in magnitude \r\nwith emissions scenarios, as with runoff (although the two are not \r\nequivalent, as runoff includes both surface runoff and streamflow). \r\nStreamflow projections additionally require the use of hydrologic \r\nmodels forced by the output from climate models and have not been \r\nas widely explored as they are not variables directly included in climate \r\nmodels. On an annual basis, streamflows have been projected to \r\nincrease in the northern high latitudes and tropical Asia and Africa, and \r\nto decrease in the Mediterranean, tropical South America, and South \r\nAfrica (Doll et al., 2018). For a 4degC global warming, half of the global \r\nland area is projected to be exposed to increased high flows (average \r\nincrease 25%), while about 60% may be exposed to decreased low \r\nflows (average decrease 50%) (Asadieh and Krakauer, 2017). "


id: b1d1cc5ca0455eb680d98989225baf01
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 25481
content:
"Changes in the seasonality of runoff and streamflow are assessed \r\nin Box  8.2. The seasonality of runoff and streamflow (calculated \r\nas the annual difference between the wettest and driest months \r\nof the year), is expected to increase with global warming in the \r\nsubtropics, especially in the Mediterranean and southern Africa with \r\nhigh confidence, and in the Amazon with medium confidence. For "


id: 889f3fe330bb8ce823fca6fd20b865a
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 19023
content:
"basins, projected runoff changes show an increase until a maximum \r\nis reached, beyond which runoff steadily declines because of limited \r\nice volumes (Huss and Hock, 2018)."


id: 5f42804b8d8c05505e53e5139e171044
created_at: 2023-03-16 14:00:45
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content:
"regions where snowmelt is an important contributor to streamflow, \r\nthere is high confidence that snowmelt occurring earlier in the \r\nyear will result in peak flows also occurring earlier in the year, and \r\nmedium confidence that reduced snow volume and the weaker solar \r\nradiation earlier in the year will reduce the most intense flows (see \r\nSection 8.2.3.1). In roughly half of 56 large-scale glacierized drainage "


id: b6f49d208d610765fe5424396eae3c7c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 26312
content:
"As future changes in flood events are assessed in Chapters 9, 11 \r\nand 12, only a summary is presented here. There are a number of "


id: 18018578718e58410e1439db4647af2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 1268
content:
"with the emissions scenario (high confidence) (Figure  8.19; Scheff \r\nand Frierson, 2014, 2015; Vicente-Serrano et al., 2020). Even under \r\na  low-emissions scenario (SSP1-2.6), projections of soil moisture \r\nshow significant decreases in the Mediterranean, southern Africa, \r\nand the Amazonian basin (high confidence) (Figure 8.19). Under mid\u0002and high-emissions scenarios (SSP2-4.5 and SSP5-8.5), coherent \r\ndeclines emerge across Europe, westernmost North Africa, south\u0002western Australia, Central America, south-western North America, \r\nand south-western South America (high confidence) (Figure  8.19; \r\nCook et al., 2020). Compared to CMIP5 results, CMIP6 models exhibit \r\nmore consistent drying in the Amazonian basin (Parsons, 2020), \r\nmore extensive declines in total soil moisture in Siberia (Cook et al., \r\n2020), and stronger declines in westernmost North Africa and south\u0002western Australia (Figure 8.19). "


id: fdade11673244ed8e65696ae9284d7de
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 37427
content:
"The AR5 concluded that regional to global-scale projections of \r\naridity and drought remained relatively uncertain compared to other \r\naspects of the water cycle. It reported that there is a likely increase in \r\ndrought occurrence (medium confidence) by 2100 in regions that are \r\ncurrently drought-prone under the RCP8.5 scenario due to projected \r\ndecreases in soil moisture. It stated that it is likely that the most \r\nprominent projected decreases in soil moisture would occur in the \r\nMediterranean, south-western USA, and southern Africa, consistent \r\nwith projected changes in the Hadley circulation and increased \r\nsurface temperatures. These AR5 conclusions are generally supported \r\nby more recent analyses of CMIP5 models (Feng and Fu, 2013; Berg \r\net al., 2017; Cook et al., 2018)."


id: e8eb3e504e97d74aeb0f720b4fef7ea6
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 34161
content:
"Although there are regions where multiple models predict consistent \r\nand significant changes in soil moisture, as with evapotranspiration \r\n(Section 8.4.1.4), there is still uncertainty in these projections related \r\nto the response of plants to elevated CO2. Most models project \r\nincreases in two variables that have opposite effects on surface \r\nwater availability: plant water use efficiency (WUE) and leaf area \r\nindex (LAI; see Section  8.4.1.4). As discussed in Sections  8.2.3.3, \r\n8.3.1.4 and 8.4.1.4, there is low confidence in how these changes in \r\nplant physiology will affect future projections of evapotranspiration, \r\nand likewise, drought and aridity."


id: 9f5e30a3e4d25a21e5e35208cfe304b9
created_at: 2023-03-16 14:00:45
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vector_id: 22618
content:
"Changes in meteorological (precipitation-based) drought duration \r\nand intensity in CMIP6 models are more robust than projected \r\nchanges in mean precipitation, more than found in CMIP5 projections \r\n(Ukkola et al., 2020). Significant increases in drought duration are \r\nexpected in Central America, the Amazonian basin, south-western \r\nSouth America, the Mediterranean, westernmost North Africa, "


id: bd88969b585bf52f16767986dd869f3b
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 27390
content:
"Results from the latest generation of models in CMIP6 are largely \r\ncongruent with CMIP5. Consistent with the coherent nature of \r\nwarming in future projections, increases in vapour pressure deficit \r\nand evaporative demand are widespread and consistent across \r\nregions, seasons, and models, increasing in magnitude in accordance "


id: a8f2086951298813a8b46bd8a4ed0c2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 24106
content:
"Africa, south-western South America, south-western North America, \r\nsouth-western Australia, Central America and the Amazonian basin."


id: acc9cd7216bb2df4810d0b343da5b4f3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 24731
content:
"Mediterranean, southern Africa, south-western North America, south\u0002western South America, and south-western Australia, as well as in \r\nCentral America and the Amazonian basin. In general, these regions \r\nare expected to become drier both due to reduced precipitation \r\n(medium confidence) and increases in evaporative demand (high \r\nconfidence). These same regions are likely to experience increases in \r\ndrought duration and/or severity (high confidence). The magnitude of \r\nexpected change scales with emissions scenarios (high confidence) \r\nbut even under low-emissions trajectories, large changes in \r\ndrought and aridity are expected to occur (high confidence) with \r\nconsequences for regional water availability. In the Mediterranean, \r\nCentral Chile, and western North America, future aridification will \r\nfar exceed the magnitude of change seen over the last millennium \r\n(high confidence)."


id: faa095ac31152c05e78fe4e5e674e9c5
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 36953
content:
"century in the high-emissions scenario. Globally, peak runoff of 2.5 to \r\n3 mm yr-1 sea level equivalent occurs around 2090 (Marzeion et al., \r\n2020). Regional projections are presented in detail in Section 9.5.1 \r\nand Figure 9.21, and briefly summarized below."


id: 1595fc19211916859da796849751f7e4
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 912
content:
"Himalaya and Central Asia: Glaciers in the Himalayas feed ten of the \r\nworld's most important river systems and are critical water sources \r\nfor nearly two billion people (Wester et al., 2019). However, they are \r\nsome of the most vulnerable 'water towers' (Immerzeel et al., 2020) \r\nthat are projected to experience volume losses of approximately 30 \r\nto 100% by 2100 depending on global emissions scenarios (Marzeion \r\net al., 2020). Under mid-range emissions scenarios glaciers in this \r\nregion are projected to reach peak runoff during the period 2020 to \r\n2040 (Marzeion et al., 2020)."


id: d7972203d20a4216840363f7520c2d6e
created_at: 2023-03-16 14:00:45
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vector_id: 31443
content:
"Alaska, Yukon, British Columbia: Post-AR5 but pre-SROCC \r\nprojections indicated a  potential 70 +-  10% reduced volume of \r\nglacier ice in western Canada relative to 2005 (Clarke et al., 2015), \r\nwith few glaciers remaining in the Interior and Rockies regions \r\nand maritime glaciers in north-western British Columbia surviving \r\nonly in a diminished state. Recent global projections support these \r\nearlier findings, showing that glacier mass in western Canada and \r\nthe USA may reduce by 50% under low-emissions scenarios and \r\nbe completely lost under the highest emissions and most sensitive \r\nglacier model combinations (Figure  9.21; Marzeion et al., 2020). \r\nArctic Canada and Alaskan glaciers are projected to experience more \r\nmodest mass loss (0-60% depending on region, scenario, and model;\r\nMarzeion et al., 2020)."


id: cc1faf290895da9557029ff09fbe78ff
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"Previous assessments have concluded that recent warming has led to \r\na reduction in low-elevation snow cover (high confidence) (SROCC), \r\npermafrost (high confidence) (SROCC), and glacier mass (high to \r\nvery high confidence) (AR5; SROCC). The SROCC noted that these \r\ndeclines are projected to continue almost everywhere over the 21st \r\ncentury (high confidence), with complete glacier loss expected in \r\nregions with only small glaciers (very high confidence). The SROCC \r\nsupported the AR5 finding that glacier recession would continue \r\neven without further changes in climate. The SROCC concluded that \r\ncryosphere changes had already altered the seasonal timing and \r\nvolume of runoff (very high confidence), which in turn had affected \r\nwater resources and agriculture (medium confidence), and projected \r\npeak water runoff had already been reached before 2019 in some of \r\nthe glacier regions considered. "


id: 71d5e468b8f96502837680c162bd32b5
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 15538
content:
"Andes: Huss and Hock (2018) concluded that peak glacier mass was \r\nreached prior to 2019 for 82-95% of the glacier area in the tropical \r\nAndes. This is consistent with more recent global model simulations \r\nthat show mass loss rates from low latitude glaciers that universally \r\ndecline from the start of simulations in 2015, regardless of emissions \r\nscenario (Marzeion et al., 2020). Peak runoff in low-latitude Andean \r\nglacier-fed rivers has therefore already passed (Frans et al., 2015; Polk \r\net al., 2017) but in the Southern Andes may occur in the latter half of \r\nthe century under high-emissions scenarios (Marzeion et al., 2020)."


id: f4fa9cbc2b792f4525a0477f6fc66825
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 36053
content:
"Chapter  9  provides detailed assessment of glacier observations \r\nand projections (Figures  9.20 and 9.21, and Section  9.5.1). Here, \r\na  summary of their key findings is presented. Since SROCC, the \r\ncoordinated Glacier Model Intercomparison Project (GlacierMIP; \r\nBox  9.3; Marzeion et al., 2020) has advanced modelling efforts. \r\nGlobal glacier volumes will substantially decline in coming decades \r\nregardless of emissions scenario; under a  high-emissions scenario \r\nsome areas will lose nearly all of their glacier mass (Section 9.5.1.3). \r\nThe projected global glacier mass loss over 2015-2100 is 29,000 \r\n+-  20,000 Gt for SSP1-2.6 to 58,000 +-  30,000 Gt for SSP5-8.5 \r\n(Section 9.5.1). Because of their lagged response to warming, glaciers \r\nwill continue to lose mass for decades even if global temperature is \r\nstabilized (very high confidence) (Section 9.5.1)."


id: 8f13728ba86d85faff0e7af4bc84d5e4
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 20050
content:
"In summary, glaciers are projected to continue to lose mass under all \r\nemissions scenarios (very high confidence). Runoff from glaciers is \r\nprojected to peak at different times in different places, with maximum \r\nrates of glacier mass loss in low latitude regions taking place in the \r\nnext few decades in all scenarios (high confidence). While runoff from \r\nsmall glaciers will typically decrease because of glacier mass depletion, \r\nrunoff from larger glaciers will increase with increasing global warming \r\nuntil glacier mass is similarly depleted, after which runoff peaks and \r\nthen declines and which tends to occurs later in basins with larger \r\nglaciers and higher ice-cover fractions (high confidence). Glaciers in \r\nthe Arctic and Antarctic will continue to lose mass through the latter \r\nhalf of the century and beyond (high confidence)."


id: 7ff8b7a3347e72cd581719441f2cacb
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 17678
content:
"Global glacier mass loss projections show a  scenario-dependent \r\ngeographic partitioning of when peak in runoff occurs (Marzeion \r\net al., 2020), consistent with previous studies (Radic et al., 2014; Huss \r\nand Hock, 2018; Hock et al., 2019b). Under a low-emissions scenario \r\n(Marzeion et al., 2020) all regions exhibit runoff in the decades \r\nprior to 2050. Under a high-emissions scenario however, low- and \r\nmid-latitude regions show peak runoff before approximately 2060, \r\nwhereas Arctic regions peak in later decades around 2070-2090. \r\nAntarctic glacier losses will not have peaked by the end of the "


id: 29590b40ec716535c96e159c681d0da2
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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content:
"et al., 2017; Magnin et al., 2020) no clear projections are currently \r\navailable (see discussion in Chapter 9). Projections of lake level means \r\nand variability show substantial changes for individual lakes (Bucak \r\net al., 2017; Li et al., 2021) but can be sensitive to methodology, due \r\nto the competing processes involved (Notaro et al., 2015). Projected \r\nchanges to wetlands and lakes due to climate change will occur in \r\nthe context of widespread and continuing human-caused conversion \r\nand degradation of wetlands (e.g, Davidson, 2014), and where water \r\nwithdrawals have a large impact on lake levels (e.g., Micklin, 2016)."


id: 5509ac8b7a47e26c1d861b123dc1ed49
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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index: climate_gpt_only_giec
vector_id: 10836
content:
"The AR5 assessed as very likely that the amount and seasonal \r\nduration of Northern Hemisphere (NH) snow cover will reduce under \r\nglobal warming (AR5 Sections 11.3.4.2 and 12.4.6.2). Changes in the \r\ntotal amount of water in the snow cover (snow water equivalent) \r\nare less certain because of the competing influences of temperature \r\nand precipitation."


id: c30381a983b1394bc0fd54518e98f089
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 28262
content:
"As snow cover is assessed in Chapter  9  (Section  9.5.3.3), only an \r\noverview of that assessment is provided here. Changes in seasonality \r\nof snow cover are assessed in Box  8.2. The continued consistency \r\nof reported results across all generations of model projections, \r\nalong with improvements in process understanding, has increased \r\nconfidence in snow cover projections since AR5. "


id: 902f1eee02be5894ef22d4972d0cc73d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 20218
content:
"In summary, there is medium confidence that inland wetland extent \r\nwill decrease in regions of projected precipitation decrease and \r\nevaporation increase, and high confidence that sea level rise will \r\nincrease saltwater intrusion into coastal wetlands. However, there \r\nis low agreement on the influence of sea level rise on the extent \r\nof coastal wetlands. Regarding lakes, there is high confidence for \r\ntemperature increases and ice decreases, based on both projections \r\nand physical expectations, and low confidence for non-homogeneous \r\ndecreases in mixing, given there is currently limited evidence."


id: d190562b775f5890f8452b1fdb891c16
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 30502
content:
"In summary, based on the results of Chapter  9, it is now virtually \r\ncertain that future NH snow cover extent and duration will continue \r\nto decrease with global warming. While most studies have focused \r\non the NH, process understanding suggests with high confidence that \r\nthese results apply to the Southern Hemisphere (SH) as well. There is \r\nhigh confidence in snowmelt occurring earlier in the year. Changes \r\nto the timing and amount of snowmelt will have a strong influence \r\non all the other aspects of the water cycle in regions with seasonal \r\nsnow, including run-off, soil moisture, and evapotranspiration."


id: 6116c1851dbf445fb65956127db9e716
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 12847
content:
"The AR5 did not include specific projections for wetlands and lakes. \r\nThe SRCCL and SROCC provided some discussion of wetlands \r\nprojections. For coastal wetlands, SRCCL noted the importance of sea \r\nlevel rise for increased saltwater intrusion, although projections of \r\ncoastal wetland area with sea level rise are inconclusive. Some studies \r\nproject substantial decreases (Spencer et al., 2016) while others \r\nindicate possible increases (Schuerch et al., 2018). SRCCL also noted \r\nthe general expectation for decreases in water resources, including \r\nwetlands, in areas of decreased rainfall due to increased evaporation."


id: e07ada7f33910424b48f1f8b4c5074a9
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content:
"Local studies of inland wetlands project decreases in a  range of \r\nenvironments including mountain (Lee et al., 2015), mid- to high \r\nlatitude (D. Zhao et al., 2018), and prairie (Sofaer et al., 2016) regions. \r\nIn addition to affecting wetland extent and density, changes in \r\nflooding can also affect the connectivity between wetlands and rivers \r\n(Karim et al., 2016). Despite a number of uncertainties underlying the \r\ngeneral response of wetlands to climate change, there are multiple \r\nways climate change may cause considerable stress on both inland \r\nand coastal wetlands (Junk et al., 2013; Moomaw et al., 2018)."


id: ace502a45b1d6f1a973d4f3285bea577
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content:
"Globally, two modelling studies have shown substantial decreases in \r\ngroundwater in regions including the Mediterranean, north-eastern \r\nBrazil and south-western Africa, with less clarity for other regions \r\n(Doll, 2009; Portmann et al., 2013). Recent regional-scale analyses \r\nof the impact of water cycle changes on groundwater recharge \r\n(e.g., Meixner et al., 2016; Tillman et al., 2017; Shrestha et al., 2018) \r\nsuggest changes in both seasonality and spatial distribution, which are \r\namplified under a higher greenhouse-gas emissions scenario (i.e., RCP \r\n8.5 compared to RCP4.5). Seasonality changes are linked to increases \r\nduring wet winter periods and declines during dry summer periods. "


id: fbf6eb501f3574c23143a0df8e44deff
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content:
"Widespread changes are also projected for lakes (Woolway et al., \r\n2020), including changes in lake temperature (Fang and Stefan, 1999; \r\nSahoo et al., 2016), ice (Sharma et al., 2019), evaporation (W. Wang \r\net al., 2018), and stability and mixing (Woolway and Merchant, \r\n2019). Note that lake ice is also considered in Chapter  12 of this \r\nReport. To date, CO2-induced lake acidification, analogous to ocean \r\nacidification, has not been the focus of many studies but may occur \r\nwith continued emissions (Phillips et al., 2015). While glacier lakes in \r\ngeneral increase with melting glaciers (Linsbauer et al., 2016; Colonia "


id: 139c84438b7c8eb34528748a4dc0223c
created_at: 2023-03-16 14:00:45
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content:
"2010), the direct CO2 effect (Biasutti, 2013) and land-atmosphere \r\ninteractions (Chadwick et al., 2017; Kooperman et al., 2018) influence \r\nprojections. CMIP6 models project a clear northward ITCZ shift over \r\neastern Africa and the Indian Ocean as well as a  southward shift \r\nover the eastern Pacific and Atlantic oceans, as a result of regionally\u0002contrasting inter-hemispheric energy flows (Mamalakis et al., 2021). \r\nThe northward movement of the ITCZ over Africa has been linked to an \r\nintensification of the Saharan heat low associated with greenhouse \r\ngas (GHG) warming (Dong and Sutton, 2015), causing the tropical \r\nrain belt to seasonally migrate farther northward and reside there \r\nlonger (Cook and Vizy, 2012; Dunning et al., 2018). In southern Africa, \r\nthe projected delay in the wet season onset (Dunning et al., 2018)\r\nis also associated with a  circulation-based northward shift in the \r\ntropical rain band (Lazenby et al., 2018). "


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vector_id: 29093
content:
"Changes in spatial distribution are linked with increases in more humid \r\nregions and declines in more arid locations. Uncertainty in projections \r\nof groundwater were found to be substantially influenced by the \r\nconceptual and numerical models employed to estimate groundwater \r\nrecharge (Meixner et al., 2016; Hartmann et al., 2017). Accordingly, \r\ncurrent research on estimating water cycles change on groundwater \r\nincludes a  focus on improving the numerical representation of \r\ngroundwater systems (Bierkens et al., 2015; Doll et al., 2016). "


id: 2d50b32b343fd5f441c311675795042d
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 4572
content:
"In summary, based on known limitations in current modelling, no \r\nconfident assessment of groundwater projections is made here, \r\nalthough important climate-related changes in groundwater \r\nrecharge are expected. In many environments, such climate-related \r\nimpacts are expected to occur in the context of substantial human \r\ngroundwater withdrawals depleting groundwater storage."


id: e26a3d65ea7ca14f302ec4a80b27c587
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 33129
content:
"In summary, consistent with the AR5, the overall weakening of the \r\ntropical circulation is projected in CMIP5 and CMIP6 simulations \r\nwith high confidence. It is likely that the zonal mean of the ITCZ \r\nwill narrow and strengthen in the core region with projected surface \r\nwarming (high confidence). Distinct regional shifts in the ITCZ will \r\nbe associated with regional changes in precipitation amount and \r\nseasonality (medium confidence)."


id: f3a319047e1a8b2f875ce31504b7abd4
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 35845
content:
"A weakening of the tropical circulation represents a balance between \r\nthermodynamic increases in low level water vapour (about 7% degC-1) \r\nand smaller increases in global precipitation (1-3% degC-1) that are \r\ninfluenced by rapid adjustments to radiative forcings as well as slow \r\nresponses to warming (Section 8.2.2.2; Bony et al., 2013; Chadwick \r\net al., 2013; Ma et al., 2018). Since AR5, additional drivers of tropical \r\ncirculation weakening have been identified, including mean SST \r\nwarming and changes in spatial patterns of SST (He and Soden, \r\n2015), and the direct CO2 radiative effect (Bony et al., 2013; He and \r\nSoden, 2015; Merlis, 2015). "


id: 8f63e250e79f27ecbd0e83e566f7dc60
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 20107
content:
"The AR5 found that the Hadley cells are likely to slow down and \r\nexpand in response to radiative forcing, but with considerable \r\ninternal variability. Given the complexities in forcing mechanisms, \r\nAR5 assigned low confidence to near-term changes in the structure \r\nof the Hadley circulation. The widening Hadley cells were expected to \r\nresult in a poleward expansion of subtropical dry zones."


id: 5b90056f6dff7263fa3c4eda9ac80a10
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 11905
content:
"Model simulations since AR5 project a more noticeable and consistent \r\nweakening of the Northern Hemisphere (NH) winter Hadley cell than \r\nthe Southern Hemisphere (SH) winter cell (Seo et al., 2014; Zhou \r\net al., 2016), related to changes in meridional temperature gradient, \r\nstatic stability, and tropopause height (Seo et al., 2014; D'Agostino \r\net al., 2017). Changes in SST patterns reduces the magnitude of \r\nHadley cell weakening (Gastineau et al., 2009; Ma et al., 2012). There \r\nis considerable structure in Hadley circulation strength changes \r\nwith longitude, associated with cloud-circulation interactions \r\n(Su et al., 2014). Subtropical anticyclones are projected to intensify \r\nover the north Atlantic and south Pacific but to weaken elsewhere \r\n(He et al., 2017)."


