# document

id: f88ff00ee19c4a43815f02792dd66325
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 36618
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of \r\nheavy precipitation (Li et al., \r\n2021; 11.SM). Median increase \r\nof more than 25% in the \r\n50-year Rx1day and Rx5day \r\nevents compared to the 1degC \r\nwarming level (Li et al., 2021) \r\nand more than 25% in annual \r\nRx1day and Rx5day and 20% \r\nin annual Rx30day compared to \r\npre-industrial (11.SM)"


id: 215619f552f75f702fa2e30cf2ac6deb
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 2678
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of heavy \r\nprecipitation (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 20% in the 50-year \r\nRx1day and Rx5day events \r\ncompared to the 1degC warming \r\nevel (Li et al., 2021) and more \r\nthan 25% in annual Rx1day, \r\nRx5day, and Rx30day compared \r\nto pre-industrial (11.SM)"


id: fe554209ff9617fd8f29f4a1b7f7f0ad
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 37547
content:
"Table 11.9 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in Asia, subdivided by AR6 regions. See Sections 11.9.1 \r\nand 11.9.4 for details."


id: 2f4b99ba675e3d7564fabdc52f9a2151
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 4862
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 3.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 7d43f09dd6eef0c7c621552fa1957455
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 17286
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nntensity and frequency of \r\nhot extremes and decrease \r\nn the intensity and frequency \r\nof cold extremes (Alexander \r\nand Arblaster, 2017; Herold \r\net al., 2018; Grose et al., 2020; \r\nEvans et al., 2021)"


id: bcffb2b54da558ba09bd5954b67b9348
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 27296
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Alexander \r\nand Arblaster, 2017; Herold \r\net al., 2018; Grose et al., 2020; \r\nEvans et al., 2021)"


id: 15b67f31da2fcdc404cc1e1568305321
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 935
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3b77c5011f22f67411921250f99bb4fa
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 6706
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 3.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 485f131210cc5e9990fecfcba61781d0
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 8760
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 0.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 1degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: a1c2c4977404c99211fd88c2f57c3848
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23011
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 0.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 1.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 54fa6e30df181d9e5fd7b0bcc300e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 10828
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 2.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 16f137372378aee01bb16dc4d92abb27
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 1136
content:
"Table 11.11 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Australasia, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 86a7663c239d8a7215a0026384786d42
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 18723
content:
"Table 11.12 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in Australasia, subdivided by AR6 regions.\r\nSee Sections 11.9.1 and 11.9.4 for details."


id: 16dcdd5ad76e74d5ecbf4846886e1577
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 1119
content:
"Table 11.13 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in Central and South America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details."


id: 49ad10210bf6e76748d2fee6723136a0
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 8983
content:
"Additional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Angeles-Malaspina et al., \r\n2018; Coppola et al., 2021b)"


id: a14051eaeeda279f8cba3f75b2136439
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 22931
content:
"Additional evidence from \r\nCMIP5 and RCM simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Hall \r\net al., 2013; Chou et al., 2014a; \r\nAngeles-Malaspina et al., 2018; \r\nCoppola et al., 2021b)"


id: 67986a76c6aacda91d54aab6c0f173a4
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 13888
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)\r\nAdditional evidence from \r\nCMIP5/CMIP3 and RCM \r\nsimulations for an increase \r\nin the intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Lopez-Franca et al., 2016; \r\nCoppola et al., 2021b) "


id: 8ef6eb3d4de4da7a3bff25d6b35bddae
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 20028
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 7a1d3c01861aa557bd15be4a7e42bd75
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 16784
content:
"Additional evidence from \r\nCMIP5/CMIP3 and RCM \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Lopez-Franca et al., 2016; \r\nCoppola et al., 2021b) "


id: 41c292229aad085cdb5554981ea1e54e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 7748
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 2.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: d867b35583f1db98202b57deb2eeb6cb
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 31573
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 3.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 1c35dad094319395e8c1f068c068e7b6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 1899
content:
"Additional evidence from \r\nCMIP5/CMIP3 and RCM \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Chou et al., \r\n2014a; Lopez-Franca et al., 2016; \r\nCoppola et al., 2021b)"


id: da213d984c6b6af1a972888cec02210a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 31842
content:
"Table 11.14 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Central and South America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 187f93535d7cec81fe1dfd84c9bac8c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 1347
content:
"Table 11.15 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in Central and South America, subdivided by AR6 \r\nregions. See Sections 11.9.1 and 11.9.4 for details. "


id: 50aa8e32bd1e5d01505fc7885afdbf29
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 10135
content:
"Table 11.16 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in Europe, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details. "


id: e4d9c7ea55185bae03a1e0ce470f377b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 33485
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021). \r\nMedian increase of more than \r\n5degC in the 50-year TXx and TNn \r\nevents compared to the 1degC \r\nwarming level (Li et al., 2021)"


id: f17079241aa26de56a74266b3f1bb4c5
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 35492
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 1degC in the 50-year \r\nTXx and TNn events compared \r\nto the 1degC warming level (Li \r\net al., 2021) and more than \r\n2.5degC in annual TXx and TNn \r\ncompared \r\nto pre-industrial (11.SM)"


id: 41ae187b3c696a0bf38df8d22f57aba7
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 7733
content:
"Additional evidence from CMIP5 \r\nand CORDEX simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Wehner et al., 2018b; Cardell \r\net al., 2020)"


id: 38a21b7a23f4bb381880f177122b793f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 6280
content:
"Additional evidence from \r\nCMIP5 and CORDEX \r\nsimulations for an increase in \r\nthe intensity and frequency \r\nof hot extremes and decrease \r\nin the intensity and frequency \r\nof cold extremes (Sillmann et al., \r\n2013b; Cardell et al., 2020)"


id: 761251acb3425dc34a01ee336268c90f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 16180
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: b0b3c36e685b67fa6310eefa79f1d0d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 25320
content:
"Additional evidence from CMIP5 \r\nand RCM simulations for an \r\nincrease in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Giorgi et al., 2014; Tomozeiu \r\net al., 2014; Engelbrecht et al., \r\n2015; Nastos and Kapsomenakis, \r\n2015; Zollo et al., 2016; Cardoso \r\net al., 2019; Cardell et al., 2020; \r\nDriouech et al., 2020; Coppola \r\net al., 2021a)"


id: 8841fa05f966d6d89e25b2437eb4764a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 18963
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Tomozeiu et al., 2014; Nastos \r\nand Kapsomenakis, 2015; \r\nZollo et al., 2016; Abaurrea \r\net al., 2018; Weber et al., \r\n2018; Cardoso et al., 2019; \r\nCardell et al., 2020; Coppola \r\net al., 2021a)"


id: cee28c56b888b47f80b5c48e74a2b3f2
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 30088
content:
"CMIP6 models project \r\na robust increase in the \r\nntensity and frequency of TXx \r\nevents and a robust decrease \r\nn the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 5.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 6degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3a7529cf75c4062074903bb9f8094761
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 6562
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes (Lau \r\nand Nath, 2014; Lhotka et al., \r\n2018)"


id: 88bc4893b68c86cefbf5cde345ebe4da
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 19045
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: b9c91b80f7b17351449fecf1e635d6f7
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 26767
content:
"Additional evidence from CMIP5 \r\nand CORDEX simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Wehner et al., 2018b; \r\nKhlebnikova et al., 2019b; \r\nCardell et al., 2020)"


id: 5f28f953d25c0bd3ec3cc11ca779b443
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 12529
content:
"Additional evidence from CMIP5 \r\nand CORDEX simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Sillmann et al., 2013b; \r\nKhlebnikova et al., 2019b; \r\nCardell et al., 2020)"


id: 12a75186a08cbbc75ab1ceb4dd61ac7a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 436
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: c45220679a8a3032f50e86e0c474cbaf
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 28456
content:
"Additional evidence \r\nfrom CMIP5 simulations \r\nfor an increase in the \r\nintensity and frequency of \r\nhot extremes and decrease in \r\nthe intensity and frequency \r\nof cold extremes (Laliberte et al., \r\n2015; Forzieri et al., 2016; Dosio \r\nand Fischer, 2018; Jacob et al., \r\n2018; Sigmond et al., 2018)"


id: 54837f6bacd20f8dedd07a2897d18d72
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 10755
content:
"Table 11.17 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for heavy \r\nprecipitation in Europe, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details."


id: 736a8e3c8f1a27d6c26b70adb65e2bbc
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 15784
content:
"High confidence: Increase. \r\nWith high confidence\r\nCMIP5 and CMIP6 (and \r\nEURO-CORDEX) show \r\na decline in winter and \r\nsummer total precipitation \r\nand increase in number of \r\nCDD. Drought intensity and \r\nfrequency increase with high \r\nconfidence, particularly in \r\nthe southern Mediterranean \r\n(11.SM; Interactive Atlas; \r\nSamuels et al., 2018; Cardell \r\net al., 2020; Cook et al., \r\n2020; Driouech et al., 2020; \r\nSpinoni et al., 2020; Coppola \r\net al., 2021a; Li et al., 2021)"


id: 566459c785050ad42499b799816a637d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 11072
content:
"Based on projections at \r\n+3degC: Large decreasing soil \r\nwater availability during \r\ndrought events compared \r\nto 1971-2000, even when \r\naccounting for adaptation \r\nto mean conditions; \r\nmore than three times \r\nlarger signal compared \r\nto response at +1.5degC \r\n(Samaniego et al., 2018)"


id: 3f6ab1fdc3e7eaae348641affef7fc94
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 7362
content:
"Strong decreases of surface \r\nand total soil moisture, in \r\nspring-summer (AMJJAS) \r\nand autumn-winter \r\n(ONDJFM) half years, with \r\nabout twice larger response \r\ncompared to +2degC (Cook \r\net al., 2020)"


id: 1e54011e115355e2a7093849806dd8bf
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 2212
content:
"Decreases of surface and \r\ntotal soil moisture, in \r\nAMJJAS and ONDJFM half \r\nyears (Cook et al., 2020)"


id: 3628dc42b74c8ed6d438ce9bc2856aa6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5924
content:
"Very large decrease in soil \r\nmoisture during drought \r\nevents in CMIP6 models \r\nat +4degC vs pre-industrial \r\nbaseline (11.SM) "


id: eb027b71978f78ab87a98dbfe7823366
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 34479
content:
"Decrease in soil moisture \r\nduring drought events \r\nin CMIP6 models at \r\n+2degC vs pre-industrial \r\nbaseline (11.SM) "


id: 912f5690c8c14375befc5cda957b396f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 20379
content:
"Giuntoli et al. (2015) (five \r\nCMIP5 models driving six \r\nglobal hydrology models): \r\n50-60% increase in \r\nfrequency of days under \r\nlow flow in 2066-2099 \r\ncompared to 1972-2005. \r\nStrong signal-to-noise ratio \r\nin terms of model agreement, \r\nstrongest hot spot globally"


id: a596dfe9699be9ad9f28abfb1b0e3423
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23626
content:
"Cook et al. (2020) [13 CMIP6 \r\nmodels and SSP3-7.0. Very \r\nstrong decrease (40-60%) of \r\ntotal runoff in spring-summer \r\nhalf-year in southern Europe. \r\nAlso strong decreases \r\n(>20%) for total runoff in \r\nautumn-winter half-year, and \r\nfor surface runoff in both half \r\nyears (AMJJAS, ONDJFM)"


id: 3555a85cce36bf2f3536296ec048eaf6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5804
content:
"Table 11.19 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for temperature \r\nextremes in North America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.2 for details. "


id: 5cf83b7ef61174f07b1a8f9c0f149d7f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 12144
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 3.5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 4.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 32f9f206bf1d6b7452c62fa97065f444
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5442
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of more \r\nthan 4.5degC in the 50-year TXx \r\nand TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC in \r\nannual TXx and TNn compared to \r\npre-industrial (11.SM)"


id: 3d736a738a66eb7eddbfc497321be356
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 7024
content:
"Additional evidence from CMIP5 \r\nand RCM simulations for an \r\nincrease in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes (Vose \r\net al., 2017; Wehner et al., 2018b)"


id: 2beeed956d9d58acb4d8412be1638daa
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 4338
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 5degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5.5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: 3671fb69db3312f0e9ec9e0032ca99ab
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5956
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(G. Li et al., 2018; X. Zhang \r\net al., 2019)"


id: b446be19e8de33c62a2167a41d8b9cb8
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 25874
content:
"CMIP6 models project \r\na robust increase in the \r\nintensity and frequency of TXx \r\nevents and a robust decrease \r\nin the intensity and frequency \r\nof TNn events (Li et al., 2021; \r\n11.SM). Median increase of \r\nmore than 4degC in the 50-year \r\nTXx and TNn events compared to \r\nthe 1degC warming level (Li et al., \r\n2021) and more than 5degC in \r\nannual TXx and TNn compared \r\nto pre-industrial (11.SM)"


id: b21b15341458de70320059b4f9dd175e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 25526
content:
"Additional evidence from \r\nCMIP5 and RCM simulations for \r\nan increase in the intensity and \r\nfrequency of hot extremes and \r\ndecrease in the intensity and \r\nfrequency of cold extremes \r\n(Bennett and Walsh, 2015; \r\nG. Li et al., 2018; X. Zhang \r\net al., 2019)"


id: b92f5154a1ae14e40dc03d77df3b681b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 26669
content:
"Table 11.20 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming \r\nprecipitation in North America, subdivided by AR6 regions. See Sections 11.9.1 and 11.9.3 for details. "


id: 31db22bed46f7be8ec05e74b9c0a7dda
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5256
content:
"Table 11.21 | Observed trends, human contribution to observed trends, and projected changes at 1.5degC, 2degC and 4degC of global warming for meteorological \r\ndroughts (MET), agricultural and ecological droughts (AGR/ECOL), and hydrological droughts (HYDR) in North America, subdivided by AR6 regions.\r\nSee Sections 11.9.1 and 11.9.4 for details."


id: 5640b2b92780eed1732637164d877959
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 11056
content:
"Table 11.A.1 | Common drought metrics, associated drought types, drought indices, general description and associated references."


id: 7941e5b2a62a43c6fd7b33f3e618dd6d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 16644
content:
"Roshanka Ranasinghe (The Netherlands/Sri Lanka, Australia), Alex C. Ruane (United States of \r\nAmerica), Robert Vautard (France)"


id: 9ac9c68e09fae2caa782193eb495c0bf
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 21883
content:
"Nigel Arnell (United Kingdom), Erika Coppola (Italy), Faye Abigail Cruz (Philippines), Suraje Dessai \r\n(United Kingdom/Portugal), A.K.M. Saiful Islam (Bangladesh), Mohammad Rahimi (Iran), \r\nDaniel Ruiz Carrascal (United States of America/Colombia), Jana Sillmann (Norway/Germany), \r\nMouhamadou Bamba Sylla (Rwanda/Senegal), Claudia Tebaldi (United States of America), \r\nWen Wang (China), Rashyd Zaaboul (United Arab Emirates/Morocco)"


id: c6d26a6ef34b415e456a360283f06644
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 28858
content:
"(Austria), Francesca Raffaele (Italy), Srivatsan Raghavan (Singapore/India), Christophe F. Randin \r\n(Switzerland/France, Switzerland), Johan Reyns (The  Netherlands/Belgium), Lucas Ruiz \r\n(Argentina), Fahad Saeed (Germany/Pakistan), Jean-Baptiste Sallee (France), Marit  Sandstad \r\n(Norway), Clemens  Schwingshackl (Norway, Germany/Italy), Sonia  I. Seneviratne (Switzerland), \r\nAimee B.A. Slangen (The Netherlands), Tannecia S. Stephenson (Jamaica), Anna Steynor (South \r\nAfrica), Markus Stoffel (Switzerland), Benjamin Sultan (France), William V. Sweet (United States \r\nof America), Sophie Szopa (France), Izuru Takayabu (Japan), Moustapha Tall (Rwanda/Senegal), \r\nN'Datchoh Evelyne Toure N'Datchoh (Cote d'Ivoire), Bart van den Hurk (The Netherlands), \r\nSergio M. Vicente-Serrano (Spain), Michalis Vousdoukas (Italy, Greece/Greece), Morgan Wairiu \r\n(Fiji), Prodromos Zanis (Greece), Xuebin Zhang (Canada)"


id: 261b204f4a09062d60840beb0f02b9c2
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 3413
content:
"Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz \r\nCarrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional \r\nImpact and for Risk Assessment. 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. 1767-1926, doi:10.1017/9781009157896.014."


id: 29c5ddfc8dfe5e538104dc51c7dd3ad6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 4003
content:
"Hemisphere (high confidence). Decreasing precipitation will emerge \r\nin a very few regions (Mediterranean, Southern Africa, south-western \r\nAustralia) (medium confidence) by mid-century (medium confidence). \r\nThe anthropogenic forced signal in near-coast relative sea level rise \r\nwill emerge by mid-century RCP8.5 in all regions with coasts, except \r\nin the West Antarctic region where emergence is projected to occur \r\nbefore 2100 (medium confidence). The signal of ocean acidification in \r\nthe surface ocean is projected to emerge before 2050 in every ocean \r\nbasin (high confidence). However, there is limited evidence of drought \r\ntrends emerging above natural variability in the 21st century. {12.5}"


id: 107aff3d9fb556af2da22501726044c9
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 77
content:
"The climatic impact-driver (CID) framework adopted in \r\nChapter 12 allows for assessment of changing climate conditions \r\nthat are relevant for regional impacts and risk assessment. CIDs \r\nare physical climate system conditions (e.g., means, events, extremes) \r\nthat affect an element of society or ecosystems and are thus a priority \r\nfor climate information provision. Depending on system tolerance, \r\nCIDs and their changes can be detrimental, beneficial, neutral or \r\na  mixture of each across interacting system elements, regions and \r\nsociety sectors. Each sector is affected by multiple CIDs and each CID \r\naffects multiple sectors. A CID can be measured by indices to represent \r\nrelated tolerance thresholds. {12.1-12.3}"


id: eee0579125449cfde7378cde1dd06b11
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 35055
content:
"Several impact-relevant changes have not yet emerged \r\nfrom the natural variability but will emerge sooner or later \r\nin this century depending on the emissions scenario (high \r\nconfidence). Increasing precipitation is projected to emerge before \r\nthe middle of the century in the high latitudes of the Northern "


id: 194814df882cc8d702627d6cbf58927
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 1463
content:
"A wide range of region-specific CID changes relative to recent \r\npast are expected with high or medium confidence, by 2050 and \r\nbeyond.Most of these changes concern CIDs related to the water cycle "


id: dcb5d657667ce4790ad76e9b3c771058
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 32225
content:
"occurs multiple times per year under RCP8.5, while under RCP4.5 \r\nit is projected to become a one-in-five-year event, representing at \r\nleast a five fold increase from RCP4.5 to RCP8.5. {12.4, 12.5}"


id: 787527c7cb2963ac580687d054d4feec
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 16512
content:
"There is low confidence in past and future changes of several \r\nCIDs. In nearly all regions there is low confidence in changes in \r\nhail, ice storms, severe storms, dust storms, heavy snowfall and \r\navalanches, although this does not indicate that these CIDs will not \r\nbe affected by climate change. For such CIDs, observations are short \r\nterm or lack homogeneity, and models often do not have sufficient \r\nresolution or accurate parametrization to adequately simulate them \r\nover climate change time scales. {12.4}"


id: 48444d711f8b5613933ea900d6eb52ad
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 8741
content:
"Since AR5, climate change information produced in climate \r\nservice contexts has increased significantly due to scientific, \r\ntechnological advancements and growing user demand (very \r\nhigh confidence). Climate services involve the provision of climate \r\ninformation in such a way as to assist decision-making. These services \r\ninclude appropriate engagement from users and providers, are based \r\non scientifically credible information and expertise, have an effective \r\naccess mechanism, and respond to user needs. Climate services are \r\nbeing developed across regions, sectors, time scales and target users. \r\n{12.6}"


id: c980541850aded9d3377aae0b3cebb53
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 29263
content:
"Climate services are growing rapidly and are highly diverse \r\nin their practices and products (very high confidence). The \r\ndecision-making context, level of user engagement and co-production \r\nbetween scientists, practitioners and intended users are important \r\ndeterminants of the type of climate service developed and its utility \r\nsupporting adaptation, mitigation and risk management decisions. \r\nUser needs and decision-making contexts are very diverse and there \r\nis no universal approach to climate services. {12.6}"


id: 910622322d81acd314b62742b519e1d4
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 20358
content:
"Realization of the full potential of climate services is often \r\nhindered by limited resources for the co-design and co-production \r\nprocess, including sustained engagement between scientists, \r\nservice providers and users (high confidence). Further challenges \r\nrelate to climate services development, provision of climate services, \r\ngeneration of climate service products, communication with users, and \r\nevaluation of the quality and socio-economic value of climate services. \r\nThe development of climate services often uncovers and presents new \r\nresearch challenges to the scientific community. {12.6}"


id: b1e8e31e9adf9ebfa8138c030dc23ef5
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 25493
content:
"This chapter follows the terminology associated with the framing \r\nintroduced in Chapter  1 (Cross-Chapter Box  1.2) and as found in \r\nAnnex VII: Glossary. The highlighted terms below are introduced and \r\nused extensively in this chapter:"


id: ef3d68992c23a65a2e760bc9a4b15ba3
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 35111
content:
"Climate change is already resulting in significant societal and \r\nenvironmental impacts and will induce major socio-economic damages \r\nin the future (AR5 WGII). The society, at large, benefits from information \r\nrelated to climate change risks, which enables the development of \r\noptions to protect lives, preserve nature, build resilience and prevent \r\navoidable loss and damage. Climate change can also lead to beneficial \r\nconditions that can be taken into account in adaptation strategies."


id: 7c88a1c1897a2445e3d6a60c4e88c51d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 17191
content:
"This chapter assesses climate change information relevant for \r\nregional impact and for risk assessment. It complements other \r\nWGI chapters that focus on the physical processes determining \r\nchanges in the climate system and on methods for estimating \r\nregional changes."


id: 4359e3e07a94330e147c9b7a0714de41
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 8005
content:
"In some cases, risk assessments may require climate information \r\nbeyond the CIDs identified in this chapter, with further impacts or \r\nrisk modelling often driven by historical climate forcing datasets \r\n(e.g.,  Ruane et  al., 2021) and full climate scenario time series \r\n(e.g., Lange, 2019) produced using methods described in Chapter 10. \r\nChapter 12 focuses on the assessment of a finite number of drivers \r\nand how they are projected to evolve with climate change, in order \r\nto inform impact and risk assessments."


id: 72e966cdd73c06354ff325389343d2db
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 15691
content:
"The chapter adopts a  regional perspective (continental regions as \r\ndefined in Chapter 1 and used in WGII; see Figure 1.18) on climatic \r\nimpact-drivers to support decision-making across a  wide audience \r\nof global and regional stakeholders in addition to governments \r\n(e.g., civil society organizations, public and private sectors, academia). \r\nWhile the focus here is on future changes, it also describes current \r\nlevels and observed trends of CIDs as an important point of reference \r\nfor informing adaptation strategies."


id: 832f6f4536e92232fc0adae36acd56df
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 18166
content:
"Figure 12.1 summarizes the rationale behind Chapter 12 as the linkage \r\n(also referred to as a 'handshake') between WGI and WGII, illustrating \r\nhow the changing profile of risk may be informed by an assessment \r\nof climatic impact-drivers, aligning WGI findings on physical climate \r\nchange with WGII needs. The implementation of mitigation policy \r\nshifts may modulate hazard probability changes (i.e.,  by reducing \r\nemissions to limit global warming) as well as regional vulnerability and \r\nexposure. The assessment herein is organized around regional climatic \r\nimpact-drivers, but also relates key indices and thresholds to increasing "


id: 26db96c1c79b8d4cf747fd87a3e56024
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"global drivers (such as mean surface warming) as a contribution to the \r\nassessment of 'Reasons for Concern' in WGII (O'Neill et al., 2017)."


id: 2efab86a7eb82b496bb3a7d56883cea2
created_at: 2023-03-16 14:00:50
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"This section details the methodological approach followed in \r\nChapter 12 and discusses the underlying rationale for the assessments \r\npresented herein. Scientific literature on vulnerability, impacts, and \r\nadaptation (as typically asssessed in IPCC WGII) is examined to identify \r\nrelevant climatic impact-drivers (CIDs) that contribute to sectoral risks \r\nand opportunities. Projected changes in corresponding CID indices are \r\nthen derived from existing literature on changes in the physical climate \r\nsystem, results of other AR6 WGI chapters, and direct calculations \r\nbased on climate projections from several model ensembles."


id: 1dc6563329ed51f6ab778ec5f74777c2
created_at: 2023-03-16 14:00:50
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"The classification of climatic impact-drivers, the ways that they \r\nchange (e.g.,  their magnitude or intensity, duration, frequency, \r\ntiming and spatial extent) is described in this section. It is \r\nemphasized that this chapter assesses literature relating only \r\nto physical climatic impact-drivers, not their impacts on human \r\nsystems or the environment. Thus, here we do not consider indicators \r\nincluding exposure or vulnerability as assessed by WGII, although \r\nthe selection of climatic impact-drivers is informed by literature \r\nfeeding into WGII."


id: be5bb619ce7071302e3d8f35eb864789
created_at: 2023-03-16 14:00:50
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"The chapter includes two Cross-Chapter Boxes. Cross-Chapter Box 12.1 \r\nconnects climatic impact-drivers to global climate drivers and levels \r\nof warming as an element of the 'Reasons for Concern' framework \r\n(AR6 WGII Chapter 16). An additional Cross-Chapter Box, including \r\nthree case studies from Europe, Asia and Africa, describes how climate \r\nservices draw upon and apply regional climate information to support \r\nstakeholder decisions (Cross-Chapter Box 12.2)."


id: fea418319845fd1dce63e750f33be25c
created_at: 2023-03-16 14:00:50
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"can be changes in impacts associated with earthquakes that interact \r\nwith climate variables and climate change, such as liquefaction \r\n(e.g.,  Yasuhara et  al., 2012) during earthquakes, or earthquakes \r\ncaused by snow and water changes (Amos et  al., 2014; Johnson \r\net  al., 2017), which are secondary effects on geophysical hazards \r\nthat are not further assessed in this chapter. The characteristics and \r\nphysical description of the climate phenomena or essential climate \r\nvariables associated with each of these CID categories are assessed \r\nand described in previous Chapters 2-11 or Chapter 12 directly as \r\nindicated in Table 12.1. The CID categories are further mapped on to \r\ndifferent sectors in Section 12.3 (Table 12.2)."


id: 992cf76b7ea2f4f3fd6cdc7d9ac57fe6
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"Many of these sectors also include assets affected by climate change \r\nthat are important for recreation and tourism, including elements \r\nof ecosystems services, health and well-being, communities, \r\nlivelihoods and sustainable development (see also Chapter  1 on \r\nthe Intergovernmental Science-Policy Platform on Biodiversity \r\nand Ecosystem Services (IPBES), and the IPCC Special Report on \r\nclimate change, desertification, land degradation, sustainable land \r\nmanagement, food security, and greenhouse gas fluxes in terrestrial \r\necosystems (SRCCL; Hurlbert et al., 2019; IPCC, 2019c))."


id: c5fb0305e47a009ed2292fbc111adad3
created_at: 2023-03-16 14:00:50
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"Potential changes in the seasonality of CIDs or the length and \r\ncharacteristics of seasons (e.g., changes in growing season length or \r\npollen season) are also important as they may shift the timing of many \r\nCIDs with broad implications for sectors and regional stakeholders \r\n(Wanders and Wada, 2015; Cassou and Cattiaux, 2016; Hansen and \r\nSato, 2016; Bronnimann et al., 2018; Marelle et al., 2018; Unterberger \r\net al., 2018; Kuriqi et al., 2020). Episodic CIDs characterize impact\u0002relevant conditions persisting from short to long time frames but \r\neventually returning to normal conditions."


id: cc73981be3f1fc1999e53e6bcbebc4fe
created_at: 2023-03-16 14:00:50
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"CIDs can be captured in seven main types: heat and cold; wet and \r\ndry; wind; snow and ice; coastal; oceanic and other. Table  12.1 \r\nprovides an overview of the seven CID types and the CID categories \r\nassociated with each type. The type 'Other' comprises additional CIDs \r\nthat are not encompassed within the other six CID types, including \r\nair pollution weather (e.g.,  meteorological conditions that favour \r\nhigh concentrations of surface ozone, particulate matter or other air \r\npollutants), near-surface atmospheric CO2 concentrations, and mean \r\nradiation forcing at the surface (which are, for example, relevant for \r\nplant growth). Icebergs, fog and lightning are also noted in this chapter \r\nbut are not broadly assessed across all subsections. In addition, there "


id: 6980d51173924edf68fc259009c51f72
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"In some situations, phenomena causing severe impacts go well \r\nbeyond a single extreme event or a single climate variable, and can \r\ninclude interaction of climatic conditions, such as sea level rise and \r\nstorm surge (Wahl et  al., 2015), precipitation in combination with \r\nstrong winds (Martius et al., 2016) or flooding quickly followed by \r\na heatwave (S.S.-Y. Wang et al., 2019; see also Section 10.5.2.4). Such "


id: 296106b2a4ef07d648b3734d01f288f9
created_at: 2023-03-16 14:00:50
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content:
"Table 12.1 | Overview of the main climatic impact-driver (CID) types and related CID categories with a short description and their link to other chapters \r\nwhere the underlying climatic phenomenon and its associated essential climate variables are assessed and described."


id: 2ad7ac1c426175d92179d0e0a68e0c1e
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"compound events, particularly in the context of climate extremes, \r\nare assessed in Section 11.8. A combination of non-extreme climatic \r\nimpact-drivers in time or space can also lead to severe impacts \r\n(Cutter, 2018)."


id: ab3457c8c539329d387d490f24b623d9
created_at: 2023-03-16 14:00:50
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"Climate change becomes relevant for regional impact management \r\nand for risk assessment when changes in mean conditions or episodic \r\nevents affect natural and societal assets (system components with \r\nsocio-economic, cultural or intrinsic value) positively or negatively \r\n(Table  12.2). Decision makers, policymakers, risk managers and \r\nengineers therefore benefit from climate information that tracks key \r\ntrends and exceedance of thresholds that represent crucial challenges \r\nfor natural and human systems. While useful indices can vary widely \r\nfor a given sector and precise tolerance threshold values are often \r\nunknown, common metrics, categories and progressions of threshold \r\nlevels allow experts to recognize coherent messages concerning \r\naltered regional impacts and risk profiles under climate change."


id: 7bc219db558f392b247d94f27a28ca4a
created_at: 2023-03-16 14:00:50
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"A global perspective on climatic impact-drivers is provided in \r\nSection 12.5.1. Section 12.5.2 focuses on assessing evidence for the \r\nemergence (Section  1.4.2.2) of an anthropogenic climate change \r\nsignal on the change in CIDs beyond natural climate variability, based \r\non the literature assessed in other chapters and additional literature, \r\nat both global and regional scales. The process of generating \r\nuser-relevant regional climate information in the context of co\u0002production and climate services is assessed in Sections 10.5, 12.6, \r\nBox 10.2 and Cross-Chapter Boxes 10.3 and 12.2. Cross-Chapter Box \r\n12.1 provides a global perspective on climatic impact-drivers related \r\nto their evolution for different GWLs (Section 1.6)."


id: 142f642207c43a8de68bfc2b022e1c9b
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"suitability of future climate zones and climate velocity challenges for \r\na given asset potentially drawing from multiple CIDs and associated \r\nsystem tolerance thresholds (Hamann et  al., 2015). Some broad \r\nconnections indicated as low confidence may be under-represented \r\nin the literature or could be acute under specific circumstances."


id: 9c57ff67a2c13e8b49c96905ff4eba5e
created_at: 2023-03-16 14:00:50
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"determine plant sprouting (Grotjahn, 2021). A number of indices have \r\nbeen developed to represent the length of the viable local growing \r\nseason, including a count of days where Tmax >5degC (Mueller et al., 2015) \r\nor the period between a year's first and last set of five consecutive days \r\nwith a weighted Tmean >=10degC (G. Li et al., 2018). Warmer conditions \r\nand altered seasonality modify the range and metabolism of some \r\npollinators, pests, diseases and weeds (Wolfe et al., 2008; Bebber, 2015; \r\nAljaryian and Kumar, 2016; IPBES, 2016; Ramesh et al., 2017; Deutsch \r\net al., 2018; Nyangiwe et al., 2018) and may reduce the effectiveness \r\nof winter storage for farmers and caching species (Sutton et al., 2016)."


id: fe62bb954642c65b20599a1e80c5be90
created_at: 2023-03-16 14:00:50
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"Warming raises accumulated seasonal heat indices used in livestock \r\nproduction, especially when humidity is high (Key et al., 2014; Lallo \r\net al., 2018), determines aquaculture suitability and is important for \r\nwild fish species migration (Tripathi et al., 2016; Brander et al., 2017). \r\nAgricultural planners may also calculate how overall warming trends \r\nalter the accumulation of vernalization units or chilling hours for \r\nagricultural or horticultural crops (often accumulated temperature \r\ndeficit below a given daily or hourly threshold; Dennis and Peacock, \r\n2009; Luedeling, 2012; Tripathi et  al., 2016; Grotjahn, 2021). \r\nWarming in the post-harvest is also important for the determination \r\nof spoilage and waste (Stathers et al., 2013) as well as food-borne \r\ndiseases (Kovats et al., 2004; Mbow et al., 2019)."


id: d2d61e54fd021a18782cd36f8375a1c5
created_at: 2023-03-16 14:00:50
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"Warming affects road degradation rates (Chinowsky and Arndt, 2012; \r\nEspinet et al., 2016) and warming rates inform designs for long-term \r\nenergy efficiency of buildings (Kalvelage et al., 2014). Mean temperature \r\ndrives seasonal energy demand, often expressed using winter heating \r\ndegree days (the accumulated deficit of daily temperatures below \r\na  'comfortable' indoor temperature, e.g.,  15.5degC) and summer \r\ncooling degree days (the accumulated excess of temperature above \r\na 'comfortable' level, e.g., 18degC; Spinoni et al., 2015; Arnell et al., 2019). \r\nEnergy resources may also need information on warming trends to \r\ndetermine suitable zones and overall productivity for biofuels and solar \r\npanels, the efficiency of which decreases with higher temperatures \r\n(Schaeffer et al., 2012; Wild et al., 2015; Solaun and Cerda, 2019)."


id: 496edd13304ea60962b032aa611a0da6
created_at: 2023-03-16 14:00:50
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"Health impacts and risk studies compare seasonal temperature \r\nconditions to limiting thresholds to understand range shifts and \r\nincubation rates for pathogens, disease vectors and zoonotic hosts \r\n(e.g.,  mosquitoes, ticks; Caminade et  al., 2012, 2014; Eisen and \r\nMoore, 2013; Lima et al., 2016; Ogden, 2017; Monaghan et al., 2018) \r\nand warming of surface ocean and lake waters conducive to bacterial \r\noutbreaks (Baker-Austin et  al., 2013; Jacobs et  al., 2015; Vezzulli \r\net al., 2015). Warmer conditions can also affect tourism (Kovacs et al., \r\n2017) and impact human health by lengthening the allergy season \r\nand increasing pollen concentration (Hamaoui-Laguel et  al., 2015; \r\nKinney et al., 2015a; Lake et al., 2017; Upperman et al., 2017; Sapkota \r\net al., 2019; Ziska et al., 2019)."


id: e0ebcf81b954bb7f8dae539ca513e698
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"Impacts and risk assessments utilize a  large variety of indices and \r\napproaches tailored to evaluate heat impacts on human health \r\n(Sanderson et al., 2017; C. Gao et al., 2018; McGregor and Vanos, 2018; \r\nStaiger et  al., 2019; J. Zhu et  al., 2019; Schwingshackl et  al., 2021). \r\nA mixture of simple and complex heat stress indices often combine "


id: 89ebc4bd5ce8df9519551f3879c0ad32
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"weight restrictions (Coffel et  al., 2017; Palko, 2017; T. Zhou et  al., \r\n2018). Heat extremes increase peak cooling demand and challenge \r\ntransmission and transformer capacity (Sathaye et al., 2013; Russo \r\net al., 2016; Craig et al., 2018; X. Gao et al., 2018) and may cause \r\ntransmission lines to sag or fail (Gupta et  al., 2012). Thermal and \r\nnuclear electricity plants may be challenged when using warmer river \r\nwaters for cooling or when mixing waste waters back into waterways \r\nwithout causing ecosystem impacts (Kopytko and Perkins, 2011; van \r\nVliet et al., 2016; Tobin et al., 2018). Extreme temperature can also \r\nreduce photovoltaic panel efficiency (Jerez et al., 2015)."


id: c8d06420ed801fa446b661467fca5c27
created_at: 2023-03-16 14:00:50
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"The magnitude and timing (relative to developmental stages) of cold \r\nextremes (such as the typical coldest day of the year) set limits in \r\nthe range of species habitat for ecosystems as well as for agricultural \r\nand forest pests (Osland et al., 2013; Cavanaugh et al., 2014; Parker \r\nand Abatzoglou, 2016; Brunner et  al., 2018; Unterberger et  al., \r\n2018). Cold air outbreaks can lead to chilling injuries for crops (even \r\nabove 0degC) and may kill outdoor livestock (particularly young animals; \r\nMader et al., 2010; Liu et al., 2013; Grotjahn, 2021), but are often \r\nnecessary for crop chill requirements (Dennis and Peacock, 2009)."