id: dcc3c6510b26c29a56ccf8c898de17f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 32232
content:
"A consistent poleward expansion of the edges of the Hadley cells is \r\nprojected (Nguyen et al., 2015; Grise and Davis, 2020), particularly in the \r\nSH, consistent with observed trends (Figure 8.21 and Section 8.3.2.2; \r\nNguyen et al., 2015). The main driver of future expansion appears to \r\nbe greenhouse gas forcing (Grise et al., 2019), with uncertainty in \r\nmagnitude due to internal variability (Kang et al., 2013). Proposed \r\nmechanisms for poleward expansion include increased dry static \r\nstability (Frierson et al., 2007; Lu et al., 2007), increased tropopause \r\nheight (Chen and Held, 2007; Chen et al., 2008), stratospheric \r\ninfluences (Kidston et al., 2015) and radiative effects of clouds and \r\nwater vapour (Shaw and Voigt, 2016; see also Section 4.5.1.5). Hadley \r\ncell expansion is thought to be associated with the precipitation "


id: 505d538a58d70abe63a037d3dc671d78
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 10090
content:
"Regional shifts in tropical convergence zones are much larger than \r\ntheir zonal mean, and associated regional changes in precipitation \r\n(Chadwick et al., 2013; Mamalakis et al., 2021) are characterized by \r\nconsiderable uncertainties across models (Kent et al., 2015; Oueslati \r\net al., 2016). Over the tropical oceans, shifts in rain bands are strongly \r\ncoupled with changes in SSTs (Xie et al., 2010; Huang et al., 2013). \r\nOver tropical land, factors including remote SST increases (Giannini, "


id: 4696ae68271818a6b43b5bbbf8e81cbe
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 8487
content:
"declines projected in many subtropical regions (Shaw and Voigt, \r\n2016), but more recent work suggests that these reductions are \r\nmainly due to the direct radiative effect of CO2 forcing  (He and \r\nSoden, 2015), land-sea contrasts in the response to forcing \r\n(Shaw and Voigt, 2016; Brogli et al., 2019) and SST changes (Sniderman \r\net al., 2019). In semi-arid, winter rainfall-dominated regions (such \r\nas the Mediterranean), thermodynamic processes associated with \r\nthe land-sea thermal contrast and lapse rate changes dominate the \r\nprojected precipitation decline in summer, whereas circulation \r\nchanges are of greater importance in winter (Brogli et al., 2019). \r\nThe hydroclimates in these regions are projected to evolve with time \r\ndue to changing contributions from rapid atmospheric circulation \r\nchanges and their associated SST responses, as well as slower SST \r\nresponses to anthropogenic forcing (Zappa et al., 2020). "


id: 6e86489c3b4eccd28f96ed9908bb2b75
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 15018
content:
"responses to global warming have been highlighted by numerical \r\nexperiments with both comprehensive and simplified models. Results \r\nsuggest a transient strengthening of the Walker circulation related to \r\nIndian Ocean warming (L. Zhang et al., 2018), followed by a slower \r\nweakening linked to a  strengthened eastern Pacific cold tongue \r\nwarming emerging after 50-100 years (Section  7.4.4.2.1; Heede \r\net al., 2020)."


id: 530f32ac778405b99e87863dc384169c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 10532
content:
"CMIP6 projections provide further evidence of a  significant long\u0002term weakening of the Walker circulation (Figure 8.21). For instance, \r\na  pronounced weakening of the upper-level tropical easterly jet is \r\nprojected both over the Indian Ocean and tropical eastern Pacific, \r\nwhere declines are projected to exceed 70% by 2100 in the high\u0002emissions SSP5-8.5 scenario (S. Huang et al., 2020). CMIP6 models \r\nagree on a  future decrease of the equatorial zonal temperature \r\ngradient (Fredriksen et al., 2020), which can lead to weaker trade \r\nwinds over the tropical Pacific. However, CMIP6 models show \r\na  diversity of SST warming patterns in the tropical Pacific (Freund \r\net al., 2020), which contributes to uncertainties in the response of \r\nboth Walker circulation and ENSO to continued warming. "


id: e5ffec11c7d1c92e9f40acedc515a427
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 33676
content:
"In summary, CMIP5 and CMIP6 models project a weakening of the \r\nHadley cells, with high confidence for the NH in boreal winter and \r\nlow confidence for the SH in austral winter. The Hadley cells are \r\nprojected to expand polewards with global warming, most notably \r\nin the SH (high confidence). There is currently low confidence in the \r\nimpacts on regional precipitation in subtropical regions. "


id: bae2d261e45ee09715052b23276867a3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 26943
content:
"In summary, there is high confidence that the Pacific Walker circulation \r\nwill weaken by the end of the 21st century, and will be associated \r\nwith decreased precipitation over the western tropical Pacific \r\nand increases farther east. Discrepancies between observed and \r\nsimulated changes in SSTs in the tropics indicate that a temporary \r\nstrengthening of the Walker Circulation can arise from a  transient \r\nresponse to GHG radiative forcing (low confidence) and from internal \r\nvariability (medium confidence)."


id: c6213bb3c333bc4958b20356a975e77b
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 28747
content:
"The AR5 determined that the Pacific Walker circulation was likely to \r\nslow down over the 21st century, which would lead to decreased \r\nprecipitation over the western tropical Pacific and increases over the \r\ncentral and eastern Pacific. Recent studies show consistency with \r\nAR5 conclusions but also show an eastward shift over the Pacific, \r\nmostly due to a shift towards more 'El Nino-like' conditions under \r\nglobal warming (Bayr et al., 2014). Other studies suggest that the \r\nweakening of the Walker circulation is related to the response \r\nof the western North Pacific monsoon and to changing land-sea \r\ntemperature contrasts, while a positive ocean-atmosphere feedback \r\namplifies the weakening of both east-west SST gradient and trade \r\nwinds in the tropical Pacific (Zhang and Li, 2017)."


id: df5a175ae1fb69b11c9de7459e23ce91
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 32636
content:
"Regions: Regional storm tracks \r\nmoving polewards at different rates in \r\ndifferent basins. Southern \r\nhemisphere storm tracks have moved \r\npolewards more clearly, partly driven \r\nby ozone depletion. Poleward \r\nmovement likely to weaken as ozone \r\nhole recovers."


id: 5aa446bd09981dff81a5748c9619e07
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
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vector_id: 11782
content:
"Figure 8.21 | Schematic depicting large-scale circulation changes and impacts on the regional water cycle. The central figures show precipitation minus \r\nevaporation (P-E) changes at 3degC or global warming relative to an 1850-1900 base period (mean of 23 CMIP6 SSP5-8.5 simulations). Annual mean changes (large map) \r\ninclude contours (ocean only) depicting control climate P-E = 0 mm day-1 lines with the solid contour enclosing the tropical rain belt region and dashed lines representing the \r\nedges of subtropical regions. Confidence levels assess understanding of how large-scale circulation change affect the regional water."


id: 25cb74b74dbe2fdb328ed9d7a993d7bc
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3373
content:
"In AR5, monsoon precipitation over land was projected to intensify \r\nby the end of the 21st century, due to thermodynamic increases in \r\nmoisture convergence despite weakening of the tropical circulation \r\n(see Section 8.2.1.3). Following the definition of regional monsoons \r\nin Annex V  and Figure  8.11, and the assessment of the observed \r\nchanges (Section  8.3.2.4), here we provide an assessment of \r\nprojected changes in regional monsoons. Assessment is provided \r\neither in terms of SSP and RCP scenarios and global warming levels \r\navailable since AR5, or from the newly available CMIP6 projections \r\n(Figure  8.22 and Table  8.2). Table  8.2 provides projected changes \r\nacross the five SSPs used in this Report for precipitation (mm day-1), \r\nP-E (mm day-1) and runoff (mm day-1) over the regional monsoons \r\nfor the mid (2041-2060) and long term (2081-2100). "


id: d63eb13758b12db76f829fe41fbbbb75
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 31221
content:
"In AR5, South and South East Asian monsoon (SAsiaM) precipitation \r\nwas projected to increase by the end of the 21st century but with \r\na  weakening of the circulation, with high agreement across the \r\nCMIP5 models (Kitoh et al., 2013; Menon et al., 2013; Sharmila et al., \r\n2015; Sooraj et al., 2015; Kitoh, 2017; Kulkarni et al., 2020). Since \r\nAR5, most studies have confirmed projected increases in South Asian \r\nmonsoon precipitation (high confidence), while one high-resolution \r\nmodel (35 km in latitude/longitude) projects monsoon precipitation \r\ndecreases during the 21st century following the RCP4.5 scenario \r\n(Krishnan et al., 2016)."


id: 296caf2e4f5e51c4400a8386a8d681e3
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3957
content:
"Future monsoon projections from CMIP6 models show an increase \r\nof SAsiaM precipitation across all the scenarios and across all the \r\ntime frames (Figure 8.22) with the maximum increase at the end of \r\nthe 21st century in SSP5-8.5 (Almazroui et al., 2020c; Z. Chen et al., \r\n2020b; Ha et al., 2020; Wang et al., 2021). Table 8.2 confirms that \r\nchanges in runoff and P-E over SAsiaM region are positive and largest \r\nin the higher emissions scenarios considered, as in precipitation. On \r\nthe other hand, changes in the ensemble mean for all the variables \r\nconsidered in the SSP1-1.9 scenario are negative for both mid and \r\nlong-term periods (Table  8.2). This is also consistently reflected \r\nin the spatial map of future precipitation changes (Figure  8.15). \r\nDifferent near-term projections of the SAsiaM may result given the "


id: ec03c1875bf37306c0f3aeea8f482b1c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 34631
content:
"Figure 8.22 | Projected regional monsoons precipitation changes. Percentage change in projected seasonal mean precipitation over regional monsoon domains (as \r\ndefined in Figure 8.11, Section 8.3.2.4 and Annex V) for near term (2021-2040), mid-term (2041-2060), and long term (2081-2100) periods based on 24 CMIP6 models and \r\nthree SSP scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5). Further details on data sources and processing are available in the chapter data table (Table 8.SM.1)."


id: b46546ce78a2ae17faf6d20dc849027f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
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vector_id: 25900
content:
"diversity in the future aerosol emissions pathways and policies for \r\nregulating air pollution (Wilcox et al., 2020). Additionally, near-term \r\nprojections of SAsiaM precipitation are expected to be constrained \r\nby internal variability associated with the PDV (X.  Huang et al., \r\n2020a). CMIP6 models also indicate a lengthening of the summer \r\nmonsoon over India by the end of the 21st century, at least in \r\nSSP2-4.5, with considerable inter-model spread in the projected late \r\nretreat (Ha et al., 2020)."


id: 661c312799567dd402c39c65b7dcadff
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 13660
content:
"intensify the EAsiaM circulation during the 21st century. However, \r\nthere are large uncertainties in projected water cycle changes over \r\nthe region (Endo et al., 2018), mostly in the near-term because of \r\nuncertainties in future aerosol emissions scenarios (Wilcox et al., \r\n2020), as well as due to the interplay between internal variability \r\nand anthropogenic external forcing (Wang et al., 2021)."


id: 2669e961593f2d467c34712761dce8a7
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 3455
content:
"In summary, consistent with AR5, there is high confidence that \r\nSAsiaM precipitation is projected to increase during the 21st century \r\nin response to continued global warming across the CMIP6 higher \r\nemissions scenarios, mostly in the mid- and long terms. "


id: 4f227e8e86738976c60977647647f9be
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 9893
content:
"In AR5, the East Asian monsoon (EAsiaM) was projected to intensify \r\nin terms of precipitation, with an earlier onset and longer duration \r\nof the summer season. Since AR5, there has been improved \r\nunderstanding of future projected changes in the EAsiaM. "


id: 1863e38d036cdbfffaf3bd1cf747944c
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 1333
content:
"In summary, despite the uncertainties in the monsoon circulation \r\nresponse in CMIP5 and CMIP6 models, there is high confidence that \r\nsummer monsoon precipitation over East Asia will increase in the \r\n21st century and medium confidence that the monsoon season will \r\nbe longer."


id: 7fac8e032bf957fdd80ac5933af713ca
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 17633
content:
"The AR5 concluded that projections of West African monsoon \r\n(WAfriM) rainfall are highly uncertain in CMIP3 and CMIP5 models, \r\nbut still suggest a small delay and intensification in late wet season \r\nrains. Studies published since AR5 are broadly consistent with this \r\nassessment. CMIP6 models agree on statistically significant projected "


id: 1fe47cdcafe449c29d4b7a3f1bc05415
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 2453
content:
"Changes in seasonality (Box 8.2) are projected with a later monsoon \r\nonset (high confidence) over the Sahel and a late cessation (medium \r\nconfidence), suggesting a  delayed wet season as a  regional \r\nresponse to global GHG forcing (Biasutti, 2013; Dunning et al., 2018; \r\nAkinsanola and Zhou, 2019). Rainfall distribution is projected to be \r\nhighly variable with a decrease in the number of rainy days in the \r\nwestern Sahel, consistent with an increase in consecutive dry days \r\nand a reduction in the number of growing season days (Cook and \r\nVizy, 2012; Diallo et al., 2016). A decrease in the frequency but an \r\nincrease in the intensity of very wet events is projected to be more \r\npronounced over the Sahel than over Guinean coast, and also under \r\nhigher emissions scenarios (i.e., RCP8.5; Sylla et al., 2015; Akinsanola \r\net al., 2018)."


id: 43592129a28834601eee8a626d72b3e7
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 8003
content:
"In summary, there is low agreement on a  projected decrease of \r\nNAmerM precipitation, however there is high confidence in delayed \r\nonsets and demises of the summer monsoon."


id: 51c98ce285f339945c66c2302a5209ac
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 10328
content:
"The AR5 reported medium confidence that the South American \r\nmonsoon (SAmerM) overall precipitation will remain unchanged, and \r\nmedium confidence in projections of extreme precipitation. The AR5 \r\nalso stated high confidence in the spatial expansion of the SAmerM, \r\nresulting from increased temperature and humidity."


id: f412c1a4ef9f0c9d1f10be7894006b75
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 35909
content:
"In summary, post-AR5 studies and newly available CMIP6 results \r\nindicate projected rainfall increases in the eastern-central WAfriM \r\nregion but decreases in the west (high confidence), with a delayed \r\nwet season (medium confidence). Overall, WAfriM summer \r\nprecipitation is projected to increase during the 21st century but \r\nwith larger uncertainty noted under high-emissions scenarios \r\n(medium confidence)."


id: 8e371494e86be7c04faa7151cd40c7a1
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 19904
content:
"The AR5 concluded that the North American monsoon (NAmerM) \r\nwill likely intensify in the future, even though there is low agreement\r\namong models. The AR5 reported medium confidence that \r\nprecipitation associated with the NAmerM will arrive later in the \r\nannual cycle and persist longer."


id: 757c9f2d5b5d2281bc1d0606d820800f
created_at: 2023-03-16 14:00:45
updated_at: 2023-03-16 14:00:45
content_type: text
index: climate_gpt_only_giec
vector_id: 16072
content:
"Since AR5, analyses of CMIP5 projections suggest little change in the \r\noverall amount of NAmerM precipitation in response to rising global \r\nsurface temperature. However, significant declines are projected in \r\nthe early monsoon season and increases in the late monsoon season, \r\nsuggesting a shift in seasonality toward a delayed monsoon onset "


id: 941e5a387510d91f7af7ead16eb90d48
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 20813
content:
"warming in the NH than SH, favouring a  northward shift of the \r\ntropical rain belt (e.g., Rotstayn et al., 2015). "


id: 8ba21216100a11525d04f128b4ff9ce1
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 19484
content:
"There are some clear projected changes in the rainfall variability \r\nand extremes of the Australian monsoon. Rainfall variability in the \r\nAustralian monsoon domain increases on time scales from daily to \r\ndecadal in CMIP5 models (Brown et al., 2017), indicating either more \r\nintense wet days or more dry days or both. There is also a projected \r\nincrease in the intensity of extreme rainfall but a reduction in the \r\nfrequency of heavy rainfall days for the Australian monsoon (Dey \r\net al., 2019a). This is consistent with Moise et al. (2020), who found \r\nan increase in Australian monsoon active phase or 'burst' rainfall \r\nintensity but a reduction in the number of burst days and events."


id: 7e976253dd273e25102266613f9922bc
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 17481
content:
"H.  Zhang et al. (2013) examined changes in Australian monsoon \r\nonset and duration in CMIP3 models and found model agreement \r\non a delay in onset and shortened duration to the north of Australia, \r\nbut less agreement over the interior of the continent. An updated \r\nstudy of CMIP5 models found similar mean changes with delayed \r\nonset and shortened duration, but substantial model disagreement \r\n(H. Zhang et al., 2016). "


id: 5384851c814bb9bd4607bddf02b2d2f0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 10609
content:
"In summary, there is high confidence that the SAmerM will experience \r\ndelayed onsets in association with increases in GHG.  However, \r\nthere is low agreement on the projected changes in terms of total \r\nprecipitation of the South American summer monsoon season. "


id: cbf6a4b679adf8442428d5382c7ddd37
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 29632
content:
"In summary, CMIP6 projections show an increase of AusMCM \r\nprecipitation across all emissions scenarios. There is strong model \r\nagreement on an increase in monsoon precipitation over the \r\nMaritime Continent while there is low agreement on the direction \r\nof change over northern Australia. There is a projected increase in \r\nrainfall variability over northern Australia, with increased intensity of \r\nrainfall during the active or 'burst' phase (medium confidence). "


id: ee4f74ac6024f0a46c9a882dee0b5a83
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 34964
content:
"The AR5 concluded that projected changes in Australian and Maritime \r\nContinent monsoon (AusMCM) rainfall and seasonality are uncertain \r\nin the CMIP5 models, with some projecting increases and others \r\nprojecting decreases for the range of emissions scenarios. Models \r\nthat perform better at simulating present day regional climate project \r\nlittle change or an increase in Australian monsoon rainfall (Jourdain \r\net al., 2013; CSIRO and BoM, 2015; Brown et al., 2016b). CMIP6 \r\nmodels project increased AusMCM precipitation in the 21st century \r\nbut with a more robust signal in SSP2-4.5 and SSP5-8.5 rather than \r\nin lower emissions scenarios (Figure 8.22). A reduced range of CMIP6 \r\nrainfall projections but continued disagreement on the sign of change \r\nis reported over Australia (Narsey et al., 2020)."


id: d7ba8e14276eb9893fd1868e16ddc38b
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 31467
content:
"Tropical cyclones (TCs) projections are primarily assessed in \r\nSection  11.7.1.5. Here, we extend this analysis by assessing the \r\nimplications of projected changes in tropical cyclones on the water cycle."


id: edc248b71e572a8e8ada63a572f4cd0e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 34869
content:
"The AR5 concluded that TC rainfall rate was likely to increase \r\nthrough the 21st century. Section 11.7.1.5 assesses that the average \r\ntropical cyclone rain-rate is projected to increase with warming (high \r\nconfidence), and peak rain rates are projected to increase at greater \r\nthan the Clausius-Clapeyron scaling rate of 7% degC-1 warming in \r\nsome regions due to increased low-level moisture convergence \r\n(medium confidence). The increase in TC rainfall rate is explained by \r\nincreased TC intensity resulting from increasing SSTs, and increased \r\nenvironmental water vapour (Chauvin et al., 2017; M. Liu et al., 2019)."


id: 5a851f08c275726a12ccf8807ddf2504
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 11755
content:
"The northern and eastern parts of the Maritime Continent have \r\nprojected increases in rainfall in CMIP5 models (Siew et al., 2014), \r\nwhile there are projected decreases over Java, Sulawesi and southern \r\nparts of Borneo and Sumatra. Rainfall changes are correlated with \r\nthe extent of warming in the western tropical Pacific in CMIP5 \r\nmodels (Brown et al., 2016b) but inter-model differences are also \r\nrelated to modelled large-scale zonal mean precipitation response \r\nin both CMIP5 and CMIP6 model ensembles (Narsey et al., 2020). \r\nDecomposition of projected rainfall changes indicates that the\r\nlargest source of model uncertainty is associated with shifts in \r\nthe spatial pattern of convection (Chadwick et al., 2013; Brown et al., \r\n2016b). Uncertainties in capturing the spatial and temporal features \r\nof the Maritime Continent monsoon depend also on the horizontal \r\nresolution of coupled climate models (e.g., Jourdain et al., 2013)."


id: b962b2584b8a5b90c54c8013a0b82109
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 26711
content:
"Consistent with the observed poleward migration of tropical cyclone \r\nactivity (Kossin et al., 2014), in the SH a larger proportion of storms \r\nare projected to decay south of 25degS at the end of the 21st century \r\nbut with negligible changes in genesis latitude and storm duration \r\nfor the Australian region (CSIRO and BoM, 2015; Sharmila and Walsh, \r\n2018). An analysis of projections for North Pacific islands indicate \r\nthat the maximum intensity of storms will increase but the number \r\nof tropical cyclones will decrease in some places, such as Guam and \r\nKwajalein Atoll in the tropical north-western Pacific, or remain the \r\nsame in other regions like near Okinawa (Japan) or Oahu (Hawaii) \r\n(Widlansky et al., 2019). TC-induced storm tides affecting landfall in "


id: 63af17f182529ffe13c6962f61917f86
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 13253
content:
"The role of anthropogenic aerosol forcing in future projections of the \r\nAustralian monsoon has been investigated for CMIP5 models (Dey \r\net al., 2019a); decreases in anthropogenic aerosol concentrations \r\nover the 21st century are expected to produce relatively greater "


id: 7916fd658888af6e43fbefe8c01c9ba7
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 16607
content:
"the Pearl River delta over South China are projected to increase by \r\nthe end of the 21st century (J. Chen et al., 2020b)"


id: 3928c7ee7d6d5b8517ff933aa65c3eab
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 6369
content:
"In AR5, the increased ability of models to simulate blocking and \r\nhigher agreement on projections led to an assessment with medium \r\nconfidence that the frequency of NH and SH blocking will not \r\nincrease, but future changes in blocking intensity and persistence \r\nwere deemed uncertain (AR5 Chapter  14, ES and Box  14.2). \r\nBlocking influences precipitation (e.g., Trigo et al., 2004), flooding \r\n(e.g.,  Yamada et al., 2016), drought (e.g.,  Dong et al., 2018b), \r\nsnow (e.g., Garcia-Herrera and Barriopedro, 2006), and glacier melt \r\n(e.g., Hanna et al., 2013), and so is of broad importance to the water \r\ncycle in areas of blocking activity."


id: 150d7d7f6f192b1226e0a2c4716e191e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 817
content:
"In summary, there is high confidence that heavy precipitation \r\nassociated with tropical cyclones is projected to increase, in response \r\nto well-understood processes related to increased low-level moisture \r\nconvergence and environmental water vapour. "


id: 19fcdb604c9abf45b8a86f876b764ebc
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1555
content:
"The AR5 did not provide an assessment of stationary wave \r\nprojections as distinct from other related aspects of circulation, such \r\nas blocking, modes of variability, and storm tracks. Here we provide \r\na  brief assessment of stationary wave projections from the water \r\ncycle perspective, with the related circulation aspects considered \r\nseparately in the following sections. "


id: 9dc0327c491c93d6c89c09057789c375
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 22344
content:
"Several studies based on CMIP5 projections show changes in \r\nNH winter stationary waves that increase precipitation over the \r\nwest coast of North America and decrease it over the eastern \r\nMediterranean and parts of south-western North America (Neelin \r\net al., 2013; Seager et al., 2014a, b, 2019b; Simpson et al., 2016; \r\nWills et al., 2019), although the underlying dynamics are not yet fully \r\nunderstood (Seager et al., 2019b; Wills et al., 2019). For the NH winter \r\nglobal teleconnection pattern, the majority of the models analyzed in \r\n(Sandler and Harnik, 2020) project the development of a preferred \r\nlongitudinal phasing for the pattern, but with strong disagreement \r\namong models over the details of the phasing and therefore the \r\nassociated regional hydrologic impacts."


id: d66d0a2b987cd123f8f5ff9019f5739c
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 31249
content:
"In summary, and despite recent improvements in the simulation of \r\nblocking, there is limited evidence in model projections of future \r\nchanges, except for boreal winter over Greenland and the North \r\nPacific where there is high confidence that blocking events are not \r\nexpected to increase in the SSP3-7.0 and SSP5-8.5 scenarios. As with \r\nstationary waves, this adds uncertainty to mid-latitude water cycle \r\nprojections at the regional scale."


id: 2d5978e7ac602ec2d85dccb2b590904e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 4577
content:
"The AR5 found that extratropical storms were expected to decrease in \r\nthe Northern Hemisphere (NH), but only by a few percent. Meanwhile, \r\nprecipitation associated with extratropical storms was projected to \r\nincrease due to thermodynamic increases in moisture but potentially \r\nalso due to intensification from increased latent heat release. Latent \r\nheating is a strong influence on extratropical storms, so it is plausible \r\nthat changes in precipitation and associated latent heating could \r\naffect extratropical storm intensity and thus precipitation (Z. Zhang \r\net al., 2019)."


id: aafb9a091d9f2ab9f6df64522963e799
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 24419
content:
"In summary, future changes in stationary waves may have an \r\nimportant influence on both the mean state and variability of the water \r\ncycle. Limitations in model representation, dynamical understanding, \r\nand the number of targeted studies on the topic currently constrain \r\nthe assessment of future changes in stationary waves. Based on \r\ncurrent knowledge, there is low confidence that projected changes in \r\nstationary wave activity will contribute to decreases of cold season \r\nprecipitation over the eastern Mediterranean and increases over the \r\nwest coast of North America."


id: 987f1378ad6f9a345f19ac8b935e233a
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 21503
content:
"There is increased evidence that precipitation associated with \r\nindividual extratropical storms is projected to increase, following \r\nthermodynamic drivers with negligible dynamic change (Yettella and \r\nKay, 2017). Comparisons with reanalyses also support the projected \r\nincrease in thermodynamic precipitation with little dynamic response "


id: f653c1e3f34e3714db3956a1463dca49
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 36265
content:
"through the greenhouse gas influence on SSTs. The importance of the \r\nstratospheric polar vortex in storm track changes has received more \r\nattention (Zappa and Shepherd, 2017; Mindlin et al., 2020) and the \r\nanticipated recovery of the ozone layer further complicates the role of \r\nthe stratosphere (Shaw et al., 2016; Bracegirdle et al., 2020b)."


id: b8ec1a509590358e886fcd345d493071
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 26626
content:
"for precipitation associated with extratropical storms (Li et al., 2014). \r\nThere is high confidence that projected increases in precipitation \r\nassociated with extratropical storms in the NH (Marciano et al., 2015; \r\nPepler et al., 2016; Michaelis et al., 2017; Yettella and Kay, 2017; \r\nZhang and Colle, 2017; Hawcroft et al., 2018; Kodama et al., 2019). \r\nA projected decrease in the number of extratropical cyclones over \r\nthe NH during the boreal summer in CMIP5 models was reported \r\nby Chang et al. (2016) who related this decrease with a decrease in \r\ncloudiness and thus accentuating increased maximum temperatures. \r\nHowever, model spread was quite large, especially over North \r\nAmerica, thus there is only low confidence in this seasonal signal."


id: 1a9237cd71150c27126b4b78add9943b
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1660
content:
"In AR5, the Southern Hemisphere (SH) storm track was deemed likely\r\nto shift poleward, the North Pacific storm track more likely than not to \r\nshift poleward, while the North Atlantic storm track was unlikely\r\nto display any discernible changes. There was low confidence in \r\nregional storm track changes and the associated surface climate \r\nimpacts, although a  weakening of the Mediterranean storm track \r\nwas a robust response of the models. Since AR5, the SH mid-latitude \r\nstorm track is projected to shift poleward and the westerlies are \r\nprojected to strengthen over Australia (CSIRO and BoM, 2015). \r\nAlthough thermodynamic effects were considered to be the most \r\nimportant factor in overall projections of increased mid-latitude \r\nprecipitation, the general poleward shift in cyclogenesis and an \r\nenhanced latitudinal displacement of individual cyclones may play \r\na role (Tamarin-Brodsky and Kaspi, 2017)."


id: 5dca429b5fbf07391d47de7b060d26c1
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 12286
content:
"The projected changes in storm tracks and the associated mechanisms \r\nhave several important implications for water cycle projections. P-E \r\nchanges in the Mediterranean, California and Chile are directly \r\nlinked to storm track changes (Zappa et al., 2020). Where the storm \r\ntracks are robustly projected to shift (SH, North Pacific) or weaken \r\n(Mediterranean), understanding the physical causes of the related \r\nchanges in precipitation helps increase confidence in the projections. \r\nUnderstanding the competing influences provides context for why \r\nother regions do not exhibit a consistent signal and cautions against \r\nregional projections based on individual models. However, model \r\nbias and the need for relatively high resolution to reproduce the \r\nrelevant dynamics is an important overall limit on confidence in \r\ncurrent CMIP6 projections."


id: dc3ec268a9574ebff26e8e28189ff236
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 32161
content:
"In summary, there is the high confidence that precipitation associated \r\nwith extratropical storms will increase with global warming in most \r\nregions. The SH storm track will likely shift poleward, the North Pacific \r\nstorm track more likely than not will shift poleward, and the North \r\nAtlantic storm track is unlikely to have a  simple poleward shift/ \r\ndisplay any discernible changes. There is low confidence in regional \r\nstorm track changes, although a  weakening of the Mediterranean \r\nstorm track is a robust response of the models."


id: 89a86d191156151218580fede3ef1e57
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 19194
content:
"The role of temperature trends in influencing storm tracks has \r\nbeen  further investigated, both in terms of upper tropospheric \r\ntropical warming (Zappa and Shepherd, 2017) and lower \r\ntropospheric  Arctic  amplification (J.  Wang et al., 2017), including \r\nthe direct role of  Arctic sea ice loss (Zappa et al., 2018), and the \r\ncompetition between their influences (Shaw et al., 2016). Physical \r\nlinkages between Arctic amplification and changes in the mid-latitudes \r\nare uncertain, as discussed in Chapter 10 (Cross-Chapter Box 10.1). The \r\nremote and local SST influence has been further examined by Ciasto \r\net al. (2016), who confirmed sensitivity of the storm tracks to the \r\nSST trends generated by the models and suggested that the primary \r\ngreenhouse gas influence on storm track changes was indirect, acting "


id: 1b8188a9d8467f3818c7b22021524dd3
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1789
content:
"Atmospheric rivers were not assessed in AR5 but are important in \r\nthe water cycle as they are linked to extreme rainfall, flooding, and \r\nchanges in terrestrial water storage including melt and ablation of \r\nglaciers and snowpack (Sections 8.2.3). In a warming world, there \r\nis high confidence that thermodynamical increases in atmospheric "


id: c9b77dbf6737c368360c623ba6362ac2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 29293
content:
"water vapour ensure that atmospheric rivers will become wetter, \r\nhence stronger, and longer-lasting (Payne et al., 2020). This is \r\nclearly observed in several regional (Ralph and Dettinger, 2011; \r\nLavers et al., 2013; Gao et al., 2015; Payne and Magnusdottir, 2015; \r\nWarner et al., 2015; Hagos et al., 2016; Gershunov et al., 2019) and \r\nin one global study (V.  Espinoza et al., 2018) of atmospheric river \r\nactivity in CMIP5 model projections. Lavers et al. (2015) indicate that \r\nintegrated vapour transport under RCP 8.5 and 4.5 could increase, \r\nand consequently this thermodynamic response (O'Gorman, 2015) \r\ncould affect mid-latitude regions where orographic precipitation is \r\nimportant (Gershunov et al., 2019). "


id: 70ba6b24205a5b8c7b0bf4ffd70d73c9
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15359
content:
"Following on from the assessment of projected changes in \r\nmodes of climate variability (MoVs) and regional teleconnections \r\n(Section  4.5.3), here we assess their consequences for projected \r\nwater cycle changes."


id: d82d8505d502eb68015399b6988d35ca
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 31536
content:
"Even over regions with statistically significant simulated rainfall \r\nteleconnections during the historical period, CMIP5 models do not \r\nproject clear changes (Perry et al., 2020). Nonetheless, CMIP5 models \r\nthat realistically reproduce Indian summer monsoon rainfall indicate \r\na strengthening of its relationship with ENSO in RCP8.5 projections, \r\nthough the response is not consistent for different varieties of ENSO \r\nevents (Roy et al., 2019). Inconsistent changes in the ENSO-Indian \r\nsummer monsoon relationship in response to global warming \r\nin CMIP5 and CMIP6 models may be related to statistical issues \r\nrather than dynamical changes (Bodai et al., 2020; Haszpra et al., \r\n2020). Over East Africa during the boreal spring and summer, ENSO \r\nteleconnections are projected to become stronger in the future \r\n(Endris et al., 2019). Meteorological drought consequences of each \r\nstrong El Nino are projected to become more severe in the region \r\n(Rifai et al., 2019)."


id: f36a42364e5c0b65fb758b10486b9df0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 35806
content:
"In semi-arid regions where atmospheric rivers have historically been \r\nimportant and precipitation is mainly confined to the cold season, the \r\ncontribution of atmospheric rivers to annual total precipitation may \r\nbe expected to grow disproportionately. For example, in California \r\ndecreases in precipitation frequency are projected as a  result of \r\nfewer non-atmospheric river storms, while the projected increase \r\nin heavy and extreme precipitation events are almost entirely \r\na  result of increased atmospheric river activity (Gershunov et al., \r\n2019). Interannual variability in precipitation amounts is projected \r\nto increase because of the overall decrease in the frequency of \r\nstorms but a stronger dependence on extremes (Polade et al., 2014), \r\nparticularly due to atmospheric rivers (Gershunov et al., 2019), \r\nespecially where interaction with topography are important (Polade \r\net al., 2014; Gershunov et al., 2019). "


id: 9e885803d96054a7d16d6658603f36fa
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 22478
content:
"Indian Ocean Dipole (IOD, Annex IV.2.4) and Indian Ocean Basin (IOB, \r\nAnnex IV.2.4) interactions with ENSO are expected to persist in the \r\nfuture (Section 4.5.3.3) but projected changes in the frequency and \r\nintensity of events remain uncertain (Hui and Zheng, 2018; Endris \r\net al., 2019; McKenna et al., 2020). Climate extremes such as those \r\nassociated with the extreme positive IOD event of 2019 are expected \r\nto occur more frequently under continued global warming (Cai et al., \r\n2021). Projected changes in IOD teleconnections are linked to model \r\nperformance in representing the IOD and its remote influence in the \r\npresent climate, apparently dominated by a positive IOD event-like \r\nmean state (G. Wang et al., 2017; Huang et al., 2019). Interactions \r\nbetween the IOD and the Indian Ocean mean state, via atmosphere-\r\nocean feedbacks, can affect the behaviour of the IOD (Ng et al., 2018). \r\nIn the eastern Horn of Africa, OND rainfall is projected to increase "


id: 723aee4cb1f65bca6bb2648e5b6f18b6
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15594
content:
"In summary, there is high confidence that the magnitude and \r\nduration of atmospheric rivers are projected to increase in future, \r\nleading to increased precipitation. This is projected to increase the \r\nintensity of heavy precipitation events on the west coast of the USA \r\nand in western Europe (high confidence)."


id: 6ab1c21111e5492fd6684f2d3c57e901
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14398
content:
"because of IOD-ENSO related SST changes in the Indo-Pacific region \r\nand associated Walker circulation changes (Endris et al., 2019). "


id: 72a66c1e55e68d581486e8a21756571a
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15653
content:
"In the SH, the positive trend projected for the SAM in the CMIP5 \r\nRCP8.5 scenario appears to mitigate the wetting in the mid- to high \r\nlatitudes and the drying over the subtropics, but with strong seasonal \r\ndependence (Lim et al., 2016). Regional precipitation changes in \r\nSouth America, South Africa, Southern Australia and New Zealand are \r\nnot well explained by changes in the SAM, but are related to broad\u0002scale changes in north-south temperature gradients associated \r\nwith enhanced warming of the tropical upper troposphere and \r\nstrengthening of the stratospheric polar vortex (Mindlin et al., 2020)."


id: a96b0012bda1b52f599ddb97f8db6ffe
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 24183
content:
"In summary, projected changes in the intensity, frequency and \r\nphase of extratropical MoVs (see also Sections  4.3 and 4.5) may \r\namplify regional changes in precipitation and contribute to an \r\nincrease in their intra-seasonal and interannual variability (medium \r\nconfidence). Regionally, there are potentially significant precipitation \r\nand atmospheric circulation changes associated with changes in \r\nextratropical dynamics (low confidence). "


id: 24270f8aa1cfa5c4fda1a8c5c27dcd54
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 3130
content:
"In summary, even though there is low confidence in how the tropical \r\nMoVs will change in the future (Sections 4.3.3.2 and 4.5.3.3), their \r\nregional hydrological consequences, in terms of precipitation, are \r\nprojected to intensify (medium confidence). For example, the ENSO \r\ninfluence on precipitation over the Indo-Pacific sector is projected \r\nto strengthen and shift eastward (medium confidence). The MJO is \r\nprojected to intensify in a warmer climate, with increased associated \r\nprecipitation (medium confidence)."


id: 4c247773045c162e33185adf7a9f2adb
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 9402
content:
"CMIP6 projections indicate that the Northern Annular Mode (NAM; \r\nAnnex IV.2.1) is expected to become more positive in winter \r\nthroughout the 21st century in the SSP3-7.0 and SSP5-8.5 scenarios \r\n(Section 4.5.1). In the near term, the Southern Annular Mode (SAM, \r\nAnnex IV.2.2) is projected to become less positive than observed \r\nduring the end of the 20th century during the austral summer in all \r\nSSPs scenarios (Section 4.3.3.1). "


id: e2588ab237261a2ea64921ad209843f8
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 33115
content:
"In the CMIP5 RCP8.5 scenario, increased amplitude and frequency \r\nof the North Atlantic Oscillation (NAO, Annex IV.2) during boreal \r\nwinter (December-January-February, DJF) is associated with higher \r\nprecipitation in northern Europe and lower precipitation in southern \r\nEurope (Tsanis and Tapoglou, 2019). However, large-ensemble \r\nanalyses show how the NAO leads to significant uncertainty in future \r\nchanges of regional climate (Section 8.5.2). For example, more than \r\na 85% increase in precipitation is projected over northern Europe, \r\nwestern Russia and much of eastern North America, with similar \r\ndecreasing resulting in drying over north-western Africa and regions \r\nadjacent to the Mediterranean Sea (Deser et al., 2017). "


id: e9ad5abe0a59807e72055d538363b007
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 34265
content:
"derived directly from global climate models (GCMs) or produced \r\nby 'offline' using global hydrological models (GHMs) driven by \r\nthe same GCMs (Orlowsky and Seneviratne, 2013; Giuntoli et al., \r\n2015, 2018; Chegwidden et al., 2019). Although some of the model \r\nresponse uncertainty is related to climatological biases (Grose \r\net al., 2017; G. Li et al., 2017; Lehner et al., 2019; Samanta et al., \r\n2019), model biases are not the only way to assess the reliability of \r\nclimate projections (compare with Box 4.1). Therefore, our focus here \r\nis on the representation of key processes that are not completely \r\nresolved in current-generation GCMs (Section  8.5.1.1) and on the \r\nmodel improvements associated with increased horizontal resolution \r\n(Section 8.5.1.2)."


id: 811399f862d52d0da0c23014220d6458
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 17829
content:
"Model response uncertainty is typically estimated as the inter-model \r\nspread (range) projected by a  set of climate models for a  given \r\nemissions scenario. It is best estimated at the end of a high-emissions \r\nscenario when internal variability has a  limited contribution to \r\ntotal uncertainty (Figure 8.23). Even for aggregated quantities, like \r\ndecadal-mean precipitation averaged over relatively large domains, \r\nmodel response uncertainty is substantial and can exceed scenario \r\nuncertainty (Hawkins and Sutton, 2011; Lehner et al., 2020, 1.5.4, \r\n4.4.1.3). This can also be true for other water cycle variables such \r\nas soil moisture, runoff and streamflow at the regional scale, either "


id: 53bf25dea6ca8a972158da84b604507d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 10643
content:
"the diurnal cycle of precipitation over land (Couvreux et al., 2015), \r\nthe rainfall intensity distribution associated with the West African \r\nmonsoon (Roehrig et al., 2013), and the intensity of tropical cyclones \r\n(Sections 10.3.3.4 and 11.7.1.3), phenomena for which atmospheric \r\nconvection also plays a key role."


id: 72bc814017c3ebcf515ea0befd25155f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15666
content:
"Moist convection is fundamental to the water cycle through its vertical \r\ntransport of momentum, heat, and moisture across the atmosphere. \r\nIt is particularly active in the tropics where it contributes to more \r\nthan half of annual precipitation and to the development of severe \r\nweather events. Given limitations in computing resources, the current\u0002generation GCMs cannot yet represent small-scale cloud processes \r\nand consequently shallow and deep convection is determined by \r\nsub-grid-scale parametrizations. While such parametrizations can be \r\nevaluated against field observations (e.g., Abdel-Lathif et al., 2018), \r\nit remains challenging to estimate convective entrainment that is \r\nvalid for both shallow and deep convection (G.J. Zhang et al., 2016). \r\nComparisons between regional projections with explicit compared \r\nwith parametrized convection also highlight the limitations of \r\nparametrized convection for assessing climate change (Kendon et al., \r\n2019; Jackson et al., 2020)."


id: 5059d4b55f78de3e0886cedabf3583a
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 10089
content:
"Atmospheric convection is particularly important for a  realistic \r\nsimulation of tropical precipitation intensities (Pendergrass and \r\nHartmann, 2014a; Kendon et al., 2019). Many CMIP5 models \r\nproduce rainfall at water vapour amounts lower than in observations \r\n(Takahashi, 2018), as well as too light and too frequent precipitation \r\nevents (Sun et al., 2015; Trenberth et al., 2017). Such biases can \r\nbe explained by a  lack of convective inhibition (Rochetin et al., \r\n2014a, b) and by too much convective and too little non-convective \r\nprecipitation (Chen and Dai, 2019). Tropical convection controls the \r\namount of precipitable water simulated over the equatorial Indian \r\nOcean, which has been identified as a key metric for differentiating \r\nmodel skill in simulating South Asian monsoon precipitation (Hagos \r\net al., 2019). Many models have difficulty in adequately simulating "


id: d5a52dd02870fafc9af2127e68dfdc3c
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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content:
"While some global modelling centres have reported progress in their \r\nparametrization of convection and in their simulation of seasonal, \r\ndaily and sub-daily precipitation (e.g.,  Danabasoglu et al., 2020; \r\nRoehrig et al., 2020), CMIP6 models as a whole only show limited "


id: 5363ea8013ee310148a9b8d6f424eec2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 10590
content:
"include also the impacts of aerosols on ice-precipitation processes. \r\nAerosols can substantially invigorate (Rosenfeld et al., 2008; Koren \r\net al., 2014; Fan et al., 2018) and electrify (Thornton et al., 2017; \r\nQ. Wang et al., 2018) deep tropical convective clouds. High-resolution \r\natmospheric simulations suggest that high aerosol concentrations \r\ncan increase environmental humidity by producing clouds that \r\nmix more condensed water into the surrounding air, which in turn \r\nfavours large-scale ascent and strong convective events (Abbott and \r\nCronin, 2021). Further assessment of uncertainties in aerosol-cloud \r\ninteractions for shallow water clouds is provided in Section 7.3.3.2."


id: 3f11909f4413e82ea8b9a23397338f8b
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 7310
content:
"In summary, since AR5 empirical convective parametrization schemes \r\nand associated precipitation biases have improved in some but not \r\nall global climate models. There is still low confidence in their ability \r\nto accurately simulate the spatio-temporal features of present-day \r\nprecipitation, especially in the tropics where a  double-ITCZ bias is \r\nstill apparent in many models. While such biases limit the reliability of \r\nprecipitation projections in some cases, there is currently only medium \r\nconfidence that model selection or weighting is a better alternative \r\nto the one-model-one-vote approach (Box 4.1). Improved water cycle \r\nprojections can be achieved by focusing on phenomena or weather \r\nevents, such as a thermodynamic intensification of convective events \r\n(high confidence, Section  8.2.2.1), however accurate quantitative \r\nestimates are currently hampered by complex, model-dependent \r\ndynamical responses (Section 8.2.2.2)."


id: dd847068920a95fb3b9817df5da593c4
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 32352
content:
"In summary, there is still low confidence in the simulated influence \r\nof the aerosol microphysical effects on future precipitation changes."