id: e941f0d685369528368ff3e25a7a9ff5
created_at: 2023-03-16 14:00:50
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"Increases in human mortality can occur on exceptionally cold days \r\n(e.g., <1st percentile of temperatures in winter) although thresholds \r\nand human-perceived temperatures linked to wind speed (i.e., 'wind \r\nchill') vary geographically due to acclimatization (Li et  al., 2013; \r\nGao et al., 2015; J. Li et al., 2018; J. Zhu et al., 2019). The timing of \r\n'unseasonal' cold spells also affect human health (Kinney et al., 2015b). \r\nExtreme cold can increase heat and electricity demand (Stuivenvolt\u0002Allen and Wang, 2019), cause water pipes to burst, and mechanically \r\nalter roads, railroads and buildings (Underwood et al., 2017)."


id: 19ecb26525f885668c06011fa39d41e5
created_at: 2023-03-16 14:00:50
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"Heat extremes factor in mortality, morbidity and the range of some \r\nthermally sensitive ecosystem species (Smith and Nagy, 2015; \r\nRatnayake et al., 2019; Thomsen et al., 2019). Combined heat and \r\ndrought stress can reduce forest and grassland primary productivity \r\n(Ciais et al., 2005; De Boeck et al., 2018) and even cause tree mortality \r\nat higher extremes (Teskey et al., 2015)."


id: 99796e1e904821261712d9fff2768d51
created_at: 2023-03-16 14:00:50
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"Extreme heat events raise temperatures in buildings and cities already \r\nwarmed by the urban heat island effect (Gaffin et al., 2012; Oleson \r\net al., 2018; Zhao et al., 2018; Mauree et al., 2019; Box 10.3) and \r\ncan induce disruptions in critical infrastructure networks (Chapman \r\net  al., 2013). Heat affects transportation infrastructure by warping \r\nroads and airport runways (Chinowsky and Arndt, 2012) or buckling \r\nrailways (Dobney et al., 2010; Depoues, 2017; Chinowsky et al., 2019), \r\nand high temperatures reduce air density leading to aircraft take-off "


id: 829ba925b84f4ebd67d5da2d19a6953e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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"Regional information about the spring and autumn seasonal periods in \r\nwhich freeze-thaw cycles are common (such as the dates of first spring \r\nthaw and last spring frost, or the number of days where Tmax >0degC and \r\nTmin <0degC) are particularly useful in estimating the rate of potential road \r\nand building damage or determining seasonal truck weight restrictions \r\n(Kvande and Liso, 2009; Chinowsky and Arndt, 2012; Palko, 2017; \r\nDaniel et al., 2018). The altitude of the freezing level also identifies \r\nportions of mountain slopes where freeze/thaw transitions or changes \r\nin snowpack condition can influence landslide and snow avalanche \r\nhazards (Coe et al., 2018). The geographical distribution of frost is also \r\na determining factor in the range of vectors for human diseases such \r\nas malaria (X. Zhao et al., 2016; Smith et al., 2020)."


id: 8562f582ecf1efb523b1bc1f23d7eedf
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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"Figure  12.3 illustrates how successive heat and cold hazards can \r\npotentially affect important natural and human systems, with climatic \r\npressures reaching new sectoral assets or becoming increasingly \r\nsevere as conditions become more extreme. While the precise value \r\nof any CID threshold may depend strongly on local environmental \r\nand system characteristics, there are common patterns and \r\ninterdependencies in the types of thresholds encountered. Changes \r\nin the regional profile of CIDs can thus substantially alter threshold \r\nexceedance likelihoods."


id: f9ce5c93f01b51e70a16fff343ed8511
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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"Changes in mean precipitation alter total water resources and \r\nlong-term surface, snowpack and groundwater reservoirs (Schewe \r\net al., 2014). Annual and seasonal wet trends can alter the suitable \r\ngeographic range of species, with implications for biodiversity and \r\nvector-borne diseases (Knouft and Ficklin, 2017; Smith et al., 2020). \r\nThe rate at which higher total streamflow increases river erosion \r\nand changes sediment loading is relevant for fish breeding (Scheurer \r\net al., 2009), the location of riverine salt fronts that affect coastal \r\nagriculture and ecosystems (Chun et  al., 2018; Vu et  al., 2018), \r\ncoastal  freshwater stratification (Baker-Austin et  al., 2013; Bell \r\net al., 2013), and the accretion of sediment in estuaries and beaches \r\n(Syvitski and Milliman, 2007). Wetter conditions may shift tourist \r\nappeal (Kovacs et al., 2017) and alter the pace of degradation for \r\npaved and especially unpaved roads (Chinowsky and Arndt, 2012)."


id: a0ec1ee10b1290ad11505b53455cf53d
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"Many agricultural systems require minimum rainfall totals or rely \r\nupon irrigation (Mbow et al., 2019). The length of the wet season \r\nhelps determine the potential for multiple cropping seasons, but \r\ninconsistency of wet season arrival times poses challenges for farm \r\nmanagement (Waha et al., 2020). Wetter growing season conditions \r\nincrease the chance of waterlogging, which can delay planting or \r\ndamage planted seeds (Rosenzweig et  al., 2002; Ben-Ari et  al., \r\n2018; Makinen et al., 2018; Wolfe et al., 2018; Kolberg et al., 2019; \r\nGrotjahn, 2021). Tomasek et  al. (2017) calculated 'workable days' \r\nfor agricultural machinery around planting and harvest time set in \r\npart by limits in soil moisture saturation below which farmers can \r\nutilize critical machinery with less rutting or soil compaction. Wetter \r\nconditions may also increase canopy moisture that is conducive to \r\ncrop pathogens (Garrett et al., 2006; Kilroy, 2015; Grotjahn, 2021)."


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"thresholds related to antecedent wet periods and extreme rainfall \r\nintensities (Alvioli et al., 2018; Monsieurs et al., 2019). Landslides and \r\nrockfalls may also be exacerbated by permafrost thaw and receding \r\nglaciers in polar and mountain areas (Cook et  al., 2016; Haeberli \r\net al., 2017; Patton et al., 2019)."


id: 222fc1e84503f14c7b3a9fbb948f4406
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 2826
content:
"Water managers often utilize a  variety of hydrological drought \r\nindices and hydrological models to characterize water resources, low \r\nflow conditions and the potential for irrigation (Wanders and Wada, \r\n2015; Mukherjee et al., 2018). Low flow volume and intermittency \r\nthresholds can indicate reductions in dissolved oxygen, more \r\nconcentrated pollutants, and higher stream temperatures relevant for \r\necosystems, water resource quality and thermal power plant cooling \r\n(Feeley et al., 2008; Doll and Schmied, 2012; Schaeffer et al., 2012; \r\nPrudhomme et  al., 2014; van Vliet et  al., 2016). Low water levels \r\nmay also restrict waterway navigation for commerce and recreation \r\n(Forzieri et al., 2018)."


id: ccd533d2cc219ea7db3a6b24747abfa3
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vector_id: 29764
content:
"Landslides, mudslides, rockfalls and other mass movements can lead \r\nto fatalities, destroy infrastructure and housing stock, and block \r\ncritical transportation routes. Climate models cannot resolve these \r\ncomplex slope failure processes (nor triggering mechanisms such as \r\nearthquakes), so most studies rely on proxies or conditions conducive \r\nto slope failure (Gariano and Guzzetti, 2016; Ho et al., 2017). Common \r\nindices include precipitation intensity-duration thresholds (Brunetti \r\net  al., 2010; Khan et  al., 2012; Melchiorre and Frattini, 2012) and "


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content:
"of high wind speed and low humidity (even for just a portion of the \r\nday) can also inform studies examining fruit desiccation and rice \r\ncracking (Grotjahn, 2021). Drought also raises disease infection rates \r\nfor West Nile virus (Paull et al., 2017), and the alternation of dry and \r\nwet spells induces swelling and shrinkage of clay soils that can lead to \r\nsinkholes and destabilize buildings (Hadji et al., 2014)."


id: fb47c7584c8ce5c5007a7bc725ec19da
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 37042
content:
"ground, with tolerance thresholds depending on crop species and \r\ndevelopmental stage (Seidl et  al., 2017; Lai, 2018; Elsner et  al., \r\n2019; Grotjahn, 2021). Severe storms particularly threaten energy \r\ninfrastructure, with maximum wind speed associated with treefall \r\nand breaking of above-ground electrical transmission lines (Ward, \r\n2013; Nik et al., 2020). The profile of heavy wind gusts is also required \r\nin the design of skyscrapers (C.-H. Wang et al., 2013) and bridges \r\n(Mondoro et al., 2018). Severe storms are difficult to simulate at the \r\nrelatively coarse spatial scales of Earth system models, thus scientists \r\noften project changes by noting areas with increased convective \r\navailable potential energy (CAPE) and strong low-level wind shear as \r\nthese are conducive to tornado formation (Diffenbaugh et al., 2013; \r\nTippett et al., 2016; Glazer et al., 2021)."


id: 6499841f27215532b53cdf4333cf852c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 13397
content:
"Tropical cyclones and severe coastal storms can deliver wind, water \r\nand coastal hazards with the potential for widespread mortality and \r\ndamages to cities, housing, transportation and energy infrastructure, \r\necosystems and agricultural lands (Burkett, 2011; NASEM, 2012; Bell \r\net al., 2013; Wehof et al., 2014; Ward et al., 2016; Cheal et al., 2017; \r\nGodoi et al., 2018; Koks et al., 2019; Pinnegar et al., 2019). Storm \r\nplanning is often tied to the Saffir-Simpson scale related to peak \r\nsustained wind speed (Izaguirre et  al., 2021), with several indices \r\nfocusing on storms' overall power and energy, size and translation \r\nspeed to anticipate destructive potential (Knutson et al., 2015; Wang \r\nand Toumi, 2016; Parker et al., 2018; Hassanzadeh et al., 2020)."


id: 939a5b2ca9b9a83004f58a22f8d27cdd
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 20736
content:
"Cryospheric changes are a focus of Chapter 9 and were central to \r\nthe recent IPCC Special Report on the Ocean and Cryosphere in \r\na  Changing Climate (SROCC; IPCC, 2019b). Here we focus on the \r\nways that scientists use snow and ice CIDs to understand current and \r\nfuture societal impacts and risks."


id: 1e02f3576911aae5c2cf0b703a660c40
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 2156
content:
"Heavy snowfall is a substantial concern for cities, settlements and \r\nkey transportation and energy infrastructure (Ward, 2013; Palko, \r\n2017; Janoski et al., 2018; Collins et al., 2019). Heavy snowfall can \r\ninterfere with transportation (Herring et al., 2018) and cause a loss \r\nof both work and school days depending on local snow removal \r\ninfrastructure. Freezing rain and ice storms can be treacherous for \r\nroad and air travel (Tamerius et al., 2016), and can knock down power \r\nand telecommunication lines if ice accumulation is high (Degelia \r\net  al., 2016). Rain-on-snow events can create a  solid barrier that \r\nhinders wildlife and livestock grazing that is important to indigenous \r\ncommunities (Forbes et al., 2016). Shifts in the frequency, seasonal \r\ntiming and regions susceptible to ice storms alter risks for agriculture \r\nand infrastructure (Lambert and Hansen, 2011; Klima and Morgan, \r\n2015; Ning and Bradley, 2015; Groisman et al., 2016)."


id: 2c682e0e0d4e2573856b6cc5cc3e54d3
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 4418
content:
"Change in ice sheet and glacier spatial extent and surface mass \r\nbalance is relevant for polar and high mountain ecosystems and \r\ndownstream assets that rely on glacial water resources (J.R. Lee et al., \r\n2017; Milner et al., 2017; Huss and Hock, 2018; Schaefli et al., 2019). \r\nThe loss of glaciers reduces the thermal consistency of cold streams \r\nsuitable for some freshwater species (Giersch et  al., 2017), and \r\nparks and recreation areas may lose appeal as glaciers and seasonal \r\nsnow cover retreat (Gonzalez et al., 2018; Wang and Zhou, 2019). \r\nRapid glacial retreat can lead to glacial lakes and outburst floods \r\nthat endanger downstream communities (Carrivick and Tweed, 2016; \r\nCook et al., 2016; Harrison et al., 2018)."


id: 2bc11494ac4adcc25edd79b5dc34571f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 4311
content:
"Information on the changing frequency and size distribution of hail can \r\nhelp stakeholders build resilience for agriculture, vehicles, transportation \r\ninfrastructure and buildings, solar panels and wild species that see \r\ncritical damage at particular hail size thresholds (Dessens et al., 2007; \r\nWebb et al., 2009; Patt et al., 2013; Fiss et al., 2019). Most climate \r\nmodels do not directly resolve hail and therefore studies often examine \r\nproxies associated with severe mesoscale storms (Tippett et al., 2015; \r\nPrein and Holland, 2018), although some regional studies now utilize \r\nhail-resolving models (Mahoney et al., 2012; Brimelow et al., 2017)."


id: 8cdbce1b18d4aa3b8f6153610c258f4e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 19680
content:
"Changes in permafrost temperature, extent and active layer thickness \r\nare metrics that track how permafrost thaw below, for example, roads, \r\nairstrips, rails and building foundations in high-latitude and mountain \r\nregions may destabilize settlements and critical infrastructure \r\n(Pendakur, 2016; Derksen et al., 2018; Duvillard et al., 2019; Olsson \r\net  al., 2019; Streletskiy et  al., 2019). Warmer conditions can also \r\naffect ecosystems, built infrastructure and water resources through \r\nthawing of especially ice-rich permafrost (>=20% ice content) and by \r\nthawing of ice wedges (Shiklomanov et al., 2017; Hjort et al., 2018), \r\ncreation of thermokarst ponds and increased subsurface drainage \r\nfor polar and high-mountain wetlands (Walvoord and Kurylyk, 2016; \r\nFarquharson et al., 2019) and the release of water pollutants such as \r\nmercury (Burkett, 2011; Schaeffer et al., 2012; Schuster et al., 2018)."


id: 51369713a15381bea407c90823bff537
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 10229
content:
"Information about the changing frequency and seasonal timing of \r\nsnow avalanches is important to assess threats to transportation \r\nroutes, infrastructure, recreational skiing and people living in alpine \r\ncommunities (Lazar and Williams, 2008; Mock et al., 2017; Ballesteros\u0002Canovas et  al., 2018; Hock et  al., 2019). Like landslides and other \r\nmass movements, snow avalanches are not directly resolved by "


id: ca1e496ff7a0208f486e8e1c0708cfd6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 29357
content:
"of floods that overtop coastal protection, due to extreme coastal \r\nwater levels (ECWL), is important for port and harbour operations \r\nand coastal energy infrastructure thresholds (Bilskie et  al., 2016; \r\nCamus et  al., 2017). Frequent inundation by salt water can also \r\nhave significant impacts on water resources, crops, aquaculture and \r\ntransportation systems due to corrosion and undercutting of coastal \r\nroads, bridges and rails (Zimmerman and Faris, 2010; N. Ahmed et al., \r\n2019; Gopalakrishnan et al., 2019)."


id: a4bf603cd511fc73734e2f8380ee39e2
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23494
content:
"climate models and are thus tracked using proxy climate information \r\ndescribing snow avalanche susceptibility, particularly the snow water \r\nequivalent, and triggering mechanisms such as warm spells, high \r\nwinds, rain-on-snow and heavy precipitation (Hock et al., 2019). The \r\nquality of snow also provides insight into avalanche hazards (Mock \r\net al., 2017), with the seasonal altitude of wet snowpack (>0.5% liquid \r\nwater by volume) particularly important in determining characteristics \r\nof potential avalanches (Castebrunet et al., 2014)."


id: 6811df8cc93ad389f15e3936a2b0cecf
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 13960
content:
"The SROCC included in-depth discussions of threats facing the world's \r\ncoastlines (IPCC, 2019b) and Section 9.6 provides further discussion \r\non coastal processes. Here we note major connections between \r\ncoastal CIDs and ecosystem and societal assets near coastlines."


id: 36e526b5c091c6161f2d00c057c4b999
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 6025
content:
"Oceanic changes and impacts were a  substantial focus of SROCC \r\n(IPCC, 2019b). Chapter 9 of this Report assesses changes in ocean \r\nprocesses, and here we note major connections used by scientists to \r\nunderstand how oceanic CIDs affect ecosystems and society."


id: ee72fa5f2c1773c468fbe9f3162e0e63
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 34982
content:
"Shifts in thermal zones affect the suitability of fisheries and marine \r\nand coastal species habitat and migration routes (Hoegh-Guldberg \r\nand Bruno, 2010; Doney et al., 2012; Burrows et al., 2014; Urban, 2015; \r\nHixson and Arts, 2016; Tripathi et al., 2016; N. Ahmed et al., 2019; \r\nBindoff et al., 2019). Intertidal species are particularly dependent on \r\nsuitable conditions for both air and sea surface temperatures (Monaco \r\nand McQuaid, 2019). The structure of ocean warming also affects the \r\nintensity of upper-ocean stratification and the timing and strength of \r\ncoastal upwelling (driven also by mean wind changes), which alters \r\nthe vertical transport of oxygen- and nutrient-rich waters affecting \r\nfishery and marine ecosystem productivity (D. Wang et al., 2015)."


id: 29de7a41330eb70d7207c5dc5054d85d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 4017
content:
"Episodic coastal flooding of coastal communities, farmland, buildings, \r\ntransportation routes, industry and other infrastructure is caused \r\nby extreme total water levels (ETWL), which is the combination \r\nof RSL, tides, storm surge and high wave setup at the shoreline \r\n(Vitousek et al., 2017; Melet et al., 2018; Vousdoukas et al., 2018, \r\n2020a; Koks et al., 2019; Kirezci et al., 2020). Coastal settlement and \r\ninfrastructure design often uses coastal flooding metrics such as the \r\nETWL frequency distribution or the 100-year average return interval \r\nstorm tide (storm surge + high tide) level (McInnes et al., 2016; Mills \r\net al., 2016; Walsh et al., 2016b; Zheng et al., 2017). The duration "


id: 439b143ec729b2ad02afb0b9251c8d2b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 8044
content:
"Uptake of atmospheric CO2 and subsequent increases in dissolved \r\nCO2 lowers ocean pH and can reduce carbonate ion concentrations \r\nbelow critical calcium carbonate saturation thresholds for marine \r\nand aquatic organisms growth, reproduction and/or survival, with \r\nextended implications for marine ecosystems including fisheries (Bell \r\net al., 2013; Kroeker et al., 2013; Barange et al., 2014; Dutkiewicz \r\net al., 2015; Ekstrom et al., 2015; Gattuso et al., 2015; Mathis et al., \r\n2015a; Nagelkerken and Connell, 2015; Behrenfeld et  al., 2016; \r\nNagelkerken and Munday, 2016; Tripathi et  al., 2016; Jiang et  al., \r\n2018; Weiss et al., 2018; N. Ahmed et al., 2019; Bindoff et al., 2019). \r\nLower pH may provide more favourable conditions for toxic algal \r\nblooms (Riebesell et al., 2018) and can interact with hypoxic zones \r\nto impact ecosystems (Gobler and Baumann, 2016; Cai et al., 2017)."


id: b8951e5b0210c2be2dd8e2cc90eaf06c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 26568
content:
"Changes in currents, sea ice brine rejection and net freshwater flux \r\nin the ocean can alter salinity with effects on mixed layer structure, \r\ndensity stratification and the vertical movement of nutrients and \r\nmarine organisms (Freeland, 2013; Haumann et al., 2016)."


id: 8bf000404c0bee997c367d8ba32079a1
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 19530
content:
"Ocean warming and increased stratification decrease the oxygen \r\ncontent of the ocean (Griffiths et al., 2017; Schmidtko et al., 2017; \r\nBindoff et al., 2019), lead to an expansion of oxygen minimum zones \r\nin the open ocean (Stramma et  al., 2012; Zhang et  al., 2013) and \r\nexacerbate the creation of anoxic 'dead zones' in the coastal oceans \r\n(Breitburg et al., 2018). Such a decline (characterized by successive \r\ndissolved oxygen concentration thresholds) could affect a wide range \r\nof marine organisms and reduce marine habitats (Chan et al., 2008; \r\nVaquer-Sunyer and Duarte, 2008; Hoegh-Guldberg and Bruno, 2010; \r\nAltieri and Gedan, 2015; Breitburg et al., 2018) and can also lead to \r\nfurther local acidification (Zhang and Gao, 2016; Laurent et al., 2017)."


id: 750ed85ccab0ba729e92e7650f6fdaf1
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 16010
content:
"Changes in surface solar and longwave radiation fluxes alter \r\nphotosynthesis rates and potential evapotranspiration for natural \r\necosystems and food, fibre and energy crops (Makinen et al., 2018); "


id: ddc53bf6e8fd64f3219935b9a993a060
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 32387
content:
"changes in radiation fluxes can also shift solar energy resources \r\n(Schaeffer et al., 2012; Jerez et al., 2015; Wild et al., 2015; Fant et al., \r\n2016; Craig et  al., 2018). Plants and aquatic systems particularly \r\nrespond to changes in photosynthetically active radiation (PAR) and the \r\nfraction of diffuse radiation (Proctor et al., 2018; Ren et al., 2018; Ryu \r\net al., 2018). Increases in ultraviolet radiation can also detrimentally \r\naffect ecosystems and human health (Barnes et al., 2019)."


id: a2ec26992ef9637e9c737abe9fcfebb1
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23202
content:
"described in Figure  1.18a. The section is organised by continents \r\n(Sections 12.4.1-12.4.6) with a specific assessment for Small Islands \r\n(Section 12.4.7), open and deep ocean (Section 12.4.8), and polar regions \r\n(Section 12.4.9) as defined in Chapter 1 (Figure 1.18c). In addition, CID \r\nindices and thresholds relevant to 'specific zones', as defined in AR6 \r\nWGII Cross-Chapter Papers, are assessed in Section 12.4.10 except for \r\nthe Mediterranean, which is addressed both under Africa and Europe \r\n(Sections 12.4.1 and 12.4.5) and is a focus in Section 10.6.4."


id: d84b62116bf74b2691c1ef60be60e41c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 31556
content:
"Additional CIDs may be relevant for regional studies but are not the \r\nfocus of assessment in this Report. For example, information about \r\nchanges in the frequency and seasonal timing of fog helps anticipate \r\nairport delays and cool beach days, and is also important for water \r\ndelivery and retention in coastal ecological and agricultural systems \r\n(Torregrosa et al., 2014)."


id: ba4dc988f722de9ba06fb1d98df1961e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 26846
content:
"Recent literature defines CID indices to represent trends \r\nand thresholds that influence sectoral assets, albeit with \r\nconsiderable variation owing to the unique characteristics of \r\nregional and sectoral assets. Indices include direct information \r\nabout the CID's profile (magnitude, frequency, duration, timing, \r\nspatial extent) or utilize atmospheric conditions as a proxy for \r\nCIDs that are more difficult to directly observe or simulate. \r\nEach sector is affected by multiple CIDs, and each CID affects \r\nmultiple sectors. Assets within the same sector may require \r\ndifferent or tailored indices even for the same CID. These indices \r\nmay be defined to capture graduated thresholds associated \r\nwith tipping points or inflection points in a particular sectoral \r\nvulnerability, with commonalities in the types of processes \r\nthese thresholds represent even as their precise magnitude \r\nmay vary by specific sectoral system and asset."


id: 511b2e1f14192efb701f24082a524893
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 10213
content:
"This section describes the historical and projected changes in commonly \r\nused indices and thresholds associated with the main climatic \r\nimpact-drivers (Sections 12.2 and 12.3) at the scale of AR6 regions "


id: 7e9f54bbf42a08b3fa6795734922afb1
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 17488
content:
"or projected emergence of the CID change signal from the natural \r\ninterannual variability if assessed with at least medium confidence\r\nin Section 12.5.2, using as a basis a criterion of S/N > 1, noise being \r\ndefined as the interannual variability. The time of emergence (ToE) \r\nis given as either: (i) already emerged in the historical period, or \r\n(ii) emerging by 2050 at least for RCP8.5/SSP5-8.5, or (iii) emerging \r\nafter 2050 but before 2100 at least for scenarios RCP8.5 or SSP5-8.5. \r\nTable cells that do not include emergence information are indicative \r\nof 'low confidence of emergence in the 21st century', which includes \r\nsituations where assessment indicates emergence will not occur \r\nbefore 2100 or that evidence is not available or insufficient for \r\na confidence assessment of time of emergence."


id: 5cae7590f5e0493263eba0c1efe45868
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 12103
content:
"Figures: The assessment of changes in CIDs is based on literature, \r\nphysical understanding (Chapters 2-11), and global and regional \r\nclimate projections of indices and thresholds presented in the \r\nAtlas, as well as in the global and regional figures in Section 12.4 \r\n(Figures 12.4-12.10) showing the future evolution of nine key CID \r\nindices/thresholds used in this assessment (see also Cross-Chapter \r\nBox  10.3). The figure indices and impact-relevant thresholds are \r\ndescribed in Annex VI: Climatic Impact-drivers and Extreme Indices."


id: 887e621c7b2c1a3858cf422c649148fb
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 19004
content:
"Figure  12.4 shows changes in six CID indices. These global maps \r\nare derived from Coupled Model Intercomparison Project Phase 6 \r\n(CMIP6) simulations for different time periods and scenarios (except \r\nfor extreme total water level where CMIP Phase 5 (CMIP5) is used). \r\nThe uncertainty due to climate models, time, scenarios and regional \r\ndownscaling is illustrated in Supplementary Material SM.12.1 to \r\nSM.12.6, which show the distribution of the spatial average of the \r\nindex among models over each land region for CMIP5, CMIP6 and \r\nCoordinated Regional Climate Downscaling Experiment (CORDEX) \r\nensembles for the recent past, mid- and end-21st century, and for \r\nGWLs of +1.5degC, +2degC and +4degC. The hatching in the figure covers \r\nareas where less than 80% of models agree on the sign of change."


id: c587af6a231d5055e313a0308162329d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 28657
content:
"Further regional detail is provided for the remaining indices in each \r\ncontinental section in the form of continental maps accompanied \r\nby regional box plots displaying changes calculated for AR6 region \r\naverages, and the associated regionally averaged uncertainty."


id: f2bef1d21258571e09901ad8e85bb681
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 35717
content:
"Climatic impact-drivers changing in a globally coherent way:\r\nFor the sake of conciseness, assessments pertaining to ocean acidity \r\nand the 'Other' CID type in Sections 12.2 and 12.3 are not provided \r\nper region in Sections 12.4.1-12.4.9 but are summarized here, given \r\nthe globally coherent way in which they change."


id: eefebf64bae2443ba09612894dfabb2f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 35075
content:
"(WAF), Central Africa (CAF), North Eastern Africa (NEAF), South \r\nEastern Africa (SEAF), West Southern Africa (WSAF), East Southern \r\nAfrica (ESAF) and Madagascar (MDG) - are the official AR6 regions \r\n(Figure Atlas.2) and one - North Africa - is used in this assessment to \r\nindicate the African portion of the Mediterranean region."


id: df32526641dd2f17635bedb7926e36cd
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 32617
content:
"Quite a large body of new literature is now available for the African \r\nclimate as a result of regionally downscaled CORDEX Africa outputs, \r\nin particular, providing projections of both the mean climate (Mariotti \r\net al., 2014; Nikulin et al., 2018; Dosio et al., 2019; Teichmann et al., \r\n2021) and extreme climate phenomena (Giorgi et al., 2014; Nikulin \r\net al., 2018; Dosio et al., 2019; Coppola et al., 2021b). CORDEX Africa \r\nsimulations are assessed in the Atlas, which finds reasonable skill in \r\nmean temperature and precipitation as well as important features \r\nof regional climate (e.g.,  timing of monsoon onset in West Africa) \r\nalthough lower performance in Central Africa."


id: fe4f69610667f0f625058c33d27c09c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 37541
content:
"Mean air temperature: The African continent has experienced \r\nincreased warming since the beginning of the 20th century in regions \r\nwhere measurements allow a  sufficient homogeneous observation \r\ncoverage to estimate trends (high confidence) (Figure Atlas.11). This \r\nwarming is very likely attributable to human influence (Chapter  3 \r\nand Atlas.4.2) at continental scale. Mean annual temperatures \r\nhave increased at a high rate since the mid-20th century, reaching \r\n0.2degC-0.5degC per decade in some regions such as north, north\u0002eastern, west and south-western Africa (high confidence) (Atlas.4.2 \r\nand Figure Atlas.11)."


id: b7d668044aed0cc679a1929ca1f7b3de
created_at: 2023-03-16 14:00:50
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vector_id: 26461
content:
"It is very likely that temperatures will increase in all future emissions \r\nscenarios and all regions of Africa (Atlas.4.4). By the end of the \r\ncentury under RCP8.5 or SSP5-8.5, all African regions will very likely\r\nexperience a warming larger than 3degC except Central Africa, where \r\nwarming is very likely expected above 2.5degC, while under RCP2.6 \r\nor SSP1-2.6, the warming remains very likely limited to below 2degC \r\n(Figure Atlas.12). A very likely warming with ranges between 0.5degC \r\nand 2.5degC is projected by the mid-century for all scenarios depending \r\non the region (high confidence). Mean temperatures for all regions \r\nare projected to increase with increasing global warming (virtually \r\ncertain) (Figure Atlas.12)."


id: 5479d4efaa1148c73faa8d4a41e143
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 10749
content:
"Extreme heat: Warm extremes have increased in most of the regions \r\n(high confidence), NEAF, SEAF and MDG (medium confidence) and \r\nwith low confidence in CAF (Table 11.4). Despite the increasing mean \r\ntemperature, there is low confidence (limited evidence) that Africa \r\nhas experienced increased extreme heat stress trend for agriculture \r\nor human health in the last two decades of the 20th century in a few \r\nregions such as West Africa, South Africa and North Africa considering \r\nthe period from 1973 to 2012 (Knutson and Ploshay, 2016)."


id: 135815152ff16ae6acff77f3e28251b5
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 556
content:
"A substantial increase in heatwave magnitude and frequency over \r\nmost of the Africa domain is projected for even 2degC global warming \r\n(high confidence) (Sections 11.3 and 11.9, and Table  11.4), with \r\npotential effects on health and agriculture. The number of days \r\nwith maximum temperature exceeding 35degC is projected to increase \r\n(Coppola et al., 2021b) in the range of 50-100 days by 2050 under "


id: d082fc8f6995f4a2ce9a71e89146c294
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 30331
content:
"Previous IPCC assessments results are summarized in Atlas.4.1.1 \r\nFor the purpose of this assessment the Africa region has been divided \r\nin nine sub-regions of which eight - Sahara (SAH), Western Africa "


id: 10c3a530c174d985a5a512440d127b2b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 111
content:
"SSP5-8.5 in WAF, ESAF and WSAF and NEAF (high confidence) \r\n(Figure  12.4b). Under SSP1-2.6, the change in the number of \r\nexceedance days remains limited to about 40-50 days per year at \r\nthe end of the century in these regions, while it increases by 150 days \r\nor more in WAF, CAF for SSP5-8.5 (Figure 12.4a,c; Figure 12.SM.1)."


id: 4159b9ab4aa96a97b625d8a6bbbc17c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 7679
content:
"Mean precipitation: Since the mid-20th  century, precipitation \r\ntrends have varied in Africa but notable drying trends are found in \r\neastern, central and north-eastern parts of Southern Africa, Central \r\nAfrica and in the Horn of Africa (Atlas.4.2)."


id: a63ceea055403213a647a4dacbff8afb
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23689
content:
"There is high confidence in projected mean precipitation decreases \r\nin North Africa and West Southern Africa and medium confidence\r\nin East Southern Africa by the end of the 21st century (Dosio et al., \r\n2019; Gebrechorkos et al., 2019; Teichmann et al., 2021; Atlas.4.5). \r\nThe Western Africa region features a gradient in which precipitation \r\ndecreases in the west and increases in the east and increase is also \r\nprojected over Eastern Africa (medium confidence) (Atlas.4.5), with \r\ntrends in Western Africa affecting the boreal summer monsoon (Chen \r\net al., 2020). Increasing precipitation for 1.5degC and 2degC GWLs are \r\nfound in central and eastern Sahel with low confidence and the \r\nwet signal is getting stronger and more extended for a 3degC and 4degC \r\nwarmer world (Atlas.4.4)."


id: 821e3c36b64dfae76ad613d13cf47a80
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 17992
content:
"A change in monsoon seasonality is also reported in Western Africa \r\nand Sahel (low confidence) with a forward shift in time (later onset and \r\nend; Section 8.2; Mariotti et al., 2011; Seth et al., 2013; Ashfaq et al., \r\n2021). This shift has been associated with a  precipitation decrease \r\nduring the monsoon season attributed to a decrease of African easterly \r\nwave activity in the 6-9-day regime (Mariotti et al., 2014) and a soil \r\nprecipitation feedback reported in Mariotti et al. (2011)."


id: 5340ab22a24dca5ad8847f995929a376
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 10568
content:
"Cold spell and frost: Africa experiences cold events and frost days \r\nthat can affect agriculture, infrastructure, health and ecosystems, \r\nespecially in Southern and North Africa, which have marked cold \r\nseasons and mountainous areas. Cold spells have likely decreased in \r\nfrequency over subtropical areas. In particular, in North and Southern \r\nAfrica, the frequency of cold events has likely decreased in the last few \r\ndecades (Sections 11.3 and 11.9). There is a high confidence that cold \r\nspells and low target temperatures will decrease in future climates \r\nunder all scenarios in West, Central and East Africa. Heating degree \r\ndays will have a substantial decrease by the end of the century for up \r\nto about one month under RCP8.5 in North and Southern Africa (high \r\nconfidence) (Coppola et al., 2021b)."


id: ef984c0420b9ca6035cdbc8745c0aa55
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 35195
content:
"River flood: Generally in Africa from 1990 through 2014, annual \r\nflood frequencies have fluctuated and there is medium confidence\r\nin an upward trend in flood events occurrences (C.-J. Li et al., 2016). \r\nIn  particular, over Western Africa, upward trends in hydrological \r\nextremes such as maximum peak discharge have likely occurred \r\nduring the last few decades (i.e.,  after 1980) and have caused \r\nincreased flood events in riparian countries of rivers such as Niger, \r\nSenegal and Volta (high confidence) (Nka et  al., 2015; Aich et  al., \r\n2016a; Wilcox et al., 2018; Tramblay et al., 2020). In Southern Africa, \r\ntrends in flood occurrences were decreasing prior to 1980 and \r\nincreasing afterwards (medium confidence) (Tramblay et al., 2020)."


id: b527b1ed88b7495036497b5a511edced
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 26040
content:
"There is high confidence that extreme heat has increased in \r\nfrequency and intensity in most African regions. Heatwaves \r\nand deadly heat stress and the frequency of exceedance of hot \r\ntemperature thresholds (e.g., 35degC) will drastically increase by \r\nthe end of the century (high confidence) under SSP5-8.5, but \r\nlimited increases are expected in SSP1-2.6. Dangerous heat \r\nstress thresholds (HI > 41degC) are projected to be crossed more \r\nthan 200 days more in West and Central Africa under SSP5-8.5, \r\nwhile this increase remains limited to a few tens of days more \r\nfor SSP1-2.6. Cold spells and frost days are projected to occur \r\nless frequently in all scenarios."


id: e258d35db10c65c455dbe7db0f60c864
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 33116
content:
"Under future climate scenarios, the extreme river discharge as \r\ncharacterized by the 30-year return period of 5-day average peak flow \r\nis projected to increase by the end of the century for RCP8.5 (more \r\nthan 10% relative to the 1971-2000 period) for most of the tropical \r\nAfrican river basins (Dankers et al., 2014) and a consistent increase \r\nof flood magnitude is projected across humid tropical Africa by 2050 "


id: c817fdcc0a08735720e609471d1ae2eb
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 29063
content:
"Gan, 2017). A growing number of studies provide further regional \r\ncontext on expanding aridity in several places in East and West Africa, \r\nrespectively (Sylla et al., 2016a; Liu et al., 2018b; Haile et al., 2020)."


id: 88e5ac950aaa38c6b651b2dade76b588
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 19073
content:
"Hydrological drought: Section 11.9 noted observed decreases in \r\nhydrological drought over the Mediterranean (high confidence) and \r\ndiminished summer river flows in West Africa (medium confidence). \r\nRecent regional modelling studies project substantial increases in \r\nhydrological drought affecting major West African river basins under \r\n1.5degC and 2degC GWLs and RCP4.5 and RCP8.5 scenarios (Oguntunde \r\net al. 2018, 2020; Sylla et al., 2018b); however, there remains low \r\nconfidence in future projections given disagreement with global \r\nmodel runoff projections (e.g., B.I. Cook et al., 2020). There is high \r\nconfidence that a 2degC GWL would see an increase in hydrological \r\ndroughts in the Mediterranean region, and medium confidence in \r\nincreasing hydrological drought conditions in the Southern Africa \r\nregions (Section 11.9)."