id: 317ed382da763c57c22c2228534a9eda
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 5196
content:
"2016; Berg and Sheffield, 2018a; Santanello et al., 2018). This has \r\nled to the development of dedicated field campaigns (Song et al., \r\n2016; Phillips et al., 2017; Dirmeyer et al., 2018), remotely sensed \r\nobservations (Ferguson and Wood, 2011; Roundy and Santanello, \r\n2017), and tailored diagnostics (Tawfik et al., 2015a, b; Miralles et al., \r\n2016, 2019; Dirmeyer and Halder, 2017). Dynamic vegetation models \r\nhave been introduced in global ESMs but they need further evaluation \r\n(Medlyn et al., 2015; Prentice et al., 2015; Cantu et al., 2018; Franks \r\net al., 2018) to provide valuable information on potential vegetation \r\nfeedbacks. Plant migration and mortality, increased disturbances \r\nfrom wild fires, insects and extreme events, interactive nitrogen cycle, \r\nor the impact of increased levels of tropospheric ozone are often \r\nignored or poorly represented in the current-generation of ESMs \r\n(Bonan and Doney, 2018; Fisher et al., 2018). "


id: 95698c548e9516609b3c9b83101981bf
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 21004
content:
"Since AR5, development of new and existing processes in land surface \r\nmodels (LSMs) have been evaluated. These include soil freezing and \r\npermafrost (Vergnes et al., 2014; Chadburn et al., 2015; K. Yang et al., \r\n2018; Gao et al., 2019), soil and snow hydrology (Brunke et al., 2016; \r\nDecharme et al., 2016), glaciers (Shannon et al., 2019), surface waters \r\nand rivers (Decharme et al., 2012), as well as vegetation (Bartlett and \r\nVerseghy, 2015; Betts et al., 2015; Knauer et al., 2015; Tang et al., \r\n2015) and the representation of hydraulic gradients throughout the \r\nsoil-plant-atmosphere continuum (Bonan et al., 2014). Such land \r\nsurface model developments have led to significant improvements \r\nin global offline hydrological simulations driven by observed \r\natmospheric forcings (e.g., C. Li et al., 2017; Decharme et al., 2019)."


id: 447b589ce9a5011692f3a450ad5cfeba
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 8199
content:
"In summary, since AR5 substantial advances have been made in \r\nthe representation of land surface processes in current-generation \r\nEarth System Models (ESMs). Offline hydrological models allow \r\nthe application of bias-adjusted atmospheric forcings, but there \r\nis low confidence of an improved response compared to coupled \r\nclimate models, given their inherent limitations (Box  10.2). While \r\nimprovements in the representation of complex land surface \r\nfeedbacks relevant to the water cycle are needed, there is currently \r\nlow confidence that they will systematically improve the reliability of \r\nwater cycle projections. "


id: 7a50f90458b81c654a654e2fa7ada6ea
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 16814
content:
"Coarse spatial resolution of climate models has often been considered \r\na key limitation in global climate projections (Di Luca et al., 2015; \r\nRoberts et al., 2018). Proposed and tested solutions include a uniform \r\nor regional increase in the resolution of GCMs, or the use of regional \r\nclimate models (RCMs). The increase in computing resources has \r\nalso led to the development of convection-permitting models (Prein \r\net al., 2015), which have been integrated over larger domains, but \r\nare still unsuitable for CMIP simulations. Statistical downscaling \r\ntools are also widely used to generate fine-scale regional climate "


id: b80a5dd4457a4fab09557f57af172753
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 26487
content:
"Since AR5, there has been increasing recognition of the need to \r\nbetter understand the role of land-atmosphere coupling and related \r\nfeedbacks (Joetzjer et al., 2014; Berg et al., 2016; Catalano et al., "


id: f98bef44955573c4544ab6a0409eb48
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 36782
content:
"information necessary for climate impacts and adaptation studies. \r\nA  comprehensive assessment of the added value of increased \r\nspatial resolution and of the benefits and shortcomings of statistical \r\ndownscaling tools are addressed in Chapter 10 (Section 10.3.3)."


id: c044209f0442e348168c26b2f1fd4469
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 27808
content:
"orographic precipitation, snow, runoff and streamflow in complex \r\ntopography areas (Zhao and Li, 2015). However, the added value \r\nmay be easier to assess in offline rather than online land surface \r\nsimulations (Doll et al., 2016) given the possible use of bias-corrected \r\natmospheric forcings. Offline high-resolution GHMs are routinely used \r\nto monitor water resources or to assess the hydrological impacts of \r\nbias-adjusted global climate projections (Davie et al., 2013; S. Huang \r\net al., 2017, 2018). Yet, the development and calibration of 'hyper\u0002resolution' hydrological models, with gridcells of typically 100 m to \r\n1  km, raises a  number of issues given the lack of comprehensive \r\nsurface or subsurface information (Bierkens et al., 2015) and the lack \r\nof coupling with the atmosphere (Berg and Sheffield, 2018a). "


id: ac73297870754a67b0aa512eea513d0a
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 24669
content:
"In summary, there is high confidence that increasing horizontal \r\nresolution in GCMs can reduce a  number of systematic model \r\nerrors of relevance for the water cycle, including synoptic circulation \r\nand the statistics of daily precipitation. High-resolution GCMs and \r\nGHMs provide improved representation of land surfaces, including \r\ntopography, vegetation and land use change, which are required to \r\naccurately simulate changes in the terrestrial water cycle. However, \r\nthere is low confidence that the higher horizontal resolution \r\nsimulations currently available provide more accurate projections of \r\nthe large-scale features of the water cycle."


id: 38665447d296278ea19da2a68c32083e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 6249
content:
"Increasing horizontal model resolution in CMIP5 and CMIP6 models \r\nleads to a systematic increase in global mean precipitation, enhanced \r\nmoisture advection to land in close connection with increased \r\norographic precipitation, and a partial reduction of the long-standing \r\ndouble ITCZ bias (Demory et al., 2014; Caldwell et al., 2019; Vanniere \r\net al., 2019). Recent studies based on HighResMIP simulations \r\n(Haarsma et al., 2016) confirm the added value of increased \r\nhorizontal resolution (at least 50 km in the atmosphere and 25 km \r\nin the ocean) for the simulation of tropical (Roberts et al., 2020) and \r\nextratropical cyclones (Priestley et al., 2020b). CMIP6 model biases \r\nin annual mean precipitation are only slightly reduced at higher \r\nresolution (Figure 3.10). "


id: 9c1ff6eac5b22b758231438c11d1e2c9
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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content:
"Regional Convective Permitting Models (CPMs), typically run at \r\na resolution less than 10 km, have been implemented over increasingly \r\nlarge domains. Compared to models with parametrized convection \r\n(Section 8.5.1.1.1), they generally show improved simulation of key \r\nfeatures of the water cycle such as orographic precipitation, sea \r\nbreeze dynamics, the diurnal cycle in precipitation, soil-moisture-\r\nprecipitation feedbacks, daily precipitation persistence, sub-daily to \r\ndaily precipitation intensities and related extremes (Section 8.2.3.2; \r\nBirch et al., 2015; Prein et al., 2015; Kendon et al., 2017; Leutwyler \r\net al., 2017; Willetts et al., 2017; Hohenegger and Stevens, 2018; \r\nBerthou et al., 2019b; Takahashi and Polcher, 2019; Fumiere et al., \r\n2020; Scaff et al., 2020; Caillaud et al., 2021). A growing number of \r\nstudies have also assessed the potential added value of using CPMs "


id: 53a28ede1656212ae464921c7656387a
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 10624
content:
"fingerprints over land (Section 8.5.2.2). The role of volcanic eruptions \r\nis also briefly assessed in terms of consequences and uncertainties in \r\nwater cycle projections (Section 8.5.2.3)."


id: 4c8647e62e134598e6c0f88aefc16379
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 9460
content:
"for regional climate projections (Ban et al., 2015; Giorgi et al., 2016; \r\nFosser et al., 2017; Kendon et al., 2017, 2019; C.  Liu et al., 2017; \r\nLenderink et al., 2019; Rasmussen et al., 2020; see also Atlas 5.6.3). \r\nAlthough projected changes in rainfall occurrence in CPMs are broadly \r\nand qualitatively consistent with the results of GCMs and RCMs \r\n(Kendon et al., 2017), there is a tendency towards stronger changes \r\nin both wet and dry extremes (Berthou et al., 2019a; Kendon et al., \r\n2019; Lenderink et al., 2019; Finney et al., 2020a). While both GCMs \r\nand RCMs project an overall decrease in summer precipitation over \r\nthe Alps, RCMs simulate an increase over the high Alpine elevations \r\nthat is not present in the global simulations (Giorgi et al., 2016). "


id: 7469f104f96d11ff3f54b47c95023364
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15907
content:
"Recent studies based on both GCMs and CPMs indicate that both \r\nCAPE and convective inhibition will increase in a  warmer climate \r\n(Section 8.2.3.2; J. Chen et al., 2020a), consistent with a shift from \r\nmoderate to less frequent but stronger convective events (Rasmussen \r\net al., 2020). If underestimated by models with parametrized \r\nconvection, such a mechanism could explain the underestimation of \r\nboth projected increase in precipitation extremes (Borodina et al., \r\n2017; Yin et al., 2018) and land surface drying (Douville and Plazzotta, \r\n2017) in the extratropics. CMIP5 models with a  larger increase in \r\nextreme precipitation also exhibit larger declines or smaller increases \r\nin light to moderate events (Thackeray et al., 2018)."


id: 1c3556e2ccb75b06cd6e0a8b43ad58ff
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1898
content:
"In summary, there is high confidence that dynamical downscaling \r\nusing limited area models adds value in simulating precipitation \r\nand related water cycle processes at the regional scale, especially \r\nin complex orography areas (Section  10.3.3.5.1). There is high \r\nconfidence that the explicit simulation of atmospheric convection can \r\nimprove the representation of weather phenomena, including the life \r\ncycle of convective storms and related precipitation extremes. Even \r\nwith an improved simulation of small-scale processes, there is only \r\nmedium confidence that there will be an improvement in RCM-based \r\nwater cycle projections as they rely on GCM boundary conditions."


id: e41bb638ea374b140acebaf33d88fe67
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 33369
content:
"time scales (Dee et al., 2017; Parsons et al., 2017). It is unclear \r\nwhether remaining discrepancies represent limitations of the climate \r\nmodels, or limitations of the proxy system models. Therefore, there \r\nis medium to high confidence (i.e.,  depending on the region) that \r\nclimate models do not underestimate water cycle internal variability. "


id: fc64be130e9f67cde0e9662ec404c8ea
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 37214
content:
"between eastern Australian rainfall and the central equatorial Pacific \r\nSSTs with varying skill, and also display periods when the ENSO \r\nteleconnection weakens substantially for several decades (Brown \r\net al., 2016a). Differences in simulated internal variability have been \r\nfound to be responsible for the inter-model spread in predicted shifts \r\nin subtropical dry zones for a given shift in the Hadley cell (Seviour \r\net al., 2018). CMIP5 models show that both internal variability \r\nand anthropogenic forcings are responsible for the drying over \r\nthe South Atlantic Convergence Zone region, though with large \r\nuncertainties (Zilli and Carvalho, 2021). Moreover, the detection of \r\nthe anthropogenic forcing on the South Atlantic Convergence Zone \r\nis strongly dependent on the characterization of model internal \r\nvariability (Talento and Barreiro, 2012). "


id: 4d747e6a5b029e45bf9dc48d6af22a84
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 9619
content:
"The mechanisms driving internal variability in the water cycle in \r\nclimate model simulations varies. While models indicate that cool \r\nSSTs in the eastern tropical Pacific (La Nina or the cool phase of \r\nthe PDO) are associated with drought in south-western North \r\nAmerica, they also show that atmospheric internal variability may \r\nbe a  more prominent driver (Coats et al., 2015, 2016; Stevenson \r\net al., 2015; Parsons et al., 2018). Simulations of the last millennium \r\nfrom CMIP5-PMIP3 reproduce the observed negative correlation "


id: 680b3ecea5d3f8d8aaf743327cfcf650
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 13956
content:
"Figure 8.24 | Impact of the North Atlantic Oscillation (NAO) on 2016-2045 climate trends. (a) Regressions of winter sea level pressure (SLP) and precipitation \r\ntrends upon the normalized leading principal component (PC) of winter SLP trends in the CESM1 Large Ensemble, multiplied by two to correspond to a two standard deviation \r\nanomaly of the PC (as internal climate variability component); (b) CESM1 ensemble-mean winter SLP and precipitation trends (as forced climate variability component); \r\n(c) b - a (forced minus internal climate variability component); (d) b + a (forced plus internal climate variability component). Precipitation in colour shading (mm day-1 per \r\n30 years) and SLP in contours (interval = 1 hPa per 30 years with negative values dashed). Figure adapted from Deser et al. (2017), https://creativecommons.org/licenses/by/4.0/; \r\nfurther details on data sources and processing are available in the chapter data table (Table 8.SM.1)."


id: a74113fc2bedb65d9740ba69e57d6b75
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 23828
content:
"of the methods used to estimate time of emergence is presented \r\nin Chapter 10 (Section 10.3.4.3). For specific regional examples of \r\nclimate change attribution and emergence of anthropogenic signal, \r\nsee Section 10.4.2."


id: 2b4556b2c2fc4181a1d01d34dd448de0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 4243
content:
"Beyond the tropics, North Pacific decadal variability (Annex IV.2.6, \r\n2.4.5, 3.7.6) exerts a  strong modulation of extratropical ENSO \r\nteleconnections, but also influences low-frequency variability of the \r\nWalker circulation, which is underestimated by most CMIP5 models \r\n(England et al., 2014). Atlantic Multi-decadal Variability (Annex IV.2.7, \r\n2.4.6, 3.7.7) teleconnections show a high model spread among CMIP5 \r\nmodels, both in terms of persistence and spatial coherence (Qasmi \r\net al., 2017), which has potential consequences for the water cycle \r\nvariability simulated over Europe. For example, internal variability \r\nwill continue to play an important role in the variability of river flows \r\nover France in coming decades (medium confidence) (Giuntoli et al., \r\n2013; Boe and Habets, 2014; Bonnet et al., 2017)."


id: 4fba2a3baa20fdeb7cf15a3248419f24
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 9981
content:
"In summary, there is medium confidence that climate models \r\nreproduce the general magnitude and character of internal variability \r\nthat influences water cycle variables. There is high confidence that \r\ninternal variability will continue to be a major source of uncertainty, \r\nat least for near-term water cycle projections at the regional scale. \r\nThere is low confidence in the region-dependent time of emergence \r\nof water cycle changes (see also Section 10.4.3), but there is medium \r\nconfidence that changes in wet extreme events will emerge earlier \r\nthan changes in average conditions."


id: cc9d4ceb0dab0dc4b286e1d14788cbb5
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vector_id: 29729
content:
"Ensembles of atmosphere-only simulations driven by observed or \r\nreconstructed SST are useful for evaluating the ability of models to \r\ncapture the circulation and/or precipitation variability observed over \r\nthe historical period (Zhou et al., 2016; Deng et al., 2018; Douville \r\net al., 2019). However, limitations of such AGCM-based attribution \r\nmethods, that is, related to the lack of air-sea interactions in the \r\nresponse, may lead to erroneous attribution conclusions in some \r\nregions for local circulation and mean and extreme precipitation \r\n(Dong et al., 2017). Other methods to measure the portion of \r\nprecipitation variability include the partitioning into dynamical \r\nas opposed to thermodynamical components (Saffioti et al., 2016; \r\nFereday et al., 2018; Lehner et al., 2018), the analysis of variance \r\n(Dong et al., 2018a) and direct characterization of stochastic weather\u0002noise (Short Gianotti et al., 2014). "


id: 3e646e4790f3842b4e601b3bdeca674d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 7188
content:
"Adapting water resource management in the face of climate change \r\nwill greatly benefit from improved prediction of land surface hydrology \r\nat the decadal time scale. Climate predictions (Section 1.4.4) differ \r\nfrom climate projections by constraining the initial state of the slow \r\ncomponents of the climate system (i.e., the ocean, the cryosphere \r\nand the terrestrial hydrology) as well as volcanic aerosols and ozone \r\ndepleting substances with observations. Anthropogenic and natural \r\nradiative forcing and low-frequency modes of variability (e.g., AMV \r\nand PDV, Annex IV.2.7 and IV.2.6) suggest the possible predictability \r\nof climate in the first decade or so of the 21st century, in addition to \r\nthe projected response to the anthropogenic forcing (Sections 4.2.3 \r\nand 4.4.1.3). "


id: bc5fd96aaefd87e4d6f435d25e7c7645
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 27218
content:
"Single-model initial condition large ensembles (SMILEs) are a powerful \r\ntool for estimating the magnitude of internal variability in historical \r\nand future climates (Section  1.4.4). Using SMILEs, it has been \r\nshown, for example, that internal NAO variability imparts substantial \r\nuncertainty to future changes in European precipitation (Figure 8.24; \r\nDeser et al., 2017). For the South Asian summer monsoon, internal \r\nvariability can overshadow the forced monsoon rainfall trend, thereby \r\nincreasing near-term projection uncertainties (X. Huang et al., 2020a). \r\nSpecific regional applications of the use of large ensembles are further \r\nassessed in Sections 10.3.4.3 and 10.3.4.4. "


id: 4769c605c5f637411c70434a231f53ef
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 8622
content:
"The additional skill associated with the initialization of the cryosphere \r\nand the land surface has received limited attention. However, there \r\nis observational evidence that oceanic decadal variations can \r\npropagate into the atmosphere and, consequently accumulate into \r\nterrestrial land surface reservoirs (e.g.,  Bonnet et al., 2017) and \r\nvegetation (e.g., Zeng et al., 1999). This land surface memory, like in \r\nsoil moisture (Alessandri and Navarra, 2008; Catalano et al., 2016) \r\nor snow (Loranty et al., 2014), may also contribute to the decadal \r\npredictability of the terrestrial component of the water cycle, but "


id: 434d3f9f998ca8c3874c49181e4ab5df
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 7991
content:
"remains difficult to assess given the limitations of observational \r\nrecords. Vegetation initialization seems to generate as much noise as \r\nsignal and does not necessarily translate into improved skill in early \r\ndecadal predictions based on ESMs (Weiss et al., 2014). "


id: a93af96a3a05fb9c4682bc64aca8f42d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 24154
content:
"single large events or clustered smaller ones, can alter the water cycle \r\n(see also Cross-Chapter Box 4.1), and regional drought events may \r\nbe enhanced by co-occurring volcanic (Liu et al., 2016; Gao and Gao, \r\n2017; Zambri et al., 2017) and GHG (e.g., Cook et al., 2018) forcing \r\n(low confidence). Volcanic eruptions may also lead to widespread \r\nprecipitation anomalies up to several years following an eruption \r\nthrough their potential influence on the El Nino Southern Oscillation \r\n(low confidence) (Stevenson et al., 2016; Dee et al., 2020; McGregor \r\net al., 2020)."


id: 25b78067c6e93d795ea9c78172d4066d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 3359
content:
"Decadal hydrological predictability in an idealized setting has also \r\nbeen investigated through offline land surface hindcast experiments, \r\ndriven by observed atmospheric forcing and/or initial conditions, \r\nsuggesting the potential for skilful predictions for terrestrial water \r\nstorage, deep soil moisture, and groundwater (Yuan and Zhu, 2018). \r\nYet, a real-world assessment is hampered by the lack of observations \r\nand is only feasible when multi-decadal records of satellite estimates \r\nof terrestrial water storage, snow mass or soil moisture are available."


id: 9b759386644d968eb3142c1c1967bac0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 22013
content:
"In summary, large volcanic eruptions reduce global mean precipitation, \r\nas well as precipitation in tropical wet regions (high confidence). \r\nThere is low confidence in specific regional and seasonal responses, \r\nprimarily due to the limitations of the observational record."


id: 369abb5334517ad0b8a259bb708f3707
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 5979
content:
"In summary, there is high confidence that the water cycle changes \r\nthat have already emerged from internal variability will become more \r\npronounced in near-term (2021-2040) projections. However, there \r\nis low confidence in decadal predictions of precipitation changes, \r\nparticularly over most land areas, because internal variability \r\nremains difficult to predict and can offset or amplify the forced water \r\ncycle response. "


id: ad15709cf5d6694eb68ac9d53d976292
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 24776
content:
"The AR5 concluded that annual and seasonal mean precipitation \r\nchanges can be estimated by linear pattern-scaling techniques (Santer \r\nand Wigley, 1990; Arnell and Gosling, 2016; Greve et al., 2018), \r\nwhich represent regional changes in precipitation as a linear function \r\nof global mean temperature change. However, there are a number of \r\ncaveats when pattern-scaling is applied to low-emissions scenarios \r\nor to scenarios where localized forcing (e.g., anthropogenic aerosols) \r\nare significant and vary in time (Collins et al., 2013). Here the focus is \r\nin on non-linear water cycle responses to increasing global warming \r\nlevels, as estimated for instance from the difference between the first \r\n2degC of global warming, and the next 2degC of warming (Figure 8.25), \r\nand their possible underlying mechanisms."


id: 3e1bf85f0e72a4bcc171f4025564d445
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 7134
content:
"Data for six major eruptions over the last century along with \r\nCMIP5 historical experiments indicate that volcanic eruptions cause \r\na  detectable decrease in streamflow in northern South America, \r\nCentral Africa, high-latitude Asia and in wet tropical-subtropical \r\nregions, and a detectable increase in south-western North America \r\nand southern South America (Iles and Hegerl, 2015). Attempts \r\nto include volcanic forcing in future projections show enhanced \r\nprecipitation variability on annual to decadal time scales with \r\nsmall reductions in Asian monsoon rainfall (Bethke et al., 2017). \r\nThe occurrence of volcanic eruptions in the coming century, either as "


id: e6a1acaaea09e2a12327f5718f3ed8d2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 33768
content:
"and the rate of change (Ceppi et al., 2018). The usual distinction \r\nbetween the fast adjustment to increased GHG concentrations and \r\nthe slower response to SST warming (Section 8.2.2.2) may, however, \r\nnot be sufficient to explain the time evolution of the hydroclimatic \r\nresponse at the regional scale, especially in subtropical land areas "


id: d387945604d18f66aa269d5e20637ade
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 30810
content:
"response of different parts of the Earth system cause evolving spatial \r\nwarming patterns (Good et al., 2016a). This occurs primarily because \r\ndifferent feedbacks occur at different time scales (Armour et al., 2013; \r\nAndrews et al., 2015), which in turn implies that the atmospheric \r\ncirculation and water cycle is dependent both on the level of warming "


id: ef335904908c619412f89381b845f5dc
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 35103
content:
"where this response critically depends on shifts in atmospheric \r\ncirculation associated with distinct 'fast' (typically five to ten years, \r\nthat is however much slower than the atmospheric adjustment \r\nassessed in Section  8.2.1) and slow SST warming patterns (Zappa \r\net al., 2020). The changing balance between the water cycle response \r\nto anthropogenic GHG and aerosol forcings is another source of non\u0002linearity across time and global warming levels (Ishizaki et al., 2013; \r\nRowell et al., 2015; Y. Liu et al., 2019b; Wilcox et al., 2020). "


id: 530e013c6f5c05e5fec777b2fcb7d709
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 10529
content:
"In summary, there is high confidence that continued global warming \r\nwill further amplify GHG-induced changes in large-scale atmospheric \r\ncirculation and precipitation. Nonetheless, there are cases where \r\nregional water cycle changes are not linearly related to global \r\nwarming due to the interaction of multiple forcings, feedbacks and \r\ntime scales (medium confidence, see also Sections 4.2.4, 7.4.3 and \r\n8.2.1). Aridity in subtropical regions is highly sensitive to fast shifts \r\nin large-scale atmospheric circulation so are particularly susceptible \r\nto such non-linearities."


id: be5c6f11093f28dc2d2e720fa6982acd
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 27498
content:
"Based on a  simple model, it was also suggested that the Indian \r\nsummer monsoon may exhibit a moisture-advection feedback which \r\nallows multiple stable states as boundary conditions change (Zickfeld \r\net al., 2005). However, limitations of this theory and comprehensive \r\nGCMs suggest a  near-linear monsoon response to a  broad range \r\nof radiative forcings (Boos and Storelvmo, 2016). Non-linear \r\nprecipitation responses to global warming have been reported in \r\nthe Indo-Pacific, where a  linear increase in SSTs can trigger non\u0002linear changes in precipitation and a  shift in the ITCZ depending \r\non the relative amplitudes of uniform and structured SST anomalies \r\n(C.T.Y. Chung et al., 2014; Toda and Watanabe, 2018)."


id: 516a71f4a7f19e078ba90f996d99cf51
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 10267
content:
"Snowmelt is a nonl-inear process and projected changes in snowfall \r\nare also a  non-linear combination of changes in total precipitation \r\nand in the fraction of solid precipitation. In cold regions, snowfall may \r\nfirst increase because of the increased water capacity of a  warmer \r\natmosphere and then decrease because snow falls as rain in an even \r\nwarmer atmosphere. Such non-linearities can contribute to elevation, "


id: af8381d19428205f0bb81982e5adb1f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 25131
content:
"latitudinal and seasonal contrasts in the observed and projected \r\nretreat of the Northern Hemisphere (NH) snow cover (Shi and Wang, \r\n2015; Thackeray et al., 2016). Mountain glaciers also represent source \r\nof non-linear runoff responses since the annual runoff can first increase \r\ndue to additional melting and then decrease as the glaciers shrink \r\n(Kraaijenbrink et al., 2017; Shannon et al., 2019). Section  9.5.1.3 \r\nconcludes with high confidence that the average annual runoff from "


id: 32f19259b402ded521c21ce5bda53da4
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 5435
content:
"glaciers will generally reach a peak at the latest by the end of the 21st \r\ncentury, and decline thereafter. This peak may have already occurred for \r\nsmall catchments with little ice cover, but tends to occur later in basins \r\nwith large glaciers. Permafrost thawing is another mechanism which \r\ncan trigger a non-linear hydrological response in the high latitudes of \r\nthe NH (Walvoord and Kurylyk, 2016), whose magnitude and potential \r\nabruptness is assessed in Section 5.4.3.3."


id: 698f29e1737e95ca3bc8772b07157451
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14201
content:
"linear interactions between the ocean, atmosphere, and land surface \r\ncan result in rapid shifts between wet and dry states (Sections 8.6.1 \r\nand 8.6.2). Cessation of solar radiation modification could also result \r\nin abrupt changes in the water cycle (Section  8.6.3). This section \r\nreviews these types of abrupt shifts and assesses the likelihood that \r\nthey will occur by 2100."


id: 41ec247ee9d2df8bed7e5617a630cf3
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 7771
content:
"Beyond changes in land surface water fluxes, non-linearities in the \r\nresponse of soil moisture and freshwater reservoirs have not been \r\nwell documented in global climate projections but deserve further \r\nattention given the complex interactions between the water, energy \r\nand carbon cycles (Berg and Sheffield, 2018a), the growing direct \r\nhuman influence on rivers and groundwater (Abbott et al., 2019), \r\nand a possible offset between the linear components of changes in \r\nprecipitation and evapotranspiration. Significant non-linearities were \r\nfound in water scarcity projections, as seen by the stronger sensitivity \r\nto the first 2degC increase in global warming (Gosling and Arnell, 2016)."


id: 1f25c0e7834af3cca7da6566a5ad678d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 2339
content:
"In summary, there is both numerical and process-based evidence \r\nthat terrestrial water cycle changes can be non-linear at the regional \r\nscale (high confidence). Non-linear regional responses of runoff, \r\ngroundwater recharge and water scarcity have been documented \r\nbased on both CMIP5 and CMIP6 models, and highlight the limitations \r\nof simple pattern-scaling techniques (medium confidence). Water \r\nresources fed by melting glaciers are particularly exposed to such \r\nnon-linearities (high confidence)."


id: e6f574ae068e706827aa338e9a9e56b0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 33821
content:
"In this Report, abrupt change is defined as a regional-to-global scale \r\nchange in the climate system that occurs faster than the  typical \r\nrate of changes in its history, implying non-linearity in the climate \r\nresponse (see Glossary). Often, abrupt change arises from positive \r\nfeedbacks in the climate system that cause the current state to \r\nbecome unstable, and cross a 'tipping point' (Lenton et al., 2008); \r\nthat is, a rapid shift from one climate state to another. The water cycle \r\nhas several attributes with potential to produce abrupt change. Non\u0002"


id: 95d7f0c32484111a032791d444ff44a2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 21075
content:
"AMOC collapse also causes the Asian monsoon systems to weaken \r\n(Figure 8.27b; W. Liu et al., 2017) counteracting the strengthening \r\nexpected in response to elevated greenhouse gases (see \r\nSection 8.4.2). Europe is projected to experience moderate drying in \r\nresponse to AMOC collapse (Jackson et al., 2015). "


id: 50d4bc7e5b55b0cc41383993ca8ea433
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 10164
content:
"In summary, given that there is medium confidence that the decline \r\nin AMOC will not involve an abrupt collapse before 2100, there is low \r\nconfidence that an AMOC-driven abrupt change in the water cycle \r\nwill occur by 2100. However, if AMOC collapse does occur, it is very \r\nlikely that there would be large regional impacts on the water cycle."


id: eb1e6efc8bb71201868209ad4cd0cefd
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 34497
content:
"Changes in the land surface, including vegetation cover and dust \r\nemissions, can trigger abrupt changes in the water cycle. Plants \r\nregulate the exchange of water and energy between the land surface \r\nand the atmosphere (Section  8.2.3.3), such that sudden shifts in \r\nplant functions, types, or biomes can trigger feedbacks that have \r\nthe potential to cause abrupt changes in the regional water cycle. \r\nDust emissions, from either climatic or land use changes, affect the \r\nradiation budget and can regionally exacerbate dry extremes. Below, \r\nwe assess the likelihood of abrupt changes in the water cycle for the \r\nwell-studied regions of the Amazon and the Sahel, and the potential \r\nfor dust emissions to amplify drought and aridity."


id: 5f1a50a14853c4af59fe5735b63b8eef
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 12515
content:
"In AR5, some simulations using a  coupled climate-carbon cycle \r\nmodel exhibited an abrupt dieback of the Amazon forest in future \r\nclimate scenarios (Oyama and Nobre, 2003; Cox et al., 2004; Malhi \r\net al., 2008). However, subsequent work demonstrated that abrupt \r\nAmazon dieback does not occur consistently across, or even within, \r\nEarth system models (Lambert et al., 2013; Boulton et al., 2017). \r\nThe occurrence of dieback is highly dependent on both how dry the \r\nsimulated climate is in the present day (Malhi et al., 2009) as well \r\nas the representation of forest structure and competitive dynamics \r\n(Levine et al., 2016). Models with a low diversity of plant characteristics \r\nand types have a higher tendency for abrupt change (Sakschewski \r\net al., 2016). Abrupt shifts and ecosystem disruptions can occur on \r\nthe sub-regional level (Pires and Costa, 2013), highlighting the need "


id: 14016366e4149349032cedf98e469976
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 654
content:
"The Amazon forest plays an active role in driving atmospheric moisture \r\ntransport and generating precipitation in the South American region \r\n(SRCCL; Drumond et al., 2014; Poveda et al., 2014; Yin et al., 2014; \r\nStaal et al., 2018, 2020; Agudelo et al., 2019; Espinoza et al., 2019). "


id: ff6cd6ad9b823bd1b2ccef4fcda950c4
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 37737
content:
"for higher-resolution modelling studies. Since AR5, CMIP6 projections \r\nsuggest that a tipping point in the Amazon system may be crossed on \r\na local or regional scale (Staal et al., 2020) but continue to be highly \r\ndependent on model biases in precipitation and the simulation of the \r\nland surface. Consequently, the timing, and probability, of an abrupt \r\nshift remains difficult to ascertain. "


id: 6939c7b44a0da1af6ac63540fea18504
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14146
content:
"Bathiany et al., 2013). Conversely, low ecosystem diversity can \r\nproduce local or regional 'hot spots' of abrupt change such as those \r\nseen in some paleoclimate records (Claussen et al., 2013). "


id: 274086525e9256d0f547462ec5f4bc4c
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 3577
content:
"In summary, while there is a  strong theoretical expectation that \r\nAmazon drying and deforestation can cause a rapid change in the \r\nregional water cycle, currently there is limited model evidence to \r\nverify this response, hence there is low confidence that such a change \r\nwill occur by 2100."


id: 490f199b61085d9e3628389fa33ee4ca
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 8880
content:
"Some climate model simulations suggest that under future high\u0002emissions scenarios, CO2 radiative forcing causes rapid greening in \r\nthe Sahel and Sahara regions via precipitation change (Claussen \r\net al., 2003; Drijfhout et al., 2015). For example, in the BNU-ESM \r\nRCP8.5 simulation, the change is abrupt with the percentage of bare \r\nsoil dropping from 45% to 15%, and percentage of tree cover rising \r\nfrom 50% to 75%, within 10 years (2050-2060; Drijfhout et al., \r\n2015). However, other modelling results suggest that this may be \r\na short-lived response to CO2 fertilization (Bathiany et al., 2014). "


id: f126ae8521f45c1070804910434bd109
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 35439
content:
"In summary, given outstanding uncertainties in how well the current \r\ngeneration of climate models capture land surface feedbacks in the \r\nSahel and Sahara, there is low confidence that an abrupt change to \r\na greener state will occur in these regions before 2100 or 2300."


id: 7de38ab788c3f9f8fffdaf1ee7980ddf
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 17380
content:
"Mineral dust aerosols in the climate system originate from both semi\u0002permanent and transient sources (Prospero et al., 2002; Ginoux et al., \r\n2012). The former are typically arid regions where significant alluvial \r\nsediments have accumulated over time, while the latter are often \r\nassociated with natural (e.g., droughts, wildfires) and anthropogenic \r\n(e.g.,  land use change, desertification) disturbances. Modern-day \r\ndust emissions are dominated by natural sources (Ginoux et al., \r\n2012), although human emissions may contribute 10-60% of the \r\nglobal atmospheric dust load (Webb and Pierre, 2018). Paleo-dust \r\nrecords suggest that human factors (land use change and landscape \r\ndisturbance) may have doubled global dust emissions between 1750 \r\nand the last quarter of the 20th century (Section 2.2.6; Hooper and \r\nMarx, 2018)."


id: 9fb7b57dc3bedc9d63894290f9ff7d72
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 22669
content:
"Dust aerosols influence the climate system and hydrologic cycle \r\nthrough both direct impacts on radiation (absorbing and scattering \r\nlongwave and shortwave) and via indirect effects on cloud and \r\nprecipitation processes (Box  8.1; Choobari et al., 2014; Kok et al., \r\n2018; Schepanski, 2018). The capacity of dust aerosols to suppress \r\nprecipitation by reducing humidity and energy availability, and "


id: fbab3e257a9de74e01e3db8f465621b5
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 37099
content:
"precipitation relative to future CO2-emissions scenarios (Bala et al., \r\n2008; A. Jones et al., 2013; Tilmes et al., 2013; Ferraro et al., 2014; \r\nCrook et al., 2015). In contrast, cirrus cloud thinning, a  longwave \r\nradiation technique, results in increased global precipitation as it \r\ncauses enhanced radiative cooling in the troposphere (medium \r\nconfidence) (Crook et al., 2015; Kristjansson et al., 2015; Jackson \r\net al., 2016)."


id: 8aa6bd7debbc8bfe0f684b398b21c7bb
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 19357
content:
"The magnitude of hydrological disruption for both the initiation and \r\ntermination of SRM depends on the method used, as well as the \r\nstrength and duration of its implementation (Ekholm and Korhonen, \r\n2016; Irvine et al., 2019). Under abrupt SRM implementation, \r\nhydrological shifts are rapid, occurring within the first decade \r\n(Crook et al., 2015). Artificial enhancement of albedo in Northern \r\nHemisphere desert regions causes a southward shift in the Hadley \r\nCell and ITCZ, and extreme drying in the northern tropics (Crook et al., \r\n2015). Uniform or tropical stratospheric sulfate injection weakens \r\nthe African and Asian summer monsoons and causes drying in the \r\nAmazon (Robock et al., 2008; Crook et al., 2015; Dagon and Schrag, \r\n2016). Changes in evapotranspiration can produce large deficits or \r\nsurpluses in soil moisture and runoff in different regions and seasons \r\n(Dagon and Schrag, 2016). "


id: 7b628d462ec2745e4937a7e8293aca29
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 17001
content:
"The importance of dust aerosol feedbacks in future abrupt climate \r\nevents, like droughts or rapid aridification, is unclear. In part, this is \r\nbecause the response of dust aerosol emissions and loading levels \r\nin the atmosphere to climate change is highly uncertain (Tegen and \r\nSchepanski, 2018; Webb and Pierre, 2018). This difficulty in predicting \r\nfuture dust responses is rooted in the fact that emissions depend on \r\nboth changes to the land surface (e.g., land use/land cover change, \r\naridification, ecological responses to climate change) and the state \r\nof the atmosphere (Tegen and Schepanski, 2018). While there is some \r\nevidence that global dust aerosol concentrations in the future will \r\nincrease (Allen et al., 2016; Tegen and Schepanski, 2018), it is highly \r\ndependent on changes in precipitation patterns and atmospheric \r\ncirculation (see the SRCCL, Section 2.4.1), and it is not clear what the \r\nradiative impact will be (Allen et al., 2016; Kok et al., 2018). "


id: 55a4cd8067cc42aeb46a79eb9a8d99c4
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 10957
content:
"Rapid changes (years to decades) in the hydrological cycle are \r\nalso expected if SRM is terminated abruptly, either purposefully or \r\nbecause of technical failure or political disagreement. We reiterate \r\nthe AR5 conclusion that if SRM 'were terminated for any reason, there \r\nis high confidence that surface temperatures would increase rapidly \r\n(within a decade or two) to values consistent with the GHG forcing'. \r\nThe additional global warming caused by SRM termination may result \r\nin a rapid increase in global mean precipitation (medium confidence) \r\n(A. Jones et al., 2013). Heterogenous regional and seasonal changes \r\nare also expected, but are model-dependent (A. Jones et al., 2013). \r\nAs with SRM initiation, the impact of SRM termination is expected to \r\nbe dependent on the technique deployed. "


id: dff719af21df2aeb009c2f592c7a7a5f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 32727
content:
"In summary, due to limited evidence, there is low confidence\r\nregarding the role of dust in abrupt climate change events over the \r\nnext century."


id: 20a042f9ead78bdc0d72879f26af05f9
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 2578
content:
"In summary, it is very likely that abrupt water cycle changes will occur \r\nif SRM is abruptly initiated or halted, especially in tropical regions. \r\nFurther assessment of the potential side-effects of SRM is found in \r\nSection 4.6.3.3."


id: 8bcc2c207e7d6cd614e7864857de0bea
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 19516
content:
"interactions between climate change and internal variability and \r\nin the detection and attribution of observed water cycle changes."


id: 7115b5b2359004566b566f8fbf6b9432
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 15422
content:
"The authors are extremely grateful to the WGI Bureau and Technical \r\nSupport Unit for their outstanding support throughout the writing \r\nof the chapter. Special thanks to Sarah Connors for her exceptional \r\ncontribution to the development of this chapter. Her help with \r\nchapter meetings and organizational support was invaluable. Thanks \r\nto Sophie Berger, Melissa Gomis, Nigel Hawtin and Tom Maycock for \r\ntheir contributions to figures and tables. We must also make a special \r\nacknowledgment of our chapter scientists, Sabin Thazhe Purayil and \r\nStephane Senesi, without whom we could not have completed our \r\nassessment nor could we have produced the excellent figures that \r\nappear in the chapter. We would also like to thank all reviewers \r\nfor their useful comments. Finally, we are infinitely indebted to \r\nour families for their extended patience and support during this \r\ndemanding process. "


id: 6fe9f1a50dfd0c52e0aab99ab2f98d64
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15226
content:
"The ways in which humans use and change land cover, for example by converting fields to urban areas or clearing \r\nforests, can affect every aspect of the water cycle. Land-use changes can alter precipitation patterns and how \r\nwater is absorbed into the ground, flows into streams and rivers, or floods the land surface, as well as how \r\nmoisture evaporates back into the air. Changes in any of these aspects of the interconnected water cycle can \r\naffect the entire cycle and the availability of freshwater resources."


id: 2a944d7ebae6d2e84cce467955a4530f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 4124
content:
"Land use describes the combination of activities and ground cover defining each area of the Earth's continental \r\nsurface. Altering land use can modify the exchange of water between the atmosphere, soil and subsurface \r\n(FAQ 8.1, Figure 1). "


id: ccb9d8b4a8ef569d71712734b9edde7c
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 29749
content:
"For instance, changes in land cover can affect the ability of soils to soak up surface water (infiltration). When soil \r\nloses its capacity to soak up water, precipitation that would normally infiltrate and contribute to groundwater \r\nreserves will instead overflow, increasing surface water (runoff) and the likelihood of flooding. For example, \r\nchanging from vegetation to urban cover can cause water to flow rapidly over buildings, roads and driveways \r\nand into drains rather than soaking into the ground. Deforestation over wide areas can also directly reduce \r\nsoil moisture, evaporation and rainfall locally but can also cause regional temperature changes that affect \r\nrainfall patterns."


id: 5baec3683edecbd3237a12b87aaabb6
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 11931
content:
"Extracting water from the ground and river systems for agriculture, industry and drinking water depletes \r\ngroundwater and can increase surface evaporation because water that was previously in the ground is now in \r\ndirect contact with the atmosphere, being available for evaporation. "


id: 701b296e7247c8ee72c6f62b80f3c533
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15251
content:
"Changing land use can also alter how wet the soil is, influencing how quickly the ground heats up and cools \r\ndown and the local water cycle. Drier soils evaporate less water into the air but heat up more in the day. This can \r\nlead to warmer, more buoyant plumes of air that can promote cloud development and precipitation if there is \r\nenough moisture in the air. "


id: 85cb7b6d26aed31738be197fd2f94225
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 18590
content:
"Changes in land use can also modify the amount of tiny aerosol particles in the air. For instance, industrial and \r\ndomestic activities can contribute to aerosol emissions, as do natural environments such as forests or salt lakes. \r\nAerosols cool down global temperature by blocking out sunlight but can also affect the formation of clouds and \r\ntherefore the occurrence of precipitation (see FAQ 7.2). "


id: a81777a32741b9407f7683fa4926639
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 23959
content:
"Vegetation plays an important role in soaking up soil moisture and evaporating water into the air (transpiration) \r\nthrough tiny holes (stomata) that allow the plants to take in carbon dioxide. Some plants are better at retaining \r\nwater than others, so changes in vegetation can affect how much water infiltrates into the ground, flows into \r\nstreams and rivers, or is evaporated. "


id: 374104bfd6ecd04ec3d7a8ff9b8e5f39
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 6081
content:
"More globally, land-use change is currently responsible for about 15% of the emissions of carbon dioxide \r\nfrom human activities, leading to global warming, which in turn affects precipitation, evaporation, and plant \r\ntranspiration. In addition, higher atmospheric concentrations of carbon dioxide due to human activities can \r\nmake plants more efficient at retaining water because the stomata do not need to open so widely. Improved \r\nland and water management (e.g., reforestation, sustainable irrigation) can also contribute to reducing climate \r\nchange and adapting to some of its adverse consequences. "


id: d8ad745a4520b9f13beafca671bc00b9
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 31603
content:
"In summary, there is abundant evidence that changes in land use and land cover alter the water cycle globally, \r\nregionally and locally, by changing precipitation, evaporation, flooding, groundwater, and the availability of \r\nfreshwater for a variety of uses. Since all the components of the water cycle are connected (and linked to the \r\ncarbon cycle), changes in land use trickle down to many other components of the water cycle and climate system. "


id: c69f451dba0674c4f6ab0fc3b4e47cf1
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 28816
content:
"A warmer climate increases the amount and intensity of rainfall during wet events, and this is expected to \r\namplify the severity of flooding. However, the link between rainfall and flooding is complex, so while the most \r\nsevere flooding events are expected to worsen, floods could become rarer in some regions. "


id: d6b0d5180f8f7ce44b1f4bcfe9d79fd6
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 31283
content:
"Floods are a natural and important part of the water cycle but they can also threaten lives and safety, disrupt \r\nhuman activities, and damage infrastructure. Most inland floods occur when rivers overtop their banks (fluvial\r\nflooding) or when intense rainfall causes water to build up and overflow locally (pluvial flooding). Flooding is \r\nalso caused by coastal inundation by the sea, rapid seasonal melting of snow, and the accumulation of debris, \r\nsuch as vegetation or ice, that stops water from draining away. "


id: a94e746d7459129804c22da000a895e2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 24167
content:
"Climate change is already altering the location, frequency and severity of flooding. Close to the coasts, rising \r\nsea levels increasingly cause more frequent and severe coastal flooding, and the severity of these floods is \r\nexacerbated when combined with heavy rainfall. The heavy and sustained rainfall events responsible for most \r\ninland flooding are becoming more intense in many areas as the climate warms because air near Earth's surface \r\ncan carry around 7% more water in its gas phase (vapour) for each 1degC of warming. This extra moisture is drawn \r\ninto weather systems, fueling heavier rainfall (FAQ 8.2, Figure 1). "


id: 82f335d4084fc45dace1af561f473e38
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 18129
content:
"A warming climate also affects wind patterns, how storms form and evolve, and the pathway those storms \r\nusually travel. Warming also increases condensation rates, which in turn releases extra heat that can energize \r\nstorm systems and further intensify rainfall. On the other hand, this energy release can also inhibit the uplift \r\nrequired for cloud development, while increases in particle pollution can delay rainfall but invigorate storms. \r\nThese changes mean that the character of precipitation events (how often, how long lasting and how heavy they \r\nare) will continue to change as the climate warms. "


id: d7be3159a86f900e3f0f2b886f3b6e52
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 31470
content:
"In addition to climate change, the location, frequency and timing of the heaviest rainfall events and worst \r\nflooding depend on natural fluctuations in wind patterns that make some regions unusually wet or dry for \r\nmonths, years, or even decades. These natural variations make it difficult to determine whether heavy rainfall \r\nevents are changing locally as a result of global warming. However, when natural weather patterns bring heavy \r\nand prolonged rainfall in a warmer climate, the intensity is increased by the larger amount of moisture in the air."