id: 66e0ca15a9bebaa3abe5ba9ed65c907d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 13777
content:
"Heavy precipitation and pluvial flood: Chapter  11 found that \r\nheavy precipitation intensity and frequency has likely increased \r\nover West and East Southern Africa but there is no evidence due to \r\na lack of studies that any significant trend is observed in any other \r\nregion. In addition, East Africa has experienced strong precipitation \r\nvariability and intense wet spells leading to widespread pluvial \r\nflooding events hitting most countries including Ethiopia, Somalia, \r\nKenya and Tanzania (medium confidence). Finally, with respect \r\nto Southern Africa, heavy precipitations events have increased in \r\nfrequency (medium confidence)."


id: fd7881140493d0140e104a7a1b2b76ae
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
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vector_id: 37394
content:
"In West Africa and Central Africa, there is high confidence that the \r\nintensity of extreme precipitation will increase in a  future climate \r\nunder both RCP4.5 and RCP8.5 scenarios and 1.5degC and 2degC GWLs \r\nthreatening widespread flood occurrences before, during and after \r\nthe mature monsoon season (Chapter  11). Extreme precipitation \r\nintensity is also increasing in several other regions, such as SAH, \r\nNEAF, SEAF, ESAF and MDG (high confidence) for 2degC GWL and \r\nhigher (Chapter 11)."


id: de78b25eb40edc1299aea8b3ba98168f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 32505
content:
"Landslides: There is an increase in reported landslides in WAF, CAF, \r\nNEAF and SEAF in the past decades but with limited evidence of \r\nsignificant trends (Gariano and Guzzetti, 2016; Haque et al., 2019). \r\nThere is low confidence (limited evidence) of a  future increase in \r\nlandslides in central-eastern Africa, and literature is largely missing \r\nto assess this important hazard (Gariano and Guzzetti, 2016)."


id: 5b984deee79dda74b3f91472dfdbee96
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 11910
content:
"Fire weather: There is low confidence (low agreement) in recent \r\nreductions in fire activity given soil moisture increases in some \r\nregions and substantial land use changes (Andela et al., 2017; Forkel \r\net  al., 2019; Zubkova et  al., 2019). Days prone to fire conditions \r\nare going to increase in all extratropical Africa until the end of the \r\ncentury and fire weather indices are projected to largely increase \r\nin North and Southern Africa, where increasing aridity trends occur \r\n(high confidence), with an emerging signal well before the middle \r\nof the century where drought and heat increase will combine \r\n(Chapter 11; Engelbrecht et al., 2015; Abatzoglou et al., 2019). There \r\nis low confidence (limited evidence) of fire weather changes for other \r\nAfrican regions."


id: 9a34338b92f51641b51dd235f33bd6ef
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 21783
content:
"Aridity: Section 11.9 assesses medium confidence in observed \r\nlong-term declines of soil moisture and aridity indices in several \r\nAfrican regions (NAF, WAF). Trends in East Africa are not definitive \r\ngiven uncertain balances between precipitation and potential \r\nevaporation (Kew et  al., 2021). Projected declines in precipitation \r\nand soil moisture trends indicate high confidence in increased aridity \r\nover the 21st century in NAF, WSAF and ESAF but low confidence\r\nelsewhere in Africa (Section 11.9; see also Figure 12.4j-l; Gizaw and "


id: a131056840f59363d8b51976465c711c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 22920
content:
"Total precipitation is projected to decrease in the northernmost \r\n(high confidence) and southernmost regions of Africa \r\n(medium confidence), with West and East Africa regions each \r\nhaving a  west-to-east pattern of decreasing-to-increasing \r\nprecipitation (medium confidence). Most African regions will \r\nundergo an increase in heavy precipitation that can lead \r\nto pluvial floods (high confidence), even as increasing dry \r\nclimatic impact-drivers (aridity, hydrological, agricultural and \r\necological droughts, fire weather) are generally projected in \r\nthe North Africa and Southern African regions (high confidence) \r\nand western portions of West Africa (medium confidence)."


id: 12ca62a6690d1cc95440ef0afaa1538c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 454
content:
"Sand and dust storm: North Africa and the Sahel, and to a lesser extent \r\nSouthern Africa, are prone to dust storms, having consequences on \r\nhealth (Querol et al., 2019), transmission of infectious diseases (Agier \r\net al., 2013; Wu et al., 2016), and solar power generation and related \r\nmaintenance costs. There is limited evidence and low agreement\r\nof secular 20th  century trends in wind speeds or dust emissions \r\n(limited length of data records, large variability). Dust variations are \r\ncontrolled by changes in surface winds, precipitation and vegetation, \r\nwhich in turn are modulated at multiple time scales by dominant \r\nmodes of internal climate variability (Chapter  10). In North Africa, \r\nwind variability explains both the observed high concentrations \r\nbetween the 1970s and 1980s and lower concentrations thereafter \r\n(Ridley et al., 2014; Evan et al., 2016). Yet, the effect of vegetation \r\nchanges may not be negligible (Pu and Ginoux, 2017, 2018)."


id: b761bf4834de18344b02a41f83f72f15
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 26380
content:
"Mean wind speed: Decreasing trends in wind speeds have \r\noccurred in many parts of Africa (low confidence due to observations \r\nwith limited homogeneity) (McVicar et al., 2012; AR5 WGI). There \r\nis high confidence in climate change-induced future decreasing \r\nmean wind, wind energy potential and strong winds in North Africa \r\nand Mediterranean regions as a  consequence of the poleward \r\nshift of the Hadley cell (Karnauskas et al., 2018a; Kjellstrom et al., \r\n2018; Sivakumar and Lucio, 2018; Tobin et  al., 2018; Jung and \r\nSchindler, 2019) in the RCP4.5 and RCP8.5 scenarios by the middle \r\nof the century or beyond, and for a  GWL of 2degC or higher. Over \r\nWestern Africa and Southern Africa a  future significant increase \r\nin wind speeds and wind energy potential is expected (medium \r\nconfidence) (Figure 12.4m-o; Karnauskas et al., 2018a; Jung and \r\nSchindler, 2019)."


id: 2ca9de52a5c8a1a2f28d1c801930765f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Changes to the frequency and intensity of dust storms also remain largely \r\nuncertain due to uncertainty in future regional wind and precipitation \r\nas the climate warms, CO2 fertilization effects on vegetation (Huang \r\net al., 2017), and anthropogenic land use and land-cover change due \r\nto land management and invasive species (Ginoux et al., 2012; Webb \r\nand Pierre, 2018). Dust loadings and related air pollution hazards (from \r\nfine particles that affect health) are projected to generally decrease \r\nin many regions of the Sahara and Sahel due to the changing winds \r\n(Evan et al., 2016) and slightly increase over the Guinea coast and West \r\nAfrica (low confidence) (Ji et al., 2018)."


id: dd249b0e2567ebb8a967802e0dba33b8
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 32288
content:
"In summary, there is high confidence of a decrease in mean \r\nwind speed and wind energy potential in North Africa and \r\nmedium confidence of an increase in Southern and Western \r\nAfrica, by the middle of the century regardless of climate \r\nscenario or global warming level equal or superior to 2degC, high \r\nconfidence of a decrease in frequency of cyclones landing in \r\nSEAF, ESAF and MDG, and low confidence of a general increase \r\nin wind storms in most African regions located south of the \r\nSahel. The evolution of dust storms remains largely uncertain."


id: 80f14b2ff1252a57ba58471aba72282e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 17809
content:
"Tropical cyclone: In the South Indian Ocean, an increase in Category 5 \r\ncyclones has been observed in recent decades (Fitchett, 2018) as in \r\nother basins (Section 11.7). However, there is a projected decrease \r\nin the frequency of tropical cyclones making landfall over Madagascar, \r\nSouth Eastern Africa and East Southern Africa in a 1degC, 2degC and 3degC \r\nwarmer world (medium confidence) (Malherbe et al., 2013; Roberts \r\net al., 2015, 2020; Muthige et al., 2018; Knutson et al., 2020). There \r\nis medium confidence in general increasing intensities for cyclones in \r\nsuch studies for African regions."


id: b95619057806cf0699e223726c001287
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 26702
content:
"In conclusion, there is high confidence that African snow and \r\nglaciers have very significantly decreased in the last decades \r\nand that this trend will continue over the 21st century."


id: 68192e1928c105a898f29102573c850f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 13963
content:
"was found to be retreating while 21% was found to be stable or \r\nprograding over the period 1974-1996 (Addo and Addo, 2016)."


id: 806082027567992fe493a811888b9c62
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 17726
content:
"Relative sea level: Around Africa, from 1900 to 2018, a new tide \r\ngauge-based reconstruction finds a  regional mean RSL change of \r\n2.07 [1.36 to 2.77] mm yr -1 in the South Atlantic and 1.33 [0.80 to \r\n1.86] mm yr-1 in the Indian Ocean (Frederikse et al., 2020), compared \r\nto a  GMSL change of around 1.7  mm yr -1 (Section  2.3.3.3 and \r\nTable  9.5). For the period 1993-2018, these RSLR rates, based on \r\nsatellite altimetry, increased to 3.45 [3.04 to 3.86]  mm yr-1 and \r\n3.65  [3.23 to 4.08]  mm yr-1 respectively (Frederikse et  al., 2020), \r\ncompared to a GMSL change of 3.25 mm yr -1 (Section 2.3.3.3 and \r\nTable 9.5)."


id: fe43e2dcb229819f64dbf294314adf9
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 37534
content:
"Relative sea level rise is virtually certain to continue in the oceans \r\naround Africa. Regional mean RSLR projections for the oceans around \r\nAfrica range from 0.4-0.5 m under SSP1-2.6 to 0.8-0.9 m under \r\nSSP5-8.5 for 2081-2100 relative to 1995-2014 (median values), \r\nwhich is within the range of projected GMSL change (Section 9.6.3.3). \r\nThese RSLR projections may, however, be underestimated due \r\nto potential partial representation of land subsidence in their \r\nassessment (Section 9.6.3.2)."


id: 4ac2d60f42cc0e248c398eeda9b31d24
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 9180
content:
"Marine heatwave (MHW): From 1982 to 2016, the coastal oceans \r\nof Africa have experienced on average 2-3 MHWs per year, with the \r\ncoastal oceans around the southern half of the continent experiencing \r\non average 2.5-3 MHWs per year. The average duration was between \r\n5 and 15 days (Oliver et al., 2018). Changes over the 20th century, \r\nderived from MHW proxies, show an increase in frequency between \r\n0.5 and 2 MHWs per decade over the region, especially off the Horn \r\nof Africa; an increase in intensity per event around Southern Africa; \r\nand an increase in MHW duration along the North African coastlines \r\n(Oliver et al., 2018)."


id: d2ff323ce735ab4842b65c3ca9dd1497
created_at: 2023-03-16 14:00:50
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content:
"Coastal flood: The present-day 1-in-100-year extreme total water \r\nlevel is between 0.1 and 1.2 m around Africa, with values around 1 m \r\nor above along the south-west, south-east and central east coasts \r\n(Vousdoukas et al., 2018)."


id: a4ff8826af2c47bb9fe9e6eb82e131b5
created_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 23526
content:
"There is high confidence that MHWs will increase around Africa. \r\nMean SST, a common proxy for MHWs, is projected to increase by \r\n1degC (2degC) around Africa by 2100, with a  hotspot of around 2degC \r\n(5degC) along the coastlines of South Africa under RCP4.5 (RCP8.5; \r\nInteractive Atlas). Under global warming conditions, MHW intensity \r\nand duration will increase in the coastal zones of all sub-regions of \r\nAfrica (Frolicher et al., 2018). Projections for SSP1-2.6 and SSP5-8.5 \r\nboth show an increase in MHWs around Australasia by 2081-2100, \r\nrelative to 1985-2014 (Box 9.2, Figure 1)."


id: 29256bd96494f4470226128b1fa220da
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 3905
content:
"In general, there is high confidence that most coastal\u0002and ocean-related hazards in Africa will increase over the \r\n21st  century. Relative sea level rise is virtually certain to \r\ncontinue around Africa, contributing to increased coastal \r\nflooding in low-lying areas (high confidence) and shoreline \r\nretreat along most sandy coasts (high confidence). Marine \r\nheatwaves are also expected to increase around the region \r\nover the 21st century (high confidence)."


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content:
"Coastal erosion: Shoreline retreat rates up to 1 m yr -1 have been \r\nobserved around the continent during 1984-2015, except in ESAF, \r\nwhich has experienced a shoreline progradation rate of 0.1 m/r over \r\nthe same period (Luijendijk et  al., 2018; Mentaschi et  al., 2018). \r\nMentaschi et  al. (2018) report a  coastal area losses of 160 km2\r\nand 460 km2 over a 30-year period (1984-2015) along the Atlantic \r\nand  Indian Ocean coasts of the continent. At the more regional \r\nlevel, in Ghana along the Gulf of Guinea about 79% of the shoreline "


id: 8e13ace543803420afcb24aa563e301a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 19883
content:
"The assessed direction of change in CIDs for Africa and associated \r\nconfidence levels are illustrated in Table 12.3. No relevant literature \r\ncould be found for permafrost and hail, although these phenomena \r\nmay be relevant in parts of the continent."


id: f092c98a3c6f4b556d072979625d64fa
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
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vector_id: 35348
content:
"Chapter  11) due to the effects of anthropogenic global warming, \r\nEl Nino and urbanization (Luo and Lau, 2017; Thirumalai et al., 2017; \r\nImada et al., 2019; Y. Sun et al., 2019; Zhou et al., 2019). But there \r\nis medium confidence of heat extremes increasing in frequency in \r\nmany parts of India (Rohini et al., 2016; Mazdiyasni et al., 2017; van \r\nOldenborgh et al., 2018; Sen Roy, 2019; Kumar et al., 2020) partly \r\ndue to the alleviation of anthropogenic warming by increased air \r\npollution with aerosols and expanding irrigation (van Oldenborgh \r\net al., 2018; Thiery et al., 2020)."


id: c535a932b0f361806d44dc22ab66d4
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"According to the region definitions given in Chapter 1, Asia is divided \r\ninto 11 regions: the Arabian Peninsula (ARP), Western Central Asia \r\n(WCA), West Siberia (WSB), East Siberia (ESB), the Russian Far East \r\n(RFE), East Asia (EAS), East Central Asia (ECA), the Tibetan Plateau \r\n(TIB), South Asia (SAS), South East Asia (SEA) and the Russian Arctic \r\nRegion (RAR). CID changes in RAR are assessed in the Polar Region \r\nsection (Section 12.4.9). As assessed in previous IPCC Reports, major \r\nconcerns in Asia are associated particularly with droughts and floods \r\nin all regions, heat extremes in SAS and EAS, sand-dust storms in \r\nWCA, tropical cyclones in SEA and EAS, snow cover and glacier \r\nchanges in ECA and the Hindu Kush Himalaya (HKH) region, and sea \r\nice and permafrost thawing in northern Asia."


id: 5d93a99eebbc64cfd625b22b6576b5a6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 12244
content:
"Since AR5, a large body of new literature is now available relevant \r\nto climate change in Asia, which includes projections of both mean \r\nclimate and extreme climate phenomena from global and regional \r\nensembles of climate simulations such as CMIP6 and CORDEX \r\n(Chapter 10 and the Atlas). Literature has also considerably grown on \r\nseveral climate topics relevant to Asia such as the mountain climate \r\n(Chapter  3 of the SROCC), and the novel regional assessments \r\nsuch as the Hindu Kush Himalaya Assessment (Wester et al., 2019). \r\nFigure 12.6 shows the regional changes in indices related to floods, \r\nand coastal erosion over Asia, which are assessed on a regional basis \r\nalong with other climatic impact-driver indices below."


id: 2239ac0976a262ccf3dece15d23f4051
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 2833
content:
"Mean air temperature: A  long-term warming trend in annual \r\nmean surface temperature has been observed across Asia during \r\n1960-2015, and the warming accelerated after the 1970s (high \r\nconfidence) (Davi et al., 2015; Aich et al., 2017; Cheong et al., 2018; \r\nS. Dong et al., 2018; IPCC, 2018; Krishnan et al., 2019; M. Zhang et al., \r\n2019). Records also indicate a higher rate of warming in minimum \r\ntemperatures than maximum temperatures in Asia, leading to more \r\nfrequent warm nights and warm days, and less frequent cold days \r\nand cold nights (high confidence) (Supari et al., 2017; Akperov et al., \r\n2018; Cheong et al., 2018; Rahimi et al., 2018; Khan et al., 2019a; L. Li \r\net al., 2019; M. Zhang et al., 2019)."


id: df49e734fc62e1704bbfd46174d1b9c0
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Cold spell and frost: Cold spells intensity and frequency, as well as \r\nthe number of frost days, in most Asian regions have been decreasing \r\nsince the beginning of the 20th century (high confidence) (Chapter 11; \r\nSheikh et al., 2015; Donat et al., 2016; Erlat and Turkes, 2016; S. Dong \r\net al., 2018; Liao et al., 2018, 2020; Lu et al., 2018; van Oldenborgh \r\net al., 2019), except for the central Eurasian regions, where there was \r\na  cooling trend during 1995-2014, which is linked to sea ice loss \r\nin the Barents-Kara Seas (medium confidence) (Atlas.5.2; Wegmann \r\net al., 2018; Blackport et al., 2019; Mori et al., 2019)."


id: 864e49b673a4da2a1dddb7842b0758e6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Projections show continued warming over Asia in the future with \r\ncontrasted regional patterns across the continent (high confidence) \r\n(Figure 4.19). For RCP8.5/SSP5-8.5 at the end of the century, the mean \r\nestimated warming exceeds 5degC in WSB, ESB and RFE and 7degC in \r\nsome parts (high confidence). In most areas of ARP and WCA, 5degC is \r\nexceeded (Ozturk et al., 2017), but EAS, SAS and SEA have a lower \r\nprojected warming of less than 5degC (Basha et al., 2017; C. Lu et al., \r\n2019; Almazroui et al., 2020; Atlas.5). Under SSP1-2.6, the warming \r\nremains limited to 2degC in most areas except Arctic regions, where it \r\nexceeds 2degC (Figure 4.19)."


id: 2330c726865a964aec4e186cc9435e43
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"It is very likely that cold spells will have a decreasing frequency in all \r\nfuture scenarios across Asian regions (J. Guo et al., 2018; Sui et al., \r\n2018; L. Li et al., 2019), as well as frost days (L. Wang et al., 2017; \r\nFallah-Ghalhari et al., 2019) except in tropical Asia (Chapter 11)."


id: fb856bae515e78c4237673c6e2ddf33e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 37073
content:
"In Asia, temperatures have warmed during the last  century \r\n(high confidence). Extreme heat episodes have become more \r\nfrequent in most regions (high confidence), and are very likely\r\nto increase in all regions of Asia under all warming scenarios \r\nduring this century. Dangerous heat stress thresholds such \r\nas HI  > 41degC will be crossed much more often (typically \r\n50-150  days per year more than the recent past) in many \r\nsouthern Asia regions at the end of the century under SSP5-8.5 "


id: b860f7e66e7e0e1a900bb558efb21107
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Extreme heat: There is increased evidence and high confidence of \r\nmore frequent heat extremes in the recent decades than in previous \r\nones in most of Asia (Acar Deniz and Gonencgil, 2015; Rohini et al., \r\n2016; Mishra et al., 2017; You et al., 2017; Imada et al., 2018; Khan \r\net al., 2019b; Krishnan et al., 2019; Rahimi et al., 2019; Yin et al., 2019; "


id: 5cce190fe8a49dfa8a2b162c250f0372
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 12115
content:
"while these numbers should remain limited to a few tens under \r\nSSP1-2.6 (high confidence). It is very likely that cold spells and \r\nfrost days will decrease in frequency in all future scenarios \r\nacross Asian regions during the century."


id: 590e698f47a139431aa915c8aee40c12
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 11509
content:
"precipitation vary considerably by region (Chapter  11). Heavy \r\nprecipitation is very likely to become more intense and frequent in all \r\nareas of Asia except in ARP (medium confidence) for a 2degC GWL or \r\nhigher (Chapter 11)."


id: 575afc306fd2143f86b3a6370828e0c0
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 11238
content:
"Mean precipitation: The most prominent features about changes in \r\nprecipitation over Asia (1901-2010) are the increasing precipitation \r\ntrends across higher latitudes, along with some scattered smaller \r\nregions of detectable increases and decreases (Knutson and Zeng, \r\n2018); however, spatial variability remains high (W. Wang et  al., \r\n2015; Limsakul and Singhruck, 2016; Supari et  al., 2017; Rahimi \r\net al., 2018, 2019; Sein et al., 2018; Kumar et al., 2019; H. Wang et al., \r\n2019; see Atlas.5) (medium confidence)."


id: ad1ef0a666c721961d5bc8b33175ccaa
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 24780
content:
"Mean precipitation is likely to increase in most areas of northern \r\n(WSB, ESB, RFE), southern (ECA, TIB, SAS) and East Asia (EAS) in \r\ndifferent scenarios (high confidence) (Huang et al., 2014; Xu et al., \r\n2017; Kusunoki, 2018; Mandapaka and Lo, 2018; Luo et  al., 2019; \r\nWu et  al., 2019; X. Zhu et  al., 2019; Almazroui et  al., 2020; Jiang \r\net al., 2020; Rai et al., 2020; see Atlas.5). Monsoon circulation will \r\nalso increase seasonal contrasts, with SAS seeing wetter wet seasons \r\nand drier dry seasons (Atlas.5.3). Higher uncertainty between CMIP5 \r\nand CMIP6 as well as spatial differences lend low confidence to \r\nmodel projections in ARP and WCA (Atlas.5.5), with large seasonal \r\ndifferences (Zhu et al., 2020) and some models projecting decreases \r\nin precipitation in Central Asia (Ozturk et al., 2017), Pakistan (Nabeel \r\nand Athar, 2020) and SEA (Supari et al., 2020)."


id: 7dd4e1b88f74ef1d2afc384ec5c9695b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 17366
content:
"River flood: Flood risk has grown in many places in China from \r\n1961 to 2017 (Kundzewicz et  al., 2019) (low confidence). In SAS, \r\nthe numbers of flood events and human fatalities have increased \r\nin India during 1978-2006 (Singh and Kumar, 2013), whereas the \r\naverage country-wide inundation depth has been decreasing during \r\n2002-2010 in Bangladesh, attributed to improved flood management \r\n(low confidence) (Sciance and Nooner, 2018)."


id: c625cf27339aa43b9de6857b29023e4e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 28749
content:
"The counteracting factors of projected increases in precipitation and \r\ntemperature across most of Asia (Section  11.9 and Atlas.5) leads \r\nto low confidence (limited evidence, inconsistent trends) for broad, \r\nlong-term aridity changes with medium confidence only for aridity \r\nincreases in West Central Asia and East Asia. A  growing number \r\nof studies highlight the potential for more localized aridity trends, \r\nincluding projection ensembles indicating significant increase in \r\naridity and more frequent and intense droughts in most parts of "


id: da64593cd73c02290a52d20505d29a2c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 31884
content:
"Heavy precipitation and pluvial flood: Pluvial floods are driven \r\nby extreme precipitation and land use. Observed changes in extreme "


id: 8aa6b68e09102b0643384f6911280b40
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 19356
content:
"confidence) (Q. Sun et al., 2019). Abatzoglou et al. (2019) found that \r\nhigher fire weather conditions due to climate change emerge in the \r\nfirst part of the 21st century in South China, WCA as well as in boreal \r\nareas of Siberia and RFE. The potential burned areas in five Central \r\nAsian countries (Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan and \r\nTurkmenistan) will increase by 2-8% in the 2030s and 3-13% in the \r\n2080s compared with the baseline (medium confidence) (1971-2000; \r\nZong et al., 2020)."


id: 4bf09f28fdaab5f7a5336e1ee5744afe
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 9371
content:
"China (Y. Li et al., 2019; Yao et al., 2020) and India under RCP4.5 and \r\nRCP8.5 for the 2020-2100 period (Gupta and Jain, 2018; Bisht et al., \r\n2019; Preethi et al., 2019)."


id: 431b4a2800f14e991d2c6e6ef4f0e1a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 7956
content:
"In conclusion, there is medium confidence that extreme \r\nprecipitation, mean precipitation and river floods will increase \r\nacross most Asian regions. There is low confidence for projected \r\nchanges in aridity and drought given overall increases in \r\nprecipitation and regional inconsistencies, with medium \r\nincreases for West Central Asia and East Asia especially beyond \r\nthe middle of the century and global warming levels beyond 2degC. \r\nFire weather seasons are projected to lengthen and intensify \r\nparticularly in the northern regions (medium confidence)."


id: 8993879259c0495c560aac2739939df2
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 19180
content:
"Mean wind speed: There is high confidence of the slowdown in \r\nterrestrial near-surface wind speed (SWS) in Asia by approximately \r\n-0.1 m s-1 per decade since the 1950s based on observations and \r\nreanalysis data, with the significant decreases in Central Asia among \r\nthe highest in the world followed by EAS and SAS (J. Wu et al., 2018; \r\nTian et al., 2019; R. Zhang et al., 2019). But a short-term strengthening \r\nin SWS was observed during the winter since 2000 in eastern China \r\n(medium confidence) (Zeng et al., 2019; Zha et al., 2019). "


id: 9336900095749d119f9d0c02731a63fe
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 20674
content:
"Agricultural and ecological drought: Section 11.9 assesses medium \r\nconfidence in observed increases to agricultural and ecological \r\ndroughts in West Central Asia, East Central Asia, and East Asia. \r\nPersistent droughts were the main factor for grassland degradation \r\nand desertification in Central Asia in the early 21st century (G. Zhang \r\net al., 2018; Emadodin et al., 2019). Compound meteorological drought \r\nand heat events, which lead to water stress conditions for agricultural \r\nand ecological systems, have become more frequent, widespread \r\nand persistent in China especially since the late 1990s (Yu and Zhai, \r\n2020). There were more agricultural droughts in northern China than \r\nin southern China, and the intensity of agricultural drought increased \r\nduring 1951-2018 (Zhao et al., 2021)."


id: 64ede034a5d3bb37e6f16e733349a1c2
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 13448
content:
"There is medium confidence of future declining mean SWS in Asia, \r\nexcept in SAS and SEA, as global projections indicate a decreasing \r\ntrend in all climate scenarios for most of northern Asia, TIB and \r\nEast Asia by the mid-century (Karnauskas et  al., 2018a; Fedotova, \r\n2019; Jung and Schindler, 2019; Ohba, 2019; J. Wu et  al., 2020; \r\nZha et  al., 2020; Figure  12.4m-o), with negative effects on wind \r\nenergy potential. Decreases in North Asia are generally modest, not \r\nexceeding 10% for the mid-century and 20% for the end of century \r\nfor the RCP8.5 and RCP4.5 scenarios (Figure 12.4m-o)."


id: fc8e73fbe6172e6eb70790530d410b3
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 37253
content:
"Severe wind storms: Consistent with the general mean decreasing \r\nsurface winds, there is medium confidence that strong winds declined \r\nfaster than weak winds in the past few decades in Asia in general \r\n(Vautard et al., 2010; Tian et al., 2019), but evidence is lacking for \r\nspatial patterns. There is low confidence that extra-tropical cyclones \r\nwill decline in number in future climate scenarios over WCA, TIB, \r\nWSB and ESB, and intensify over the Arctic regions as a result of the \r\npoleward shift of storm tracks (Basu et al., 2018; Chapter 11). There is \r\nlimited evidence for projection of changes in severe winds occurring \r\nin convective storms in Asia."


id: e3caa7b0dcf2e12c1001bdc63d47d14e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 33317
content:
"Studies examining a 2degC GWL give low confidence for projected broad \r\nchanges to agricultural and ecological drought across all Asia regions, \r\nalthough at 4degC GWL agricultural and ecological drought increases are \r\nprojected for West Central Asia and East Asia along with a decrease in \r\nSouth Asia (medium confidence) (Section 11.9). Summer temperature \r\nincrease will enhance evapotranspiration, facilitating ecological and \r\nagricultural drought over Central Asia towards the latter half of this \r\ncentury (Chapter  11; see also Figure  12.4 for soil moisture and DF \r\nindices; Ozturk et al., 2017; Reyer et al., 2017b; Senatore et al., 2019). \r\nHowever, broader changes in droughts could not be determined in \r\nAsia due to the mixture of total precipitation signals together with \r\ntemperature increase patterns (Section 11.9 and Atlas.5)."


id: 1f30128a908ddb2b19fa42e1e7c914db
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 2345
content:
"Tropical cyclone: There was an increase in the number and \r\nintensification rate of intense tropical cyclones (TC), such as \r\nCategory 4-5 (wind speeds >58 m s-1), in the Western North Pacific \r\n(WNP) and Bay of Bengal since the mid-1980s (medium confidence) \r\n(Section  11.7; Kim et  al., 2016; Mei and Xie, 2016; Walsh et  al., \r\n2016a; Knutson et  al., 2019). There is medium confidence that "


id: 1b77faf719a8f179115149ca413063b0
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 1782
content:
"there has been a significant north-westward shift in TC tracks and \r\na poleward shift in the average latitude where TCs reach their peak \r\nintensity in the WNP since the 1980s (Knutson et al., 2019; J. Sun \r\net al., 2019; Lee et al., 2020), increasing exposure to TC passage and \r\nmore destructive landfall over eastern China, Japan, and Korea in the \r\nlast few decades (Kossin et al., 2016; Li et al., 2017; Altman et al., \r\n2018; Liu and Chan, 2019), and decreasing exposure in the region \r\nof SAS and southern China (Cinco et al., 2016; Kossin et al., 2016; \r\nsee Chapter 11). However, while the analysis shows fewer typhoons, \r\nmore extreme TCs have affected the Philippines (low confidence) \r\n(Takagi and Esteban, 2016). The frequency and duration of tropical \r\ncyclones has significantly increased over time over the Arabian \r\nSea and insignificantly decreased over the Bay of Bengal during \r\n1977-2018 (low confidence) (Fan et al., 2020)."


id: 91896bae79f6127024ccdbc6909b969
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Observations do show significant changes in the seasonal timing of \r\nEurasian snow cover extent (especially for earlier spring snowmelt) \r\nsince the 1970s, with seasonal changes expected to continue in the \r\nfuture (high confidence) (Yeo et al., 2017; Zhong et al., 2021). By 2100, \r\nsnowline elevations are projected to rise between 400  and 900 m \r\n(4.4  to 10.0 m yr-1) in the Indus, Ganges and Brahmaputra basins \r\nunder the RCP8.5 scenario (Viste and Sorteberg, 2015)."


id: c7e15f37ac0ba2ad27ba5805b98813
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 29028
content:
"Glacier: Observation and future projection of glacier mass changes \r\nin Asia are assessed in Section 9.5.1 grouped in three main regions: \r\nnorthern Asia, High Mountains of Asia, and Caucuses and Middle \r\nEast. All regions show continuing decline in glacier mass and area \r\nin the coming century (high confidence). Under RCP2.6 the pace of \r\nglacier loss slows, but glacier losses increase in RCP8.5 and peak \r\nin the mid to late 21st century. GlacierMIP projections indicate that \r\nglaciers in the High Mountains of Asia lose 42+-25%, 56+-24% and \r\n71+-21% of their 2015 mass by the end of the century for RCP2.6, \r\nRCP4.5 and RCP8.5 scenarios respectively. Under the same scenarios, \r\nglaciers in North Asia would lose 57+-40%, 72+-38% and 85+-30% \r\nof their mass, and glaciers in the Caucuses and the Middle East \r\nwould lose 68+-32%, 83+-19% and 94+-13% of their mass (see also \r\nKraaijenbrink et al., 2017; Rounce et al., 2020)."


id: 1af5a38297ec87c2e2f7a5d4eb6a832e
created_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 1713
content:
"There is medium confidence that future TC numbers will decrease but \r\nthe maximum TC wind intensities will increase in the western Pacific as \r\nelsewhere (Chapter 11, see Figure 11.24; Choi et al., 2019; Cha et al., \r\n2020; Knutson et al., 2020). The simulations for the late 21st century \r\nfor the RCP8.5 scenario yield considerably more TCs in the WNP that \r\nexceed 49.4 m s-1 (Category 3) intensity (Mclay et al., 2019). There is \r\nmedium confidence that the average location of the maximum wind \r\nwill migrate poleward (see Chapter 11), and TC translation speeds \r\nat the higher latitudes would decrease (Yamaguchi et al., 2020). As \r\na consequence, the intensity of TCs affecting the Japan Islands would \r\nincrease in the future under the RCP8.5 scenario (Yoshida et  al., \r\n2017), whereas the frequency of TCs affecting the Philippine region \r\nand Vietnam is projected to decrease (Kieu-Thi et al., 2016; C. Wang \r\net al., 2017; Gallo et al., 2019) (medium confidence)."


id: f1138002918b21c882d9e858194775ca
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 35427
content:
"Although enhanced meltwater from snow and glaciers largely offsets \r\nhydrological drought-like conditions (Pritchard, 2019), this effect is \r\nunsustainable and may reverse as these cryospheric buffers disappear \r\n(medium confidence) (Gan et al., 2015; W. Dong et al., 2018; Huss and \r\nHock, 2018). In the Himalayas and the TIB region higher temperatures \r\nwill lead to higher glacier melt rates and significant glacier shrinkage \r\nand a  summer runoff decrease (medium confidence) (Sorg et  al., \r\n2014). Glacier runoff in the Asian high mountains will increase up \r\nto mid-century, and after that runoff might decrease due to the loss \r\nof glacier storage (medium confidence) (Lutz et al., 2014; Huss and \r\nHock, 2018; Rounce et al., 2020)."


id: f9dfb60ffb55ca131cb12d40ffa62ee2
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Sand and dust storm: The Asia-Pacific region contributes \r\n26.8 per cent to global dust emissions as of 2012 (UNESCAP, 2018). \r\nIn West Asia, the frequency of dust events has increased markedly \r\nin some areas (east and north-east of Saudi Arabia, north-west of \r\nIraq and east of Syria) from 1980 to the present (Nabavi et al., 2016; \r\nAlobaidi et al., 2017). This marked dust increase has been associated \r\nwith drought conditions in the Fertile Crescent (Notaro et al., 2015; Yu \r\net al., 2015), likely amplified by anthropogenic warming (Kelley et al., \r\n2015; Chapter 10). Dust storm frequency in most regions of northern \r\nChina show a decreasing trend since the 1960s due to the decrease in \r\nsurface wind speed (medium confidence) (Guan et al., 2017)."


id: b4756587e48420c5f7071584dc3284d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Compared with the 1990s, the number of lakes in TIB in the 2010s \r\ndecreased by 2%, whereas total lake area expanded by 25% (S. Wang \r\net al., 2020) due to the joint effect of precipitation increase and glacier \r\nretreat. Many new lakes are predicted to form as a  consequence \r\nof continued glacier retreat in the Himalaya-Karakoram region \r\n(Linsbauer et al., 2016). As many of these lakes will develop at the \r\nimmediate foot of steep icy peaks with degrading permafrost and \r\ndecreasing slope stability, the risk of glacier lake outburst floods \r\nand floods from landslides into moraine-dammed lakes is increasing \r\nin Asian high mountains (high confidence) (Haeberli et  al., 2017; \r\nKapitsa et al., 2017; Bajracharya et al., 2018; Narama et al., 2018; \r\nS. Wang et al., 2020)."


id: a21e6711fc3fbadfb68c27d746e7db8e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"While dust activity has decreased greatly over EAS, current climate \r\nmodels are unable to reproduce the trends (Guan et al., 2015, 2017; \r\nZha et al., 2017; C. Wu et al., 2018). Thus, there is limited evidence for \r\nfuture trends of sand and dust storms in Asia."


id: d335a66398da394a494715ac3878b730
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 30756
content:
"In conclusion, surface wind speeds have been decreasing in \r\nAsia (high confidence), but there is a large uncertainty in future \r\ntrends. There is medium confidence that mean wind speeds will \r\ndecrease in Central and northern Asia, and that tropical cyclones \r\nwill have decreasing frequency and increasing intensity overall."


id: 3e14acffab183be1b977df4ebca0209d
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Permafrost: Permafrost is thawing in Asia (high confidence). \r\nTemperatures in the cold continuous permafrost of north-eastern \r\nEast Siberia rose from the 1980s up to 2017, and the active layer \r\nthicknesses in Siberia and Russian Far East generally increased \r\nfrom late 1990s to 2017 (Romanovsky et  al., 2018). The change \r\nin mean annual ground temperature for northern Siberia is about \r\n+0.1 to +0.3degC per decade since 2000 (Romanovsky et al., 2018). \r\nGround temperature in the permafrost regions of TIB (taking 40% \r\nof TIB currently) increased (0.02-0.26degC per decade for different "


id: a371a4afbb1afe748115dbc477728470
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23278
content:
"Snow: There is no significant interannual trend of total snow cover \r\nfrom 2000 to 2016 over Eurasia (X. Wang et al., 2017a; Sun et al., 2020). "


id: 256868eeff0fb8bb45d41def3e46301e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
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vector_id: 3310
content:
"In summary, snowpack and glaciers are projected to continue \r\ndecreasing and permafrost to continue thawing in Asia (high \r\nconfidence). There is medium confidence of increasing heavy \r\nsnowfall in some regions, but limited evidence on future \r\nchanges in hail and snow avalanches."


id: 8266ae96689422e37db8832e7712e729
created_at: 2023-03-16 14:00:50
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content:
"boreholes) during 1980 to 2018, and the active layer thickened at \r\na  rate of 19.5  cm per decade (L. Zhao et  al., 2020). There is high \r\nconfidence that permafrost in Asian high mountains will continue to \r\nthaw and the active layer thickness will increase (Bolch et al., 2019). \r\nThe permafrost area is projected to decline by 13.4-27.7% and \r\n60-90% in TIB (L. Zhao et al., 2020) and 32%+-11% and 76%+-12% \r\nin Russia (Guo and Wang, 2016) by the end of the 21st century under \r\nthe RCP2.6 and RCP8.5 scenarios respectively (high confidence)."


id: 12f20c82eb49dcd25fc1822cbfc70e1c
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 487
content:
"Lake and river ice: Lake ice cover duration got shorter in many lakes \r\nin TIB (Yao et al., 2016; Cai et al., 2019; Guo et al., 2020) and some \r\nother areas such as north-west China (Cai et al., 2020) and north-east \r\nChina (Yang et al., 2019) in the last two decades (high confidence). \r\nRiver ice cover extent decreased in TIB as well (H. Li et  al., 2020; \r\nYang et  al., 2020a). Climate warming also leads to a  significant \r\nreduction in the period with ice phenomena and the decrement \r\nof ice regime hazard in Russian lowland rivers (Agafonova et  al., \r\n2017), and the Inner Mongolia reach of the Yellow River in northern \r\nChina (Wan et  al., 2020) (high confidence). Lake ice and river ice \r\nin Asia are expected to decline with projected increases in surface \r\nair temperature towards the end of this century (high confidence) \r\n(Guo et al., 2020; Yang et al., 2020a)."


id: 775a7f593d11e8ded4ca7b975e1bd463
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Relative sea level rise is very likely to continue in the oceans around \r\nAsia. Regional mean RSLR projections for the oceans around Asia \r\nrange from 0.3-0.5 m under SSP1-2.6 to 0.7-0.8 m under SSP5-8.5 \r\nfor 2081-2100 relative to 1995-2014 (median values), which is \r\nwithin the range of projected GMSL change (Section 9.6.3.3). These \r\nRSLR projections may, however, be underestimated due to potential \r\npartial representation of land subsidence in their assessment \r\n(Section 9.6.3.2)."


id: e333913fc8b33460c65fadf139564430
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Coastal flood: The present-day 1-in-100-year ETWL is between \r\n0.5-8 m around Asia, with values above 2.5 m or above common \r\nalong the coasts of Central and north-eastern Asia (Vousdoukas et al., \r\n2018; Kirezci et  al., 2020). Sea level rise and land subsidence will \r\njointly lead to more flooding in delta areas in Asia (high confidence) \r\n(Takagi et al., 2016; J. Wang et al., 2018)."


id: bde22238e83a9f34125c28403f1cbf1b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Hail: The hailstorm in the Asian region shows a decreasing trend in \r\nseveral regions (low confidence, limited evidence). In China severe \r\nweather days including thunderstorms, hail and/or damaging wind \r\nhave decreased by 50% from 1961 to 2010 (M. Li et  al., 2016; \r\nZhang et al., 2017), and the hail size decreased since 1980 (Ni et al., \r\n2017). A  rate of decrease of 0.214 hail days per decade has also \r\nbeen reported for Mongolia between 1984-2013, where the annual \r\nnumber of hail days averaged is 0.74 (Lkhamjav et al., 2017)."


id: d7c0b84bb38b5acfc6cacf1dbcd57f95
created_at: 2023-03-16 14:00:50
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content:
"Extreme total water level magnitude and occurrence frequency \r\nare expected to increase throughout the region (high confidence) \r\n(Figure  12.4p-r and Figure  12.SM.6). Across the region, the 5-95th \r\npercentile range of the 1-in-100-year ETWL is projected to increase \r\n(relative to 1980-2014) by 7-44 cm and by 10-52 cm by 2050 under \r\nRCP4.5 and RCP8.5 respectively. By 2100, this range is projected to \r\nbe 11-91 cm and 28-187 cm under RCP4.5 and RCP8.5 respectively "


id: ab9a5d7917e4086bf195ea0991a79432
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 24520
content:
"Snow avalanche: There is as yet limited evidence for the evolution of \r\navalanches in Asia. Tree-ring-based snow avalanche reconstructions in \r\nthe Indian Himalayas show an increase in avalanche occurrence and \r\nrunout distances in recent decades (Ballesteros-Canovas et al., 2018)."


id: c0da44eba3d4d420d8430230f3b33df0
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 27908
content:
"mmary of confidence in direct\r\nve within each AR6 region (de\r\n of the assessment method). T\r\nRegion\r\na (ARP) \r\na (WCA) \r\nB) \r\n) \r\n(RFE) \r\n (ECA) \r\nTIB) \r\nSEA) \r\nsts and in the absence of addition"


id: bd0fccf7d451e55ef706ec84a6dcb956
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 27307
content:
"In general, there is high confidence that most coastal/ocean\u0002related climatic impact-drivers in Asia will increase over the \r\n21st century. Relative sea level rise is very likely to continue \r\naround Asia, contributing to increased coastal flooding in low\u0002lying areas (high confidence) and shoreline retreat along most \r\nsandy coasts (high confidence). Marine heatwaves are also \r\nexpected to increase around the region over the 21st century \r\n(high confidence)."


id: 632182659bdd1b490af306c53cd59523
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"(Vousdoukas et al., 2018; Kirezci et al., 2020). Furthermore, the present\u0002day 1-in-100-year ETWL is projected to have median return periods \r\nof around 1-in-50-years by 2050 and 1-in-10-years by 2100 under \r\nRCP4.5 in most of Asia, except SEA and ARP, in which the present-day \r\n1-in-100-year ETWL is projected occur once per year or more, both by \r\n2050 and 2100 (Vousdoukas et al., 2018). The present-day 1-in-50-year \r\nETWL is projected to occur around three times a year by 2100 with \r\na SLR of 1 m across Asia (Vitousek et al., 2017). Compound impacts \r\nof precipitation change, land subsidence, sea level rise, upstream \r\nhydropower development, and local water infrastructure development \r\nmay lead to larger flood extent and prolonged inundation in the \r\nVietnamese Mekong Delta (Triet et al., 2020)."


id: 584ca04d5e7b99d61d78690565e44748
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 11398
content:
"The assessed direction of change in climatic impact-drivers for Asia \r\nand associated confidence levels are illustrated in Table 12.4."


id: cf60df6f4fed334016eaeede685c063b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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"Coastal erosion: Over the past 30 years, South, South East and East \r\nAsia exhibit the most pronounced delta changes globally due to strong \r\nhuman-induced changes to the fluvial sediment flux (Nienhuis et al., \r\n2020). Satellite derived shoreline change estimates over 1984-2015 \r\nindicate shoreline retreat rates between 0.5  m  yr -1 and 1  m yr -1\r\nalong the coasts of WCA and ARP, increasing to 3 m yr-1 in SAS. Over \r\nthe same period, shoreline progradation has been observed along \r\nthe coasts of RFE (0.2 m yr-1), SEA (0.1 m yr-1) and EAS (0.5 m yr-1) \r\n(Luijendijk et  al., 2018; Mentaschi et  al., 2018). Meanwhile, there \r\nhas been a gross coastal area loss of 3,590 km2 in South Asia, and \r\na loss of 2,350 km2 in Pacific Asia, over a 30-year period (1984-2015) \r\n(Mentaschi et al., 2018)."


id: a18c664923ff93558da9b06f51105ce2
created_at: 2023-03-16 14:00:50
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content:
"For the purpose of this assessment, Australasia is divided into five \r\nsub-regions as defined in Section  1.4.5: Northern Australia (NAU), \r\nCentral Australia (CAU), Eastern Australia (EAU), Southern Australia \r\n(SAU) and New Zealand (NZ)."


id: d8e2852882b7a5141813024121a15e43
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"A detailed national scale climate change assessment of observed \r\nand projected climate change, based on over 40 CMIP5 models and \r\nhigh resolution downscaling (CSIRO and BOM, 2015), and biannual \r\nshort updates thereafter are available for Australia (CSIRO and BOM, \r\n2016, 2018, 2020). Similar national assessments for New Zealand are \r\nalso available (MfE and Stats NZ, 2017, 2020; MfE, 2018). The severe \r\nextreme events such as heatwaves and river floods that have occurred \r\nin Australasia, especially over the last decade, have enabled a number \r\nof attribution studies, improving the understanding of regional climate \r\nchange mechanisms that drive such extreme events (Chapter 11)."


id: e016a2845ae84dbc6cb76d576c7a7d3
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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content:
"Marine heatwave: There have been frequent marine heatwaves \r\n(MHW) in the coastal oceans of Asia, connected to the increase \r\nbetween 0.25degC and 1degC in mean SST of the coastal oceans since \r\n1982-1998 (Oliver et al., 2018). There is high confidence that MHWs \r\nwill increase around most of Asia. Mean SST is projected to increase \r\nby 1degC (2degC) around Asia by 2100, with a  hotspot of around 2degC \r\n(5degC) along the coastlines of the Sea of Japan and the RFE under \r\nRCP4.5 (RCP8.5; Interactive Atlas). Under global warming conditions, \r\nMHW intensity and duration are projected to increase in the coastal \r\nzones of all sub-regions of Asia, but most notably in SEA and SAS \r\n(Frolicher et al., 2018). Projections for SSP1-2.6 and SSP5-8.5 both \r\nshow an increase in MHWs around Asia by 2081-2100, relative to \r\n1985-2014 (Box 9.2, Figure 1)."


id: f74d347b2550de6bb3fc378411b6bb0b
created_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 36425
content:
"Figure  12.7 illustrates projected changes in two selected climatic \r\nimpact-driver indices for Australasia."


id: bbafb7086687fcf62d1c36c50b4dada7
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 27083
content:
"Mean air temperature: Across Australia mean temperatures have \r\nincreased by 1.44degC +- 0.24degC during the period 1910-2019, with \r\nmost of the warming occurring since 1950 (Atlas.6.2; CSIRO and \r\nBOM, 2020; Trewin et al., 2020). In New Zealand, an increase of 1.1degC \r\nhas been measured from 1909-2016 (Atlas.6.2; MfE and Stats NZ, "


id: b813d4cb75d0330f6da3191dda37a60e
created_at: 2023-03-16 14:00:50
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content:
"35degC under SSP5-8.5, which are consistent with the above assessed \r\nliterature and across the two CMIP generations, and indicate a strong \r\ndifference depending on the mitigation scenario (e.g., over 100 days \r\nmore per  year under  SSP5-8.5 in NAU, but, in general, less than \r\n60 days more per year under SSP1-2.6 in NAU; Figure 12.SM.1)."


id: 613fa1249ef6794627bf8a9f62aab13b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 12873
content:
"2020). In the period 1980-2014 a rate of increase of 0.1degC-0.3degC per \r\ndecade has been observed (Atlas.11 and Atlas.20)."


id: 300f489439b3b663a1758c3f0230d3e1
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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index: climate_gpt_only_giec
vector_id: 4990
content:
"The projected frequency of exceeding dangerous humid heat \r\nthresholds is increasing in Australia, with a  strong increase in \r\nNorthern Australia for RCP8.5 (high confidence) (Zhao et al., 2015; \r\nMora et  al., 2017; Brouillet and Joussaume, 2019), consistently \r\nacross CMIP5, CMIP6 and CORDEX simulations (Figure 12.4d-f and \r\nFigure  12.SM.2). Using the HI index, by end-century, the average \r\nnumber of days exceeding 41degC is projected to increase in NAU by \r\nabout 100 days and by about 25 days under SSP5-8.5 and SSP1-2.6, \r\nrespectively. The projections for New Zealand indicate no appreciable \r\nincrease in the number of days with HI > 41degC across SSPs, time \r\nperiods and CMIP generations (Figure 12.4d-f and Figure 12.SM.2)."


id: a9aeea2bb9612cd8bd56cb10f570259e
created_at: 2023-03-16 14:00:50
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"Cold spell and frost: Excepting parts of Southern Australia, the \r\nAustralasian region has a significant trend of decreasing frequency \r\nin cold extremes since the 1950s (high confidence) (Table  11.10) \r\nand there is high confidence that such trends are attributable \r\nto anthropogenic influence (Table  11.10). The number of frost \r\ndays per  year in Australia has on average declined at a  rate of \r\n0.15 days/decade in the past century (Alexander and Arblaster, 2017), \r\nexcept in some regions of Southern Australia, where an increase in \r\nboth number and season length has been reported (Dittus et  al., \r\n2014; Crimp et al., 2016b). The number of frost days has decreased \r\nat 12 of 30 monitoring sites around New Zealand over the period \r\n1972-2019 (MfE and Stats NZ, 2020)."


id: 9b1bc0d1c23eb9f3ddb592f7a78248ca
created_at: 2023-03-16 14:00:50
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"Less frequent cold extremes are virtually certain in Australasia \r\n(Table 11.10) while a decrease of frost days is projected with high \r\nconfidence for the region. Projections, relative to 1986-2005, for \r\nthe number of frost days per year in Australia indicate declines of \r\n0.9 days by mid-century and 1.1 days by end-century for RCP4.5, \r\nwhile for RCP8.5, the projected declines are 1.0 days and 1.3 days \r\nby mid- and end-century respectively (Alexander and Arblaster, 2017; \r\nHerold et al., 2018). Projections for New Zealand indicate that the \r\nnumber of frost days will decrease by 30% (RCP2.6) to 50% (RCP8.5) \r\nby 2040, relative to 1986-2005. By 2090, the decrease ranges from \r\n30% (RCP2.6) to 90% (RCP8.5) (MfE and Stats NZ, 2017)."


id: cad9f070ab79cbd50f3b12abd9e66913
created_at: 2023-03-16 14:00:50
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"In general, there is high confidence that most heat hazards in \r\nAustralasia will increase and that cold hazards will decrease \r\nover the 21st century. The mean temperature in Australasia is \r\nvirtually certain to continue to rise through the 21st century, \r\naccompanied by less frequent cold extremes (virtually \r\ncertain) and frost days (high confidence), and more frequent \r\nhot extremes (virtually certain). Heat stress is projected to \r\nincrease in Australia (high confidence)."


id: 713c14048050e2342e1241bcf33cc02e
created_at: 2023-03-16 14:00:50
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vector_id: 15451
content:
"Mean precipitation: Here, only increases in precipitation (under \r\n'Wet') are addressed, with decreases (under 'Dry') addressed in \r\n'Aridity' below."


id: ae7316c0e7e8d8334f7eb67378eda79f
created_at: 2023-03-16 14:00:50
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vector_id: 24975
content:
"In terms of wet climatic impact-drivers, detectable anthropogenic \r\nincreases in precipitation in Australia have been reported particularly \r\nfor north-central Australia for the period 1901-2010 (Knutson \r\nand Zeng, 2018). Figure Atlas.11 indicates no significant trend in \r\nprecipitation over the region during the baseline period 1960-2015, \r\nexcept for the Global Precipitation Climatology Project (GPCP) \r\ndataset, which shows an increasing trend in north-central Australia. \r\nIn New Zealand, increases in annual rainfall have been observed \r\nbetween 1960-2019 in the south and west of the South Island and \r\neast of the North Island. Note however, for the most part, the above \r\nreported trends in New Zealand have been classified as statistically \r\nnot significant (Figure Atlas.20)."


id: ac7adae4073d75d78099bb32fcbd1e7a
created_at: 2023-03-16 14:00:50
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vector_id: 24675
content:
"and 1-in-100-year flood peaks for rivers in many parts of the \r\ncountry may increase by 5 to 10% by 2050 and more by 2100 \r\n(with large variation between models and emissions scenarios), with \r\na  corresponding decrease in return periods for specific flood levels \r\n(Gray et al., 2005; Carey-Smith et al., 2010; McMillan et al., 2010, 2012; \r\nBallinger et al., 2011)."


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vector_id: 36433
content:
"Heavy precipitation and pluvial flood: Rainfall extremes have \r\nbeen detected to increase in Australasia, with low confidence\r\n(Table 11.10). There is high confidence that R x 1 day and R x 5 day \r\nprecipitation extremes will increase for 2degC or lower warming for the \r\nregion as a whole, but on a sub-regional basis there is only medium \r\nconfidence of increases in NAU and CAU and low confidence of \r\nincreases on EAU, SAU and NZ. For warming levels exceeding 2degC, \r\nthese extremes are very likely to increase in NAU and CAU and they \r\nare likely to increase elsewhere in the region (Section 11.9)."


id: 744a8859e1af66ea7f1cc78b1b7ee1ea
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 15893
content:
"Annual mean precipitation is projected to increase in Central and \r\nnorth-east Australia (low confidence) and in the south and west \r\nof New Zealand (medium confidence) (Atlas.6.4). Liu et al. (2018a) \r\nshow that under 1.5degC warming, Central and north-east Australia \r\nwill become wetter. Projected patterns in annual precipitation exhibit \r\nincreases in the west and south of New Zealand (Atlas.6.4; Liu et al., \r\n2018a) and project that the South Island will be wetter under both \r\n1.5degC and 2degC warming. However, there is limited model agreement \r\nfor projected rainfall changes in Australasia as shown in the Atlas."


id: 41ffede81e5d4658d1c069a0f0400a78
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 7784
content:
"Landslide: Based on local slope characteristics, lithology and seismic \r\nactivity, the South Island and the eastern half of the North Island of \r\nNew Zealand are vulnerable to landslide occurrence (Broeckx et al., \r\n2020). The potential for land and rockslides increases with, amongst \r\nother factors, total precipitation rates, precipitation intensity, \r\nmountain permafrost thaw rates, glacier retreat and air temperature \r\n(Crozier, 2010; Allen and Huggel, 2013; Gariano and Guzzetti, 2016; \r\nIPCC, 2019a). Given the increase of the magnitude of these physical \r\nvariables in areas that are already highly susceptible to mass \r\nmovements (MfE, 2018), there is low confidence that the occurrence \r\nof landslides will increase under future climate conditions."


id: 3e75b28db44b33a24ea3e144f70a846f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 7205
content:
"River flood: Streamflow observations in Australia have shown that \r\nnegative trends dominate in annual maximum flow and that stations \r\nwith significant negative trends were mostly located in the south-east \r\nand south-west (Gu et  al., 2020). The observed peak flow trend in \r\nSouthern Australia is attributed to the decrease of soil moisture, \r\nalthough an increase of flood magnitude is possible for very rare \r\nevents. For the more frequent flood events, the increase of extreme \r\nprecipitation is balanced by the decrease of soil moisture. (Wasko and \r\nNathan, 2019)."


id: a695bc4dc1abdc9e45761206a8bf62f7
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23734
content:
"Aridity: In terms of dry climatic impact-drivers, a substantial decrease \r\nin precipitation has been observed across Southern Australia during \r\nthe cool season (April-October) (medium confidence). The drying \r\ntrend has been particularly strong over south-west Western Australia \r\nbetween May and July, with rainfall since 1970 being around \r\n20% less than the 1900-1969 average (CSIRO and BOM, 2020). \r\nDetectable decreases in mean precipitation, attributable at least \r\nin part to anthropogenic forcing, have been reported for parts of \r\nsouth-west Australia (Delworth and Zeng, 2014; Knutson and Zeng, \r\n2018), south-east Australia, and Tasmania (Knutson and Zeng, 2018). \r\nIn New Zealand, the north-east of the South Island and western and \r\nthe northern parts of the North Island show decreasing precipitation \r\ntrends during 1960-2019 (MfE and Stats NZ, 2020)."


id: cc705fcb3ddcf76f582ece8c523daf40
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 29701
content:
"There is medium confidence that river flooding will increase in New \r\nZealand. Projections for New Zealand indicate that the 1-in-50-year "


id: fba9a8df5c95d3961b82e13631e4516f
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 37095
content:
"become drier (mainly in Southern Australia) under RCP8.5. Liu et al. \r\n(2018b) project that the North Island of New Zealand will be drier \r\nunder both 1.5degC and 2degC warming."


id: 7cc583a1042787c0748ab172859613f6
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 17228
content:
"increased at two monitored sites (MfE and Stats NZ, 2020). Due to \r\nthe intensification and the shift of the austral storm track by the \r\nend of the century (Yin, 2005), increases in extreme wind speed in \r\nNew Zealand are projected over the South Island and the southern \r\npart of the North Island by mid- and end-century for all RCPs (low \r\nconfidence) (MfE, 2018)."


id: 5d5d5d323fc786ab6c4bb16a5f8d7034
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 12211
content:
"Tropical cyclone: In Australia, the number of TCs has generally \r\ndeclined since 1982, and the frequency of intense TCs that make \r\nlandfall in north-eastern Australia has declined significantly since the \r\n19th century (medium confidence) (Kuleshov et al., 2010; Callaghan \r\nand Power, 2011; Holland and Bruyere, 2014; Knutson et al., 2019; \r\nCSIRO and BOM, 2020). There is high confidence that cyclones making \r\nlandfall along north-eastern and northern Australian coastlines will \r\ndecrease in number and low confidence of an increase in their \r\nintensities for 2degC of global warming as well as for the mid-century \r\nperiod with scenarios RCP4.5 and above (Roberts et al., 2015, 2020; \r\nBacmeister et al., 2018; Knutson et al., 2020), with the amplitude of \r\nchanges increasing from RCP4.5 to RCP8.5 (Bacmeister et al., 2018). \r\nDecreases in frequency are projected for 'east coast lows' (Walsh \r\net al., 2016b; Dowdy et al., 2019a)."


id: 249b34d9552f5a0a5a945df998beb239
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 3203
content:
"Sand and dust storm: Australia is recognized to be the largest dust \r\nsource in the Southern Hemisphere (Zheng et  al., 2016). Land-use \r\nand land-cover change have increased dust emissions in Australia \r\nin the past 200 years (Marx et al., 2014). While projections suggest \r\na decrease in severe winds in Central and Southern Australia, changes \r\nin vegetation due to increased aridity and hydrological drought could \r\nbe expected to result in increased wind erosion and dust emission \r\nacross the country (medium confidence) (Webb et al., 2020)."


id: 3669dbba9a05c52193c1716f559a54b9
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5953
content:
"Mean wind speed: There is low confidence of a mean wind speed \r\ntrend in the last decades (low agreement) (McVicar et  al., 2012; \r\nTroccoli et al., 2012; Azorin-Molina et al., 2018; J. Wu et al., 2018), as \r\nlong-term measurements are not homogeneous."


id: a5a1c52706bbe2f02ef4bcaa73c1d34b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 23628
content:
"In future climate scenarios wind speed trends in Australia exhibit \r\ngenerally weak amplitudes with low agreement among models \r\n(Figure 12.4m-o and Figure 12.SM.5) with uncertain consequences \r\non wind power potential (CSIRO and BOM, 2015; Karnauskas \r\net al., 2018a; Jung and Schindler, 2019). However, there is medium \r\nconfidence that, by the end of the century, annual mean wind power \r\nwill significantly increase in north-eastern Australia under RCP8.5, but \r\nthere is low confidence of an increase by end-century under RCP4.5, \r\nand for any scenario by mid-century (Karnauskas et al., 2018a). In \r\nNew Zealand, mean wind patterns are projected to become more \r\nnorth-easterly in summer, and westerlies to become more intense in \r\nwinter (low confidence), in agreement with the strengthening of the \r\nSouthern Hemisphere storm tracks (Section 4.5.1)."


id: 360fa4b11bcd9a7b0d362c98fc7346b8
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5910
content:
"In Australasia, there is low confidence in projected mean wind \r\nspeeds and wind power potential, with a medium confidence\r\nincrease projected only in north-eastern Australia under high \r\nemissions scenarios and by the end of the 21st century. Tropical \r\ncyclones in north-eastern and North Australia are projected to \r\ndecrease in number (high confidence) while their intensity is \r\nprojected to increase (low confidence)."


id: 4c0fa130e9ecd8a87db8e48cb6f6b95e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 9393
content:
"Snow: The snow season length in Australia has decreased by 5% \r\nduring 2000-2013 relative to 1954-1999, especially in spring \r\n(Pepler et al., 2015). A shift in the date of peak snowfall has also \r\nbeen observed with an 11-day advance over the same period (Pepler \r\net al., 2015). A decreasing trend in maximum snow depth has been \r\nobserved for Australian alpine regions since the late 1950s, with \r\nthe largest declines during spring and at lower altitudes. Maximum \r\nsnow depth is highly variable and is strongly influenced by rare heavy \r\nsnowfall days, which have no observed trends in frequency (CSIRO \r\nand BOM, 2020). "


id: 20518f280c3051931f15dbf2dc877d5
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 2536
content:
"Severe wind storm: There is generally low confidence in observed \r\nchanges in extreme winds and extratropical storms in Australasia \r\n(Section 11.7.2). CMIP5 projections of severe winds indicate a general \r\nincrease in north-eastern Australia, and decreases in some parts \r\nin Southern and Central Australia (medium confidence) by the end \r\nof the century under RCP8.5 (CSIRO and BOM, 2015; Kumar et al., \r\n2015; Jung and Schindler, 2019). Elsewhere trends are diverse and \r\nvary across simulations with low agreement. Projections of changes \r\nin the 1-in-25-year return period winds (based on annual maxima) \r\nfor 2074-2100 relative to 1979-2005 for RCP8.5 show an increase in \r\ntropical areas of Northern Australia (Kumar et al., 2015)."


id: baae1f51b877a2f33dbb3ac20e673450
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 26911
content:
"Projections for Southern Australia and New Zealand show a continuing \r\nreduction in snowfall during the 21st  century (high confidence). \r\nThe magnitude of decrease varies with the altitude of the region and \r\nthe emissions scenario. At elevations lower than 1500 m, years without \r\nsnowfall are projected from 2030 in some models. By 2090, and under "


id: 850a6792e544aae2b48069636e8d39e1
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 18452
content:
"under RCP4.5 and RCP8.5 respectively (Figure  12.4q). By 2100 \r\n(Figure 12.4p,r), this range is projected to be 25-80 cm and 50-190 cm \r\nunder RCP4.5 and RCP8.5 respectively (Vousdoukas et  al., 2018; \r\nKirezci et al., 2020). Furthermore, the present-day 1-in-100-year ETWL \r\nis projected to have median return periods of around 1-in-20-years by \r\n2050 and 1-in-1-year by 2100 in SAU and NZ and return periods of \r\naround 1-in-50-years by 2050 and 1-in-20-years by 2100 in NAU under \r\nRCP4.5 (Vousdoukas et al., 2018), while the present-day 1-in-50-year \r\nETWL is projected to occur around three times a year by 2100 with \r\na SLR of 1 m around Australasia (Vitousek et al., 2017)."


id: 705135b261d3016a9c607b96a8d48ed3
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 15287
content:
"RCP8.5, such years are projected to become common (CSIRO and BOM, \r\n2015). The number of annual snow days in New Zealand is projected \r\nto decrease under all RCPs, by up to 30 days or more by 2090 under \r\nRCP8.5, relative to 1986-2005 (MfE, 2018)."


id: 70b61395c7fea0a978278087dcbb075e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 15355
content:
"Glacier: Glacier mass and areal extent in New Zealand is projected \r\nto continue to decease over the 21st  century (high confidence) \r\n(Section 9.5.1.3). Glacier ice volume from 1977-2018 in New Zealand \r\nhas decreased from 26.6 to 17.9 km3 (a loss of 33%; Salinger et al., \r\n2019). Relative to 2015, glaciers in New Zealand are projected to \r\nlose 36+-44%, 53+-33% and 77+-27% of their mass by the end of \r\nthe century under RCP2.6, RCP4.5 and RCP8.5 respectively, with the \r\nloss rates decreasing over time under RCP2.6 and increasing under \r\nRCP8.5 (Marzeion et al., 2020)."


id: efb2d59d72b2601f49499c5638f65ee4
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 35210
content:
"Coastal erosion: Satellite derived shoreline retreat rates for \r\nthe period between 1984-2015 show retreat rates between \r\n0.5 and 1 m yr-1 around the region, except in SAU where a shoreline \r\nprogradation rate of 0.1 m yr-1 has been observed (Luijendijk et al., \r\n2018; Mentaschi et al., 2018). Mentaschi et al. (2018) report a coastal \r\narea loss of 350 km2 over the same period in Western Australia from \r\nsatellite observations."


id: 1a42f51915dcfed79d8b506edf03e621
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 1597
content:
"In summary, snowfall is expected to decrease throughout the \r\nregion at high altitudes in both Australia (high confidence) \r\nand New Zealand (medium confidence). In New Zealand, \r\nglacier ice mass and extent are expected to decrease over the \r\n21st century for all scenarios (high confidence)."


id: 9cfcddf7436d7926d312b8638f25f84b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 22239
content:
"Relative sea level: Around Australasia, from 1900-2018, a  new \r\ntide gauge-based reconstruction finds a regional mean RSL change \r\nof 1.33 [0.80 to 1.86]  mm yr -1 in the Indian Ocean-South Pacific \r\nregion (Frederikse et  al., 2020), compared to a  GMSL change of \r\naround 1.7 mm yr-1 (Section 2.3.3.3 and Table 9.5). For the period \r\n1993-2018, the RSLR rates, based on satellite altimetry, increased \r\nto 3.65 [3.23 to 4.08] mm yr -1 (Frederikse et al., 2020), compared to \r\na GMSL change of 3.25 mm yr-1 (Section 2.3.3.3 and Table 9.5)."


id: 3281b3f62f8f8907beaf789d142538e5
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5362
content:
"Relative sea level is virtually certain to increase throughout the region \r\nover the 21st century (Section 9.6.3, Figure 9.28). Regional mean RSLR \r\nprojections for the oceans around Australasia range from 0.4-0.5 m \r\nunder SSP1-2.6 to 0.7-0.9 m under SSP5-8.5 for 2081-2100 relative to \r\n1995-2014 (median values), which means local RSL change falls within \r\nthe range of mean projected GMSL change (Section 9.6.3.1). However \r\nthese RSLR projections may be underestimated due to potential partial \r\nrepresentation of land subsidence (Section 9.6.3.2)."


id: fc69b6fada356b1287ff32a246d5a110
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 37220
content:
"Distinct from long-term coastline recession, storms and storm surges \r\nalso result in episodic coastal erosion. In general, the historically \r\nmeasured maximum episodic coastal erosion (either eroded volume \r\nor coastline retreat distance) or that due to a 1-in-100-year return \r\nperiod storm wave height is used as a design criterion for coastal \r\nzone management and planning in Australia (Wainwright et  al., \r\n2014; Mortlock et al., 2017)."


id: f2598c869d3a8006b0c471a9dd66d012
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 35657
content:
"Coastal flood: The most commonly used index for episodic coastal \r\ninundation in Australia is the summation of a  high end SLR and \r\nthe 1-in-100-year storm tide level (the combined sea level due to \r\nstorm surge and tide) (CSIRO and BOM, 2016; McInnes et al., 2016). \r\nHowever, episodic coastal flooding is caused by extreme total water \r\nlevels (ETWL), which is the combination of SLR, tides, surge and \r\nwave setup (Section 12.3.5.2). The present-day 1-in-100-year ETWL \r\nis between 0.5-2.5 m around most of Australia, except the north\u0002western coast where 1-in-100-year ETWL can be as large as 6-7 m \r\n(Vousdoukas et al., 2018; O'Grady et al., 2019; Kirezci et al., 2020)."


id: 64919f6111f099bd9ccf4afcd6876535
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 13390
content:
"While there is wide recognition in Australia that the combined \r\neffect of SLR, changing storm surge and wave climates will directly \r\naffect  future episodic coastal erosion (McInnes et  al., 2016; \r\nRanasinghe, 2016; Harley et al., 2017) only a few projections of how \r\nthis hazard may evolve are available for Australia. In one such study, \r\nJongejan et al. (2016) provide projections of how the full exceedance \r\nprobability curve of the maximum erosion per year may evolve over \r\nthe 21st century (due to the combined action of SLR, storm surge \r\nand storm waves). Their results show that, for example, the 0.01 \r\nexceedance probability maximum coastline retreat in 2025 will have \r\nan exceedance probability of 0.015 by 2050 and 0.07 by 2100."


id: edc1c04c336e36ff5dc096cbc9b6357a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 34868
content:
"Extreme total water level magnitude and occurrence frequency \r\nare expected to increase throughout the region (high confidence) \r\n(Figure 12.4p-r and Figure 12.SM.6). Across the region, the 5-95th \r\npercentile range of the 1-in-100-year ETWL is projected increase \r\n(relative to 1980-2014) by 5-35 cm and by 10-40 cm by 2050 "


id: 5d40b0ac75b75b2fb682ac449ce698a3
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 12184
content:
"Central America (SCA), North-Western South America (NWS), Northern \r\nSouth America (NSA), South American Monsoon (SAM), North-Eastern \r\nSouth America (NES), South-Western South America (SWS), South\u0002Eastern South America (SES) and Southern South America (SSA). \r\nThe Caribbean is placed under the Small Islands section (12.4.7) of \r\nthis chapter."


id: 365cc0db7e578e90d6c2a4d935d91ca1
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 5945
content:
"New literature is now available for the regional climate as a result \r\nof observational research and coordinated modelling outputs of \r\nCORDEX South America (Solman, 2013; Sanchez et  al., 2015) and \r\nCORDEX-CORE (Giorgi et al., 2018; Coppola et al., 2021b; Teichmann \r\net al., 2021). Of particular interest are the new projections of both \r\nmean climate and extremes. This new regional climate information is \r\nkey to main sectors sensitive to climate change in Central and South \r\nAmerica such as water resources, infrastructure, agriculture, livestock, \r\nforestry, silviculture and fisheries (Magrin, 2015; Lopez Feldman \r\nand Hernandez Cortes, 2016), human health (changes in morbidity \r\nand mortality, and emergence of diseases in previously non-endemic \r\nareas; Nunez et  al., 2016) and biodiversity (Uribe Botero, 2015), \r\nurban planning, navigation and tourism."


id: 14810285255f77246aaafbbbaca4719b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 736
content:
"In general, there is high confidence that most coastal/ocean\u0002related hazards in Australasia will increase over the 21st century. \r\nRelative sea level rise is virtually certain to continue in the \r\noceans around Australasia, contributing to increased coastal \r\nflooding in low-lying areas (high confidence) and shoreline \r\nretreat along most sandy coasts (high confidence). Marine \r\nheatwaves are also expected to increase around the region \r\nover the 21st century (high confidence)."


id: 3ded9e0c42a4a41f17f9f1a11e5febfd
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 7103
content:
"The assessed direction of change in climatic impact-drivers for \r\nAustralasia and associated confidence levels are illustrated in \r\nTable 12.5, together with emergence time information (Section 12.5.2). \r\nNo assessable literature could be found for hail and snow avalanches, \r\nalthough these phenomena may be relevant in parts of the region."


id: f987b9910462350d2843ad263e3f65a5
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 36777
content:
"(high confidence) (Atlas.7.2.5) and the well-known dipole for \r\nSouth America, meaning increasing precipitation over subtropical \r\nregions like the Rio de La  Plata basin (SES) (high confidence) and \r\ndecreasing precipitation in the Amazon (NSA) (medium confidence) \r\n(Chou et al., 2014; Llopart et al., 2014; Reboita et al., 2014; Sanchez \r\net al., 2015; Teichmann et al., 2021). These features are consistent \r\nwith observations (Sena et al., 2018) and are evident in regional and \r\nglobal model projections by mid- and end-of-century for both RCP4.5 \r\nand RCP8.5 (Jones and Carvalho, 2013)."


id: 4a974527d85b80fb657dd492bb56b108
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 9137
content:
"Cold spell and frost: A decreasing frequency of cold days and nights \r\nhas been observed in many sub-regions (Table 11.13). There is medium \r\nconfidence (limited agreement) of a decrease in frost days in SWS, SES \r\nand SSA. Projections consistently suggest a  general decrease in the \r\nfrequency of cold spells and frost days in the region as indicated by \r\nseveral indices based on minimum temperature (Chou et  al., 2014; \r\nLopez-Franca et al., 2016; C. Li et al., 2021). Heating degree days are \r\nconsistently projected to decrease by 5 degree days per year in the \r\nAmazon region, and up to 20-30 degree days per year in NWS, SWS \r\nand SES, under RCP8.5/SSP5-8.5 by mid century (Coppola et al., 2021b)."


id: acf7d787d7e1487db886eb3b2021c16e
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 24761
content:
"In conclusion, it is virtually certain that warming will continue \r\neverywhere in Central and South America and there is high \r\nconfidence that by the end of the century most regions will \r\nundergo extreme heat stress conditions much more often than \r\nin recent past (e.g., increase of dangerous heat with HI > 41degC, \r\nor Tx > 35degC) with more than 200 additional days per year \r\nunder SSP5-8.5, while such conditions will be met typically \r\n50-100 more days per year under SSP1-2.6 over the same \r\nregions. Cold spells and frost days will have a decreasing trend \r\n(high confidence)."