id: e306f7eb232613781b6025fad3c2e457
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 33213
content:
"An increased intensity and frequency of record-breaking daily rainfall has been detected for much of the land \r\nsurface where good observational records exist, and this can only be explained by human-caused increases in \r\natmospheric greenhouse gas concentrations. Heavy rainfall is also projected to become more intense in the future \r\nfor most places. So, where unusually wet weather events or seasons occur, the rainfall amounts are expected to \r\nbe greater in the future, contributing to more severe flooding. "


id: f3689943e119c1b11ba508961014a2b4
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 35804
content:
"A mix of both increases and decreases in flooding have been observed in some regions and these changes have \r\nbeen attributed to multiple causes, including changes in snowmelt, soil moisture and rainfall. Although we \r\nknow that a warming climate will intensify rainfall events, local and regional trends are expected to vary in \r\nboth direction and magnitude as global warming results in multiple, and sometimes counteracting, influences. \r\nHowever, even accounting for the many factors that generate flooding, when weather patterns cause flood \r\nevents in a warmer future, these floods will be more severe. "


id: 8fb108c9a6cfe3ff927976fe7733fc3e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 20151
content:
"Flooding presents a hazard but the link between rainfall and flooding is not simple.\r\nWhile the largest flooding events can be expected to worsen, flood occurrence may decrease in some regions. "


id: 37ec0dc35e925b0505232cc2f83e30b3
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 6174
content:
"Droughts usually begin as a deficit of precipitation, but then propagate to other parts of the water cycle (soils, \r\nrivers, snow/ice and water reservoirs). They are also influenced by factors like temperature, vegetation and \r\nhuman land and water management. In a  warmer world, evaporation increases, which can make even wet \r\nregions more susceptible to drought."


id: 309d67618582d949e1e89bb2007525f4
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 5068
content:
"Baylor Fox-Kemper (United States of America), Helene T. Hewitt (United Kingdom), Cunde Xiao (China)"


id: b3a16efc083c6cd6fdafcbafe410947e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 25772
content:
"Gudfinna Adalgeirsdottir (Iceland), Sybren S. Drijfhout (The Netherlands), Tamsin L. Edwards \r\n(United Kingdom), Nicholas R. Golledge (New Zealand/United Kingdom), Mark Hemer (Australia), \r\nRobert E. Kopp (United States of America), Gerhard Krinner (France/Germany, France), Alan Mix \r\n(United States of America), Dirk Notz (Germany), Sophie Nowicki (United States of America/\r\nFrance, United States of America), Intan Suci Nurhati (Indonesia), Lucas Ruiz (Argentina), \r\nJean-Baptiste Sallee (France), Aimee B.A. Slangen (The Netherlands), Yongqiang Yu (China)"


id: 9afe69da69e8bd3c7ac025b4e5413d40
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 21922
content:
"(United Kingdom), Johannes Quaas (Germany), Roshanka Ranasinghe (The Netherlands/Sri Lanka, \r\nAustralia), Roelof Rietbroek (The Netherlands), Malcolm J. Roberts (United Kingdom), Alessio Rovere \r\n(Germany/Italy), Maria  Santolaria Otin (Spain, France/Spain), Abhishek Savita (Australia/India), \r\nAlex Sen Gupta (Australia/United Kingdom, Australia), Helene Seroussi (United States of America/\r\nFrance), Sharon L. Smith (Canada), Olga N. Solomina (The Russian Federation), Esther Stouthamer \r\n(The  Netherlands), Fiametta Straneo (United States of America/Italy, United States of America), \r\nWilliam V. Sweet (United States of America), Thomas Wahl (United States of America/Germany), Lisan Yu \r\n(United States of America), Jiacan Yuan (United States of America/China), Jan David Zika (Australia)"


id: 1f214a826e18eb4e2e5856de00b00f6c
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 2337
content:
"Unnikrishnan Alakkat (India), Benjamin P. Horton (Singapore/United Kingdom), Simon Marsland \r\n(Australia)"


id: 9a709bf2e5a169ea814016608c822277
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 21822
content:
"Gregory G. Garner (United States of America), Tim H. J. Hermans (The Netherlands), Lijuan Hua (China), \r\nTamzin Palmer (United Kingdom), Brodie Pearson (United States of America/United Kingdom)"


id: 8efeca6ecf4726f001dbe7d3add12b5e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 20035
content:
"Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Adalgeirsdottir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, \r\nG.  Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallee, A.B.A. Slangen, and Y. Yu, 2021: Ocean, \r\nCryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working \r\nGroup I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. \r\nZhai, A. Pirani, S.L.  Connors, C. Pean, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. \r\nLonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekci, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, \r\nCambridge, United Kingdom and New York, NY, USA, pp. 1211-1362, doi:10.1017/9781009157896.011."


id: b1341a3c6c92e583c3f5ee176dab7d1b
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 25385
content:
"Marine heatwaves  - sustained periods of anomalously high \r\nnear-surface temperatures that can lead to severe and persistent \r\nimpacts on marine ecosystems - have become more frequent \r\nover the 20th century (high confidence). Since the 1980s, they \r\nhave approximately doubled in frequency (high confidence) and \r\nhave become more intense and longer (medium confidence).\r\nThis  trend will continue, with marine heatwaves at global scale \r\nbecoming four times [2 to 9, likely range] more frequent in 2081-2100 \r\ncompared to 1995-2014 under SSP1-2.6, and eight times [3 to 15, likely\r\nrange] more frequent under SSP5-8.5. The largest changes will occur in \r\nthe tropical ocean and the Arctic (medium confidence). {Box 9.2}"


id: c451d8b37131899aeaf2d9be560fe3e2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 28455
content:
"The upper ocean has become more stably stratified since \r\nat least 1970 over the vast majority of the globe (virtually \r\ncertain), primarily due to surface-intensified warming and \r\nhigh-latitude surface freshening (very high confidence). Changes \r\nin ocean stability affect vertical exchanges of surface waters with \r\nthe deep ocean and large-scale ocean circulation. Based on recent \r\nrefined analyses of the available observations, the global 0-200 m \r\nstratification is now assessed to have increased about twice as much \r\nas reported by SROCC, with a 4.9 +- 1.5% increase from 1970 to 2018 \r\n(high confidence) and even higher increases at the base of the surface \r\nmixed layer. Upper-ocean stratification will continue to increase \r\nthroughout the 21st century (virtually certain). {9.2.1}"


id: 9ba197aa3ac8129842471af4529ded22
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 22043
content:
"At the ocean surface, temperature has, on average, increased by \r\n0.88 [0.68 to 1.01] degC between 1850-1900 and 2011-2020, with \r\n0.60 [0.44 to 0.74] degC of this warming having occurred since 1980. \r\nThe ocean surface temperature is projected to increase between \r\n1995 to 2014 and 2081 to 2100 on average by 0.86 [0.43 to \r\n1.47, likely range] degC in SSP1-2.6 and by 2.89 [2.01  to 4.07, \r\nlikely range] degC in SSP5-8.5. Since the 1950s, the fastest surface \r\nwarming has occurred in the Indian Ocean and in western boundary \r\ncurrents, while ocean circulation has caused slow warming or surface \r\ncooling in the Southern Ocean, equatorial Pacific, North Atlantic, and \r\ncoastal upwelling systems (very high confidence). At least 83% of the \r\nocean surface will very likely warm over the 21st century in all Shared \r\nSocio-economic Pathways (SSP) scenarios. {2.3.3, 9.2.1}"


id: 98965a8f283f92e03212c73b160f88b8
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 21522
content:
"The Atlantic Meridional Overturning Circulation (AMOC) will \r\nvery likely decline over the 21st century for all SSP scenarios. \r\nThere is medium confidence that the decline will not involve \r\nan abrupt collapse before 2100. For the 20th century, there is low \r\nconfidence in reconstructed and modelled AMOC changes because of \r\ntheir low agreement in quantitative trends. The low confidence also \r\narises from new observations that indicate missing key processes in \r\nboth models and measurements used for formulating proxies and \r\nfrom new evaluations of modelled AMOC variability.  This results \r\nin low confidence in quantitative projections of AMOC decline in the \r\n21st  century, despite the  high confidence  in the future decline as \r\na qualitative feature based on process understanding. {9.2.3}"


id: 1b0ea12245834748182e48cc0f51e12
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 1729
content:
"Southern Ocean circulation and associated temperature \r\nchanges in Antarctic ice-shelf cavities are sensitive to changes \r\nin wind patterns and increased ice shelf melt (high confidence). \r\nHowever, limitations in understanding feedback mechanisms \r\ninvolving the ocean, atmosphere and cryosphere, which are not fully \r\nrepresented in the current generation of climate models, generally \r\nlimit our confidence in future projections of the Southern Ocean and \r\nof its forcing on Antarctic sea ice and ice shelves. {9.2.3, 9.3.2, 9.4.2}"


id: fd9ad7b994fc17c5330a926f1716a218
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 37417
content:
"Many ocean currents will change in the 21st  century as \r\na  response to changes in wind stress associated with \r\nanthropogenic warming (high confidence). Western boundary \r\ncurrents have shifted poleward since 1993 (medium confidence), \r\nconsistent with a poleward shift of the subtropical gyres. Of the four \r\neastern boundary upwelling systems, only the California Current \r\nsystem has experienced some large-scale upwelling-favourable "


id: 57e62295682adbe65ec6fd2dc35f23e3
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 11332
content:
"The Antarctic Ice Sheet has  lost 2670 [1800 to 3540] Gt \r\nmass over the period 1992-2020, equivalent to 7.4 [5.0  to \r\n9.8] mm global mean sea level rise. The mass-loss rate was, on \r\naverage, 49 [-2 to +100] Gt yr -1 over the period 1992-1999, \r\n70 [22 to 119] Gt yr-1 over the period 2000-2009 and 148 [94 to \r\n202] Gt yr -1 over the period 2010-2019. Mass losses from West \r\nAntarctic outlet glaciers outpaced mass gain from increased snow \r\naccumulation on the continent and dominated the ice-sheet mass \r\nlosses since 1992 (very high confidence). These mass losses from the \r\nWest Antarctic outlet glaciers were mainly induced by ice-shelf basal \r\nmelt (high confidence) and locally by ice-shelf disintegration preceded \r\nby strong surface melt (high confidence). Parts of the East Antarctic \r\nIce Sheet have lost mass in the last two decades (high confidence). \r\n{2.3.2, 9.4.2, Atlas.11.1}"


id: fba9d32502dc1eeb360e53779e381a6c
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 37096
content:
"wind intensification since the 1980s (medium confidence). In the \r\n21st century, consistent with projected changes in the surface winds, \r\nthe East Australian Current Extension and Agulhas Current Extension \r\nwill intensify, while the Gulf Stream and Indonesian Throughflow \r\nwill weaken (medium confidence). Eastern boundary upwelling \r\nsystems will change, with a dipole spatial pattern within each system \r\nof reduction at low latitude and enhancement at high latitude \r\n(high confidence). {9.2.1, 9.2.3}"


id: 1834feec2713a625282f20a7360ed7c7
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1296
content:
"For Antarctic sea ice, regionally opposing trends and large \r\ninterannual variability result in no significant trend in satellite\u0002observed sea ice area from 1979 to 2020 in both winter and \r\nsummer (high confidence). The regionally opposing trends result \r\nprimarily from changing regional wind forcing (medium confidence). \r\nThere is low confidence in model simulations of future Antarctic sea \r\nice decrease, and lack of decrease, due to deficiencies of process \r\nrepresentation, in particular at the regional level. {2.3.2, 9.2.3, 9.3.2}"


id: 18643c4a28e505e66b78b66341fd53c7
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1335
content:
"The Greenland Ice Sheet has  lost 4890 [4140 to 5640] Gt \r\nmass over the period 1992-2020, equivalent to 13.5 [11.4 to \r\n15.6] mm global mean sea level rise. The mass-loss rate was \r\non average 39 [-3 to +80] Gt yr-1 over the period 1992-1999, \r\n175 [131 to 220] Gt yr-1 over the period 2000-2009 and \r\n243 [197 to 290] Gt yr -1 over the period 2010-2019. This mass \r\nloss is driven by both discharge and surface melt, with the latter \r\nincreasingly becoming the dominating component of mass loss with \r\nhigh interannual variability in the last decade (high confidence). The \r\nlargest mass losses occurred in the north-west and the south-east of \r\nGreenland (high confidence). {2.3.2, 9.4.1}"


id: a2b8fd1c3d33a5e230e397e5f151a7f5
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 23167
content:
"Glaciers lost 6200 [4600 to 7800] Gt of mass (17.1 [12.7 to \r\n21.5] mm global mean sea level equivalent) over the period \r\n1993-2019 and will continue losing mass under all SSP scenarios \r\n(very high confidence). During the decade 2010-2019, glaciers \r\nlost more mass than in any other decade since the beginning of \r\nthe observational record (very high confidence). For all regions \r\nwith long-term observations, glacier mass in the decade 2010-2019 \r\nis the smallest since at least the beginning of the 20th  century \r\n(medium confidence). Because of their lagged response, glaciers \r\nwill continue to lose mass at least for several decades even if global \r\ntemperature is stabilized (very  high  confidence). Glaciers  will lose "


id: fa3a71fcc178c3556a0fe7c101578cd0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 36888
content:
"29,000 [9000 to 49,000] Gt and 58,000 [28,000 to 88,000] Gt over \r\nthe period 2015-2100 for RCP2.6 and RCP8.5, respectively (medium \r\nconfidence), which represents 18 [5 to 31] % and 36 [16 to 56] % \r\nof their early-21st-century mass, respectively. {2.3.2, 9.5.1, 9.6.1, \r\n9.6.3, 12.4}"


id: 294e097f5dc031b3b1dce050c284d009
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 3936
content:
"Ocean thermal expansion (38%) and mass loss from glaciers (41%) \r\ndominate the total change from 1901 to 2018. The contribution of \r\nGreenland and Antarctica to GMSL rise was four times larger during \r\n2010-2019 than during 1992-1999 (high confidence). Because of \r\nthe increased ice-sheet mass loss, the total loss of land ice (glaciers \r\nand ice sheets) was the largest contributor to global mean sea level \r\nrise over the period 2006-2018 (high confidence). {2.3.3, 9.6.1, 9.6.2, \r\nCross-Chapter Box 9.1, Table 9.A.1, Box 7.2}"


id: a7e7f0aea025b17d9b4aec7f753756e4
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 23929
content:
"At the basin scale, sea levels rose fastest in the Western Pacific \r\nand slowest in the Eastern Pacific over the period 1993-2018 \r\n(medium confidence). Regional differences in sea level arise from: \r\nocean dynamics; changes in Earth gravity, rotation and deformation \r\ndue to land ice and land-water changes; and vertical land motion. \r\nTemporal variability in ocean dynamics dominates regional patterns \r\non annual to decadal time scales (high confidence). The anthropogenic \r\nsignal in regional sea level change will emerge in most regions \r\nby 2100 (medium confidence). {9.2.4, 9.6.1}"


id: 59cfd839612aeb33f7e324c453e19dc1
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 11634
content:
"Increases in permafrost temperature have been observed over \r\nthe past three to four decades throughout the permafrost \r\nregions (high confidence), and further global warming will \r\nlead to near-surface permafrost volume loss (high confidence).\r\nComplete permafrost thaw in recent decades is a  common \r\nphenomenon in discontinuous and sporadic permafrost regions \r\n(medium confidence). Permafrost warmed globally by 0.29 [0.17 to \r\n0.41, likely range] degC between 2007 and 2016 (medium confidence). \r\nAn increase in the active layer thickness is a pan-Arctic phenomenon \r\n(medium confidence), subject to strong heterogeneity in surface \r\nconditions. The volume of perennially frozen soil within the upper 3 m \r\nof the ground will decrease by about 25% per 1degC of global surface \r\nair temperature change (up to 4degC above pre-industrial temperature) \r\n(medium confidence). {9.5.2}"


id: dd0cd1ff86b1a0982c9fe2cd79b67437
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 32276
content:
"Northern Hemisphere spring snow cover extent has been \r\ndecreasing since 1978 (very high confidence), and there is\r\nhigh confidence that this trend extends back to 1950. Further \r\ndecrease of Northern Hemisphere seasonal snow cover \r\nextent is virtually certain under further global warming. The \r\nobserved sensitivity of Northern Hemisphere snow cover extent to \r\nNorthern Hemisphere land surface air temperature for 1981-2010 \r\nis -1.9 [-2.8 to -1.0, likely range] million km2 per 1degC throughout \r\nthe snow season. It is virtually certain that Northern Hemisphere \r\nsnow cover extent will continue to decrease as global climate \r\ncontinues to warm, and process understanding strongly suggests \r\nthat this also applies to Southern Hemisphere seasonal snow \r\ncover (high  confidence). Northern Hemisphere spring snow cover \r\nextent will decrease by about 8% per 1degC of global surface air \r\ntemperature change (up to 4degC above pre-industrial temperature) \r\n(medium confidence). {9.5.3}"


id: feef00304767701fc95782a7a81b22b0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 37655
content:
"It is  virtually certain  that GMSL will continue to rise until \r\nat least 2100, because all assessed contributors to GMSL \r\nare likely to virtually certain  to continue contributing \r\nthroughout this century. Considering only processes for which \r\nprojections can be made with at least medium confidence, \r\nrelative to the period 1995-2014, GMSL will rise by 2050 \r\nbetween 0.18  [0.15  to 0.23, likely range] m (SSP1-1.9) and \r\n0.23  [0.20  to  0.29, likely range]  m (SSP5-8.5), and by 2100 \r\nbetween 0.38  [0.28 to  0.55, likely range] m (SSP1-1.9) and \r\n0.77 [0.63  to 1.01, likely range]  m (SSP5-8.5). This GMSL \r\nrise is primarily caused by thermal expansion and mass loss from \r\nglaciers and ice sheets, with minor contributions from changes in \r\nland-water storage. These likely range projections do not include \r\nthose ice-sheet-related processes that are characterized by deep \r\nuncertainty. {9.6.3}"


id: e5a0152441094a60af84be06dc61f119
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 33635
content:
"Global mean sea level (GMSL) rose faster in the 20th century \r\nthan in any prior century over the last three millennia \r\n(high confidence), with a  0.20 [0.15 to 0.25] m rise over \r\nthe period 1901-2018 (high confidence). GMSL rise has \r\naccelerated since the late 1960s, with an average rate of \r\n2.3 [1.6 to 3.1] mm yr-1 over the period 1971-2018 increasing \r\nto  3.7  [3.2  to 4.2]  mm  yr-1 over the period 2006-2018 \r\n(high confidence). New observation-based estimates published \r\nsince SROCC lead to an assessed sea level rise over the period \r\n1901-2018 that is consistent with the sum of individual components. "


id: c1d7524c18d881226de63a322be48c57
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 28078
content:
"At sustained warming levels between 2degC and 3degC, the Arctic \r\nOcean will be practically sea ice free throughout September in \r\nmost years (medium confidence); there is limited evidence that the \r\nGreenland and West Antarctic ice sheets will be lost almost completely \r\nand irreversibly over multiple millennia; both the probability of their \r\ncomplete loss and the rate of mass loss will increase with higher \r\ntemperatures (high confidence); about 50 to 60% of current glacier \r\nmass outside Antarctica will be lost (low confidence); Northern \r\nHemisphere spring snow cover extent will decrease by up to 30% \r\nrelative to 1995-2014 (medium confidence); permafrost volume \r\nin the top 3 m will decrease by up to 75% relative to 1995-2014 \r\n(medium confidence). Committed GMSL rise over 2000 years will be \r\nabout 4 to 10 m with 3degC of peak warming (medium agreement, \r\nlimited evidence). {9.3.1, 9.4.1, 9.4.2, 9.5.1, 9.5.2, 9.5.3, 9.6.3}"


id: ecc77ca7ba4b9f25c26a0ebeeba2425f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 34732
content:
"Higher amounts of GMSL rise before 2100 could be caused \r\nby earlier-than-projected disintegration of marine ice shelves, \r\nthe abrupt, widespread onset of marine ice sheet instability \r\nand marine ice cliff instability around Antarctica, and faster\u0002than-projected changes in the surface mass balance and \r\ndischarge from Greenland. These processes are characterized by \r\ndeep uncertainty arising from limited process understanding, limited \r\navailability of evaluation data, uncertainties in their external forcing \r\nand high sensitivity to uncertain boundary conditions and parameters. \r\nIn a low-likelihood, high-impact storyline, under high emissions such \r\nprocesses could in combination contribute more than one additional \r\nmetre of sea level rise by 2100. {9.6.3, Box 9.4}"


id: d75952b10a04b748805ff9b2dbd8e1d5
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 31400
content:
"Beyond 2100, GMSL will continue to rise for centuries due \r\nto continuing deep-ocean heat uptake and mass loss of the \r\nGreenland and Antarctic ice sheets, and will remain elevated for \r\nthousands of years (high confidence). Considering only processes \r\nfor which projections can be made with at least medium confidence\r\nand assuming no increase in ice-mass flux after 2100, relative to the \r\nperiod 1995-2014, by 2150, GMSL will rise between 0.6 [0.4 to 0.9, \r\nlikely range] m (SSP1-1.9) and 1.4 [1.0 to 1.9, likely range] m (SSP5-8.5). \r\nBy 2300, GMSL will rise between 0.3 m and 3.1 m under SSP1-2.6, \r\nbetween 1.7 m and 6.8 m under SSP5-8.5 in the absence of marine ice \r\ncliff instability, and by up to 16 m under SSP5-8.5 considering marine \r\nice cliff instability (low confidence). {9.6.3}"


id: 688a39de0c7c6325c12c807b35c1d7f2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14038
content:
"There are two major advances of this chapter compared with AR5 \r\nand SROCC facilitated by community efforts. The first is the temporal \r\nand spatial increase in observations of both the ocean and the \r\ncryosphere (Section  1.5.1.1). In particular, extended observations \r\nhave allowed for improved assessment of past change and closure \r\nof both the energy and sea level budgets in a  consistent way \r\n(Cross-Chapter Box 9.1) and the sea level budget for the last century \r\n(Section 9.6.1.1). Higher resolution observations have revealed the \r\ndetails of the Atlantic Meridional Overturning Circulation (AMOC; \r\nSection 9.2.3.1) and globally resolved glacier changes for the first time \r\n(Section 9.5.1.1). Improved methodology has resulted in a doubling \r\nof the assessed level of observed increase in global ocean 0-200 m \r\nstratification compared to SROCC assessment (Section 9.2.1.3)."