id: 50614e9945e1400c3c66a6b3f86beae2
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 10092
content:
"Available projections for the region show increases in river floods in \r\nSES and SAM (medium confidence). Projections indicate that SES and \r\nthe coasts of Ecuador and Peru will experience a tendency towards \r\nwetter conditions that can be a proxy for longer periods of flooding \r\nand enhanced river discharges (Zaninelli et al., 2019). CORDEX models \r\nproject the strongest changes for the peak flow with a return period \r\nof 100 years in SES by mid-century and under RCP8.5 (Figure 12.8). At \r\nthe continental scale, on the contrary, Alfieri et al. (2017) suggest that \r\n100-year river floods will decrease under RCP8.5. Regional projections \r\nof river floods have high uncertainty, however, owing to differences in "


id: dd5166715c0098f55f96c7dc1c2fd2b
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
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vector_id: 32313
content:
"Mean precipitation: The Atlas documents diverse historical \r\nprecipitation trends in the region, including a  small but not \r\nsignificant increasing trend in SCA, a  decreasing trend in south\u0002eastern and north-eastern Brazil, and an increasing trend in SSA. \r\nProjections indicate a  drying signal for SCA (medium confidence) \r\n(Coppola et  al., 2014a; Nakaegawa et  al., 2014), NES and SWS "


id: 358f92a1c109ec0b4e3b80017cd69820
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 5835
content:
"hydrological models (low confidence) (Reyer et al., 2017a). Fabrega \r\net al. (2013) projected increases in surface runoff for Panama, while \r\nZulkafli et al. (2016) identified increases in 100-year floods of 7.5 and \r\n12.0% in projections for the Peruvian Amazon wet season under RCPs \r\n4.5 and 8.5 respectively. Wetter conditions and +-20% variations in \r\nannual mean streamflow are also projected for the Rio de La Plata \r\nunder the warming levels of 1.5degC, 2degC and 3degC above pre-industrial \r\nconditions (Montroull et al., 2018). In central Chile, 50-year peak flows \r\nare expected to be greater by mid-century than 100-year peak flows \r\nobserved over the reference period (Bozkurt et al., 2018)."


id: 31c6c7e7670c968e91988a2af12f0d9a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
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vector_id: 5240
content:
"Llopart et  al., 2014; Atlas.7). Seasonal changes are also projected \r\nby end century under RCP 8.5, with decreases in June-July-August \r\n(JJA) rainfall projected for NSA, the coastal region of SES, SAM and \r\nthe southern portion of SWS (Marengo et  al., 2016). Decreases in \r\nDecember -January-February (DJF) rainfall are projected for the \r\ncentral part of South America in the near term (Kitoh et al., 2011; \r\nChou et al., 2014; Cabre et al., 2016). Regional projections for Central \r\nand South America also indicate an increase in dryness in SCA and \r\nNES by mid- to end-century (medium confidence) (Chou et al., 2014; \r\nMarengo and Bernasconi, 2015)."


id: 4822be19846e54c88d621554dd595844
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
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vector_id: 8722
content:
"Heavy precipitation and pluvial flood: Table  11.14 indicated \r\nthat there is low confidence due to limited evidence of extreme \r\nprecipitation trends in almost all Central and South America, except \r\nin SES where increases in the magnitude and frequency of heavy \r\nprecipitation have been observed (high confidence). In general, \r\ndata scarcity persists for a  representative continental assessment. \r\nChapter 11 projections indicate low confidence of increase, compared \r\nto the modern period, in the intensity and frequency of heavy \r\nprecipitation in SCA and SWS for all GWLs, and medium confidence\r\nof increase in NSA, NES, SSA, SAM and SES for GWL of 4degC. In NWS, \r\na wide range of changes is projected (low confidence)."


id: f9fbabb138bd2c44e37826046de42437
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
index: climate_gpt_only_giec
vector_id: 36837
content:
"Hydrological drought: Chapter 11 assessed mostly low confidence\r\nin observed changes in hydrological droughts given a lack of studies \r\nand clear evidence, with medium confidence only for a streamflow \r\ndecrease in sub-regions of SWS (Table 11.15). Some trends are \r\nbecoming more clear, such as the ones reported for Colombia (NWS) \r\nby Carmona and Poveda (2014), who indicated that 62% of the 25- \r\nto 50-year-long monthly average streamflow time series exhibited \r\nsignificant decreasing trends. However, studies of discharge changes \r\nindicate that uncertainty is still large, as argued by Pabon-Caicedo \r\net al. (2020) for the full extent of the Andes."


id: af8a638e4eb6f6292e7dd9c04af7fe91
created_at: 2023-03-16 14:00:50
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content_type: text
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vector_id: 25134
content:
"A number of studies project decreases in runoff and river discharge \r\nfor SCA, Colombia, Brazil and the southern part of South America \r\nby the end of this century (Nakaegawa and Vergara, 2010; Arnell \r\nand Gosling, 2013; van Vliet et al., 2013). Section 11.9 assessed high \r\nconfidence in projections of increases in hydrological droughts in \r\nNSA, SAM, SWS, and SSA under for 4degC GWL, medium confidence\r\nin SCA, and low confidence in the rest of the sub-regions given \r\ninsufficient evidence, lack of signal or mixed signals among the \r\navailable studies. Signals are much more uncertain for the middle of \r\nthe century (or for a 2degC GWL)."


id: 5ca05823d58d6450d05e4b0e550ee672
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
content_type: text
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vector_id: 12090
content:
"Landslide: Several regions in Central America, as well as Colombia \r\nand south-eastern Brazil, are considered areas of high incidence of \r\nobserved fatal landslides. In these areas, El Nino-Southern Oscillation \r\n(ENSO)-driven fluctuations in rainfall amounts (Sepulveda and Petley, \r\n2015) and climate change (Nehren et  al., 2019) seem to be key \r\nfactors. Rockfalls, ice- and rock-ice avalanches, lahars and landslides \r\nhave been reported frequently in the southern, extratropical Andes \r\nin the last decades (Gariano and Guzzetti, 2016). A large number of \r\nice- and moraine-dammed lakes have consequently failed, causing \r\nfloods that rank amongst the largest events ever recorded (Iribarren \r\nAnacona et al., 2015). However, published literature is largely missing \r\nfor a reliable assessment of past and future trends of such hazards."


id: 1efb4500ecf60814c48f25d23f38eab0
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 2314
content:
"Agricultural and ecological drought: Section  11.9 assessed low \r\nconfidence in observed changes in agricultural and ecological drought \r\nacross Central and South America due to regional heterogeneity \r\nand differences depending on the drought metrics used, except \r\nin NES, which has seen a  dominant increase in drought severity \r\n(medium confidence)."


id: d2307827c85e0a24acd92f776ce3e83a
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 30599
content:
"Aridity: Several regional studies suggest increasing trends in the \r\nfrequency and length of droughts in the region, such as: over NWS \r\n(Dominguez-Castro et al., 2018), NSA (Marengo and Espinoza, 2016; \r\nCunha et al., 2019) and NES (Marengo and Bernasconi, 2015), over \r\nsouthern Amazonia (Fu et al., 2013; Boisier et al., 2015), in the Sao \r\nFrancisco River basin and the capital city Distrito Federal in Brazil \r\n(Borges et  al., 2018; Bezerra et  al., 2019), in the southern Andes \r\n(Vera and Diaz, 2015), in central southern Chile (Boisier et al., 2018), \r\nin SES (Rivera and Penalba, 2014) and, during recent years, in SSA \r\n(Rivera and Penalba, 2014). Chapter 8 indicated medium confidence\r\nof anthropogenic forcing on observed drying trends in central Chile. \r\nAdditional discussion on droughts and aridity trends in South America \r\nis presented in Sections 8.3.1.6, 8.4.1.6 and 8.6.2.1."


id: a837db7c1d4335d958242445d1d1d049
created_at: 2023-03-16 14:00:50
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vector_id: 23985
content:
"Sections 8.3.2.4 and 8.4.1.6 point to two important drying hotspots in \r\nSouth America with long-term soil moisture decline and precipitation \r\ndeclines: the Amazon basin (SAM and NSA) and SWS (medium \r\nconfidence) (Figure  12.4). End-of-century RCP8.5 projections \r\nshow a  longer dry season in the central part of South America \r\nand decreased precipitation over the Amazon and central Brazil \r\n(Teichmann et al., 2013; Coppola et al., 2014a; Giorgi et al., 2014; "


id: a2ec09061c0b78407195a3021cef7f28
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 23201
content:
"Severe wind storm: Similar observational limitations inhibit an \r\nassessment of long-term extreme wind trends. However, Pes et  al. \r\n(2017) found extreme wind increases in most of Brazil over the past \r\ndecades. Future projections indicate a slight decrease in the number \r\nof extratropical cyclones in mid-latitudes (limited evidence, low \r\nconfidence) (Reboita et al., 2018), and an increase of extreme winds in \r\ntropical areas (limited evidence, low confidence) (Kumar et al., 2015). \r\nClimate models project a shift and an intensification of southern storm \r\ntracks, with most effects offshore over the Southern Ocean (Chapter 4), \r\nwith low confidence (low agreement) of significant extreme wind \r\nchanges over land and coastal areas across the 21st century (Chang, \r\n2017; Augusto Sanabria and Carril, 2018; Reboita et al., 2021)."


id: a4c87e05bccac5702059da1359baf251
created_at: 2023-03-16 14:00:50
updated_at: 2023-03-16 14:00:50
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vector_id: 23502
content:
"occurrence of extended droughts, such as the recently experienced \r\n2010-2015 megadrought (which is still driving impacts), is projected \r\nto increase from one to up to five events per 100 years under RCP8.5 \r\n(Bozkurt et al., 2018). Section 11.9 highlights change in confidence \r\nin increases in drought severity in SCA, NSA, NES, SAM, SWS, and \r\nSSA from low to high under the three GWLs of 1.5degC, 2degC and 4degC. \r\nNES and SES change from low confidence to medium confidence\r\nincreases in agricultural and ecological drought severity by 4degC GWL \r\nwith different metrics and high agreement between studies. Only \r\nSAM and SSA have projections of agricultural and ecological drought \r\nincreasing with high confidence for the middle of the century, or for \r\na 2degC GWL, and NSA, NES and SCA are projected to increase with \r\nmedium confidence."


id: 358d9eeeb3b96d2a9408fca3a41794f5
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 5833
content:
"Tropical cyclone: CMIP5 and CMIP6 simulations, including the \r\nnew High Resolution Model Intercomparison Project (HighResMIP), \r\nproject a decrease in the frequency of tropical cyclones in the Atlantic \r\nand Pacific coasts of Central America for the mid-century or under \r\na  2degC GWL, accompanied with an increased frequency of intense \r\ncyclones (medium confidence) (Section 11.7.1.5; Diro et  al., 2014; \r\nKnutson et al., 2020; Roberts et al., 2020)."


id: 9f9b85862dec0c4ab71bb7fa7b5c261f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 22652
content:
"In summary, there is limited evidence of current trends in \r\nobserved wind speed and wind storms in Central and South \r\nAmerica. Climate projections indicate a decrease in frequency \r\nof tropical cyclones in Central America accompanied with an \r\nincreased frequency of intense cyclones, and an increase in \r\nmean wind speed and wind power potential in most parts of \r\nCentral and South America (medium confidence)."


id: a3fe79d92aea0ecf8ae74effd8f3dd7
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 23356
content:
"Mean precipitation is projected to change in a dipole pattern \r\nwith increases in NWS and SES and decreases in NES and \r\nSWS (high confidence) with further decreases in NSA \r\nand SCA (medium confidence). There is medium confidence\r\nof an increase in river floods in SAM and SES. There is high \r\nconfidence of an increase in drought duration in NES, an in \r\nthe number of dry days and drought frequency in NSA and \r\nSAM. Dry climatic impact-drivers are projected to increase \r\nat the regional level with higher global warming levels. \r\nThe strongest signal of future increase in agricultural and \r\necological drought, aridity and fire weather is over the \r\nAmazon region (high confidence). "


id: 354d7e1c3383948a71796335193531e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 5797
content:
"Mean wind speed: Due to the lack of long-term homogeneous \r\nrecords or limited observations in the region, past wind speed trends \r\nare difficult to establish. Global climate models project an increase \r\nin wind speeds, under all future scenarios, augmenting wind power \r\npotential in most parts of Central and South America, especially in \r\nNES, where changes lie in the range 0-20% by 2050 under RCP8.5 \r\nand 0-40% under RCP8.5 (medium confidence) (Karnauskas \r\net  al., 2018a; Reboita et  al., 2018; Jung and Schindler, 2019). In \r\nPatagonia, wind speeds are projected to decrease. For RCP4.5 \r\nchanges remain marginal and have low confidence (low agreement) \r\n(Figure 12.4m-o)."


id: 2fc11bfcf3813fd3cb1c7c13e8e5fa7a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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content:
"Glacier: Observation and future projection of Central and South \r\nAmerica glacier mass changes are assessed in Section 9.5.1, grouped \r\nin two main regions: Low Latitude region (98% of which is glaciers in \r\nthe Andes) and the Southern Andes region. An increase in the number \r\nand areal extent of glacial lakes in the Southern Andes was reported \r\nfor the period 1986-2016 (Wilson et al., 2018). Similar changes are \r\nbeing observed in the central Andes (Colonia et al., 2017). Since 1800 \r\nat least 15 ice-dammed lakes and 16 moraine-dammed lakes have \r\nfailed in the extratropical Andes, causing high-magnitude glacial lake "


id: 615242b1560d7b36e430ce7c94fe42d8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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content:
"outburst floods (Rojas et al., 2014; Cook et al., 2016; Wilson et al., \r\n2018; Drenkhan et al., 2019). Partially due to glacier shrinkage and \r\nlake growth, the frequency of outburst floods has increased in the \r\nlast 30-40 years (Carey et al., 2012; Iribarren Anacona et al., 2015)."


id: 35d481e0b9af2593c263a6aa465b0e99
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 5882
content:
"be underestimated due to potential partial representation of land \r\nsubsidence in their assessment (Section 9.6.3.2)."


id: f70d97bd6b2d3bdc98be1d0394719849
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 36378
content:
"Glaciers across South America are expected to continue to lose \r\nmass and glacier area in the coming century (high confidence) \r\n(Section  9.5). In terms of their mass, glaciers in the Low Latitude \r\nregion are projected by GlacierMIP to lose 67 +- 42%, 86 +- 24% and \r\n94 +- 13%, of their 2015 baseline mass by the end of the century \r\nunder RCP2.6, RCP4.5 and RCP8.5 respectively (Marzeion et  al., \r\n2020). Glaciers in the Southern Andes show decreasing mass loss \r\nrates for RCP2.6, and increasing rates for RCP8.5, which peak in the \r\nmid to late 21st century. Glaciers in the Southern Andes are projected \r\nto lose 26+-27%, 33+-26% and 47+-26% of their 2015 mass by the \r\nend of the century under RCP2.6, RCP4.5 and RCP8.5 respectively \r\n(Section 9.5.1.3)."


id: 91c36bea77bfed941e12aa398207174c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 20470
content:
"The central Andes will experience the highest disturbance to the thermal \r\nregime of the 21st  century. As a  consequence, in the Argentinean \r\nAndes up to 95% of rock glaciers in the southern desert Andes and \r\nin the central Andes will rest in areas above 0degC under the worst case \r\nscenario of warming (the freezing level might move up more than twice \r\nas much as during the entire Holocene; Drewes et al., 2018)"


id: 78eb3c61bc3eb097193ea1b776dedfbf
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 16578
content:
"Coastal erosion: According to satellite data, shoreline retreat rates \r\nof around 1 m yr-1 have been observed along the sandy coasts \r\nof SCA, SES and SSA over the period 1984-2015, while shoreline \r\nprogradation rates of around 0.25 m yr-1 has been observed in \r\nNWS and NSA. The sandy shorelines in NES and SWS have remained \r\nmore or less stable over the same period (Luijendijk et  al., 2018; \r\nMentaschi et  al., 2018). Using satellite observations, Mentaschi \r\net al. (2018) report a coastal area loss of 250 km2 over a 30-year \r\nperiod (1984-2015) along the Pacific coast of South America, and of \r\n780 km2 along the Atlantic coastlines."


id: 9712333fcab05e83a7f1571ae7c9299c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 21284
content:
"Permafrost: There is limited information on the ongoing changes \r\nand projections of permafrost conditions in the region. Based on \r\nmodel projections under the IPCC A1B scenario, permafrost areas in \r\nthe Bolivian Andes will eventually be lost, but this could take years \r\nto decades or longer depending on permafrost thickness (Rangecroft \r\net al., 2016). "


id: 113d7f63fbdbf86cd550f86bbf22772d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 189
content:
"In conclusion, glacier volume loss and permafrost thawing will \r\ncontinue in the Andes Cordillera under all climate scenarios \r\n(high confidence), causing important reductions in river flow \r\nand potentially high-magnitude glacial lake outburst floods."


id: 622254b68fbccdba521a84753e8fe0c5
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 12994
content:
"Relative sea level: Around Central and South America, over \r\n1900-2018, a new tide gauge-based reconstruction finds a regional \r\nmean relative sea level (RSL) change of 2.07 [1.36 to 2.77] mm yr-1 in \r\nthe South Atlantic, 2.49 [1.89 to 3.06] mm yr-1 in the subtropical North \r\nAtlantic and 1.20 [0.76 to 1.62] mm yr-1 in the East Pacific (Frederikse \r\net al., 2020), compared to a global mean sea level (GMSL) change of \r\naround 1.7 mm yr-1 (Section 2.3.3.3 and Table 9.5). For the period \r\n1993-2018, these RSLR rates, based on satellite altimetry, increased \r\nto 3.45 [3.04 to 3.86)] mm yr-1, 4.04 [2.77 to 5.24] mm yr-1 and 2.35 \r\n[0.70 to 4.06] mm yr-1 respectively (Frederikse et al., 2020), compared \r\nto a GMSL change of 3.25 mm yr-1 (Section 2.3.3.3 and Table 9.5)."


id: 996978bfa9df00ac74229c30d1863e04
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 21657
content:
"Relative sea level rise is extremely likely to continue in the oceans \r\naround Central and South America. Regional mean RSLR projections \r\nfor the oceans around Central and South America range from 0.3-0.5 \r\nm under SSP1-2.6 to 0.5-0.9 m under SSP5-8.5 for 2081-2100 relative \r\nto 1995-2014 (median values), which is around the projected GMSL \r\nchange (Section  9.6.3.3). These RSLR projections may, however, "


id: 3aafcef738330b8f19628772ac3e4cfa
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 6602
content:
"Marine heatwave: The mean sea surface temperature (SST) of the \r\nAtlantic Ocean and the Caribbean around Central and South America \r\nincreased from 0.25degC to 1degC over the period 1982-1998 (Oliver \r\net al., 2018). This mean ocean surface warming is connected to longer "


id: 54ed9b6d678990a39be0fc2f418c37bf
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 10823
content:
"et al., 2018; Vautard et al., 2020; Coppola et al., 2021a) to assess \r\nsignals of climate change in Europe has emerged. These scenario\u0002based simulations have been the basis of a number of impact studies \r\n(e.g.,  Jacob et  al., 2014, 2018; Somot et  al., 2018; Faggian and \r\nDecimi, 2019) highlighting the use of the climatic impact-drivers. The \r\ndevelopment of the science of attribution of weather events (Stott \r\net al., 2016) has provided evidence of links between climate change \r\nand hazard changes such as the 2017 Mediterranean heatwave (Kew \r\net al., 2019) and many others (Chapter 11)."


id: cd952197a5957056ec2015d97ec6e42
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29880
content:
"The ability of global and regional models to reproduce the observed \r\nchanges in mean and extreme temperature and precipitation \r\nin Europe is assessed in the literature (Atlas.8.3). In summary, \r\nboth GCMs and RCMs have their limitations but, in general, the \r\nincreased resolution of RCMs is shown to clearly add value in terms \r\nof resolving spatial patterns and seasonal cycles of precipitation \r\nand precipitation extremes in many European regions, especially in \r\nregions of complex topography such as the Alps and for quantities \r\nsuch as snowmelt-driven runoff, regional winds and Mediterranean \r\nhurricanes (Medicanes)."


id: 4c409c988fbe5157f04de5e5c07a29a3
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vector_id: 9422
content:
"There is high confidence that MHWs will increase around Central \r\nand South America. Mean SST is projected to increase by 1degC (2degC) \r\nby 2100, with a  hotspot of about 2degC (4degC) along the coast of \r\nSouth-Eastern South America and North-Western South America \r\nunder RCP4.5 (RCP8.5; Interactive Atlas). More frequent MHWs \r\nare projected around the region for GWLs of 1.5degC, 2degC and 3.5degC \r\nrelative to the modelled reference value for 1861-1880 (Frolicher \r\net  al., 2018). Projections for SSP1-2.6 and SSP5-8.5 both show an \r\nincrease in MHWs around Central and South America by 2081-2100, \r\nrelative to 1985-2014 (Box 9.2, Figure 1)."


id: d051cd5a0b8ebf660705aecf4342fd69
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 30306
content:
"Examples of projected climatic impact-driver thresholds are illustrated \r\nin Figures 12.4 and 12.9 based on the most recently updated EURO\u0002CORDEX RCM projections, CMIP5 and CMIP6 GCMs for comparison. \r\nFor a more comprehensive representation of other climatic impact\u0002driver index trends assessed in this section the reader is referred to \r\nthe interactive Atlas."


id: bdaa520f83b6b1aecdb35b2704fa812b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 27406
content:
"Mean air temperature: Since AR5, studies have confirmed that the \r\nmean warming trend in Europe is increasing (Atlas.8.2). The observed \r\nwarming trend patterns are largely consistent with those simulated by \r\nglobal and regional climate models and it is very likely that such trends \r\nare, in large part, due to human influence on climate (Section 3.3.1)."


id: 8a3f883fd342c6d2c857c8a6b09810b6
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 19287
content:
"In summary, relative sea level rise is extremely likely to continue \r\nin the oceans around Central and South America, contributing to \r\nincreased coastal flooding in low-lying areas (high confidence) \r\nand shoreline retreat along most sandy coasts (high confidence). \r\nMarine heatwaves are also expected to increase around the \r\nregion over the 21st century (high confidence)."


id: ce1a3b056dd4bcdbd891f120e883ef66
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29939
content:
"All temperature trends are very likely to continue for a  global \r\nwarming of 1.5degC or 2degC and 3degC (Atlas.8.4). Future warming leads \r\nto the exceedance of different temperature thresholds relevant for \r\nvector-borne diseases (medium confidence) (Caminade et al., 2012; \r\nMedlock et  al., 2013), invasive allergens (medium confidence) \r\n(Storkey et al., 2014; Hamaoui-Laguel et al., 2015), SST thresholds in \r\nthe Mediterranean (likely to exceed 20degC), or relevant for the Vibrio\r\nbacteria development (Vezzulli et al., 2015). Future warming is also \r\nprojected to lead to the exceedance of cooling degree day index \r\n(>22degC) thresholds, characterizing a  potential increase in energy \r\ndemand for cooling in southern Europe with increases likely exceeding \r\n40% in some areas (Spinoni et al., 2015) by 2050 under RCP8.5 (high \r\nconfidence) (Section 12.3 and Atlas.8; Coppola et al., 2021a)."


id: 9d5ca137f1960352336805512bf84aa7
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 22284
content:
"The assessed direction of change in climatic impact-drivers for Central \r\nand South America and associated confidence levels are illustrated in \r\nTable 12.6. No assessable literature could be found for sand and dust \r\nstorm, lake and sea ice, heavy snowfall and ice storms, hail and snow \r\navalanches, although these phenomena may be relevant in parts of \r\nthe region."


id: da9bcd9caf63f8ea101a122a62593728
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 31922
content:
"The regional European climate and main hazards have been previously \r\nassessed in SREX, AR5 WGII, SR1.5, SROCC and SRCCL and a summary \r\nof key findings can be found in the Europe section of Atlas.8.1. For the \r\npurpose of this assessment Europe is divided into four climatic regions: \r\nNorthern Europe (NEU), Western and Central Europe (WCE), Eastern \r\nEurope (EEU) and Mediterranean (MED) (Figure Atlas.24)."


id: 223787f0e026631a9a45aadd64a39c02
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 2830
content:
"Extreme heat: The frequency of heatwaves observed in Europe \r\nhas very likely increased in recent decades due to human-induced \r\nchange in atmospheric composition (Section 11.3) and a detectable \r\nanthropogenic increase in a  summer heat stress index over all \r\nregions of Europe has been identified based on WBGT index trends \r\nfor 1973-2012 (medium confidence, limited evidence) (Knutson and \r\nPloshay, 2016)."


id: c74bf3b0370fced5ec88cf6e26390351
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 28945
content:
"Since AR5 and SR1.5, a  large body of literature that uses the \r\nEURO-CORDEX and MED-CORDEX ensembles of high-resolution \r\nsimulations (Jacob et  al., 2014; Ruti et  al., 2016; Kjellstrom "


id: 823b36a7d5ece175d32e02b711047862
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 18017
content:
"It is very likely that the frequency of heatwaves will increase during \r\nthe 21st  century regardless of the emissions scenario in each \r\nEuropean region, and for 1.5degC and 2degC GWLs (Section  11.3.5). \r\nHeat stress due to both high temperature and humidity, affecting \r\nmorbidity, mortality and labour capacity (Section 12.3) is projected to \r\nincrease under all emissions scenarios and GWLs by the middle of the \r\ncentury (Figure 12.4a-f). Under RCP8.5, the expected number of days \r\nwith WBGT higher than 31degC is about 25, 30 and 40 days per year, \r\nas projected by EURO-CORDEX, CMIP5 and CMIP6 respectively on \r\naverage over the Mediterranean region, and around 30, 40 and 60 days \r\nper year in low coastal plain areas such as the Po Valley, the Italian, \r\nGreek and Spanish coasts, and the Mediterranean islands (Coppola "


id: 8183fe3455cd0448bf73c367ca2d57c3
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 17907
content:
"et al., 2021a). An average increase of a few days per year of maximum \r\ndaily temperature exceeding 35degC, a typical critical threshold for crop \r\nproductivity, is expected by the mid-century in central Europe, and \r\nan increase of 10-20 days is expected for the Mediterranean areas \r\n(Figure 12.4b; Coppola et al., 2021a). By contrast, under SSP1-2.6, the \r\nincrease in this number of days remains limited to less than about \r\n10 days, and confined to the Mediterranean regions. Mitigation is \r\nexpected to have a strong effect, with the dangerous heat threshold \r\nof HI > 41degC projected to be crossed 5-10 days more per year in the \r\nMediterranean regions and a few days per year more in WCE and EEU \r\nunder SSP5-8.5, while such increases would be virtually absent under \r\nSSP1-2.6 (Figure 12.4d-f)."


id: 83b8a69ef36a55f8e2b1786afc25cc70
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 18258
content:
"Cold spell and frost: Temperature observations for winter cold spells \r\nin Europe show a  long-term decreasing frequency (Brunner et  al., \r\n2018), with their probability of occurrence projected to decrease \r\nin the future (high confidence) and virtually disappear by the end \r\nof the century (Section 11.3). The frequency of frost days will very \r\nlikely decrease for all scenarios and all time horizons (Lindner et al., \r\n2014; Coppola et al., 2021a) with consequences for agriculture and \r\nforests. A  simple heating degree day index, characterizing heating \r\ndemand, shows a large observed decreasing trend for winter heating \r\nenergy demand in Europe (Spinoni et  al., 2015). This trend is very \r\nlikely to continue through the 21st  century, with decreases in the \r\nrange of 20-30% for Northern Europe, about 20% for central Europe \r\nand 35% for southern Europe, by mid-century under RCP8.5 (Spinoni \r\net al., 2018b; Coppola et al., 2021a; Interactive Atlas)."


id: a1db610f704f03e175f7dc29c9755b69
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 23027
content:
"high flow does not show uniform trends for the entire region (Hall et al., \r\n2014; Mediero et al., 2015) or specific regions (Mudersbach et al., 2017; \r\nVicente-Serrano et al., 2017; Tramblay et al., 2019), regional patterns \r\nof significant flood trends do exist. Based on the most extended river \r\nflow database spanning the period 1960-2010, an increase in floods \r\nfrequency in north-western Europe, decreasing in medium and large \r\ncatchments in southern Europe and decreasing floods in Eastern Europe \r\nhas been detected (Bloschl et al., 2019) in line with Mediero et al. (2014), \r\nArheimer and Lindstrom (2015), Gudmundsson et al. (2017), Krysanova \r\net al. (2017), Kundzewicz et al. (2018) and Mangini et al. (2018)."


id: fb3a052fd3b4dea38615c0c9dd005933
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 37033
content:
"There is high confidence of river floods increasing in Western and \r\nCentral Europe (WCE) and medium confidence of a  decrease in \r\nNorthern (NEU), Eastern (EEU) and southern Europe (MED) for mid\u0002and end-century under RCP8.5 and low confidence under RCP2.6. The \r\nprojected increase in WCE is roughly 10% (18% by end of century) \r\nand the projected decrease in NEU is 5% (11% by end of century) for \r\nthe peak flow with a return period of 100 years for mid-century, under \r\nRCP8.5 (Di Sante et al., 2021; Figure 12.9a for mid-century (Q100) \r\nprojections of flood discharges per unit catchment area (Bloschl \r\net al., 2019) based on EURO-CORDEX models)."


id: dcf36f91fcf754694058cef662f656df
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 32259
content:
"In summary, irrespective of the scenario, it is virtually certain\r\nthat warming will continue in Europe, and there is high \r\nconfidence that the observed increase in heat extremes is \r\ndue to human activities. It is very likely that the frequency \r\nof heat extremes will increase over the 21st century with an \r\nincreasing gradient toward the southern regions. Extreme \r\nheat will exceed critical thresholds for health, agriculture and \r\nother sectors more frequently (high confidence), with strong \r\ndifferences between mitigation scenarios. It is very likely that \r\nthe frequency of cold spells and frost days will keep decreasing \r\nover the course of this century and it is likely that cold spells \r\nwill virtually disappear towards the end of the century."


id: 43cdced162bf8f9fbe1ad523b72e5613
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 8077
content:
"Mean precipitation: Precipitation has generally increased in northern \r\nEurope and decreased in southern Europe, especially in  winter \r\n(Fischer and Knutti, 2016; Knutson and Zeng, 2018) but in the latter, \r\nprecipitation trends are strongly dependent on the examined period \r\n(Atlas.8). These trends in precipitation increases in the north and \r\ndecreases in the south are also represented by global and regional \r\nclimate simulations (Jacob et  al., 2014; Rajczak and Schar, 2017; \r\nLionello and Scarascia, 2018; Coppola et  al., 2021a; Atlas.8.2) and \r\nhave been attributed to climate change (Sections 3.3.2, 8.3.1)."


id: 6fbd2e719a9f2f08373169e844ac781d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 15204
content:
"Heavy precipitation and pluvial flood: Heavy precipitation \r\nfrequency trends have been detected in Europe with high confidence\r\nfor the NEU and Alpine regions and with medium confidence in \r\nWCE, and also attributed to climate change with high confidence in \r\nNEU (Section 11.9). Guerreiro et al. (2017), based on observations, \r\nshowed that 20% of city areas in WCE and MED regions are affected \r\nby pluvial flooding and less than 10% of city areas in the northern \r\nand western coastal cities."


id: e0002395b442973490603bb81eacbe5a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 32735
content:
"Studies since AR5, together with EURO-CORDEX and MED-CORDEX \r\nexperiments and the latest CMIP6 ensemble, have increased \r\nconfidence in regional projections of mean and extreme precipitation \r\n(Prein et al., 2016) despite their wet bias, and show that it is very \r\nlikely that precipitation will increase in Northern Europe in DJF and \r\ndecrease in the Mediterranean in JJA under all climate scenarios \r\nexcept RCP2.6/SSP1-2.6 and for both mid- and end-century periods \r\n(Coppola et al., 2021a; Atlas.8.5)."


id: 59f4870ebdf76adc200bb953108d51ad
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 11662
content:
"Projections based on multiple lines of evidence from global to \r\nconvective permitting model scales show high confidence in \r\nextreme precipitation increase in the northern, central and eastern \r\nEuropean regions (NEU, WCE, EEU) and in the Alpine area. Increases \r\nwith medium confidence are projected for the Mediterranean basin \r\n(with a negative gradient towards the south) for mid- and end-century \r\nunder RCP4.5, RCP8.5 and SSP5-8.5 and for 2degC GWL and higher \r\n(Section 11.9; MedECC, 2020)."


id: facc1af91506a0e03c381ef8eda98ae
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 36979
content:
"River flood: There is high confidence of an observed increasing \r\ntrend of river floods in Western and Central Europe (WCE) and \r\nmedium confidence of a decrease in Northern (NEU) and southern \r\nEurope (MED)."


id: c557f31ff9a625001d3a1f8d16bef3d5
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 28631
content:
"The SR1.5 shows evidence of an increase in reported floods in the UK \r\nover the period 1884-2013, and increasing trends in annual maximum \r\ndaily streamflow data over 1966-2005 in parts of Europe. Although "


id: 5d3e53d14bf5097a00611c5ea3d4663b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 12183
content:
"A reduction of drought length and magnitude is projected for NEU \r\nand EEU (Roudier et  al., 2016). In the southern Alps, both winter \r\nand summer low flows are projected to be more severe, with a 25% \r\ndecrease in the 2050s (Vidal et al., 2016)."


id: aaf739421e76bbd9e9846453a0c64949
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 24416
content:
"Agricultural and ecological drought: There is medium confidence\r\nthat agricultural and ecological droughts have increased in \r\nWestern and Central Europe and in the Mediterranean region, and \r\nmedium confidence that anthropogenic drivers contributed to the \r\nMediterranean increase (Sections 8.3.1.6 and 11.9)."


id: 8f6e9657e339e277d1b6af3a0b5e8fd0
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 20115
content:
"Chapter  11 assesses that agricultural and ecological droughts will \r\nincrease in the Mediterranean regions (high confidence) and Western \r\nand Central Europe (medium confidence) by mid-century and with \r\nhigh confidence by the end of the century for the MED for 2degC GWL \r\nand higher and all scenarios except RCP2.6/SSP1-2.6 (Section 11.9.4). \r\nLow confidence in direction of change is assessed for EEU and NEU \r\nunder all scenarios and global warming levels (Figure 12.4k)."


id: a02ddbc7fbb4aea0a602058d4f2dafb1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 22736
content:
"Aridity: The Mediterranean region shows evidence of large-scale \r\ndecreasing precipitation trends over 1901-2010, which are at least \r\npartly attributable to anthropogenic forcing according to CMIP5 \r\nmodels (Knutson and Zeng, 2018). Nevertheless, there is low \r\nagreement among studies on observed precipitation trend in the \r\nMediterranean region (Section 11.9.4 and Atlas.8.2)."


id: eba843e50c0ba9ef237db7874d5ea85c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 34576
content:
"Precipitation is projected to decrease by mid- and end-century for the \r\nRCP8.5 and SSP5-8.5 with strong agreement among CMIP5, CMIP6 and \r\nCORDEX regional climate ensemble models on the direction of change. \r\nWith both temperature increase and precipitation decrease there is high \r\nconfidence on increased aridity in the MED region (Sections 8.4.1.6 \r\nand 11.9.4 and Atlas.8.2; Coppola et al., 2021a). In NEU there is high \r\nconfidence of decrease in aridity linked to mean precipitation increase \r\n(Section 8.4.1.6, Atlas 8.2) and meteorological drought decrease based \r\non indicators like Standardized Precipitation Index and consecutive dry \r\ndays (Section 11.9.4, Figure 12.4, Coppola et al,, 2021a)."


id: c183429e66bd701ad370784cf9eab883
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 28033
content:
"Hydrological drought: There is high confidence that hydrological \r\ndroughts have increased in the Mediterranean basin with medium \r\nconfidence in anthropogenic attribution of the signal, and high \r\nconfidence that they will continue to increase through the 21st century \r\nfor 2degC GWL and higher and all scenarios except RCP2.6/SSP1-2.6. \r\n(Sections 8.3.1.6, 8,4.1.6, and 11.9.4). There is medium confidence\r\nin hydrological drought increase in WCE and low confidence in \r\ndirection of change for EEU and NEU from mid-century onwards and \r\nfor 2degC GWL and higher and all scenarios except RCP2.6/SSP1-2.6 \r\n(Section 11.9 and Figure 12.4g-i)."


id: 29328dfb9f4a6629c6dd3b5669b83218
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 3916
content:
"Streamflow droughts are projected to become more severe and \r\npersistent in the Mediterranean and western Europe (current \r\n100-year events could occur approximately every 2-5 years by 2080; \r\nForzieri et al., 2016). "


id: 4b62be29454b22791b99308bf3544c7
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 9276
content:
"The opposite tendency is projected in Northern, Eastern and central \r\nEurope where higher precipitation that outweighs the effects of \r\nincreased evapotranspiration is expected to result in a decrease in \r\nstreamflow drought frequency (Forzieri et al., 2014). For a 2degC GWL \r\ndroughts will become more intense in the MED and in France and \r\nlonger mainly due to less rainfall and higher evapotranspiration. "


id: bad3832424f2ee1a57f0feb32733b466
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 26929
content:
"In summary, there is high confidence that river floods will \r\nincrease in central and Western Europe and medium confidence\r\nthat they will decrease in Northern, Eastern and southern \r\nEurope, for mid- and end of century under RCP8.5 and  with \r\nlow confidence under RCP2.6. There is high confidence that \r\naridity will increase by mid- and end-century under the RCP8.5 \r\nand SSP5-8.5, and high confidence that agricultural, ecological \r\nand hydrological droughts will increase in the Mediterranean \r\nregion by mid- and far end of century under all RCPs except \r\nRCP2.6/SSP1-2.6 and also for 2degC and higher GWLs. There is high \r\nconfidence in fire weather increase in the Mediterranean region."


id: ea045b400144b9918a09c4f2b791bb9c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 34313
content:
"Severe wind storm: There are large uncertainties in past evolutions \r\nof windstorms and extreme winds in Europe. Extreme near-surface \r\nwinds have been decreasing in the past decades (Smits et al., 2005; \r\nTian et  al., 2019; Vautard et  al., 2019) according to near-surface \r\nobservations. Significant negative trends of cyclone frequency in spring \r\nand positive trends in summer have been found in the Mediterranean \r\nbasin for the period 1979-2008 (Lionello et  al., 2016). By contrast \r\nincreasing trends have been found in Arctic Ocean areas (Wickstrom \r\net al., 2020). These trends are not associated with significant trends in \r\nextratropical cyclones (Sections 8.3.2.8 and 11.7.2)."


id: b5829b78863ca55eddaa43d4eccfa6e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 26085
content:
"There is high confidence that mean wind speeds will decrease \r\nin Mediterranean areas and medium confidence of such \r\ndecreases in Northern Europe for global warming levels of \r\n2degC or more and beyond the middle of the century. A slightly \r\nincreased frequency and amplitude of extratropical cyclones, \r\nstrong winds and extratropical storms is projected for northern, \r\ncentral and western Europe by the middle of the century and \r\nbeyond and for global warming levels of 2degC or higher (medium "


id: 4a386f002203f95a788986b1ae3156bc
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 9083
content:
"confidence). The frequency of Medicanes is projected to \r\ndecrease (medium confidence), but their intensity is projected \r\nto increase by mid century and beyond and for global warming \r\nlevels of 2degC or more. Proxies of intense convection indicate \r\nthat the large-scale conditions conducive to severe convection \r\nwill tend to increase in the future climate (low confidence)."


id: a066f13e5ce3c51cfbd1582322ce90a4
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 22774
content:
"day (2017) ice volume is projected to be lost by 2100. In contrast, \r\nunder the strong warming of RCP8.5, glaciers in the European Alps \r\nare projected to largely disappear by 2100 (94 +- 4% volume loss \r\ncompared to 2017; Zekollari et al., 2019)."


id: 28707c8984ba11ff751479db412703a1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 3775
content:
"Permafrost: In Europe, permafrost is found in high mountains and in \r\nScandinavia, as well as in Arctic Islands (e.g., Iceland, Novaya Zemlia or \r\nSvalbard). In recent decades permafrost has been lost (Section 9.5.2) \r\nand accelerated warming at high altitudes and latitudes has favoured \r\nan increase of permafrost temperatures of the order of 0.2 +- 0.1degC \r\nbetween 2007 and 2016 (Romanovsky et  al., 2018; Noetzli et  al., \r\n2019). Over the 21st  century, permafrost is very likely to undergo \r\nincreasing thaw and degradation under all scenarios (Hock et  al., \r\n2019) and it is virtually certain that permafrost extent and volume will \r\ndecrease with increase of global warming (Section 9.5.2)."


id: e8a992edfe089ff87bbe51be940093e6
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 34115
content:
"Permafrost thawing is projected to affect the frequency and \r\nmagnitude of high-mountain mass wasting processes (Stoffel \r\nand Huggel, 2012). The temporal frequency of periglacial debris flows \r\nin the Alps is unlikely to change significantly by the mid-21st century \r\nbut is likely to decrease during the second part of the century under \r\nthe A1B scenario, especially in summer (Stoffel et al., 2011, 2014). \r\nThere is medium confidence that most of the Northern Europe \r\nperiglacial processes will disappear by the end of the century, even \r\nin the RCP2.6 scenario (Aalto et al., 2017). The magnitude of debris \r\nflow events might increase (Lugon and Stoffel, 2010) and the debris\u0002flow season may last longer under the A1B scenario (Stoffel and \r\nCorona, 2018). Quantitative data for the European Alps is highly site \r\ndependent (Haeberli, 2013)."


id: d3c4b5b63c33baa0b8ae2df4aa72d590
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 30842
content:
"Heavy snowfall, ice storms and hail: There is low confidence that \r\nclimate change will affect ice and snow-related episodic hazards \r\n(limited evidence). The change in snowpack in the Alps is expected \r\nto lead to a possible reduction in overall avalanche activity by end of \r\nthe century (low confidence), except possibly in winter and at high \r\naltitudes (Castebrunet et al., 2014)."


id: 9e2a5d11c23f60a1fb852a7caf8782b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 22408
content:
"For ice storms, or freezing rainstorms, there is also limited evidence\r\ndue to a limited number of studies. Heavy snowfalls have decreased \r\nin frequency in the past decades and this is expected to continue in \r\nthe future climate (low confidence) (Beniston et al., 2018). Freezing \r\nrain is projected to increase in western, central and southern Europe \r\nby the end of the century under RCP4.5 and RCP8.5 (low confidence) \r\n(Kamarainen et  al., 2018). Rain-on-snow events, are decreasing in \r\nnorthern regions (Pall et al., 2019) and by 48% on average in southern \r\nScandinavia (Poschlod et al., 2020) due to decreases in snowfall."


id: cb833786088536201c9b4d0f2df4a17a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29567
content:
"In summary, future snow cover extent and seasonal duration \r\nwill reduce (high confidence) and it is virtually certain that \r\nglaciers will continue to shrink. A  reduction of glacier ice \r\nvolume is projected in the European Alps and Scandinavia \r\n(high confidence). There is high confidence that permafrost \r\nwill undergo increasing thaw and degradation over the \r\n21st  century. Most of the Northern Europe periglacial will \r\ndisappear by the end of the century even for a lower emissions \r\nscenario (medium confidence) and the debris-flow season may \r\nlast longer in a warming climate (medium confidence)."


id: eba84c0c089b20ffb8e8cfd97843ca7b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 34577
content:
"(Luijendijk  et  al., 2018; Mentaschi et  al., 2018). Mentaschi et  al. \r\n(2018) report a coastal area loss of 270 km2 over a 30-year period \r\n(1984-2015) along the Atlantic coastlines of Europe."


id: d1aae3bcb95b44b5dc675c5d174a18e1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 30520
content:
"Relative sea level: Around Europe, over 1900-2018, a  new tide \r\ngauge-based reconstruction finds a  regional mean RSL change of \r\n1.08 [0.79 to 1.38] mm yr -1 in the subpolar North Atlantic (Frederikse \r\net al., 2020), compared to a GMSL change of around 1.7 mm yr -1\r\n(Section 2.3.3.3 and Table 9.5). For the period 1993-2018, the RSLR \r\nrates around Europe, based on satellite altimetry, increased to 2.17 \r\n[1.66 to 2.66] mm yr-1 (Frederikse et al., 2020), compared to a GMSL \r\nchange of 3.25 mm yr-1 (Section 2.3.3.3 and Table 9.5)."


id: 9a607c33861c626502108917188f0fa2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 21816
content:
"Relative sea level rise is extremely likely to continue in the oceans \r\naround Europe. Regional mean RSLR projections for the oceans around \r\nEurope range from 0.4-0.5 m under SSP1-2.6 to 0.7-0.8 m under \r\nSSP5-8.5 for 2081-2100 relative to 1995-2014 (median values), \r\nwhich means that there are locally large deviations from the projected \r\nGMSL change (Section 9.6.3.3). These RSLR projections may however \r\nbe underestimated due to potential partial representation of land \r\nsubsidence in their assessment (Section 9.6.3.2). The signal is strongest \r\nfor the North Sea and Atlantic coasts, followed by the Black Sea. The \r\nBaltic Sea, on the contrary, shows the lowest increase due to land \r\nuplift (Vousdoukas et al., 2017). The model agreement is higher for the \r\nMediterranean and in line with previous findings by Gualdi et al. (2013)."


id: 79516c71d500e4d3e2725fc487e49af7
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 16654
content:
"Local assessments of both long term shoreline retreat and episodic \r\ncoastal erosion are given by Li et  al. (2014b), Toimil et  al. (2017), \r\nBon de Sousa et al. (2018) and Le Cozannet et al. (2019). In terms \r\nof episodic coastal erosion, 31-88% of all Aegean beaches are \r\nprojected to experience complete erosion, with a RCP4.5 sea level \r\nrise of 0.5 m and a surge of 0.6 m, but with substantial uncertainty \r\n(Monioudi et al., 2017)."


id: a4ec213c3105890dcfc8165f5281788c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 23517
content:
"Coastal flood: The present-day 1-in-100-year ETWL is between 0.5 \r\nand 1.5 m in the MED basin and 2.5 and 5.0 m in the western Atlantic \r\nEuropean coasts, around the UK and along the North Sea coast, and \r\nlower at 1.5-2.5 m along the Baltic Sea coast (Kirezci et al., 2020). \r\nSimilar values are reported by Vousdoukas et al. (2018)."


id: dd9144ef21b707e964854d183cae3a89
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 32362
content:
"Marine heatwave: The mean SST of the Atlantic Ocean and \r\nthe Mediterranean has increased between 0.25degC and 1degC since \r\n1982-1998. This mean ocean surface warming is correlated to longer \r\nand more frequent marine heatwaves in the region (Oliver et al., 2018). \r\nOver the period 1982-2016, the coastlines of Europe experienced on \r\naverage more than 2.0 MHW yr-1, with the eastern Mediterranean \r\nand Scandinavia experiencing 2.5-3 MHWs yr-1. The average duration \r\nwas between 10 and 15 days. Changes over the 20th century, derived \r\nfrom MHW proxies, show an increase in frequency of between 1.0 and \r\n2.0 MHWs per decade in Europe, although the trend is not statistically \r\nsignificant; with an increase in intensity per event in the North Atlantic \r\nand the Mediterranean, and a decrease in the Atlantic off the British \r\nIsles. The total number of MHW days per decade has increased in the \r\nMediterranean (Oliver et al., 2018)."


id: cc5ab6ec520f2251b99449c7db1d4ef4
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29690
content:
"Mean SST is projected to increase by 1degC-3degC around Europe by \r\n2100, with a hotspot of around 4degC-5degC along the Arctic coastline \r\nof Europe under RCP4.5 and RCP8.5 scenarios (see Interactive Atlas), \r\nleading to a continued increase in MHW frequency, magnitude and \r\nduration (Oliver et al., 2018; MedECC, 2020). Projections for SSP1-2.6 \r\nand SSP5-8.5 both show an increase in MHWs around Europe by \r\n2081-2100, relative to 1985-2014 (Box  9.2, Figure  1). Darmaraki \r\net al. (2019) project that, by the end of the 21st century and under \r\nRCP8.5, there will be one MHW occurring every year in the northern \r\nMediterranean sea, and that these MHWs would be three months \r\nlonger, four times more intense, and 42 times more severe than \r\npresent day MHWs in the region. Frolicher et al. (2018) show that, \r\nin Europe, the change in the probability for the number of days of "


id: b6fc478cbcb51cfa77185954e78d3915
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 26320
content:
"Coastal erosion: Satellite-derived shoreline change estimates over \r\n1984-2015 indicate shoreline retreat rates of around 0.5  m  yr-1\r\nalong the sandy coasts of WCE and MED, around 4 m yr-1 in EEU \r\n(Caspian Sea region) and more or less stable shorelines in NEU "


id: 55e0133c2513ee362d34c92ec77e89
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 10992
content:
"MHWs exceeding the 99th percentile of the pre-industrial level is \r\n4%, 15% and 30% for global warming levels of 1degC, 2degC and 3.5degC, \r\nrespectively. MHW increase in the Mediterranean will impact on \r\nmany species that live in shallow waters and have reduced motility, \r\nwith consequences for related economic activities (Galli et al., 2017)."


id: 612415fc9d96f9f33b68c79c77f5e77
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 12858
content:
"on connections to warming levels provided by SR1.5 (IPCC, 2018), \r\nand climate information related to land degradation and land-use \r\nsuitability in SRCCL (IPCC, 2019c), and ocean and coastal hazards in \r\nthe SROCC (IPCC, 2019b). Recent national assessments in the USA \r\n(USGCRP, 2017, 2018) and Canada (Bush and Lemmen, 2019) enhance \r\nthe local perspective and assessments across a number of CIDs and \r\ntheir sectoral connections. For the purpose of this assessment, North \r\nAmerica is sub-divided into six sub-regions, as defined in Chapter 1: \r\nNorth Central America (NCA), Western North America (WNA), Central \r\nNorth America (CNA), Eastern North America (ENA), North-Eastern \r\nNorth America (NEN), and North-Western North America (NWN). \r\nGreenland and Arctic regions of North-Eastern and North-Western \r\nNorth America are further assessed in Section  12.4.9, and the \r\nCaribbean and Hawaiian Islands are assessed in Section 12.4.7."


id: a36db200c16899705882e2b501237b6d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 23276
content:
"In general, there is high confidence that most coastal/ocean\u0002related climatic impact-drivers in Europe will increase over the \r\n21st century for all scenarios and time horizons. Relative sea \r\nlevel rise is extremely likely to continue around Europe (except \r\nin the northern Baltic Sea), contributing to increased coastal \r\nflooding in low-lying areas and shoreline retreat along most \r\nsandy coasts (high confidence). Marine heatwaves are also \r\nexpected to increase around the region over the 21st century \r\n(high confidence)."


id: b026e74eb849d2a73d013894ab10b915
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 25241
content:
"Compound events: One typical compound event that is observed in \r\nthe European area is compound flooding due to the combination of \r\nextreme sea level events and extreme precipitation events associated \r\nwith high levels of runoff. In the present climate, the Mediterranean \r\ncoasts are exposed to a higher probability of this type of compound \r\nflooding event (Bevacqua et al., 2019). Under RCP8.5, the probability \r\nof these events is projected to increase along northern European \r\ncoasts (west coast of UK, northern France, the east and south coast \r\nof the North Sea, and the eastern half of the Black Sea), with the \r\npercentage of coastline now experiencing such events at least once \r\nevery 6 years increasing by between 3% and 11% by the end of the \r\n21st century (Bevacqua et al., 2019)."


id: 5e01a3757576412ad0e5ed9c987de3cc
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 12321
content:
"Under RCP8.5, regions in Russia, France and Germany are projected \r\nto experience an increase in the frequency and the length of wet and \r\ncold compound events, while Spain and Bulgaria are projected to stay \r\nlonger in the hot and dry state by mid-century (Sedlmeier et al., 2016)."


id: dd7d5d176e44d8ab4f6164054c1832b2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 32348
content:
"Compound events of dry and hot summers have increased in Europe. \r\nManning et al. (2019) found that the probability of such compound \r\nevents has increased across much of Europe between 1950-1979 \r\nand 1984-2013, notably in southern, eastern and western Europe. \r\nCompound hot and dry extremes are projected to increase in Europe by \r\nmid-century for the SRES A1B and RCP8.5 with a particularly strong \r\nsignal projected in southern and eastern Germany and the Czech \r\nRepublic (Sedlmeier et al., 2016)."


id: 5fd91b0e2523ee93af1367d40853e555
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 12659
content:
"Extreme heat: Section 11.9 assessed that extreme temperatures in \r\nNorth America have increased in recent decades (medium evidence,\r\nmedium agreement) other than in Central and Eastern North America \r\n(low confidence), and extreme heat in all regions is projected to \r\nincrease with climate change (high confidence). Observed trends in \r\nextreme heat are more positive for heat extreme indices that include \r\ntemperature and humidity given historical expansion of irrigation \r\nand intensification of agriculture (Mueller et al., 2017; Grotjahn and \r\nHuynh, 2018; Thiery et al., 2020). Several studies noted statistically \r\nsignificant increases in intensity and particularly the frequency, \r\nduration, and seasonal length of the physiologically hazardous \r\nextreme heat conditions across North America (Grineski et al., 2015; \r\nHabeeb et al., 2015; Martinez-Austria et al., 2016; Petitti et al., 2016; \r\nL.A. Vincent et al., 2018; Garcia-Cueto et al., 2019)."


id: ae095082a398c395c5e30253f659c73
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 24919
content:
"The assessed direction of change in climatic impact-drivers for Europe \r\nand associated confidence levels are illustrated in Table 12.7, together \r\nwith emergence time information (Section  12.5.2). No assessable \r\nliterature could be found for sand and dust storms, although these \r\nphenomena may be relevant in parts of the region."


id: 515111e619e77e547ae5b9a9d6cde7d2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 10248
content:
"Major changes in North American CIDs were assessed in WGII AR5 \r\nChapter  26 (Romero-Lankao et  al., 2014), with additional detail "


id: 5a94ea0f7ef020ce2ef97d0bae524c73
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 11770
content:
"Climate change is virtually certain to shift the balance of \r\ntemperature towards warming trends and away from cold \r\nextremes, with increases in the magnitude, frequency, duration \r\nand seasonal and spatial extent of heat extremes driving \r\nimpacts across North America. The frequency of dangerous \r\nheat threshold exceedance (such as HI > 41degC) is particularly \r\nsensitive to scenario pathway, with 75-150 days more under \r\nSSP5-8.5 but less than 60 days more under SSP1-2.6 by the \r\nend of the century in NCA, CNA and the south-western USA."


id: cd2676a527fb9740bf667f94e9d28278
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29828
content:
"The number of days crossing dangerous heat thresholds such as \r\nHI  >  41degC will be very sensitive to the mitigation scenario at the \r\nend of the century (Wuebbles et al., 2014; Zhao et al., 2015; Dahl \r\net al., 2019; Schwingshackl et al., 2021). At the end of the century \r\nunder SSP5-8.5, a CMIP6 median increase of exceedances of 75-150 \r\ndays per year is projected over much of North Central America, \r\nCentral North America and the south-western USA while this \r\nincrease is projected to remain limited below 60 days under SSP1-2.6 \r\n(Figure  12.4d,f and Figure 12.SM.2). Steinberg et  al. (2018) also \r\nprojected more frequent and longer 'heat-health' events in California \r\nextending into October."


id: 2edec03274ce6927ee112e9fd4bc08f6
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 4806
content:
"Mean precipitation: Atlas.9.2 found that trends in annual \r\nprecipitation over 1960-2015 are generally non-significant, though \r\nthere are consistent positive trends over parts of ENA and CNA, \r\ntogether with significant decreases in precipitation in parts of the \r\nsouth-western USA and north-western Mexico."


id: ec90c4c205bbc5e350fb66bd7c336ba0
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 34698
content:
"Cold spell: Chapter  11 assessed high confidence in decreasing \r\nfrequency and intensity of cold spells over North America (Section 11.9). \r\nThe number of days with extreme wind chill hours (humidex <-30) \r\ndecreased at 76% of examined Canadian stations from 1953 to 2012 \r\n(Mekis et al., 2015) and cold days and coldest nights decreased in \r\nMexico from 1980 to 2010 (Garcia-Cueto et al., 2019)."


id: b99be53143faa628cb13bbad114e099b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 26738
content:
"Atlas.9.4 assessed very high confidence in increases in mean \r\nprecipitation over most of northern and Eastern North America, with \r\nmedium confidence of decrease over Northern Central America and \r\nlow confidence elsewhere (see Figure Atlas.26, and Cross-Chapter \r\nBox Atlas.1, Figure  1). Changes are most dramatic in the spring \r\nand winter, when wet conditions are projected to extend from the \r\nnorthern portions of the continent as far south as the central Great \r\nPlains, while Mexico becomes drier; in contrast, summer changes are \r\nuncertain across most of the continent other than wetter conditions \r\nin northern Canada (Easterling et al., 2017; Bukovsky and Mearns, \r\n2020; Almazroui et al., 2021; Teichmann et al., 2021)."


id: 32fa4a421641049449b86a20b525d187
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 5443
content:
"River flood: There is limited evidence and low agreement on \r\nobserved climate change influences for river floods in North America \r\n(Section 11.5). Trends in streamflow indices are mixed and difficult \r\nto separate from river engineering influences, with large changes \r\nbut little spatial coherence across the USA, making it difficult to \r\nidentify trends with confidence (Peterson et  al., 2013; Mallakpour \r\nand Villarini, 2015; Archfield et al., 2016; Wehner et al., 2017; Villarini \r\nand Slater, 2018; Hodgkins et al., 2019; Neri et al., 2019). There is \r\nhigh confidence in historical shifts in the timing of peak streamflow \r\ntowards higher winter and earlier spring flows in snowmelt-driven \r\nbasins in Canada (Burn and Whitfield, 2016; Bonsal et al., 2019) and "


id: 413fb3d858b27947301e88dd4d078ac1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 7661
content:
"increases in evapotranspiration that will counteract precipitation \r\nchanges over much of the country (Coe, 2016)."


id: 6542714e4572cea651e58953cfc0eb96
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 13508
content:
"Heavy precipitation and pluvial flood: Section 11.4 assessed high \r\nconfidence in observed increases in extreme precipitation events \r\n(including hourly totals) in Central and Eastern North America with \r\nlow confidence in broad trends elsewhere in the continent despite \r\nobservational increases in some portions of each region (L.A. Vincent \r\net al., 2018; Garcia-Cueto et al., 2019; X. Zhang et al., 2019)."


id: 9430dc0d025e72b313f82066e292b545
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 20825
content:
"Hydrological drought: Section  11.9 asssessed low confidence of \r\nsignificant observational trends and projected future changes in the \r\ncharacteristics of episodic hydrological drought in North America given \r\nlimited evidence and low agreement in modeled changes. C. Zhao \r\net al. (2020) found that increases in hydrological drought frequency \r\n(particularly the 100 yr drought) were far more prevalent than for \r\nmeteorological drought across 5797 watersheds in the USA and Canada, \r\nindicating a strong influence of evaporative demand. Reductions in the \r\noverall supply of meltwater from a declining snowpack also increase \r\nthe potential for intermittent hydrological droughts in the western USA \r\n(Mote et al., 2018; Livneh and Badger, 2020)."


id: 3f0d3fea6aa466c6b6568b00f63a7cb2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 7306
content:
"evaporative demand will extend the regions where more intense \r\necological and agricultural droughts develop when meteorological \r\ndroughts occur (Wehner et al., 2017; B.I. Cook et al., 2019, 2020). \r\nStudies utilizing a  variety of drought indices and soil moisture \r\nprojections consistently project increased drought extending from \r\nMexico into the southern Canadian Plains during the summer (Swain \r\nand Hayhoe, 2015; Ahmadalipour et  al., 2017; Feng et  al., 2017; \r\nBonsal et al., 2019; Tam et al., 2019; B.I. Cook et al., 2020)."


id: d8a96a508c8f00a6737bf415a3e5f7c3
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 31601
content:
"Mean wind speed: Mean wind speeds have declined in North \r\nAmerica - as in other Northern Hemisphere areas - over the past \r\nfour decades (medium confidence) (AR5 WGI) with a reversal in the \r\nlast decade (low confidence) not fully consistent across studies (Tian \r\net al., 2019; Zeng et al., 2019; Z. Zhang et al., 2019). Tian et al. (2019) \r\nfound a corresponding reduction in the wind power potential across \r\nthe eastern parts of North America."


id: ab4dae363a9e40076aa8bc3adb5363c6
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 24463
content:
"Mean wind speeds are expected to decline over much of North \r\nAmerica (Figure 12.4m-o), but the only broad signal of consistent \r\nchange across model types is a reduction in wind speed in Western \r\nNorth America (high confidence). These declines reduce wind power \r\nendowment by 2050 and as early as the 2020-2040 near-term period \r\nin the USA Mountain West, while there is disagreement between \r\nglobal- and regional-model change projections in the upper and \r\nlower Great Plains, Ohio River Valley, Mexico and eastern Canada \r\n(Karnauskas et al., 2018a; Jung and Schindler, 2019; Chen, 2020)."


id: 26568755062cec02d2c5377df9fa4889
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 3448
content:
"Severe wind storm: There is limited evidence and low agreement\r\nin observed changes in North American CID indices associated with \r\nextratropical cyclones (Section  11.7), severe thunderstorms, severe \r\nwind bursts (derechos), tornadoes, or lightning strikes (Vose et al., \r\n2014; Easterling et  al., 2017; Kossin et  al., 2017). Observational \r\nstudies have indicated a reduction in the number of tornado days in \r\nthe USA, but increases in outbreaks with 30 or more tornadoes in one \r\nday (Brooks et al., 2014), the density of tornado clusters (Elsner et al., \r\n2015), and overall tornado power (Elsner et al., 2019)."


id: a99493a6c69ee790dbb6aa4003853b81
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 24214
content:
"Tropical cyclone: Section  11.7.1 identified recent reductions in \r\ntropical cyclone translation speed and higher tropical cyclone rainfall \r\ntotals over the North Atlantic, as well as substantial natural variability. \r\nProjections indicate low confidence in change in North Atlantic tropical \r\ncyclone numbers, but medium confidence in Mexico and the US Gulf and \r\nAtlantic coasts for more intense storms with higher wind, precipitation, \r\nand storm surge totals when they do occur (Section 11.7.1; Diro et al., \r\n2014; DOE, 2015; Walsh et  al., 2016a; Kossin et  al., 2017; Marsooli \r\net  al., 2019; Ting et  al., 2019; Knutson et  al., 2020). A  more rapid \r\nintensification of tropical cyclone winds and destructive power also "


id: f263a9459b3294964c40be1d6600e83c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 35664
content:
"Changes in North American wet and dry climatic impact\u0002drivers are largely organized by the 'north-east (more wet) to \r\nsouth-west (more dry)' pattern of mean precipitation change, \r\nalthough heavy precipitation increases are widespread and \r\nincreasing evaporative demand expands aridity, agricultural \r\nand ecological drought, and fire weather (particularly in \r\nsummer) (high confidence)."


id: 8d56819b30a5b6bd2552a95dbef23e81
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 19756
content:
"(see Atlas.9.5). Changes include a reduction in the number of days with \r\nsnowfall in across all of North America, with the exception of northern \r\nCanada (Danco et al., 2016; McCrary and Mearns, 2019), a delay of \r\nabout a  week in first snowfall in the western USA by 2050 under \r\nRCP8.5 (Pierce and Cayan, 2013), and more prominent reductions in \r\nCanadian snow cover in the October-December period (Mudryk et al., \r\n2018). Reduced total snowpack and earlier snowmelt lower dry season \r\nstreamflow (Kormos et al., 2016; Rhoades et al., 2018). Figure 12.10b \r\nshows a reduction in days suitable for skiing (SWE > 10 cm; Wobus \r\net al., 2017b) across the USA and southern Canada, although some \r\nportions of northern central Canada see an increase."


id: 3561def31ea09ee1d2bfba9d7c1428dd
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 5809
content:
"heightens the tropical cyclone hazard (Bhatia et al., 2019). Greenhouse \r\ngas forcing is projected to shift tropical cyclones poleward (Kossin \r\net al., 2016), while also holding the potential for higher precipitation \r\ntotals (Risser and Wehner, 2017; Knutson et al., 2020) particularly given \r\nevidence that storms increasingly stall near North American coastlines \r\n(Hall and Kossin, 2019)."


id: 1d983e3d9b37c826e92acdd901f9dc4
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 2098
content:
"Tropical cyclones, severe wind and dust storms in North \r\nAmerica are shifting towards more extreme characteristics, \r\nwith a  stronger signal towards heightened intensity than \r\nincreased frequency, although specific regional patterns are \r\nmore uncertain (medium confidence). Mean wind speed and \r\nwind power potential are projected to decrease in Western \r\nNorth America (medium confidence) with differences between \r\nglobal and regional models lending low confidence elsewhere."


id: a37a81835c7796204f16150f899150da
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 23283
content:
"Permafrost: Warmer ground temperatures are expected to extend the \r\ngeographical extent and depth of permafrost thaw across northern \r\nNorth America (very high confidence) (Section 9.5.2). Observations \r\nacross Canada show that permafrost temperature is increasing and \r\nthe active layer is getting thicker (Section  2.3.2.5; Derksen et  al., \r\n2018; Biskaborn et al., 2019; Romanovsky et al., 2020). Slater and \r\nLawrence (2013) note that the RCP8.5 end-of-century period in North \r\nAmerica only has shallow permafrost as the most probable condition \r\nin the Canadian Archipelago. Melvin et  al. (2017) noted the loss \r\nof shallow permafrost in five RCP8.5 CMIP5 models across a wide \r\nswathe of southern Alaska by 2050, along with increases of active \r\nlayer thickness. There is high confidence in continued reductions in \r\nmountain near-surface permafrost area with high spatial variability \r\ngiven local snow and temperature changes (Section 9.5.2; Peng et al., \r\n2018; Hock et al., 2019)."


id: afc131dc00b5f4ac1e5c76c34d10bc90
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 25169
content:
"Snow: The seasonal extent of snow cover has reduced over North \r\nAmerica in recent decades (robust evidence, high agreement) \r\n(see also Sections 2.3.2.2 and 9.5.3, and Figure Atlas.25). The average \r\nsnow-cover extent in North America decreased at a  rate of about \r\n8500  km2  yr-1 over the 1972-2015 period, reducing the average \r\nsnow cover season by two weeks, primarily due to earlier spring melt \r\n(US EPA, 2016). Observations indicate earlier spring snowpack melting \r\n(Dudley et  al., 2017) and a  reduction in end-of-season snowpack \r\nmetrics important to water resources over the Rocky Mountains \r\n(particularly since 1980) and Pacific Northwest (Pederson et al., 2013; \r\nKormos et al., 2016; Kunkel et al., 2016; Fyfe et al., 2017; Mote et al., \r\n2018). In situ measurements in Canada show more heterogenous \r\ntrends in snow amount and density (Brown et al., 2019)."


id: 647b86ebff4a79bc2a8529da9d41bdd1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 13377
content:
"Lake, river and sea ice: Anthropogenic warming reduces the seasonal \r\nextent of lake and river ice over many North American freshwater \r\nsystems, with ice-free winter conditions pushing further north with \r\nrising temperatures (high confidence). Observations in Central and \r\nEastern North America show reduced average seasonal lake-ice cover \r\nduration (Benson et  al., 2012; Mason et  al., 2016; US EPA, 2016). \r\nSatellite observations show declines in lake ice (Du et al., 2017) and \r\nloss of more than 20% of winter river-ice length in much of Alaska \r\n(2008-2018 compared to 1984-1994; Yang et al., 2020a). Spring lake \r\nand river ice in Canada is projected to break up 10-25 days earlier \r\nwhile autumn freeze-up occurs 5-15 days later by mid-century, with \r\nlarger declines in lake-ice season closer to the coasts (Dibike et  al., \r\n2012) and for rivers in the Rocky Mountains and north-eastern USA "


id: d37a0cc75e8bdc88a67bc8f7fe8b5883
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 30797
content:
"(Yang et al., 2020a), although global models have difficulty with frozen \r\nfreshwater system dynamics (Derksen et al., 2018). Substantial ice loss \r\nis projected over the Laurentian Great Lakes (Hewer and Gough, 2019; \r\nMatsumoto et  al., 2019). The southern extent of lakes experiencing \r\nintermittent winter ice cover moves northward with rising temperature, \r\npushing nearly out of the continental USA at low elevations under a \r\n4.5degC GWL (Sharma et al., 2019). Higher spring flows and the potential \r\nfor winter thaws are also projected to heighten the threat of ice jams \r\n(Rokaya et al., 2018; Bonsal et al., 2019) while reducing the seasonal \r\nviability of ice roads and recreational use (Pendakur, 2016; Mullan \r\net al., 2017; Knoll et al., 2019)."


id: df799d88e24b10a3411e64fe07ae4d31
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 32661
content:
"Snow avalanche: There is limited evidence of directional changes \r\nin snow avalanches over North America. Mock and Birkeland \r\n(2000) identified a  1969-1995 decrease in snow avalanches over \r\nthe western United States, although they note the heavy influence \r\nof natural variability. A similar decline was observed over western \r\nCanada (Bellaire et al., 2016; Sinickas et al., 2016), but clear trends \r\nare difficult to discern given sparse observations and shifts in \r\navalanche management. We concur with the SROCC assessment \r\nof medium confidence and high agreement that snow avalanche \r\nhazards generally decrease at low elevations given lower snowpack, \r\neven as high elevations are increasingly susceptible to wet-snow \r\navalanches (Hock et al., 2019; see also Lazar and Williams, 2008)."


id: ad13a8061baae62f968f17dada283e64
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 24775
content:
"Seasonal sea ice coverage along the majority of Canadian and Alaskan \r\ncoastlines is declining (robust evidence, high agreement) and there is \r\nhigh confidence that sea ice loss continues under climate change, as \r\nfurther assessed in Section 12.4.9."


id: 6c05c1bf89595ea8da3af46566822d8a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 14621
content:
"Observations and projections agree that snow and ice CIDs \r\nover North America are characterized by reduction in glaciers \r\nand the seasonality of snow and ice formation, loss of shallow \r\npermafrost, and shifts in the rain/snow transition line that \r\nalters the seasonal and geographic range of snow and ice \r\nconditions in the coming decades (very high confidence)."


id: f93b28014d8cbc238cef2b249d4f80d7
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 36720
content:
"Ice storm: There is limited evidence in the literature of unique \r\nchanges in ice storms observed or projected over North America. \r\nGroisman et al. (2016) examined 40 years of observations and found \r\nweak decreases in freezing rain events over the south-eastern USA \r\nin the most recent decade. Ning and Bradley (2015) project that the \r\naverage snow-rain transition line, which is associated with mixed \r\nprecipitation, moves 2deg latitude northward over Eastern North \r\nAmerica by the end of the 21st  century under RCP4.5 (4deg under \r\nRCP8.5; see also Klima and Morgan, 2015)."


id: 5d29901490c752fc4900a29d14ff4bba
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 12174
content:
"Relative sea level rise is virtually certain to continue in the oceans \r\naround North America, except in the northern part of north-eastern \r\nCanada and portions of southern Alaska. Regional mean RSLR \r\nprojections for the oceans around North America range from 0.4-1.0 \r\nm under SSP1-2.6 to 0.7-1.4 m under SSP5-8.5 for 2081-2100 relative \r\nto 1995-2014 (median values), which means that there are locally \r\nlarge deviations from the projected GMSL change (Section 9.6.3.3), \r\nincluding decreases in RSL in northern north-eastern Canada \r\nfrom land uplift (see also Sweet et al., 2017; Greenan et al., 2018; \r\nOppenheimer et al., 2019). The RSLR projections here may however \r\nbe underestimated due to potential partial representation of land \r\nsubsidence in their assessment (Section 9.6.3.2)."


id: bea3ca9d045cc68f823a80b28caa676
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 27547
content:
"Hail: There is limited evidence and low agreement for observed \r\nchanges in the frequency or intensity of North American hail \r\nstorms. J.T. Allen et al. (2015) and Allen (2018) found that temporal \r\ninconsistencies in the US and Canadian hail records made long-term \r\nclimate analysis difficult, although B.H. Tang et al. (2019) identified \r\nan increasing frequency of environmental conditions conducive \r\nfor large hail (diameter >= 5 cm) over the central and eastern USA. \r\nThere is limited evidence and medium agreement in projections of \r\nincreased hail damage potential over North America. Some regional \r\nand convective-permitting model projections indicate a longer hail \r\nseason with fewer events and larger hail sizes that result in higher \r\nhail damage potential (Brimelow et al., 2017; Trapp et al., 2019)."


id: f507f07650a7d0a37c1f924d705a50f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 36064
content:
"with particularly high retreats in NWN (160 m) and CNA (330 m). The \r\ntotal length of sandy coasts in North America that are projected to \r\nretreat by more than a median of 100 m by 2100 under RCP4.5 and \r\nRCP8.5 is about 15,000 km and 25,000 km respectively, an increase \r\nof approximately 70%."


id: 9a4d544ea46a2521357f05520544816f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 21805
content:
"Marine heatwave: There is high confidence in observed increases \r\nin marine heatwave (MHW) frequency and future increases in marine \r\nheatwaves are very likely around North America (Box 9.2). The total \r\nnumber of MHW days per decade increased in the North American \r\ncoastal zone, albeit somewhat more in the Pacific (Oliver et al., 2018; \r\nSmale et  al., 2019). Projected increases in degree heating weeks \r\n(Heron et al., 2016) and degree heating months (Frieler et al., 2013) \r\nindicate increasing bleaching-level and mortality-level heating stress \r\nthreshold events for reefs in Florida and Mexico."