id: 7ec4b2720a65b71b1af4dba0b4ad2e02
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 17508
content:
"This chapter provides a holistic assessment of the physical processes \r\nunderlying global and regional changes in the ocean, cryosphere and \r\nsea level, as well as improved understanding of observed, attributed \r\nand projected future changes since the IPCC Fifth Assessment Report \r\n(AR5) and the Special Report on the Ocean and Cryosphere in \r\na Changing Climate (SROCC; see outline in Figure 9.1). The ocean and \r\ncryosphere (defined as the frozen components of the Earth system \r\nsuch as sea ice, ice sheets, glaciers, permafrost and snow) exchange \r\nheat and freshwater with the atmosphere and each other (Figure 9.2). \r\nIn a warming climate, the combined effects of thermal expansion of \r\nseawater and melting of the terrestrial cryosphere result in global \r\nmean sea level rise (Box 9.1)."


id: 7218ee34397be2e1404c481c49c677b7
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15578
content:
"The second advance is the use of a  hierarchy of models and \r\nemulators to update projections of oceanic, cryospheric and sea \r\nlevel change arising from Coupled Model Intercomparison Project \r\nPhase 6 (CMIP6) and related projects (Section  1.5.4.3, Table  1.3, \r\nand Annex  II).2 The CMIP6 included an ice-sheet modelling \r\nintercomparison for the  first time. Particular modelling advances \r\nrelevant to this chapter are the increase in ocean resolution in the \r\nHigh Resolution Model Intercomparison Project (HighResMIP) and \r\nOcean Model Intercomparison Project phase 2 (OMIP-2) experiments \r\n(Sections 1.5.3.1 and 9.2), projections of future glacier (GlacierMIP) \r\nand ice sheet (ISMIP6) and Linear Antarctic Response Model "


id: dc50ae19a4db97118c184a42b1dc5a6f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 32170
content:
"Ocean acidification and deoxygenation are covered in Chapter  5, \r\nand regional changes to the ocean and cryosphere are covered in \r\nChapter 12 and the Atlas. Ecosystem range shifts and climate risk \r\nfor marine biodiversity associated with ocean change are assessed \r\nin AR6 Working Group II (WGII). The notion of 'climate velocity' often \r\nused in impact studies, which is defined as the speed and direction \r\nat which a  climate variable moves across a  corresponding spatial \r\nfield, is underpinned by the assessment of changes in the physical \r\ncharacteristics of the ocean provided in this chapter."


id: fdcf71c5ce94ed60e3c79dd4b0237eb9
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 37450
content:
"Intercomparison Project (LARMIP-2) response from multi-model \r\nstudies (Sections 9.5.1 and 9.4, and Box 9.3), and new methods to \r\nsynthesize ocean and cryosphere models into sea level projections for \r\nall Shared Socieo-economic Pathway scenarios (SSPs; Sections 1.6.1, \r\n9.4.1.3, 9.4.2.5 and 9.6.3, and Cross-Chapter Box 1.4) and warming \r\nlevels (Sections 9.6.3 and 1.6.2, and Cross-Chapter Box  11.1). \r\nIn  particular, sea level projections and the individual contributions \r\n(Section 9.6.3.3) are consistent with equilibrium climate sensitivity \r\nand surface temperature assessments across this Report (Box 4.1 and \r\nCross-Chapter Box 7.1)."


id: 85d193dd221703487c71705b921fb9a7
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 18597
content:
"There are other advances in scientific understanding. In the cryosphere, \r\nthis chapter assesses how fast-responding elements (sea ice, permafrost \r\nand snow; Sections 9.3, 9.5.2 and 9.5.3) track warming levels across \r\nobservations and projections independent of scenario, process \r\nunderstanding of uncertainty in Antarctic Ice Sheet projections \r\n(Section 9.4.2 and Box 9.4) and new insight into thresholds for Arctic \r\nsea ice (Section 9.3.1.1) and Greenland and West Antarctic ice sheets \r\n(Sections 9.4.1.4 and 9.4.2.6). In the ocean, process understanding \r\nof ocean heat uptake (Section 9.2.2.1 and Cross-Chapter Box 5.3) \r\nand observed changes in ocean stratification (Section 9.2.1.3) have \r\nimplications for ocean biogeochemistry are also important."


id: b57a8489100d47ff8a0818a8825b6c0a
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 26082
content:
"Sea level change arises from processes acting on a  range of spatial and temporal scales, in the ocean, cryosphere, solid Earth, \r\natmosphere and on land (Figure 9.2). Relative sea level (RSL) change is the change in local mean sea surface height relative to \r\nthe sea floor, as measured by instruments that are fixed to the Earth's surface (e.g., tide gauges). This reference frame is used when \r\nconsidering coastal impacts, hazards and adaptation needs. In contrast, geocentric sea level change is the change in local mean \r\nsea surface height with respect to the terrestrial reference frame, and is the sea level change observed with instruments from space. \r\nThis box provides a brief summary of sea level processes using standard terminology (Gregory et al., 2019). "


id: 7e3d45efce53295360e54ff900155c83
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 17426
content:
"Global mean sea level change (Sections 9.6 and 2.3.3.3) is the change in volume of the ocean divided by the ocean surface area. \r\nIt is the sum of changes in ocean density ('global mean thermosteric sea level change') and changes in the ocean mass as a result of \r\nchanges in the cryosphere or land-water storage ('barystatic sea level change'). "


id: 5e22636d24a029c956666361c1978144
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 12334
content:
"Steric sea level change is caused by changes in the ocean density and is composed of 'thermosteric sea level change' and 'halosteric \r\nsea level change'. Thermosteric sea level change (also referred to as 'thermal expansion') occurs as a result of changes in ocean \r\ntemperature: increasing temperature reduces ocean density and increases the volume per unit of mass. Halosteric sea level change\r\noccurs as a result of salinity variations: higher salinity leads to higher density and decreases the volume per unit of mass. Although \r\nboth processes can be relevant on regional to local scales, thermosteric changes contribute to global mean sea level change, whereas \r\nglobal mean halosteric change is negligible (Gregory et al., 2019). There is high confidence in the understanding of processes causing \r\nthermosteric sea level change (Section 9.2.4.1)."


id: 7749b769f585e118373773c55e36f9ce
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 16327
content:
"The Greenland and Antarctic ice sheets are the largest reservoirs of frozen freshwater and therefore potentially the largest contributors \r\nto sea level rise. Fluctuations in ice-sheet volume arise from the imbalance between accumulation (either at the ice-sheet surface or on \r\nthe underside of ice shelves) and loss from sublimation, surface and basal melting, and iceberg calving. Ice sheets discharge the majority \r\nof their mass through marine-terminating ice streams that are in some cases buttressed by floating ice shelves. Changes in the thickness \r\nand extent of the ice shelves due to melt from below, calving, or disintegration, as a result of surface meltwater penetrating crevasses, \r\ncan affect the flow of the inland ice streams. There is medium confidence in ice-sheet processes but low confidence in their forcing \r\n(ocean changes and ice-shelf collapse) and in instability processes (Sections 9.4.1 and 9.4.2).3"


id: 1e5a015cfcb19987df8d9da7ca2bac00
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 2216
content:
"Glaciers contribute to sea level change via an imbalance between mass gain and mass loss processes, which leads to adjustments \r\nin the glacier geometry over an extended period of time, called the response time. The response time may range from a few years to \r\na few hundred years. The glacial meltwater does not all flow immediately into the ocean: it can refreeze, feed rivers (where it may be \r\nextracted for domestic use), evaporate, or be stored in (proglacial) lakes or closed basins. There is medium to high confidence in the \r\nunderstanding of processes leading to sea level contributions from glaciers (Section 9.5.1)."


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created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 18730
content:
"Land-water storage includes surface water, soil moisture, groundwater storage and snow, but excludes water stored in glaciers \r\nand ice sheets. Changes in land-water storage can be caused either by direct human intervention in the water cycle (e.g., storage of \r\nwater in reservoirs by building dams in rivers, groundwater extraction for consumption and irrigation, or deforestation) or by climate \r\nvariations (e.g., changes in the amount of water in internally drained lakes and wetlands, the canopy, the soil, the permafrost and "


id: 4a292469e8fd7b3850781ba9ef6ab51c
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 9072
content:
"the snowpack). Land-water storage changes caused by climate variations may be indirectly affected by anthropogenic influences. \r\nIt is difficult to assign a single confidence level to land-water storage as understanding can vary from low confidence in groundwater \r\nrecharge processes to high confidence in water storage via snowpack changes (Sections 8.2.3 and 8.3.1.7)."


id: 5bbf83bec3da8124403a4311046599a5
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 11947
content:
"Ocean dynamic sea level change refers to the change in mean sea level relative to the geoid and is associated with the circulation \r\nand density-driven changes in the ocean. Ocean dynamic sea level change varies regionally but by definition has a  zero global \r\nmean. It includes the depression of the sea surface by atmospheric pressure. There is medium confidence in the understanding of \r\nocean processes leading to dynamic sea level change (Section 9.2.4.2)."


id: 11ad3b00716ed34e08f52cd430a3a94d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 271
content:
"Glacial isostatic adjustment is ongoing GRD in response to past changes in the distribution of ice and water on Earth's surface. \r\nOn a time scale of decades to tens of millennia following mass redistribution, Earth's mantle flows viscously as it evolves toward \r\nisostatic equilibrium, causing solid Earth movement and geoid changes, which can result in regional to local sea level variations. There \r\nis medium confidence in the understanding of glacial isostatic adjustment processes."


id: 2e120daeb4e0ddcfb7961b112df0f8d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 4688
content:
"Vertical land motion is the change in height of the land surface or the sea floor and can have several causes in addition to elastic \r\ndeformation associated with contemporary GRD and viscoelastic deformation associated with glacial isostatic adjustment. Subsidence \r\n(sinking of the land surface or sea floor) can occur through compaction of alluvial sediments in deltaic regions, removal of fluids such \r\nas gas, oil, and water, or drainage of peatlands. Tectonic deformation of the Earth's crust can occur as a result of earthquakes and \r\nvolcanic eruptions. There is medium confidence in the understanding of vertical land motion processes. "


id: dcb639ca13a80938910330f2c5f9042f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 32226
content:
"with buoy-based observations and improved treatment of sea ice, \r\nhave had important consequences for key climate change indicators \r\nsuch as global mean surface temperature (GMST), global surface \r\nair temperature (GSAT), and SST (Cross-Chapter Box  2.3). The AR5 \r\nassessment is confirmed, and it is now very likely that global mean SST \r\nchanged by 0.88 [0.68 to 1.01] degC from 1850-1900 to 2011-2020, and \r\n0.60 [0.44 to 0.74] degC from 1980 to 2020 (Figure 9.3 and Table 2.4)."


id: 7281d2ec7cdab3c3aec274920bdae265
created_at: 2023-03-16 14:00:46
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vector_id: 15635
content:
"The IPCC Fifth Assessment Report (AR5; Hartmann et  al., 2013) \r\nassessed that it is virtually certain that global sea surface temperature \r\n(SST) has increased since the beginning of the 20th century (very high \r\nconfidence). The Special Report on Ocean and Cryosphere in \r\na Changing Climate (SROCC) did not assess past SST change. Since \r\nAR5, improvements in the understanding of recent SST biases in the \r\nobservational records, especially extending ship-based observations "


id: 82d41d7664a241a2711375272f3335ba
created_at: 2023-03-16 14:00:46
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vector_id: 18107
content:
"Regions vary in the rate of SST warming, with slight cooling in some \r\nregions (Figure 9.3). The SROCC (Collins et al., 2019) and Section 7.4.4 \r\nassess SST changes over specific regions, which are consistent with the \r\nchanges reported here. The tropical ocean has been warming faster \r\nthan other regions since 1950, with the fastest warming in regions "


id: c749ed563f332ced303e2b959b374de8
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 28943
content:
"of the tropical Indian and western Pacific oceans (Figure 9.3), due to \r\na combination of local atmosphere-ocean coupling, the Indonesian \r\nThroughflow (Section  9.2.3.4 and Figure  9.11), and trends in the \r\nWalker circulation (Sections 2.3.1.4.1 and 3.3.3.1, and Figure 3.16). \r\nThe western boundary currents of the subtropical gyres have warmed \r\nfaster than the global mean over the past century. There remains low \r\nagreement in the changes of the location and the dynamical changes \r\nin western boundary current extensions (Sections 2.3.3.4.2 and \r\n9.2.3.4, and Figure 9.3). In the Arctic, the mean SST increase over the \r\nlast two decades is similar to, or only slightly higher than, the global \r\naverage (J.-L Chen et al., 2019). In contrast, the eastern Pacific Ocean, "


id: 721300f4181c09a12e4178161df6cb4d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 15575
content:
"subpolar  North Atlantic Ocean and Southern Ocean have warmed \r\nmore slowly than the global average or cooled (Figure 9.3). Surface \r\nwarming in the subpolar Southern Ocean has been slower than \r\nthe global average since the 1950s, and this pattern is consistent \r\nwith the upwelling around Antarctica renewing surface water with \r\npre-industrial, deeper water masses (Section  9.2.3.2; Frolicher \r\net al., 2015; J. Marshall et al., 2015; Armour et al., 2016). New evidence \r\nsince SROCC (Meredith et  al., 2019) confirms slight cooling since \r\nthe 1980s around the subpolar Southern Ocean, contrasting with \r\nmarked warming directly northward of it (Section 9.2.3.2; Haumann \r\net al., 2020; Rye et al., 2020; Auger et al., 2021). In eastern boundary "


id: c4e98521c3b1fa21e97f36ab04d6a7e6
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 28553
content:
"direction of SST changes in observations are consistent with CMIP6 \r\nonly when including internal variability (Olonscheck et  al., 2020). \r\nThis is notably the case in the equatorial Pacific, North Atlantic, \r\nand Southern Ocean, which are regions where SST is of known \r\nimportance in controlling heat uptake (Section 9.2.2.1) and the global \r\nradiative feedback parameter (Section 7.4.4.3). Overall, despite some \r\npersistent regional biases, CMIP6 coupled climate models reproduce \r\nthe observed SST trends or high internal variability over the past \r\ncentury over a range of different multi-decadal periods (Figure 9.3; \r\nOlonscheck et al., 2020; Watanabe et al., 2021), highlighting their skill \r\nto inform future large-scale SST changes at regional scale. Warming \r\nis projected at varying rates in all regions by 2050, except the North \r\nAtlantic Subpolar Region, the equatorial Pacific, and the Southern \r\nOcean where models disagree (high confidence)."


id: 544ffb072c0a0a3a05df47cfd463c64b
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 10726
content:
"upwelling systems, SROCC (Bindoff et  al., 2019) reported low \r\nagreement between SST trends in recent decades, due to varying \r\nspatio-temporal resolution and interannual to multi-decadal \r\nvariability. Satellite evidence not included in SROCC shows that \r\n92% of these regions warmed more slowly than neighbouring \r\noffshore locations between 1982 and 2015, so upwelling may buffer \r\nthe near shore from warming (Section 9.2.3.5; Varela et al., 2018). \r\nCoupled ocean-atmospheric modes of variability strongly affect \r\nregional SST (Cross-Chapter Box  3.1 and Annex IV). In  summary, \r\na positive SST trend since 1950 is evident globally, but there is very \r\nhigh confidence that the Indian Ocean, western equatorial Pacific \r\nOcean, and western boundary currents have warmed faster than the \r\nglobal average, while the Southern Ocean, the eastern equatorial \r\nPacific, and the North Atlantic Ocean have warmed more slowly, or \r\nhave slightly cooled."


id: 224f0626a0d6ac5af017e630be80e932
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 2846
content:
"on future emissions scenario, and some of the observed cooling trends \r\nover the 20th  century will eventually transition to a  warming SST \r\non centennial time scales, in particular in the Southern Ocean (high \r\nconfidence) and in the equatorial Pacific (medium confidence), while \r\nthe North Atlantic subpolar gyre will continue to warm more slowly \r\nthan the global average (high confidence)."


id: 7beebaafe4a1867e3cb9693578f848b9
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 17100
content:
"Air-sea fluxes of energy, freshwater, and momentum (wind stresses) \r\nare difficult to observe directly (Cronin et al., 2019), so estimates of \r\nthe global mean net air-sea heat flux are inferred from observed \r\nocean warming (Section 2.3.3.1, Box 7.2, and Cross-Chapter Box 9.1). \r\nAir-sea heat fluxes resemble the warming patterns of CMIP3 \r\n(Domingues et al., 2008; Levitus et al., 2012) and are consistent with \r\nthe ensemble mean warming rate of CMIP5 (Cheng et  al., 2017, \r\n2019) and CMIP6 models (Section 3.5.1.3). Regional air-sea fluxes \r\nin models remain a  key driver of uncertainty (Huber and Zanna, \r\n2017; Tsujino et  al., 2020). A  substantial part of the upper 700 m \r\nenergy increase is very likely attributed to anthropogenic forcing via \r\nincreasing radiative forcing (Sections 3.5.1.3, 7.2 and 7.3)."


id: a5955df474a2a3bc2db0d18185067974
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 23624
content:
"hide larger increases occurring at the seasonally and regionally \r\nvariable pycnocline depth. There is also limited evidence that summer \r\nstratification change within the pycnocline has occurred at a rate of \r\n8.9 +- 2.7% per decade from 1970 to 2018, and limited evidence of \r\na winter pycnocline stratification increase (Cummins and Ross, 2020; \r\nSallee et al., 2021)."


id: 624efc92604611fc25d1d8f968552d68
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 13019
content:
"Boucher et al., 2020; Danabasoglu et al., 2020; Dunne et al., 2020; \r\nKelley et al., 2020). In summary, the representation of upper-ocean \r\nstratification and mixed layers has improved in CMIP6 compared \r\nto CMIP5. While it is virtually certain that the global mean upper \r\nocean will continue to stratify in the 21st  century, there is only \r\nlow confidence in the future evolution of mixed-layer depth, \r\nwhich is projected to mostly shoal under high emissions, except in \r\nhigh-latitude regions where sea ice retreats."


id: 3527aec0719b6dd59830c6647608c792
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 5773
content:
"not resolved in climate models (D'Asaro, 2014; Buckingham et al., \r\n2019; McWilliams, 2019) and despite significant improvements \r\nin their parametrization over the last decade (Fox-Kemper et  al., \r\n2011; Jochum et al., 2013; Q. Li et al., 2016, 2019; Qiao et al., 2016) \r\nand significant improvement in some models (Li and Fox-Kemper, \r\n2017; Dunne et  al., 2020), biases in mixed-layer representation \r\ngenerally persist (Heuze, 2017; Williams et al., 2018; Cherchi et al., \r\n2019; Golaz et al., 2019; Voldoire et al., 2019; Yukimoto et al., 2019; "


id: 424fdf9176c49699a69ce433b89904e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 7833
content:
"Marine heatwaves (MHW) are periods of extreme high sea temperature relative to the long-term mean seasonal cycle (Hobday et al., \r\n2016). Studies since the Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC; Collins et al., 2019) confirm the \r\nassessment that MHW can lead to severe and persistent impacts on marine ecosystems - from mass mortality of benthic communities, \r\nincluding coral bleaching, changes in phytoplankton blooms, shifts in species composition and geographical distribution, and toxic algal \r\nblooms, to decline in fisheries catch and mariculture (Smale et al., 2019; Cheung and Frolicher, 2020; Hayashida et al., 2020; Piatt et al., \r\n2020). Unlike synoptic atmospheric heatwaves (Section 11.3), MHWs can extend for millions of square kilometres, persist for weeks to \r\nmonths, and occur at subsurface (Bond et al., 2015; Schaeffer and Roughan, 2017; Perkins-Kirkpatrick et al., 2019; Laufkotter et al., 2020)."


id: 6a1509909c808097cbe317b5f24a4217
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14297
content:
"variability in redistributing heat, driving interhemispheric asymmetry \r\nof the recent rate of ocean warming (Rathore et al., 2020; L. Wang \r\net al., 2021). Since SROCC, one new study shows that the subpolar \r\nNorth Atlantic 'warming hole' observed since the 1980s has emerged \r\nfrom internal climate variability and can be attributed to greenhouse \r\ngas emissions (Chemke et  al., 2020). A  new analysis of a  suite of \r\nclimate models (Hobbs et  al., 2021) confirms SROCC assessment, \r\nbased on one paper (Swart et  al., 2018), attributing the observed \r\nSouthern Ocean warming to anthropogenic forcing. Given the large \r\nfraction of global ocean warming in the Southern Ocean and the \r\nsparse observations there before 2005, there is limited evidence that \r\nglobal OHC increase since 1971 might have been underestimated \r\n(Cheng and Zhu, 2014; Durack et al., 2014). Cross-Chapter Box 9.1 "


id: 217541cff1e772d5b3dbbb26267e56
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 2686
content:
"The rate of ocean warming varies regionally, with some regions having \r\nexperienced slight cooling (Figure  9.6). The SROCC (Bindoff  et  al., \r\n2019) assessed that ocean warming in the 0-700 m depth is \r\nglobally widespread, with slower than global average warming in \r\nthe subpolar North Atlantic. The SROCC (Meredith et al., 2019) also \r\nestimated that the Southern Ocean accounted for around 75% of \r\nglobal ocean heat uptake during 1870-1995 and that 35-43% of the \r\nupper 2000 m global ocean warming occurred in the Southern Ocean \r\nover 1970-2017 (45-62% for 2005-2017). The SROCC noted that this \r\ninterhemispheric asymmetry might (at least partially) be explained by \r\nhigh concentrations of aerosols in the Northern Hemisphere. Here, \r\nwe confirm these assessments, bring new evidence attributing these \r\nregional trends, and discuss the role of decadal ocean circulation "


id: 530bf254fcc71ebad533fb08990f364d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 10525
content:
"accounts for an increased error before 2005 in global OHC change. \r\nIn summary, in the upper 2000 m since the 1970s, the subpolar \r\nNorth Atlantic has been slowly warming, and the Southern Ocean \r\nhas stored a disproportionally large amount of anthropogenic heat \r\n(medium confidence)."


id: 3a31bad8acf75528893a2874c2322857
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 6522
content:
"observational record may underestimate the rate of deep-ocean \r\nwarming from 1990 to 2010 by about 20% (Garry et  al., 2019) \r\nwhich is included in the assessed OHC error (Cross-Chapter Box 9.1). \r\nThere is still low agreement in deep-ocean changes from ocean data \r\nassimilation reanalyses (Palmer et  al., 2017) and low confidence\r\nin such inferences. In summary, while observational coverage \r\nbelow 2000 m is sparser than in the upper 2000 m, there is high \r\nconfidence that deep-ocean warming below 2000 m has been larger \r\nin the Southern Ocean than in other ocean basins due to widespread \r\nAABW warming."


id: 11567edac89800e68159c6325aff25ea
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 210
content:
"Major volcanic eruptions have caused interannual to decadal cooling \r\nphases within the marked long-term increase in global OHC  - \r\nMount Agung in 1963, El Chichon in 1982 and Mount Pinatubo \r\nin 1991 (Cross-Chapter Box 4.1; Church et al., 2005; Fasullo et al., \r\n2016; Stevenson et  al., 2016; Fasullo and Nerem, 2018). In  the \r\nfirst few years following an eruption, heat exchange with the \r\nsubsurface ocean allows atmospheric cooling to be sequestered \r\ninto the seasonal thermocline, therefore reducing the magnitude of "


id: 14192973e3773d1161832ab1e6c4f04e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 671
content:
"While heat redistribution reflects changes in ocean circulation and is \r\na useful concept to understand the underlying processes driving OHC \r\npatterns, change in ocean heat transport (OHT) arises due to changes \r\nin ocean circulation and ocean temperature and affects regional \r\nOHC  change. The AR5 did not assess change in OHT  and SROCC \r\n(Meredith et al., 2019) only assessed projected OHT increases into \r\nthe Nordic Seas and the Arctic Ocean. New evidence of increasing \r\nnorthward OHT into the Arctic has been observed in recent decades "


id: 79fccacb79ae15de33c54a1e87c27cfb
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 16768
content:
"the  peak atmospheric temperature anomaly (Gupta and Marshall, \r\n2018). However, while explosive volcanic eruptions only disturb \r\nthe Earth's radiative budget and surface fluxes for a  few years, \r\nthe ocean preserves an anomaly in OHC in the upper 500 m (also \r\naffecting thermosteric sea level) many years after the eruption \r\n(Gupta and Marshall, 2018; Bilbao et al., 2019). The anomaly affects \r\nthe atmosphere through air-sea heat fluxes with surface conditions \r\nreturning to normal only after several decades (Gupta and Marshall, \r\n2018; Bilbao et al., 2019), or on centennial time scales in the case \r\nof repeated eruptions (G.H. Miller et al., 2012; Atwood et al., 2016; \r\nGupta and Marshall, 2018). In summary, there is medium confidence\r\nthat oceanic mechanisms buffer the atmospheric response to \r\nvolcanic eruptions on annual time scales by storing volcanic cooling \r\nin the subsurface ocean, affecting OHC and thermosteric sea level on \r\ndecadal to centennial time scales."


id: cf1159c8a5066548eb66f76acb46ab18
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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index: climate_gpt_only_giec
vector_id: 30113
content:
"The SROCC (Bindoff et al., 2019) assessed that the ocean will continue \r\nto take up heat in the coming decades for all plausible scenarios, \r\nand here this assessment is confirmed with very high confidence. \r\nThe SROCC reported that, compared with the observed changes since \r\nthe 1970s, the warming of the ocean by 2100 would very likely double \r\nto quadruple for low-emissions scenarios (RCP2.6) and increase five \r\nto seven times for high-emissions scenarios (RCP8.5). The SROCC also \r\nconcluded with high confidence that the overall warming of the ocean \r\nwould continue this century, even after radiative forcing and mean \r\nsurface temperatures stabilize. The SROCC projected that OHC in the "


id: ca87d086792ad81330f3368497ac93ad
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 29428
content:
"Todd et al., 2020; Couldrey et al., 2021). In the 700-2000 m depth \r\nrange, CMIP5 and CMIP6 models project the largest warming to be \r\nin the North Atlantic Deep Water and Antarctic Intermediate Water \r\n(Figure 9.7) while below 2000 m, the North Atlantic cools in many \r\nmodels, and Antarctic Bottom Waters warm (Sallee et  al., 2013b; \r\nHeuze et al., 2015). In summary, on decadal time scales, redistribution \r\nwill dominate regional patterns of OHC change without affecting the \r\nglobally integrated OHC; however, by 2100, particularly under strong \r\nwarming scenarios, there is high confidence that regional patterns \r\nof OHC change will be dominated by added heat entering the sea \r\nsurface, primarily in water mass formation regions in the subtropics; \r\nand reduced aerosols will increase the relative rate of Northern \r\nHemisphere heat uptake (medium confidence)."


id: 6b2a49fb7acc5190eefab12047668654
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14486
content:
"The SROCC assessed that the warming of the deep ocean is slow \r\nto manifest, with multi-century or longer response times, so global \r\nOHC (and global mean thermosteric sea level) will continue to \r\nrise for centuries (Figures 9.9 and 9.30). New studies show that \r\nthis continuation persists, even after cessation of greenhouse gas \r\nemissions (Ehlert and Zickfeld, 2018). Ocean warming will continue, \r\neven after emissions reach zero because of slow ocean circulation \r\n(Larson et al., 2020). OHC will increase until at least 2300, even for \r\nlow-emissions scenarios, but with a scenario-dependent rate (Nauels \r\net  al., 2017; Palmer et  al., 2018) and depends on cumulative CO2\r\nemissions, as well as the time profile of emissions (Bouttes et  al., \r\n2013). Past long-term changes in total OHC illustrate adjustment \r\nrelevant to expected future changes (Figure 9.9). Observational data "


id: ebb34a53c516f43a45e3529e85a5a94
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 34583
content:
"The AR5 (Rhein et  al., 2013) assessed that it was very likely that \r\nsubsurface salinity changes reflect surface salinity change, and \r\nthat basin-scale regions of high salinity and evaporation had trended \r\nmore saline, while regions of low salinity and more precipitation had \r\ntrended fresher since the 1950s. The SROCC (Bindoff et  al., 2019) \r\nassessment was consistent with AR5. Section  2.3.3.2 strengthens \r\nevidence that subsurface salinity trends are connected to surface trends \r\n(very likely), which are, in turn, linked to an intensifying hydrological \r\ncycle (medium confidence). Increasing evidence from updated \r\nobservational records indicates that it is now virtually certain that \r\nsurface salinity contrasts are increasing. At basin scale, Section 2.3.3.2 \r\nand AR5 concur that it is very likely that the Pacific and Southern Ocean \r\nhave freshened, and the Atlantic has become more saline. Figures 3.25 \r\nand 3.27 compare CMIP6 models to salinity observations."


id: beed00eef7fc2dd85b214c1ca52997d7
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 27592
content:
"The CMIP5 historical simulations have patterns similar to, but \r\nwith greater spatial variability than, observed estimates and \r\ncorrespondingly smaller amplitudes in the multi-model mean (Durack, \r\n2015; Cheng et al., 2020; Silvy et al., 2020). Section 3.5.2.1 reports, \r\nhowever, that the fidelity of ocean salinity simulation has improved \r\nin CMIP6, and near-surface and subsurface biases have been reduced \r\n(medium confidence), though the structure of the biases strongly \r\nreflects those of CMIP5. At regional scale, salinity biases are at least \r\npartially a result of inaccurate ocean dynamics (Levang and Schmitt, \r\n2020). Despite the regional limitations, Section 3.5.2.2 assesses that, \r\nat the global scale, it is extremely likely that human influence has \r\ncontributed to observed surface and subsurface salinity changes \r\nsince the mid-20th  century (strengthened from the very likely \r\nAR5 assessment)."


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vector_id: 18960
content:
"Water masses refer to connected bodies of ocean water, formed at the \r\nocean surface with identifiable properties (temperature, salinity, density, \r\nchemical tracers) resulting from the unique formation conditions of the \r\noverlying atmosphere and/or ice, before being transferred (subducted) \r\nto the deeper ocean below the surface  turbulent layer. As water \r\nmasses subduct, they ventilate the subsurface ocean, transferring \r\ncharacteristics acquired at the ocean surface to the subsurface. \r\nBy  integrating surface flux changes, water masses provide higher \r\nsignal-to-noise ratios for detecting and monitoring climate change \r\nthan surface fluxes (Bindoff and McDougall, 2000; Durack and Wijffels, \r\n2010; Silvy et al., 2020)."


id: f11eb9799ddc0c798c6a3c299553e1ab
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
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vector_id: 35435
content:
"facilitate access of CDW to the sub-ice-shelf cavities (Section 9.4.2.1). \r\nHowever, there is low confidence in the quantitification, importance \r\nand the ability of present models, especially at coarse resolution, to \r\nproject changes in each of these processes (Section 9.4.2.2). Some \r\nstudies have projected a possible shift from cold to warm sub-ice-shelf \r\ncavities causing a  sudden flush of warm water underneath ice \r\nshelves, but there is low confidence in the driving processes and the \r\nthreshold to trigger the shift (Box  9.4; Hellmer et  al., 2012, 2017; \r\nSilvano et al., 2018; Hazel and Stewart, 2020)."


id: 9f4b2a53c12c970462324bed8048f1cd
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 22605
content:
"Atlantic Meridional Overturning Circulation (AMOC) is the main \r\noverturning current system in the South and North Atlantic \r\noceans. It transports warm upper-ocean water northwards, \r\nand cold, deep water southwards, as part of the global ocean \r\ncirculation system (Section  2.3.3.4.1). Changes in AMOC influence \r\nglobal  ocean heat content (OHC) and transport (Section  9.2.2.1); \r\nglobal ocean  anthropogenic carbon uptake changes and climate \r\nsensitivity (Cross-Chapter Box  5.3); and dynamical sea level \r\nchange (Section  9.2.4). Since AR5/SROCC, confidence in modelled \r\nand reconstructed AMOC has decreased due to new observations \r\nand model disagreement. Confidence levels have been revisited in \r\nmodelled AMOC evolution during the 20th century, the magnitude of \r\n21st-century AMOC decline, and the possibility of an abrupt collapse \r\nbefore 2100."


id: 689fdd92f971c5ea55cbb324b49dfa13
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14054
content:
"in the 20th  century, and the uncertainty over the realism of the \r\n20th  century modelled AMOC response (Section  3.5.4.1), we have \r\nlow confidence in both."


id: 6e989e053073ab3e0475b58b9f467af5
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 15027
content:
"It is unclear what causes a weakening of the deepest limb of AMOC \r\nat 26.5degN, if the main sources for this flow farther north remain \r\nconstant. Various estimates of AMOC and associated heat transport \r\nsuggest an increase since the 1940s with a  subsequent decrease \r\nsince the 1990s (Section 2.3.3.4.1), supported by ocean reanalysis \r\n(Jackson et al., 2019), forced ocean model simulations (Robson et al., \r\n2012; Danabasoglu et  al., 2016) and CMIP6 simulations (Menary \r\net al., 2020a). This suggests that the observed AMOC-shift between \r\n2007 and 2011 may be part of a  longer-term decrease (medium \r\nconfidence), which has been attributed to be part of multiannual \r\nvariability (Rhein et al., 2019)."


id: 19151f1d84ed76583f69f3f709153365
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1439
content:
"The SROCC (Collins et  al., 2019) found that AMOC will very likely \r\nweaken over the 21st century. In CMIP6 projections, the modelled \r\ndecline starting in the 1990s continues in all future projections, almost \r\nindependent of the forcing scenario until about 2060, after which \r\nlow-emissions scenarios show stabilization, while high-emissions \r\nscenarios continue to exhibit AMOC decline (Figure  9.10; Menary \r\net al., 2020b; Weijer et al., 2020). Despite differences in overall AMOC \r\nstrength, location and latitude of deep convection, sea ice and SST \r\nbias and representation of deep overflows, the model projections are \r\nqualitatively similar. This agreement suggests that AMOC decline may \r\nbe governed by large-scale constraints independent of the details of "


id: 6ade38f1176cebabf78f26d825749445
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 14428
content:
"The changing Southern Ocean circulation system exerts a  strong \r\ninfluence on the global climate by modulating: (i) global OHC \r\n(Section  9.2.2.1); (ii) global ocean anthropogenic carbon uptake \r\n(Cross-chapter Box  5.3); global ocean overturning circulation \r\n(Section  9.2.3.1); (iii) climate sensitivity (Section  7.4.4 and \r\nCross-chapter Box 5.3); (iv) sea level through basal melt of ice shelves \r\n(9.4.2); and (v) Southern Hemisphere sea ice cover (Section 9.3.2)."


id: b7d52538d5d85f2b01fdc52803dea22a
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 26458
content:
"The SROCC (Meredith et  al., 2019) had low  confidence in all \r\nCMIP5-based model projections due to their inability to explicitly \r\nresolve eddy processes, and their inability to properly consider future \r\nmeltwater change from the Antarctic Ice Sheet. These limitations of "


id: b9e01c337846a01253b9fd590f70600e
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 26783
content:
"central Pacific, and thus the meridional temperature gradients that \r\ndrive tropical instability waves (Terada et  al., 2020), along with \r\na weakening, flattening and shoaling of the tropical thermocline and \r\nequatorial undercurrent (Luo and Rothstein, 2011). A weak or absent \r\nequatorial undercurrent (Kuntz and Schrag, 2020) and a too-diffuse \r\nand incorrectly sloped tropical thermocline (Zhu et al., 2020) remain \r\nissues in most CMIP6 models. In summary, while future changes in \r\ntropical modes of variability remain unclear, change in atmospheric \r\nand ocean circulation will drive continued change in tropical ocean \r\ntemperature in the 21st  century (medium confidence), with part \r\nof the region experiencing drastic marine heat wave conditions \r\n(high confidence)."


id: 91d232beea4439c92d012ff0f6e0fcd1
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 20474
content:
"The tropics are a  tightly coupled ocean-atmosphere system with \r\ntightly interconnected basins (Cai et al., 2019). The zonal atmospheric \r\nWalker Circulation and the Indonesian Throughflow (Figure 9.11) are \r\nkey connections between the Pacific and Indian oceans, and variations \r\nin the Walker and Hadley Circulations are tightly linked to the tropical \r\nPacific SST and currents. The tropics have a profound influence on the \r\nclimate system through the multiple modes of variability they host, \r\nwhich have widespread global influence at seasonal to annual time \r\nscale (Annex IV)."


id: e4aa98869b371ead5156ddcfd41749f6
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 33453
content:
"All climate models reproduce WBCs and gyres, but eddy\u0002present or eddy-rich models (roughly 10-25 km and about \r\n10 km resolution, respectively) represent these currents more \r\nrealistically than eddy-parameterized models (very high confidence) \r\n(Small  et  al.,  2014; Griffies et  al., 2015; Chassignet et  al., 2017, \r\n2020; Hewitt et  al., 2017, 2020; Roberts et  al., 2018). Compared \r\nto observations or to eddy-present and eddy-rich models, the eddy\u0002parameterized models from CMIP5 and CMIP6 simulate weaker and \r\nwider WBCs, as well as less realistic locations of subtropical and \r\nsubpolar gyre boundaries (Figure 9.11). Increased resolution admits "


id: 83898697228dd35e974cabc6608ae6f0
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 18228
content:
"Under future scenarios RCP4.5 and RCP8.5, AR5 (Collins et  al., \r\n2013) assessed an intensification and poleward extension of "


id: 934e7d07dff795e89666d5bb69759203
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 20689
content:
"1990-2015. Realistic representation of the Bering Strait transport \r\nin the current generation of climate models is challenging because \r\nthe strait is narrow compared to the resolution of climate models \r\n(Clement Kinney et al., 2014; Aksenov et al., 2016). For the Atlantic \r\nto Arctic transport, Section 2.3.3.4 reports that the major branches \r\nof Atlantic Water inflow across the Greenland-Scotland Ridge have \r\nremained stable, with only the smaller pathway of Atlantic Water \r\nnorth of Iceland showing a strengthening trend during 1993-2018. \r\nSection 2.3.3.4 also assesses that the Arctic outflow remained stable \r\nfrom the mid-1990s to the mid-2010s. Future changes in these \r\ncurrents have not yet been studied in CMIP6 models."


id: 1b9fde3aaa9dd870351bb7a5e982eaa2
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 1803
content:
"the southern Hemisphere subtropical gyres in the 21st  century. \r\nNew evidence since AR5 further reinforces their conclusions, which \r\nare now extended to all subtropical gyre systems in the Northern \r\nand Southern hemispheres (Yang et al., 2016, 2020). CMIP6 models \r\nproject changes in WBCs that are consistent with projected changes \r\nin the surface winds. Under strong radiative forcing, in scenario \r\nSSP5-8.5, CMIP6 models project that the East Australian Current \r\nExtension, Agulhas Current Extension and Brazil Current will intensify \r\nin the 21st century, while the Gulf Stream will weaken (Figure 9.11). \r\nAlthough CMIP5/CMIP6 are limited in resolution, medium confidence\r\nis given to changes in WBCs due to consistency across generations of \r\nclimate models, including CMIP6, despite changes in model structure, \r\nresolution and parametrizations."


id: a8e8a65b9fd9dcc8124ab8ae97b7a34d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 24102
content:
"Under increased radiative forcing, SROCC (Bindoff et  al., 2019) \r\nassessed that climate models project, in the 21st  century, \r\na reduction of wind and upwelling intensity in EBUS at low latitudes, \r\nand enhancement at high latitudes, under scenario RCP8.5, with an \r\noverall reduction in either upwelling intensity or extension. It also \r\nhighlighted that coastal warming and wind intensification may lead \r\nto variable countervailing responses to upwelling intensification \r\nat local scales. Despite differences among EBUS (D. Wang et  al., \r\n2015), there is growing evidence since SROCC in this pattern of \r\nchange.  While it has long been hypothesized that, for upwelling \r\nwinds, change is linked to air temperature contrast between ocean \r\nand land (Bakun, 1990), this hypothesis has increasingly been "


id: eeaee41f0ab859998f66681dc3f67d86
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
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vector_id: 35023
content:
"The SROCC assessed that the annual Bering Strait volume transport \r\nfrom the Pacific to the Arctic Ocean increased from 2001-2014, \r\nconsistent with an estimated increased northward heat transport of \r\nabout 60% from 2001-2014, and an increased freshwater transport \r\nof 30 +- 20 km3 yr-1 from 1991 to 2015 (Meredith et  al., 2019). \r\nSection  2.3.3.4 assesses that volume transport from the Pacific to \r\nthe Arctic has increased since the 1990s from 0.8 Sv to 1.0 Sv over "


id: 61f198f24ef0ff41871cb570d853c44d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 12974
content:
"In summary, SROCC and this Report conclude that the California \r\nCurrent system has experienced some upwelling-favourable wind \r\nintensification since the 1980s (high confidence), while low agreement\r\namong reported wind changes in the Benguela, Canary, and Humboldt \r\nsystems prevent a  similar assessment. As in SROCC, there is low \r\nconfidence in attribution of observed changes to anthropogenic or \r\nnatural causes. New evidence reinforces our confidence in SROCC \r\nassessment that, under increased radiative forcing, EBUS winds will \r\nchange with a dipole spatial pattern within each EBUS of reduction \r\n(weaker and/or shorter) at low latitude, and enhancement (stronger \r\nand/or longer) at high latitude (high confidence). There is medium \r\nconfidence that, across all scenarios, upwelling wind changes in \r\nEBUS will remain moderate in the 21st  century, within +-10-20% \r\nfrom present-day values."


id: e90c7e47c49d839d86aa27496255c7eb
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 34187
content:
"Changes in globally averaged ocean heat content (OHC) cause \r\nglobal mean thermosteric sea level (GMTSL) change (Box 9.1). The \r\nobserved increased OHC for 1971-2018 of 325 to 546 ZJ (very likely\r\nrange) (Section 7.2, Box 7.2) has led to a GMTSL rise of 0.03 to 0.06 \r\nm out of a total global mean sea level (GMSL) of 0.07 to 0.15 m \r\n(very likely range) (Section 2.3.3.3, Tables 2.7 and 9.5, and Cross\u0002Chapter Box 9.1)."


id: bf42b84a095af2071c6c13e86ac608c1
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 27643
content:
"Beyond the world's coastlines lie the shoreline, shallow estuaries, \r\ncontinental shelves, and deeper fjords and slopes, where depths \r\nincrease rapidly from the shelves to the deep-ocean floor. It is more \r\ndifficult to transport fluid across (rather than along) the shelf-break \r\nor slope (Brink, 2016), and estuaries and shelves have complex "


id: 4b53e95c332a0b3e8688b8b2b6d5c14b
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 9263
content:
"pronounced thermosteric sea level rise along the American coast \r\naround 40degN (Figures 9.12 and 9.26), leading to a relatively large \r\nocean dynamic sea level rise in this region (Yin, 2012; Bouttes et al., \r\n2014; Slangen et al., 2014b; Little et al., 2019; Lyu et al., 2020a)."


id: ff0842c0b7996ca69a897fe05a0c4cc1
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 37674
content:
"In summary, ocean dynamic sea level change involves changes to \r\ntemperature and salinity and responses of currents to changing \r\nforcing, with significant variability driven by unforced oceanic \r\nvariability. Projections of dynamic sea level variability require fully \r\nthree-dimensional ocean models, and only high-resolution ocean \r\nmodels are statistically consistent on short time scales with satellite \r\naltimeter observations (very high confidence)."


id: c6619d71d8bfcec3faf803c90447a52d
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 28785
content:
"The Southern Ocean Meridional Dipole is driven by a  northward \r\nadvection of excess heat (from changes in surface fluxes) by the \r\nwind-driven circulation followed by subduction or diffusive uptake \r\nin mid-latitudes, northward redistribution of existing heat by the \r\nstrengthening of that circulation, and the meridional contrast in \r\nthermal expansivity due to its temperature-dependence (Armour et al., \r\n2016; Gregory et  al., 2016; Lyu et  al., 2020b; Todd  et  al.,  2020; \r\nCouldrey et al., 2021)."


id: 8ba618fa78bcfa36694bf5d175139279
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 19489
content:
"The positive Arctic ocean dynamic sea level change is driven by \r\nincreased freshwater input (Couldrey et  al., 2021). The Northwest \r\nPacific Dipole is driven by the intensification of the Kuroshio Current \r\nin response to reduced heat loss and in some models to wind stress \r\nchange (C. Chen et al., 2019; Couldrey et al., 2021)."


id: c80ce2f04da5907d576c020c1d783b6f
created_at: 2023-03-16 14:00:46
updated_at: 2023-03-16 14:00:46
content_type: text
index: climate_gpt_only_giec
vector_id: 29054
content:
"The SROCC discussed the regional distribution of Arctic sea ice loss, \r\nand the findings remain valid for the updated time series covering \r\n2019 (Figure 9.13). Sea ice loss in winter is strongest in the Barents \r\nSea, while summer losses occur primarily at the summer sea ice \r\nregion margins, in particular in the East Siberian, Chukchi, Kara and \r\nBeaufort Seas (Frey et al., 2015; Chen et al., 2016; Onarheim et al., \r\n2018; Peng and Meier, 2018; Maksym, 2019). In the Bering Sea, \r\nexpanding winter sea ice cover was observed until 2017 (Frey et al., \r\n2015; Onarheim et al., 2018; Peng and Meier, 2018), but a marked \r\nreduction in sea ice concentration has occurred since then (high \r\nconfidence) (Stabeno and Bell, 2019)."