id: 3554ba9fb263adce90ec99972fdf7ac1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 5802
content:
"Mean SST is projected to increase by 1degC (3degC) around North America by \r\n2100, with a  hotspot of around 4degC (5degC) off the North American \r\nAtlantic coastline under RCP4.5 (RCP8.5) conditions (see Interactive \r\nAtlas). Frolicher et al. (2018) projected increasing MHW frequency and \r\nspatial extent at a 2degC global warming level with the largest increases \r\nin the Gulf of Mexico and off the southern USA East Coast (>20x) as \r\nwell as off the coast of the Pacific Northwest (>15x). Projections for \r\nSSP1-2.6 and SSP5-8.5 both show an increase in MHWs around North \r\nAmerica by 2081-2100, relative to 1985-2014 (Box 9.2, Figure 1)."


id: b2f364a80c8b4e811c40e423a14aa17b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 25666
content:
"There is high confidence that most coastal CIDs in North America \r\nwill continue to increase in the future with climate change. An \r\nobserved increase in relative sea level rise is virtually certain to \r\ncontinue in North America (other than around the Hudson Bay \r\nand southern Alaska) contributing to more frequent and severe \r\ncoastal flooding in low-lying areas (high confidence) and \r\nshoreline retreat along most sandy coasts (high confidence). \r\nMarine heatwaves are also expected to increase all around the \r\nregion over the 21st century (high confidence)."


id: 764ce71d881e7d88808e7ddf8b536eda
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 16202
content:
"Coastal erosion: There is limited evidence of changes in North \r\nAmerican episodic storm erosion caused by waves and storm surges. \r\nObservations show increased extreme wave energy on the Pacific \r\ncoast, but no clear trend on other USA coasts given substantial \r\nnatural variability (Bromirski et al., 2013; Vose et al., 2014). In terms of \r\nlong-term coastal erosion, shoreline retreat rates of around 1 m yr-1\r\nhave been observed during 1984-2015 along the sandy coasts of \r\nNWN and NCA while portions of the US Gulf Coast have seen a retreat \r\nrate approaching 2.5 m yr-1 (Luijendijk et al., 2018; Mentaschi et al., \r\n2018). Sandy shorelines along ENA and WNA have remained more or \r\nless stable during 1984-2014, but a shoreline progradation rate of \r\naround 0.5 m yr-1 has been observed in NEN. Mentaschi et al. (2018) \r\nreport 1984-2015 coastal area land losses of 630 km2 and 1260 km2 \r\nalong the Pacific and Atlantic coasts of the USA, respectively."


id: b8f8007befe2a35f24eaae310cfc9635
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 26635
content:
"The assessed direction of change in climatic impact-drivers for North \r\nAmerica and associated confidence levels are illustrated in Table 12.8."


id: a82701cf22f7184629e98984bc64d0bb
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 23974
content:
"Projections indicate that sandy coasts in most of the region \r\nwill experience shoreline retreat through the 21st  century (high \r\nconfidence). Median shoreline change projections presented by \r\nVousdoukas et  al. (2020b) show that sandy shorelines in NWN, \r\nENA, and NCA will retreat by between 40 and 80 m by mid-century \r\n(relative to 2010) under both RCP4.5 and RCP8.5. Projections for NEN \r\nand WNA are lower at 20-30 m under the same RCPs. The highest \r\nmedian mid-century projection in the region is for CNA at around \r\n125 m under both RCPs. RCP4.5 projections for 2100 show shoreline \r\nretreats of 100 m or more along the sandy coasts of NWN, CNA, \r\nand NCA, while retreats of between 40 and 80 m are projected in \r\nother regions. Under RCP8.5, retreats exceeding 100 m are projected \r\nin all regions except NEN and WNA (approximately 80 m) by 2100, "


id: 8c4d9b350ad1e6d7d11d77c677105a50
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 19582
content:
"et al., 2018; Taylor et al., 2018), with livestock temperature-humidity \r\ntolerance thresholds increasingly surpassed (Lallo et  al., 2018). \r\nIn  CAR, a  median increase of more than a month per year where \r\ntemperatures exceed 35degC is projected by end of the 21st century \r\nunder SSP5-8.5 (Figure  12.4a-c and Figure  12.SM.1). Heatwaves \r\nare projected to increase in CAR by the mid- and end-century under \r\nRCP8.5 (Sections 11.3.5 and 11.9, and Table 11.13). Figure 12.4d-f \r\nand Figure 12.SM.2 also show an increase of about 30-60 days in \r\nwhich HI exceeds 41degC by 2041-2060 under SSP5-8.5 relative to \r\n1995-2014 in CAR, with an additional increase of about 50-100 \r\ndays by end of the 21st  century for RCP8.5/SSP5-8.5, but this \r\nincrease remains below 50 days for RCP2.6/SSP1-2.6. The Pacific \r\nIslands region is also among those projected to have an increase in \r\nWBGT by end-century under RCP8.5, increasing the risk of heat stress \r\nin the region (Newth and Gunasekera, 2018)."


id: 27f28078140e9c4f231f4101fb502009
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 3694
content:
"It is very likely that the significant recent warming trends \r\nobserved in the small islands will continue in the 21st century, \r\nwhich will likely further increase heat stress in these regions."


id: 6301cbf5bf6b911b7f6c4f1aa62cdb2e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 13148
content:
"The AR5 identified the key climate and ocean-related hazards affecting \r\nsmall islands, which occur at different time scales and have diverse \r\nimpacts on multiple sectors (Christensen et al., 2013; Nurse et al., 2014). \r\nRecent findings from SR1.5 and SROCC emphasize that the multiple \r\ninterrelated climate hazards currently faced by low-lying islands and \r\ncoastal areas will be amplified in the future, especially at higher global \r\nwarming levels (Hoegh-Guldberg et al., 2018; IPCC, 2019b)."


id: d3a3c08a081e6fef8aef8f884019bd6a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 30822
content:
"Mean precipitation: Observational datasets have generally \r\nrevealed no significant long-term trends in rainfall in the Caribbean \r\nover the 20th century when analysed at seasonal and inter-decadal \r\ntimescales, except for some areas where there is evidence for \r\ndecreasing trends for the period 1901-2010 but not for the period \r\n1951-2010 (Cross-Chapter Box Atlas.2, Table  1, and Atlas.10.2; \r\nKnutson and Zeng, 2018). Although there are spatial variations, \r\nannual rainfall trends in the western Indian Ocean are mostly \r\ndecreasing, with generally non-significant trends in the western \r\ntropical Pacific since the 1950s (low confidence). Significant drying \r\ntrends are noted in the southern Pacific subtropics and south-western \r\nFrench Polynesia during the 1951-2015 period (McGree et al., 2019), \r\nand in some areas of Hawaii during the 1920-2012 period (medium \r\nconfidence) (Cross-Chapter Box Atlas.2, Table 1, and Atlas.10.2)."


id: efd337961fdb20821e24dfc05f5f903e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 35238
content:
"Mean air temperature: Significant warming trends are clearly \r\nevident in the small islands, such as those in the Pacific, CAR, \r\nand western Indian Ocean, particularly over the latter half of the \r\n20th  century (see Figure Atlas.11; Atlas.10.2; Cross-Chapter Box \r\nAtlas.2, Table  1). This observed warming signal in the tropical \r\nwestern Pacific has been attributed to anthropogenic forcing (Wang \r\net al., 2016). There is high confidence of warming over small islands \r\neven at 1.5degC GWL (Atlas.10.4 and Figure Atlas.28; Hoegh-Guldberg \r\net al., 2018). Mean temperature is very likely to increase by 1degC-2degC \r\n(2degC-4degC) by 2041-2060 (2081-2100) under RCP8.5 (BOM and \r\nCSIRO, 2014) and SSP3-7.0 (Atlas.10.4, Figure  4.19 and Figure \r\nAtlas.12; Almazroui et al., 2021)."


id: 53db677a4ee213472e1d1e9eb24050ef
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 10661
content:
"Atlas.10.4 projects precipitation reduction over the Caribbean \r\n(high confidence) (Almazroui et al., 2021) and parts of the Atlantic and \r\nIndian oceans, particularly in June to August, by end of 21st century \r\nunder SSP5-8.5. Precipitation is generally projected to increase under \r\nSSP5-8.5 and for higher GWLs in the small islands in parts of the \r\nwestern and equatorial Pacific, but there is low confidence in broad \r\nchanges given drier conditions projected for the southern subtropical \r\nand eastern Pacific Ocean (limited agreement given spatial and \r\nseasonal variability) (Atlas.10.4 and Figure Atlas.28)."


id: 944b7fb997dcce08c8198d13a856e88d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 20842
content:
"Extreme heat: Observational records indicate warming trends in \r\nthe temperature extremes since the 1950s in CAR and the Pacific \r\nsmall islands (high confidence) (Sections 11.3.2 and 11.9, and \r\nTable 11.13). A detectable anthropogenic increase in summer heat \r\nstress has been identified over a number of island regions in CAR, \r\nwestern tropical Pacific, and tropical Indian Ocean, based on wet bulb \r\nglobe temperature (WBGT) index trends for 1973-2012 (medium \r\nconfidence) (Knutson and Ploshay, 2016). An increasing trend in \r\nthe maximum daytime heat index is also noted in CAR during the \r\n1980-2014 period, as well as more extreme heat events since 1991 \r\n(Ramirez-Beltran et al., 2017)."


id: 81e5288253666ed8b61ee1fb1f635c46
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 17963
content:
"River flood: There is limited evidence on observed changes in river \r\nflooding in the small islands. Long-term records in Hawaii indicate \r\nno clear trends in peak flow, except for the significant decrease \r\nin peak streamflow in Hawaii Island over the period 1967-2016 \r\n(Bassiouni and Oki, 2013; Clilverd et  al., 2019). Similarly, there is \r\nno significant trend in the frequency and height (after adjusting for \r\naverage sea level rise) of river flood in Fiji over the period 1892-2013 \r\n(McAneney et al., 2017). There is low confidence on the direction of \r\nfuture change of river flooding in the small islands due to the limited \r\nliterature. In Oahu, Hawaii, extreme peak flow events with high "


id: ffff430ca185906f2f8cef6f2c5190e0
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 37810
content:
"Compared with the recent past, it is likely that the intensity and \r\nfrequency of hot (cold) temperature extremes will increase (decrease) \r\nin the small islands (Section 11.9 and Table 11.13; BOM and CSIRO, \r\n2014). Warm spell conditions will occur up to half the year in CAR \r\nat 1.5degC GWL with an additional 70 days at 2degC (Hoegh-Guldberg "


id: 9d318f89757953b5d8beacf0bd92ca9
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 22264
content:
"return periods are projected to increase by end of the 21st century \r\nunder RCP8.5, but there is also high uncertainty in these projections \r\n(Leta et al., 2018)."


id: eb0c691171f8e2ad283fdbd2b236ed5f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 34485
content:
"Hydrological drought: There is low confidence of widespread \r\nchanges to hydrological drought in CAR or Pacific small islands in \r\nrecent decades, although an increasing number of studies document \r\nlocal changes. Records in Hawaii indicate downward trends in low \r\nstreamflow and base flow from 1913 to 2008 (Bassiouni and Oki, \r\n2013). Decadal variability of Hawaiian streamflow coincides with \r\nrainfall fluctuations associated with the Pacific Decadal Variability \r\nalthough significant average declines in surface and baseflow runoff \r\nof about 8% and 11% per decade, respectively, have been noted \r\nduring the 1987-2016 period (Clilverd et al., 2019)."


id: 2979df9aae719fdc29e094b0b2706016
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 3961
content:
"There is low confidence in hydrological drought change projections, \r\ngiven low signal-to-noise ratios and the challenge in representing \r\nisland scales in global analyses. Prudhomme et al. (2014) recognized \r\nCAR as one of the regions with the highest increase in regional \r\ndeficit index (RDI; a measure of the fraction of area in hydrological \r\ndrought conditions) by the end of the 21st  century under RCP8.5. \r\nDaily streamflow and extreme low flows in two watersheds in Oahu, \r\nHawaii are projected to decline by mid- and end of the 21st century \r\nunder RCP4.5 and RCP8.5, which would result in more frequent \r\nhydrological droughts in this area (Leta et al., 2018)."


id: bfc22b635ca91b77f77fadddf42872e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 27728
content:
"Landslide: Heavy rainfall, such as from tropical cyclones, can trigger \r\nlandslides over steep terrain in the small islands (Bessette-Kirton \r\net al., 2019). There is limited evidence to determine long-term trends \r\nin rainfall-induced landslides in the small islands (Kirschbaum et al., \r\n2015; Sepulveda and Petley, 2015; Froude and Petley, 2018; Bessette\u0002Kirton et  al., 2019). There is low confidence in future changes in \r\nlandslides in the small islands. The direction of change may depend \r\non future changes in precipitation, tropical cyclones, climate modes \r\n(e.g.,  El Nino-Southern Oscillation, ENSO), as well as human \r\ndisturbance, but more data and understanding of the complexity of \r\nthese relationships are needed, especially in these vulnerable areas \r\n(Sepulveda and Petley, 2015; Gariano and Guzzetti, 2016; Froude and \r\nPetley, 2018)."


id: b4a0dbcfa95f7f8d2164a9d09d5a243a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 25953
content:
"Fire weather: There is limited evidence on trends in wildfire in CAR \r\nand the Pacific. Records of wildfire in Hawaii from 2005 to 2011 \r\nindicate a peak in area burned during the hot and dry summer months, \r\nbut Trauernicht et al. (2015) note the difficulty in establishing the link \r\nbetween past climate and wildfire trends due to human activities and \r\nvegetation changes. Availability of literature limits assessment on \r\nfuture fire weather in the small islands. Drying and warming trends \r\ntend to increase fire probability aside from the climate impact on fuel \r\nloading, for example, grassland fires in Hawaii (Trauernicht, 2019), and \r\nwildfires in Puerto Rico (Van Beusekom et al., 2018)."


id: ce4255661d4bb11d0148c242f3a4e89b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29971
content:
"Observed and projected rainfall trends vary spatially across \r\nthe small islands. Higher evapotranspiration under a warming \r\nclimate are projected to partially offset future increases \r\nor amplify future reductions in rainfall, resulting in drier \r\nconditions and increased water stress in the small islands \r\n(medium confidence)."


id: 6d85ddd0f59dc690c462fbf54db12d79
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 14839
content:
"Projections indicate that small islands will generally face \r\nfewer but more intense tropical cyclones (medium confidence) \r\nalthough there is substantial variability across small island \r\nregions given projected regional shifts in storm tracks."


id: 5d9b3dfa259c2856253938ad4723bca4
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 12252
content:
"Relative sea level: Relative sea level rise (RSLR) continues to be \r\na major threat to small islands and atolls, since it can exacerbate the \r\nimpacts of other climate hazards on low-lying coastal communities \r\nand infrastructures, ecosystems, and freshwater resources (Nurse \r\net al., 2014; Hoegh-Guldberg et al., 2018). In the Indian Ocean-South \r\nPacific region, a new tide gauge-based reconstruction finds a regional \r\nmean RSL change of 1.33 [0.80 to 1.86] mm yr-1 over 1900-2018 \r\n(Frederikse et  al., 2020) compared to a  GMSL change of around \r\n1.7  mm yr-1 (Section  2.3.3.3 and Table  9.5). RSLR rates based on \r\nsatellite altimetry for the period 1993-2018 in the region increased \r\nto 3.65 [3.23 to 4.08] mm yr -1 (Frederikse et al., 2020), compared to \r\na GMSL change of 3.25 mm yr-1 (Section 2.3.3.3 and Table 9.5). "


id: 8169c692bcc1b696cf95a8985bf8ed8d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 17889
content:
"Tropical cyclone: Tropical cyclones have devastating impacts on the \r\nsmall islands due to intense winds, storm surge and rainfall, although the \r\nassociated rainfall can also be beneficial for freshwater resources. It is \r\nlikely that tropical cyclone intensity and intensification rates at a global \r\nscale have increased in the past 40 years but it is not clear if regional\u0002scale changes are basin-wide or due to shifts in tropical cyclone tracks \r\n(Section 11.7.1.2). Other, less data-sensitive tropical cyclone features, \r\nsuch as the poleward migration of where tropical cyclones reach \r\npeak intensity in the western North Pacific since the 1940s (medium \r\nconfidence) and the slowdown in tropical cyclone translational speed \r\nover contiguous USA since 1900 (medium confidence), can affect rainfall \r\nand flooding over small islands in CAR and the Pacific (Section 11.7.1.2)."


id: 4f8f1f53eda2ce8dba958f3605262fce
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 9948
content:
"Relative sea-level rise is very likely to continue surrounding the \r\noceans in the Small Island States. Around the small islands, regional \r\nmean RSLR projections vary widely, from 0.4-0.6 m under SSP1-2.6 \r\nto 0.7-1.6 m under SSP5-8.5 for 2081-2100 relative to 1995-2014 \r\n(median values), but in general they are situated in areas with RSL \r\nchanges ranging from the mean projected GMSL change to above\u0002average values (Section  9.6.3.3). These RSLR projections may \r\nhowever be underestimated due to potential partial representation \r\nof land subsidence in their assessment (Section 9.6.3.2)."


id: a4730f4d4fe3cb7f55f785f4778af066
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 23440
content:
"Coastal flood: Relative sea level rise, storm surges and swells \r\ncontribute to coastal inundation in the small islands, where studies \r\non historical trends in coastal flooding are currently limited. For \r\nexample, a  swell event due to distant extratropical cyclones in \r\nDecember 2008 raised extreme water levels leading to flooding \r\naffecting five Pacific island nations: Marshall Islands, Micronesia, \r\nPapua New Guinea, Kiribati and Solomon Islands (Hoeke et al., 2013; \r\nMerrifield et al., 2014). Over low-lying atoll islands in the north-west \r\ntropical Pacific, potential increases in the frequency and areal extent \r\nof coastal flooding, especially at higher SLR scenarios, are expected \r\nto have negative consequences for freshwater resources and island \r\nhabitability (Storlazzi et al., 2015, 2018). Select tide gauges across \r\nthe Pacific also indicate increasing trends in the frequency of minor \r\nflooding since the 1960s (Marra and Kruk, 2017)."


id: 49e4569c54550cd27e01888fe3369745
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
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vector_id: 9028
content:
"As relative sea levels increase, the potential for coastal flooding \r\nincreases in the small islands (high confidence). Across the Pacific and \r\nCAR small islands, the 5-95th percentile range of the 1-in-100-year \r\nETWL is projected to increase (relative to 1980-2014) by 10-35 cm \r\nand by 14-41 cm by 2050 under RCP4.5 and RCP8.5, respectively \r\n(Figure 12.4q). By 2100, this range is projected to be 27-81 cm and \r\n44-188 cm under RCP4.5 and RCP8.5, respectively (Figure 12.4p,r; \r\nVousdoukas et al., 2018; Kirezci et al., 2020). Furthermore, by 2050, \r\nthe present-day 1-in-100-year ETWL is projected to have median \r\nreturn periods of between 1-in-1-year and 1-in-50-year in both the \r\nPacific and CAR small islands, with some Pacific islands projected \r\nto experience the present-day 1-in-100-year ETWL more than once "


id: 152670a5305d546d3e53c0e0af5e8f37
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 840
content:
"d chang\r\ned in C\r\nd). The t\r\n and Co\r\nEtht\r\nCold spell\r\n confiden\r\nease in p\r\nin weste\r\nh Pacific\r\n/sources \r\ne)\r\no high c\r\n5-8.5 (m"


id: 8bc5c13acf70abc36b49217048428af8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 19507
content:
"a decrease in frequency (two annual events) over the eastern Pacific \r\nOcean (Box 9.2; Oliver et al., 2018). The intensity of MHWs has also \r\nincreased between 0.2degC and 0.5degC over the equatorial portions of \r\nthe North Atlantic and the South Pacific. Over the eastern tropical \r\nPacific, the decrease in intensity and duration of MHW is between \r\n0.5degC and 1.0degC and between 30 and 75 days, respectively (Box 9.2; \r\nOliver et al., 2018). There is high confidence that MHWs will increase \r\naround all small island nations. Marine heatwaves are projected to \r\nbe more intense and prolonged where the largest changes are noted \r\nin the equatorial region with maximum annual intensities up to 1.2degC \r\n(1.8degC) and annual mean duration reaching 100 days (200 days) at \r\n1.5degC (2.0degC) warming levels (Frolicher et al., 2018). Projections for \r\nSSP1-2.6 and SSP5-8.5 both show an increase in MHWs around all \r\nsmall island nations by 2081-2100, relative to 1985-2014 (Box 9.2, \r\nFigure 1)."


id: 8e71376138bc880435c0adf2746e5f66
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 19933
content:
"a year (Vousdoukas et al., 2018; Oppenheimer et al., 2019). By 2100, \r\nthe present-day 1-in-50-year ETWL is projected to occur around \r\nthree times a year by 2100 with an SLR of 1 m at Pacific and CAR \r\nsmall islands (Vitousek et al., 2017). In the western tropical Pacific, \r\nthe magnitude and frequency of coastal flooding due to SLR can be \r\nmodulated by changes in the wave climate (Shope et al., 2016)."


id: 521db7356a9efbf5c74b254f5cfa3b23
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 10372
content:
"In summary, relative sea level rise is very likely in the oceans \r\naround small islands, and along with storm surges and waves \r\nwill exacerbate coastal inundation in small islands. Shoreline \r\nretreat is projected along sandy coasts of most small islands \r\n(high confidence). There is high confidence that MHWs will \r\nincrease around all small island nations."


id: 52e89928e333f4405cda9aa5f4ae11bb
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 10499
content:
"The assessed direction of change in climatic impact-drivers for \r\nCAR and Pacific small islands and associated confidence levels are \r\nillustrated in Table 12.9. Cold, snow, and ice-related climatic impact\u0002drivers, and sand and dust storms are not broadly relevant in the small \r\nislands that were assessed."


id: 64a25e055a44d3e1637604c62d2e3347
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 13408
content:
"Mean ocean temperature: It is very likely that global mean sea \r\nsurface temperature (SST) has increased by 0.88 [0.68 to 1.01] degC "


id: cc2595ebf6325018f14e7a5533b6b40c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29659
content:
"and polar zones (Sections 2.3.3.5 and 5.3.3.2). Over the period \r\n1870-1899 to 2080-2099, ocean surface pH is projected to decline \r\nby -0.16  +-  0.002 under SSP1-2.6, and by -0.44 +- 0.005 under \r\nSSP5-8.5 (Sections 4.3.2.5 and 5.3.4.1). Declining ocean pH will \r\nexacerbate negative impacts on marine species (medium confidence) \r\n(Albright et al., 2016; Kwiatkowski et al., 2016; Watson et al., 2017)."


id: 8e7b8aa704574a22719dd1d82b98ba0a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 19939
content:
"Ocean salinity: Salinity contrasts have increased since the 1950s, \r\nnear the ocean surface (virtually certain) and in the subsurface \r\n(very likely), with high-salinity regions becoming more saline and \r\nlow-salinity regions becoming fresher (Section  2.3.3.2). At the \r\nbasin scale, it is very likely that the Pacific and the Southern Oceans \r\nhave freshened and that the Atlantic has become more saline \r\n(Section 2.3.3.2). The SROCC (IPCC 2019b) assessment that a general \r\npattern of fresh ocean regions getting fresher and salty ocean \r\nregions getting saltier will continue in the 21st century is confirmed \r\nin Section 9.2.2.2."


id: 3ae6bed6651fd6fa744771e1eead218e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 6633
content:
"Ocean acidity: With the increasing CO2 concentration, the global \r\nmean ocean surface pH is decreasing and is now the lowest it \r\nhas been for at least a  thousand years (very high confidence) \r\n(Section  2.3.3.5). It is very likely that, since the 1980s, ocean \r\nsurface pH has changed at a rate of -0.016 to -0.019 per decade in \r\nthe subtropical open oceans, at -0.010 to -0.026 per decade in the \r\ntropical Pacific, and at -0.003 to -0.026 per decade in open subpolar "


id: a242e119c072abe310145ce4248ec5ed
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 23096
content:
"there is medium confidence in specific regional declines that are \r\nexpected to expand both anoxic and hypoxic zones, with such \r\nreductions of oxygen expected to persist for thousands of years \r\n(Yamamoto et al., 2015; Frolicher et al., 2020)."


id: c7c6c78fb576aec5d79503764e0462c8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29007
content:
"25 days per decade for later autumn advance, with consequences for \r\nArctic marine mammals (AMMs) due to sea ice habitat loss (Laidre \r\net al., 2015). The Arctic is projected to be ice-free more often during \r\nsummer under 2degC global warming compared to 1.5degC global warming \r\n(Section 9.3.1.1; see also Sections 12.4.9 and 4.4.2.1), opening new \r\nshipping lanes for international commerce (Valsson and Ulfarsson, \r\n2011) and lengthening the season for offshore resource extraction \r\n(Schaeffer et al., 2012). Iceberg numbers are expected to increase as \r\na result of global warming, forming an elevated hazard to shipping and \r\noffshore facilities (Bigg et al., 2018)."


id: 740da5c03d8e212fbed5c700865f431f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 15860
content:
"Sea ice: The Arctic sea ice area for September has decreased from 6.23 \r\nto 3.76 million km2 and for March from 14.52 to 13.42 million km2\r\nbetween 1979-1988 and 2010-19 (Section 2.3.2.1.1). There is high \r\nconfidence that sea ice in the Arctic will further decrease in the future \r\nunder all emissions scenarios (Section 9.3.1.1). In contrast, there is no \r\nclear observed trend in the Antarctic sea ice area over the past few \r\ndecades and there is low confidence of future changes (Section 9.3.1.1). \r\nThe duration of the summer ice season in the Arctic has increased by 5 \r\nto 20 weeks between 1979 and 2013, with a significant trend ranging \r\nfrom 5 to 17 days per decade for earlier spring retreat and from 5 to "


id: 1365da8df23c2c7c00d7dccd090b93aa
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 564
content:
"It is virtually certain that global mean SST will continue \r\nto increase throughout the 21st  century, resulting in the \r\nexceedance of numerous climatic impact-driver thresholds \r\nrelevant to marine ecosystems (medium confidence). Marine "


id: 1dfc4c30dbbb627a501ef2f046294cf6
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 2149
content:
"Table 12.10 | Summary of confidence in direction of projected change in climatic impact-drivers in open and deep ocean regions, representing their \r\naggregate characteristic changes for mid-century for scenarios RCP4.5, SSP2-4.5, SRES A1B, or above within each AR6 region (defined in Chapter 1), \r\napproximately corresponding (for CIDs that are independent of sea level rise) to global warming levels between 2degC and 2.4degC (see Section 12.4 for \r\nmore details of the assessment method). The table also includes the assessment of observed or projected time-of-emergence of the CID change signal from the natural \r\ninterannual variability if found with at least medium confidence in Section 12.5.2. Asterisks indicate regions that extend across both sides of the map."


id: aa55ddd709f2032eb2922bf3c2cc86df
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
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content:
" Emerging after 2050 and by 2100 at least in scenarios RCP8.5/SSP5-8.5 (medium to high confidence)"


id: ad67e707c8f54453e5a3a8fff4027ef4
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 24818
content:
"heatwave days are projected to increase in global oceans, with \r\na larger increase in the tropical ocean and Arctic Ocean (high \r\nconfidence). It is virtually certain that upper-ocean stratification \r\nwill continue to increase in the 21st  century. Future ocean \r\nwarming will very likely assist the development of both anoxic \r\nand hypoxic zones, with such reductions of oxygen expected to \r\npersist for thousands of years. Future projections also indicate \r\nfreshening of the Pacific, Southern and Indian oceans and \r\na saltier Atlantic Ocean (medium confidence)."


id: 33b5dbe6138f3f78c862adca9bc2f9c3
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 5553
content:
"on higher mean temperatures, with J.R. Lee et al. (2017) projecting \r\nmore than 50 additional degree days above freezing (2098 RCP8.5 \r\ncompared with 2014) over parts of the Antarctic Peninsula but \r\nsmaller changes over mainland Antarctica."


id: d6a18fe955243569fc7f17cea971534c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 31275
content:
"Mean precipitation: Atlas.11.2 indicated medium confidence in \r\nobserved increases in Arctic precipitation, with the largest rises in the \r\ncold season. Antarctic precipitation showed no significant overall \r\ntrend since the 1970s, with a positive trend over the 20th century \r\n(Sections 9.4.2.1 and Atlas.11.1). Increases in Arctic and Antarctic \r\nprecipitation during the 21st century are very likely, with projected \r\npercentage increases that are much higher than most subpolar \r\nregions of the world (Figure Atlas.29)."


id: 44c47cf65dba82605ac82a75f7ee81c8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
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vector_id: 8241
content:
"The assessed direction of change in climatic impact-drivers for \r\nopen and deep ocean regions and associated confidence levels are \r\nillustrated in Table  12.10, following the AR6 WGI ocean reference \r\nregions (Figure Atlas.2b)."


id: 5f10970cc1d9aeeddd28629de95e749e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
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vector_id: 12504
content:
"Floods and heavy precipitation: Observations and model \r\nprojections indicate high confidence in increasing Arctic river runoff \r\nin response to increasing total precipitation (Box et  al., 2019; \r\nDurocher et  al., 2019; Meredith et  al., 2019) with a  shift towards \r\nearlier meltwater flooding (AMAP, 2017). Higher Arctic precipitable \r\nwater totals are also connected with observed increases in heavy \r\nprecipitation and convective activity (high confidence) (Ye et  al., \r\n2015; Kharin et al., 2018; Chernokulsky et al., 2019). Higher flood \r\nmagnitudes are also driven by future increases in rain-on-snow event \r\ndays, amounts, and runoff, which are more significant in the Arctic \r\nthan in mid-latitudes (where seasonal snow cover is often further \r\nreduced; AMAP, 2017; Jeong and Sushama, 2018b)."


id: cb9f91c4863054f8634952b4d73fae1e
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 29581
content:
"Several recent climate assessments of polar regions describe robust \r\npatterns of recent and future climatic changes driving impacts and \r\nrisk for polar environmental, societal, and economic assets. These \r\nhave included the IPCC SROCC (Meredith et al., 2019), the Report \r\non Snow, Water, Ice and Permafrost in the Arctic (AMAP, 2017), and \r\nnational assessments for the USA (Markon et al., 2018) and Canada \r\n(Derksen et al., 2018). This section examines Greenland and Iceland, \r\nthe Russian Arctic, Antarctica, and the Arctic portions of Northern \r\nEurope and North America (Figure 1.18c)."


id: 7b39e7b0dbc868c8fe98dc681e8f7655
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 16976
content:
"Landslide and snow avalanche: There is a growing number of studies \r\non mass movements in polar regions. Although there is low confidence\r\nin widespread observational trends for landslides or snow avalanches, \r\na rise in the number of future landslides is supported by strong links to \r\nincreases in heavy precipitation, glacier retreat, and thawing of ice-rich \r\npermafrost that can lead to retrogressive thaw slumps in Arctic regions \r\n(Section 2.3.2.5; Kokelj et al., 2015; Derksen et al., 2018; Lewkowicz \r\nand Way, 2019; Patton et al., 2019; Ward Jones et al., 2019)."


id: bb94069d09f8a34d93f05490f7f6b264
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 27067
content:
"Mean air temperature: Atlas.11.2 shows high confidence in\r\nwarming of the Arctic in observations and projections, measuring \r\namong the fastest-warming places at more than twice the global \r\nmean, with substantially higher temperature increases in the cold \r\nseason (see also AMAP, 2017; Meredith et  al., 2019). Atlas.11.1 \r\nassessed very likely warming in observations of West Antarctica from \r\n1957 to 2016, but limited evidence of mean air temperature change \r\nacross East Antarctica even as there is high confidence in future \r\nwarming across the continent (Figure Atlas.29; Meredith et al., 2019)."


id: 863642982885b86c3c79778c5f2b59d8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 18655
content:
"Aridity and drought: Recent decades have seen a general decrease \r\nin Arctic aridity, with projections indicating a  continuing trend \r\ntowards reduced aridity (high confidence) as increased moisture \r\ntransport leads to higher precipitation, humidity and streamflow \r\n(Meredith et  al., 2019) and a  corresponding decrease in dry days \r\n(Khlebnikova et al., 2019a). There is low confidence overall of recent \r\nor projected drought changes in polar regions (Section 11.9) even \r\nas increasing evidence shows that drainage from permafrost thaw, \r\nhigher potential evapotranspiration, and changing seasonal patterns \r\nof melt have caused lake reduction and soil moisture deficits in \r\nseveral areas that match with projections of future drought increase \r\ndespite overall precipitation increases (Andresen and Lougheed, \r\n2015; Bring et al., 2016; Spinoni et al., 2018a; Feng et al., 2019; Finger \r\nHiggens et al., 2019)."


id: 46213ac38dd997cff5e46b5712b662ba
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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content:
"Fire weather: Fire season lengthened from 1979 to 2015 over Arctic \r\nportions of North America (Jain et al., 2017), corresponding also to \r\na 1975-2015 increase in lightning-ignited fires in Arctic North-Western \r\nNorth America (Girardin et  al., 2013; Veraverbeke  et  al.,  2017). "


id: c7c825a6ee32dce591acee44aa75d521
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 29009
content:
"Abatzoglou et al. (2019) climate model simulations project significant \r\nfire weather index increases in boreal forests of Arctic Europe, \r\nArctic Russia and Arctic North-Eastern North America (medium \r\nconfidence). Trends towards more frequent fires in tundra regions \r\nare expected to continue, driven in particular by increasing potential \r\nevapotranspiration and changes in vegetation (high  confidence) \r\n(Hu et al., 2015; AMAP, 2017; Young et al., 2017)."


id: 1c5d604ce126bcc62ee9472df0b37aad
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 1916
content:
"Antarctic Periphery: 7 +- 12%, 13 +- 10%, and 16 +- 19%. Areas \r\nwith receding glaciers are also potentially vulnerable to glacial lake \r\noutburst floods (Harrison et al., 2018)."


id: 37f903b6e51a97f5d2b9772e6f8d61bb
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 6180
content:
"Mean wind speed and severe storm: There is medium confidence \r\nof mean wind decrease over the Russian Arctic, Greenland and \r\nIceland, and Arctic North-Eastern North America (Karnauskas et al., \r\n2018a; Jung and Schindler, 2019), but low confidence of changes \r\nin the other Arctic regions and Antarctica. Bintanja et  al. (2014) \r\nprojected that a  strengthening of the Southern Annular Mode \r\nwould decrease easterlies along Antarctica's coasts with only small \r\nchanges in katabatic winds (although this effect may diminish \r\nwith stratospheric ozone recovery). In contrast, Gorter et al. (2014) \r\nregional climate model projections indicated a  reduction in mean \r\nwinds over the interior of Greenland by RCP4.5 2100 while coastal \r\nwinds increase. Reanalysis data and climate models indicate few \r\ncoherent regional trends of polar cyclone frequency or relationships \r\nwith cyclone depth and size (Akperov et  al., 2018, 2019; Day and \r\nHodges, 2018; Zahn et al., 2018)."


id: 65b2aa62edf0c4c9b6209ff149597a30
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 13578
content:
"Snow: Atlas.11.1 identified likely increases in surface mass balance \r\n(driven by snowfall) across Antarctica in the 20th  century (medium \r\nconfidence). In the Arctic, overall snow extent and seasonal duration \r\nare projected to continue recent declines (high confidence), although \r\nmid-winter snowpack increases in some of the coldest and high\u0002elevation locations given higher precipitation totals (medium \r\nconfidence) (Section 9.5.3, Atlas.9 and Atlas.11.2; Bring et al., 2016; \r\nDanco et  al., 2016; AMAP, 2017; Meredith et  al., 2019). Higher \r\ntemperatures result in a  higher percentage of Arctic precipitation \r\nfalling as rain (particularly in autumn and spring) (high confidence), \r\nwith most land regions (outside of Greenland and Antarctica) becoming \r\ndominated by rainfall (more than 50% of total precipitation) by RCP8.5 \r\n2100 (Bintanja and Andry, 2017; Irannezhad et al., 2017)."


id: 792ff6dad53c331671305926f6d3d9df
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 16632
content:
"Future declines in Arctic sea ice are virtually certain, although there \r\nis low confidence in declines of Antarctic sea ice given dynamical \r\nprocesses in the Southern Ocean and the recovery of stratospheric \r\nozone (Section 9.3; Meredith et al., 2019). Projections of an 'ice-free' \r\nArctic vary, depending on definitions representing transportation \r\nneeds, however Laliberte et  al. (2016) noted that the median of \r\n42 CMIP5 models projected <5% sea ice for the month of September \r\nby 2050, with equivalent conditions for the entirety of the August-\r\nOctober period by 2090. Section 9.3.1 assessed high confidence that \r\npractically ice-free conditions (<1 million km2 in the September mean) \r\nwould likely first appear before 2050 even under strong mitigation \r\nscenarios (Sigmond et al., 2018; Stroeve and Notz, 2018; Notz and \r\nSIMIP Community, 2020)."


id: 6368ff6638fdecd728d713cfac0e4809
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 13212
content:
"once every five years (or more frequently) by 2100. Arctic coastal \r\nerosion is also expected to increase with climate change (medium \r\nconfidence; high agreement but limited evidence of projections), \r\naccelerated in some regions by subsurface permafrost thaw and \r\nincreased wave energy (Gibbs and Richmond, 2015; Fritz et al., 2017; \r\nOppenheimer et al., 2019; Casas-Prat and Wang, 2020). A longer ice\u0002free season for the RCP8.5 2080s is projected to help drive more \r\nthan 100 m of shoreline retreat in North-Western North America \r\nArctic coastal communities (Melvin et al., 2017; Greenan et al., 2018; \r\nMagnan et  al., 2019). Assessment of coastal flooding and erosion \r\nchanges in Antarctica are limited by a lack of studies."


id: 8ece6c57bb9f575a0a5a394895be9d56
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 19992
content:
"Lake and river ice: There is high confidence in observations of \r\nsignificant declines in seasonal ice cover thickness and duration over \r\nmost Arctic lakes, with many lakes projected to lose more than one \r\nmonth of ice cover by mid-century (medium confidence) (Meredith \r\net al., 2019; Sharma et al., 2019). Some lakes that previously froze to \r\nthe bottom ('bedfast') now maintain liquid bottom water year round, \r\nand others shift from perennial to seasonal ice cover (Surdu et al., \r\n2016; Engram et al., 2018). Yang et al. (2020a) identified a decline in \r\nArctic cold-season river ice extent in satellite observations (particularly \r\nin Alaska) and projected reductions in average Northern Hemisphere \r\nseasonal river ice duration of 6.10 +- 0.08 days per  degree global \r\nsurface air temperature."


id: 240c671d3f82a86c2b54266b0d3d682f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 3114
content:
"Marine heatwave: Recent years have seen marine heatwaves \r\n(MHWs) and increasing extreme coastal SSTs in Arctic systems (Lima \r\nand Wethey, 2012; Collins et al., 2019; Frolicher, 2019). Projections \r\nshow increases in MHW intensity, frequency and duration will be \r\nlarger over the Arctic Ocean than mid-latitude oceans due in part to \r\nlow interannual variability under current sea ice (high confidence). \r\nFrolicher et  al. (2018) used 12 CMIP5 models to project median \r\nMHW days increasing about 25-fold and 50-fold at the 2degC and \r\n3.5degC GWLs, respectively, in response to mean ocean warming \r\nand sea ice loss, and the smallest global changes still leading to \r\nincreases in the Southern Ocean around Antarctica (see also Cross\u0002chapter Box 9.1)."


id: afe4b137fd3e330a31c3ded8f3b469c7
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 25197
content:
"Heavy snowfall and ice storm: There is limited evidence of changes \r\nin heavy snowfall due to competing influences of shortened snowfall \r\nseasonality with more intense (and larger overall) precipitation in \r\nthe Arctic. Episodic heavy snowfall trends in Antarctica are difficult \r\nto separate from large interannual variability (limited evidence) \r\n(Gorodetskaya et al., 2014, Turner et al., 2020). Limited evidence also \r\nhinders clear signals in ice storms, although warming shifts the \r\nfreezing line (around which ice storms occur) poleward and upslope \r\n(Bintanja and Andry, 2017). Groisman et  al. (2016) used 40 years \r\nof observations to identify an increase of freezing rain events in \r\nNorway, North America, and eastern and western Russia. Increases \r\nin winter rainfall have led to more frequent development of difficult \r\nwildlife and livestock grazing conditions as basal ice conditions coat \r\nthe ground below snowpack (Peeters et al., 2019)."


id: 395218ee80ccd906578a1ddf98e2bb2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 6394
content:
"Relative sea level: Satellite altimetry and tide data show that \r\nrelative sea levels (with glacial isostatic adjustment) are rising \r\nin Arctic Europe and Arctic North-Western North America, declining in \r\nportions of southern Alaska and Arctic North-Eastern North America \r\nand no clear trend in Greenland and the Russian Arctic (Sweet et al., \r\n2018; Rose et al., 2019), which is broadly consistent with findings in \r\nOppenheimer et al. (2019). Areas with low or negative change have \r\nsubstantial land uplift counteracting the global mean sea level trend \r\n(Greenan et al., 2018; Sweet et al., 2018; Madsen et al., 2019). SROCC \r\nprojections indicate high confidence in future rises in relative sea \r\nlevel for all Arctic regions other than areas of substantial land uplift \r\nin north-eastern Canada, the west coast of Greenland, and narrow \r\nportions of West Antarctica (Oppenheimer et al., 2019)."


id: fe8888a9b26be40a2d689377ba61f65d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 37586
content:
"Coastal flooding and erosion: Higher sea levels and reduced \r\ncoastal sea ice protection will increase future extreme sea levels in \r\nthe Arctic (high confidence for Arctic Northern Europe, the Russian \r\nArctic, and Arctic North-Western North America (medium confidence) \r\nfor Greenland and Iceland and Arctic North-Eastern North America \r\ngiven glacial isostatic adjustment). Vousdoukas et al. (2018) project \r\nthat the current 1-in-100-year extreme total water level would have \r\nmedian return periods of 1-in-20-years to 1-in-50-years by 2050, \r\nincreasing to 1-in-5-years to 1-in-20-years by 2100 under RCP4.5 \r\nalong nearly the entire Arctic coastline by 2100 (excluding GIC for \r\nwhich projections are not available). Projections for RCP8.5 indicate \r\nthat the present-day 1-in-100-year ETWL would have median return \r\nperiods of 1-in-10-years to 1-in-50-years by 2050 and would occur "


id: 3fdef8e79e784e4c0922b5037985a2f5
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 7432
content:
"This section focuses on CIDs affecting specific zones with heightened \r\nvulnerability and coherent characteristics that cut across traditional \r\ncontinental regions (see also Section 12.3). It is designed to match the \r\nstructure of the Cross-Chapter Papers in the WGII Report, although "


id: 65e24c6a136e806a3dd6989652654d82
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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content:
"polar regions were addressed in more extensive detail in Sections \r\n12.4.8 and 12.4.9 of this Report and the Mediterranean Region will \r\nnot be handled separately given that its climatic impact-drivers are \r\ndiscussed in Sections 12.4.1 and 12.4.5 as well as in Cross-Chapter \r\nBox 10.3."


id: 26ec34a16ac633836b90486d2875685a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 3515
content:
"In conclusion, biodiversity hotspots around the world will \r\neach face unique challenges as climatic impact-drivers change. \r\nHowever, heat, drought and length of dry season, fire weather, \r\nsea surface temperature and deoxygenation are relevant \r\ndrivers to terrestrial, freshwater and marine ecosystems, and \r\nhave marked increasing trends."


id: c4e6ee64b4faa88eebce9de41cd011c4
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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content:
"Hotspots of biodiversity are defined by the AR6 WGII as 'geographic \r\nareas with exceptionally high richness of species, including rare \r\n(endemic) species' (WGII Cross-Chapter Paper 1). The AR6 assessment \r\nis based on 238 distinctive regions often called the 'Global 200 \r\necoregions' (Olson and Dinerstein, 2002)."


id: bfa43596273c605c4007ab19415966c5
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 27709
content:
"Cities and settlements by the sea are exposed to specific climate \r\nand climate change patterns and to compound coastal hazard risks \r\n(AR6  WGII Cross-Chapter Paper 2). The AR5 WGII found that, in \r\ngeneral, 'urban climate change-related risks are increasing (including \r\nrising sea levels and storm surges, heat stress, extreme precipitation, \r\ninland and coastal flooding, landslides, drought, increased aridity, \r\nwater scarcity, and air pollution)' (Revi et al., 2014). Since AR5 \r\na  number of studies have been carried out to understand urban \r\nclimate and its change. Box 10.3 identified a continuing strong role of \r\nthe urban heat island in amplifying heat extremes in cities, although \r\nchanges in the urban heat island are an order of magnitude smaller \r\nthan projected localized warming trends (very high confidence)."


id: 6ea8fe58851f4525a0b34307be2d3b94
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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content:
"Coastal cities' proximity to the sea somewhat mitigates the effect \r\nof urban heat islands (high confidence) (Salvati et  al., 2017; \r\nSantamouris et  al., 2017; Y. Wang et  al., 2018; Martinelli et  al., \r\n2020). Cities and settlements by the sea typically experience \r\nhigher humidity levels than inland regions, combining with heat to \r\nenhance heat stress and induce exceedance of critical heat stress \r\nthresholds for outdoor activities, with potential enhanced exposure \r\nto heat for informal settlements (J. Wang et al., 2019). Such threshold \r\nexceedances are projected to increase for many coastal areas (high \r\nconfidence), including the Persian Gulf where heat stress is projected \r\nto be extreme (Pal and Eltahir, 2016; Ahmadalipour and Moradkhani, \r\n2018), and some low-lying areas in Europe such as the Po Valley and \r\ncoastal Mediterranean areas (Coppola et al., 2021a; Schwingshackl \r\net al., 2021; see also the heat stress index shown in Figure 12.4d-f)."


id: 5370263bb5a18c838a3d27a61b74c37
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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content:
"There is low confidence in broad patterns of future drying or wet \r\ntrends across the land and freshwater biodiversity hotspots in the \r\nhumid tropics, although drying trends have been detected and \r\npredicted in parts of the Amazon (Fu et al., 2013; Boisier et al., 2015). \r\nThere is medium confidence (limited evidence, high agreement) \r\nthat in several regions the length of the dry season has already \r\nincreased and is projected to further increase in some parts of the \r\nMediterranean, Amazonia and sub-Saharan Africa (Debortoli et al., \r\n2015; Dunning et al., 2018; Hochman et al., 2018; Saeed et al., 2018). \r\nLonger dry seasons also extend the seasonal length and geographical \r\nextent of fire weather in all future scenarios (medium confidence) \r\n(Jolly et al., 2015; Abatzoglou et al., 2019)."


id: 7878602e3dccf3432bff90b72c5051ac
created_at: 2023-03-16 14:00:51
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content:
"Barlow  et  al.,  2016; Otto et  al., 2018). Over the period 1961-2013, \r\nthe annual area of drylands in drought has increased, on average \r\nby slightly more than 1% per year, with large interannual variability \r\n(Olsson et al., 2019). In general, droughts have increased in several arid \r\nand semi-arid areas over the last decades (medium confidence), and \r\nare likely to increase in the future as indicated by a number of indices \r\ncalculated from climate (Liu et al., 2018b; Zkhiri et al., 2019; Coppola \r\net al., 2021b; Driouech et al., 2021; see also Figure 12.4j-l)."


id: e7b58a46ac7c6d5ae1f6243fd02af046
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 33954
content:
"cyclones are projected to become more intense and severe tropical \r\ncyclones more frequent (high confidence) (Section 11.7)."


id: c636e7079a87ec888c6269f5f99639a8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 28762
content:
"The SROCC highlighted coastal settlements in the Arctic as being \r\nparticularly exposed to several CID changes (Magnan et al., 2019). \r\nEnhanced waves, due to extended season of sea ice retreat, are \r\nprojected to foster coastal flooding and erosion (Section  12.4.9; \r\nGudmestad, 2018; Casas-Prat and Wang, 2020). Climate change is \r\nalso affecting sea ice quality and season length along coasts of the \r\nArctic Ocean where populations depend on sea ice for hunting or \r\ntransportation (Section 12.4.9; Pearce et al., 2015)."


id: dc66b4d7f1719433c9a9e4d6c7011dd2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 32178
content:
"In summary, coastal cities and settlements are particularly \r\naffected by a  number of climatic impact-drivers that have \r\nalready changed and will continue to change whatever \r\nthe emissions scenario. These include increases in extreme \r\nheat, pluvial floods, coastal erosion and coastal flood (high \r\nconfidence). Increasing relative sea level, compounding with \r\nincreasing tropical cyclone storm surge and rainfall intensity, \r\nwill increase the probability of coastal city flooding (high \r\nconfidence). Arctic coastal settlements are particularly exposed \r\nto climate change due to sea ice retreat (high confidence)."


id: fc20037403a9cccdb7677ad35dcebcf
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 37169
content:
"Drylands, which include hyper-arid, arid, semi-arid and dry sub-humid \r\nareas (IPCC, 2019c), lie on all continents and cover 46% of the global \r\nland area and host more than one-third of the current population \r\n(Olsson et al., 2019). Huang et al. (2016b) found that aridity changes \r\nhave helped expand dryland area by about 4% from 1948 to 2004, \r\nwith the largest expansion of drylands occurring in semi-arid regions \r\nsince the early 1960s. Section  4.5.1 assessed high confidence of \r\na future poleward expansion of the Hadley cell, leading to a poleward \r\nshift of dryland areas in all scenarios considered. There is no evidence \r\nof a future global trend in aridification of drylands (IPCC, 2019a), but \r\nhigh confidence of aridification in some areas (e.g., Mediterranean, \r\nCentral America, Southern Africa; IPCC, 2019a; see also Figure 12.4j-l). \r\nHowever, drivers of desertification largely include land-cover changes \r\nand land-use management, along with climate change (IPCC, 2019a)."


id: 74208940795da1745053afa31b5ee822
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 15867
content:
"In conclusion, desert and semi-arid areas are strongly affected \r\nby climatic impact-drivers such as extreme heat, drought and \r\ndust storms. Heat hazards are very likely increasing in all \r\nfuture climate scenarios, but uncertainty remains regarding \r\nany broadly consistent future changes in other climatic \r\nimpact-drivers for deserts and semi-arid regions."


id: 1804028f0c91f72a28b2fae544866e37
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 1270
content:
"Mountains cover about 30% of the land areas on Earth (not counting \r\nAntarctica) and deliver a  number of vital services to humanity \r\n(WGII Cross-Chapter Paper 5; IPCC, 2019b). Climate change in high \r\nmountains was addressed in SROCC, which emphasized changes in \r\nseveral climatic impact-drivers. These included an observed general \r\ndecline in low-elevation snow cover, glaciers and permafrost (high \r\nconfidence), which induced changes in natural hazards such as \r\ndecrease in slope stability (high confidence), changes to the frequency \r\nof glacial lake outbursts (limited evidence), and climate effects on \r\nother climatic impact-drivers (avalanche, rain-on-snow floods) with \r\nvarious degrees of confidence (Hock et al., 2019)."


id: 733332ee828701f5e13db9d38f9baeb2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 15740
content:
"Warming temperatures and extreme heat are major climatic impact\u0002drivers with multiple potential impacts on societies, health, and \r\nhabitability in semi-arid and arid regions that are already near \r\nphysiological limits for outdoor activities. Semi-arid regions will very \r\nlikely undergo a warming in all future scenarios (Chapter 4 and Atlas) \r\nand likely undergo an increase in duration, magnitude and frequency \r\nof heatwaves (Chapter 11) (Figure 12.4a-c). It is likely that heat stress \r\nwill be much more intense by the end of the century in many areas \r\nunder all scenarios, such as deserts and semi-arid zones in Asia (Murari \r\net al., 2015; Mishra et al., 2017), Australia and Africa (Zhao et al., 2015; \r\nXia et al., 2016; Guo et al., 2017; Dosio et al., 2018; Schwingshackl \r\net al., 2021), with consequences for labour productivity with respect \r\nto high heat-humidity conditions (Figure 12.4d-f)."


id: f53c744be1055aa28493d93bc8cd8bad
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 36096
content:
"There is a growing body of literature indicating elevation-dependent \r\nwarming (EDW; different rates of warming by altitude although not \r\nnecessarily increasing with altitude) in several mountain regions but \r\nnot globally (Hock et al., 2019; Pepin et al., 2019; Ahmed et al., 2020; \r\nB. Li et al., 2020; Williamson et al., 2020; You et al., 2020; Micu et al., \r\n2021). Statistically significant elevational enhancement to long\u0002term trends in maximum near-surface air temperatures and diurnal \r\ntemperature range were observed in southern central Himalaya \r\nand in the Swiss Alps (Rottler et  al., 2019; Thakuri et  al.,  2019). "


id: b7cf07576b83d4a066c4412930245296
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 26453
content:
"Aguilar-Lome et al. (2019) reported that winter daytime land surface \r\ntemperatures in the Andean region between 7degS and 20degS show \r\nthe strongest trends at higher elevations: +1.7degC per decade above \r\n5000m above sea level. Palazzi et  al. (2019) identified changes in \r\nalbedo and downward thermal radiation as key drivers of EDW \r\naccording to the simulation outputs of a  high-spatial-resolution \r\nmodel in three important mountainous areas: the Colorado Rocky \r\nMountains, the Greater Alpine Region and the Himalayas-Tibetan \r\nPlateau, but mechanisms for EDW remain complex (Hock et  al., \r\n2019). Warming is also affecting mountain lake surface temperatures, \r\nincreasing probabilities of ice-free winters and the frequency and \r\nduration of 'lake heatwaves' (high confidence) (O'Reilly et al., 2015; \r\nWoolway et al., 2020, 2021) with a high variability from lake to lake."


id: e6a8599b45fc08ffc442d451feccc818
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
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vector_id: 33771
content:
"river ice, changes in the amount and seasonality of streamflows and \r\nhydrologic droughts in snow-dominated and glacier-fed river basins \r\n(e.g., in Central Asia; Sorg et al., 2014; Reyer et al., 2017b) (medium \r\nconfidence), and decreases in the stability of mountain slopes and \r\nsnowfields. Glacier recession could lead to the creation of new glacial \r\nlakes in places like the Himalaya-Karakoram region (Linsbauer et al., \r\n2016) and in Alaska and Canada (Carrivick and Tweed, 2016; Harrison \r\net  al., 2018) (medium confidence). With increasing temperature \r\nand precipitation these can increase the occurrence of glacier lake \r\noutburst floods and landslides over moraine-dammed lakes (high \r\nconfidence) (Carey et al., 2012; Rojas et al., 2014; Iribarren Anacona \r\net al., 2015; Cook et al., 2016; Haeberli et al., 2017; Kapitsa et al., \r\n2017; Narama et al., 2018; Wilson et al., 2018; Drenkhan et al., 2019; \r\nS. Wang et al., 2020)."


id: 83956701a04afaa36b36edaaf642e37f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 18238
content:
"In conclusion, mountains face complex challenges from \r\nspecific climatic impact-drivers drastically influenced by \r\nclimate change: regional elevation-dependent warming (high \r\nconfidence), low-to-mid-altitude snow cover and snow-season \r\ndecrease even as some high elevations see more snow \r\n(high  confidence), glacier mass reduction and permafrost \r\nthawing (high confidence), and increases in extreme \r\nprecipitation and floods in most parts of major mountain \r\nranges (medium confidence)."


id: cd08e6d5606be351db2bf0c0874ec09d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 29805
content:
"Tropical forests, which are among the world's most biologically diverse \r\necosystems, are essentially located in Central and South America, \r\nAfrica and South East Asia (AR6 WGII Cross-Chapter Paper 7). The AR5 \r\nand SR1.5 indicated several specific climatic impact-driver changes \r\nthat are particularly important to tropical forests: mean temperature \r\nincrease, long-term drying trends (including shifts in the length of the \r\ndry season), prolonged drought, wildfires and surface CO2 increase for \r\ninland forests (IPCC, 2013, 2018). The SRCCL assessed an enhanced \r\nrisk and severity of wildfires in tropical rainforests (high confidence), \r\nbut fires are not only a  natural process but are also affected by \r\ndeforestation and other human influences (IPCC, 2019a)."


id: d22839de0ae15d4b716c5733a758fa56
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 30590
content:
"Temperature is rising in all tropical regions covered with forests and \r\nwill very likely continue to rise, reaching levels unprecendented in \r\nrecent decades as the temperature trends rapidly emerge from weak \r\nhistorical interannual variability (Sections 12.4.1-12.4.4 and 12.5.2; \r\nsee also Chapter 4 and Atlas)."


id: 14d621514b8b232e0cc0554854711de1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 788
content:
"Regional patterns of increasing drought or unusual wet and dry \r\nperiods are predicted with agreement over many climate models \r\nsuch as over the Amazon basin (Boisier et  al., 2015; Duffy et  al., \r\n2015; Zulkafli et al., 2016; Coppola et al., 2021b). There is medium \r\nconfidence (limited evidence, high agreement) that in several \r\ntropical-forest regions (e.g., Amazonia, West Africa) the dry season \r\nlength has increased (Fu et al., 2013; Debortoli et al., 2015; Saeed \r\net al., 2017; Dunning et al., 2018; Wadsworth et al., 2019), and there \r\nis low confidence (limited evidence) that deforestation influences the \r\nshift in the onset of the wet season in south Amazonia (Leite-Filho \r\net  al., 2019). In contrast, the wet season is increasing in northern \r\nAustralia tropical forests (Catto et al., 2012)."


id: 4d0fd29493c52ad6b31a797815d90147
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
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vector_id: 9549
content:
"Declines in low-elevation snow depth and seasonal extent are \r\nprojected for all SSP-RCPs (see Sections 12.4.1-12.4.6), along with \r\nreductions in mountain glacier surface area, increases in permafrost \r\ntemperature, decreases in permafrost thickness, changes in lake and "


id: 54a0f4229ee98a7515cc2601878c36d2
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 10771
content:
"In conclusion, most tropical forests are challenged by a mix \r\nof emerging warming trends that are particularly large in \r\ncomparison to historical variability (medium confidence). Water \r\ncycle changes bring prolonged drought, longer dry seasons, \r\nand increased fire weather to many tropical forests, with \r\nplants also responding to CO2 increases (medium confidence)."


id: 9b21f197d7325b1777665e72a8d49a44
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 21947
content:
"Section 12.4 assessed changes in climatic impact-drivers by region, \r\nprimarily based on a large number of local- and regional-scale studies \r\n(even though global studies are also used). This section presents an \r\nassessment of changes in CIDs at the global scale. It is based on both \r\na bottom-up synthesis of the results in Section 12.4, and a top-down \r\nassessment from global-scale studies undertaken here. Cross-Chapter \r\nBox 12.1 summarizes global-scale CIDs with levels of warming."


id: bb4122eebe0a7a662630e4dc10583d2d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 27005
content:
"Global-scale studies use similar indices of climatic impact-drivers \r\nacross space, although these indices may not always be those used \r\nat the local or regional scale. Most published global-scale studies \r\nconcentrate on single sectors or climatic impact-drivers, but some \r\ntake a multi-sectoral perspective (e.g., Warszawski et al., 2014; Arnell \r\net al., 2016, 2019; Schleussner et al., 2016; Mitchell et al., 2017; Betts \r\net al., 2018; Byers et al., 2018; Mora et al., 2018; O'Neill et al., 2018; \r\nZscheischler et al., 2018). Only a few published global-scale studies \r\n(e.g., Coppola et al., 2021; Schwingshackl et al., 2021) have used \r\nCMIP6 scenarios to date. "


id: 10fb80697f2c6eec2de979af80fec6ae
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 147
content:
"All regions will experience, before 2050, increased warming, an \r\nincrease of extreme heat and a decrease in cold spells, regardless of \r\nthe emissions trajectory (high confidence). Tropical regions, but also \r\nmid-latitude regions to a lesser extent, will experience an increasing \r\nnumber of days with heat indices crossing dangerous thresholds \r\nused to characterize heat stress, such as HI > 41degC (Figure 12.4). \r\nThe increase, by the end of century, exceeds 100 days per year in \r\nmost tropical areas under SSP5-8.5 but remains much more limited "


id: 96cdc9ebabae5b3d4fa167227a75d9a0
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 21243
content:
"experiencing simultaneous severe water stress events (based on SPEI) \r\nin a year increased from 15% under current conditions to up to 60% at \r\nthe end of the 21st century under high emissions."


id: 9257a4538e83b874cb1e06beeb8a1c38
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 20548
content:
"Integration of the results of Section  12.4 shows that the total \r\nnumber of tropical cyclones is projected to decrease through the \r\n21st  century, particularly with high emissions, but the number of \r\nvery intense tropical cyclones is projected to increase in most areas \r\n(at least medium confidence) (e.g.,  Bacmeister et  al., 2018; see \r\nSection 11.7.1). Furthermore, regions with glaciers will lose glacier \r\nmass and regions concerned with snow cover will see a reduction in \r\nsnow depth, the duration, or extent of cover (medium confidence in \r\npolar regions, high confidence elsewhere)."


id: bf1c0574614867a70fbb0f846f9d2aa6
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 27620
content:
"The regional assessment in Section  12.4 shows that fire weather \r\nis projected to increase with medium or high confidence in every \r\ncontinent of the world, including Arctic polar regions. Globally, fire \r\nweather is projected to increase in future, primarily due to higher \r\ntemperatures and exacerbated where precipitation reduces. By 2050, \r\n60% of the global land area would see a  significant increase in \r\nfire weather under RCP8.5 (Abatzoglou et  al., 2019). There is less \r\nconfidence in the projected distribution of change in fire weather \r\nacross regions in global-scale studies. For example, Moritz et  al., \r\n(2012) projected an increase in fire weather in mid- and high latitudes \r\nbut a reduction in the tropics, whilst Yu et al. (2019) and Bedia et al. \r\n(2015) projected an increase in the tropics. These differences reflect \r\ndifferences in methodologies and fire weather indices adopted in \r\ndifferent studies."


id: f64c332b3fa0ed6c2131ceb9891e56f7
created_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 36258
content:
"Relative sea level rise (RSLR) is projected in all regions (except for \r\na few Arctic polar regions) with likelihoods varying from very likely\r\nto virtually certain depending on the region. This will increase the \r\nfrequency of extreme sea levels and, depending on the level of \r\ncoastal flood protection, coastal flooding (Vousdoukas et al., 2018; \r\nKirezci et al., 2020). In terms of globally averaged extreme total water \r\nlevel (ETWL) frequency changes, the present-day 1-in-100-year event \r\nis projected to become 1-in-30-year and 1-in-20-year events by 2050 "


id: c5f34b2b80d40da48f8c00e664139482
created_at: 2023-03-16 14:00:51
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content:
"under RCP4.5 and RCP8.5, respectively. The present day 1-in-100-\r\nyear ETWL is projected to become a 1-in-5-year event by 2100 under \r\nRCP4.5, while under RCP8.5, such events are projected to occur more \r\nthan once a year (Vousdoukas et al., 2018)."


id: 3eea273b5973aba5bc4e7c477aa2ac1d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 7279
content:
"There is high confidence that most of the world's sandy coasts will \r\nexperience shoreline retreat, in the absence of terrestrial or offshore \r\nsediment sources. Median projections presented by (Vousdoukas et al., \r\n2020b) indicate that 13.6% (36,097 km) and 15.2% (40,511 km) of \r\nthe world's sandy beaches could retreat by more than 100 m by 2050 \r\n(relative to 2010) under RCP4.5 and RCP8.5 respectively, implying \r\na 12% increase in severely threatened shoreline length under RCP8.5, \r\nrelative to RCP4.5. These median projections increase to 35.7%-49.5% \r\n(RCP4.5 and RCP8.5, respectively; or 95,061 km-131,745 km) by the \r\nend of the century, implying a 38% increase in severely threatened \r\nshoreline length under RCP8.5, relative to RCP4.5."


id: 41feb4ff0fd2235524961a8d40968682
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 7783
content:
"Changes in climatic impact-drivers may remain within the range of \r\nnatural variability or have a time of emergence that varies by region \r\nand scenario. This section assesses the evidence for the effects of \r\nanthropogenic climate change on the emergence of changes in \r\nCID index, past, present and future, as evidenced by the literature \r\nassessed in other chapters, as well as additional literature assessed \r\nhere, at both global and regional scales. In many cases, however, \r\nsufficient literature for a robust region-by-region assessment of ToE is \r\nlacking. The assessment herein is made by CID. Regional emergence \r\nassessment is reported in Tables 12.3-12.11 but is undertaken in this \r\nsection."


id: dc6d55256a94eaf287d4ff96da6f027c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 32182
content:
"In a few other regions, only a small number of CIDs are projected to \r\nchange with high confidence (e.g., Sahara, Central Africa, Western \r\nAfrica, Madagascar, Arabian Peninsula, South-Eeastern South \r\nAmerica, New Zealand, Small Islands). The lower confidence levels \r\nassociated with changes in CIDs in these regions can be due either \r\nto weaker change signals compared to natural variability, or due to \r\nlimited evidence and model uncertainties leading to low agreement, \r\nand does not mean that climate change will affect these regions any \r\nless than in other regions."


id: 9d51a5f666dc5084324afdc6993f55f8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 22277
content:
"In summary, there is high confidence that all regions of the \r\nworld will experience changes in several climatic impact\u0002drivers by mid-century, albeit at region-specific rates of \r\nchange and confidence levels for each CID. Consequently, \r\nchanging CIDs have the potential to affect climate-related \r\nrisks in all regions of the world."


id: 9f2639c65499cc0b77a7a2afbf48a21b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 22574
content:
"Droughts, aridity and fire weather: There is low confidence in \r\nthe emergence of drought frequency in observations, for any type \r\nof drought, in all regions. Even though significant drought trends \r\nare observed in several regions with at least medium confidence\r\n(Sections  11.6 and 12.4), agricultural and ecological drought \r\nindices have interannual variability that dominates trends, as can \r\nbe seen from their time series (medium confidence) (H. Guo et al., \r\n2018; Spinoni et  al., 2019; Haile et  al., 2020; M. Wu et  al., 2020). \r\nStudies of the emergence of drought with systematic comparisons \r\nbetween trends and variability of indices are lacking, precluding "


id: 3e19d634f4d266c9a63c6815f182c3c1
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 7130
content:
"(Section 9.6.1.4; Lyu et al., 2014) (medium confidence). Emergence \r\nstudies for ETWL and coastal erosion are lacking and hence it is not \r\ncurrently possible to robustly assess emergence in these CIDs."


id: fefcb41247f17dc8fa7733972c326c2c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 37665
content:
"a comprehensive assessment of future drought emergence. Historical \r\nclimate simulations indicate that fire weather indices have already \r\nemerged in several regions (the Amazon basin, Mediterranean, \r\nCentral America, West and Southern Africa) (low confidence, limited \r\nevidence) (Abatzoglou et al., 2019), and emergence is projected with \r\nlow confidence by the middle of the century in several other regions \r\n(Southern Australia, Siberia, most of North America and Europe) \r\nwhen considering several indices together."


id: 85150be86fa7d5124b0483a8e03efab7
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 18464
content:
"Mean ocean temperature and marine heatwave: The emergence \r\nof the sea surface temperature increase signal has been observed in \r\nglobal oceans over the last century, and the largest S/N values are \r\nfound in the tropical Atlantic and tropical Indian oceans (Hawkins \r\net al., 2020). There is high confidence in the widespread occurrence \r\nof marine heatwaves in all basins and marginal seas over the last \r\ndecades (Chapter  9), but the emergence of this signal above the \r\nnatural variability has not yet been addressed in detail."


id: 79059156d79a31d24759051f98f4bd82
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 16593
content:
"Wind: Observed mean surface wind speed trends are present in many \r\nareas (Section  12.4), but the emergence of these trends from the \r\ninterannual natural variability and their attribution to human-induced \r\nclimate change remains of low confidence due to various factors \r\nsuch as changes in the type and exposure of recording instruments, \r\nand their relation to climate change is not established. For future \r\nconditions, there is limited evidence of the emergence of trends in \r\nmean wind speeds due to the lack of studies quantifying wind speed \r\nchanges and their interannual variability. The same limitation also \r\nholds for wind extremes (severe storms, tropical cyclones, sand and \r\ndust storms)."


id: 357d152018536b6ea482ab7599265a0d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 5823
content:
"Sea ice: Sea ice area decrease in the Arctic in all seasons has \r\nalready emerged from the interannual variability (high confidence) \r\n(Chapter  9). By contrast, the Antarctic sea ice area shows no \r\nsignificant trend, and therefore no emergence."


id: 918d1dd646e9493d7567a1bb8dc3bb5d
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 20441
content:
"For other snow and ice CIDs (heavy snowfall and ice storm, hail, snow \r\navalanche), there is limited evidence of emerging signals."


id: f66df2e64974fcb590d9cb7f6a41d89b
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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index: climate_gpt_only_giec
vector_id: 36283
content:
"Relative sea level, coastal flood and coastal erosion: Near\u0002coast RSLR will emerge before 2050 for RCP4.5 along the coasts of \r\nall AR6 regions (with coasts) except East Asia, the Russian Far East, \r\nMadagascar, the southern part of Eastern North America and the \r\nAntarctic regions (medium confidence) (Section 9.6.1.4; Bilbao et al., \r\n2015). Under RCP8.5, emergence of near-coast RSLR is projected \r\nby mid-century along the coasts of all AR6 regions (with coasts), \r\nexcept WAN where emergence is projected to occur before 2100 "


id: ce4bd1ecb0fe96da7a45a0666d440fc4
created_at: 2023-03-16 14:00:51
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vector_id: 29983
content:
"Table 12.12 | Emergence of CIDs in different time periods, as assessed in this section. The colour corresponds to the confidence of the region with the highest \r\nconfidence: white cells indicate where evidence is lacking or the signal is not present, leading to overall low confidence of an emerging signal."


id: 6bdaf2e3b767ed6574024e45c302690f
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content:
"1. High confidence except over a few regions (CNA and NWS) where there is low agreement across observation datasets."


id: d99171f1a8110715f4d3a9c33b22f8a8
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"Cross-Chapter Box 12.1 | Projections by Warming Levels of Hazards Relevant to the \r\nAssessment of Representative Key Risks and Reasons for Concern"


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"Contributors: Claudia Tebaldi (United States of America), Guofinna Aoalgeirsdottir (Iceland), Sybren Drijfhout (United Kingdom), \r\nJohn  Dunne (United States of America), Tamsin Edwards (United Kingdom), Erich Fischer (Switzerland), John Fyfe (Canada), \r\nRichard Jones (United Kingdom), Robert Kopp (United States of America), Charles Koven (United States of America), Gerhard Krinner \r\n(France), Friederike Otto (United Kingdom/Germany), Alex C. Ruane (United States of America), Sonia I. Seneviratne (Switzerland), \r\nJana Sillmann (Norway/Germany), Sophie Szopa (France), Prodromos Zanis (Greece)"


id: 7db978195f0d3e842aa6d83bb2197998
created_at: 2023-03-16 14:00:51
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"RFCs further synthesize the landscape of risks from climatic changes into five categories (from the IPCC Third Assessment Report \r\nonward; Smith et al., 2001): "


id: 8679209a5d02bdd879ac9697cce50992
created_at: 2023-03-16 14:00:51
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vector_id: 18699
content:
"Importantly, the assessment of risk in WGII considers hazards as only one component of an integrated assessment that involves their \r\ncomplex interaction with exposure and vulnerability of the systems at risk (Reisinger et al., 2020)."


id: e240943ab5b267778c25a9813629e64d
created_at: 2023-03-16 14:00:51
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content:
"Hazards relevant to RKRs and RFCs are identified among aspects of the climate system that have an episodic, short-term nature, like \r\nextreme events (particularly relevant to RFC2 but contributing to many other risk categories). Increasing GWLs translate into changing \r\ncharacteristics of frequency, duration, intensity, seasonality and spatial extent for many of these hazards that are also apparent in \r\nscenario-based results (Chapters 11 and 12, and Sections 12.4 and 12.5.1). Other relevant hazards coincide with long-term trends \r\nembodying a gradual change that may result in unfavourable environmental conditions. Also, increasing GWLs increase the likelihood \r\nof compound temporal or spatial occurrence of similar or different hazards (Section 11.8). Furthermore, RFC5's focus on singular \r\nevents includes concern surrounding potential tipping points and irreversible behaviour in the physical climate system."


id: 33b3e86267fccb53bd3ecb61069f5c2d
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"Cross-Chapter Box 12.1, Table 1 organizes information by hazard and presents current state and future change assessments with \r\nincreasing GWLs (defined by increasing global surface air temperature, GSAT; see Cross-Chapter Box 2.3). We draw on individual \r\nchapters across the WGI report for the assessment of how these hazards vary with GWL. Hazards for which a relation to GWLs has not \r\nbeen assessed are not reported in the table."


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" most cases co\r\nfound in more \r\n Tipping Points \r\nur as a Funct\r\nagnitude and in\r\nas 1.5degC; chang\r\n(in high-latitude \r\nceedance may s\r\nred to today, ch\r\nand four times \r\nhose associated \r\nare (e.g., 1-in-10 \r\n over all contin\r\nat lower GWLs a\r\non generally foll\r\n). Increase in fre\r\nents (high confi\r\n50-year events, \r\nnfidence).\r\nded area extent\r\nfrequency and m\r\nn areas where h\r\nfidence).\r\nwith GSAT; aver\r\needs of most int\r\nck of change in \r\nmes more freque\r\na GWL of 2.0 [1\r\nnding to a GWL \r\nl oceans and Ar"


id: 3d1b7eba9deb6808f9795b111eb1b9bc
created_at: 2023-03-16 14:00:51
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"Climate services are a significantly evolving source of climate change \r\ninformation to support adaptation, mitigation and risk management \r\ndecisions. As an evolving field, there are multiple definitions of \r\nclimate services (Brasseur and Gallardo, 2016). The Global Framework \r\nfor Climate Services defines a  climate service as the provision of \r\nclimate information to assist decision-making. The service includes \r\nappropriate engagement from users and providers, is based on \r\nscientifically credible information and expertise, has an effective \r\naccess mechanism, and responds to user needs (Hewitt et al., 2012)."


id: 746e4bbf917927fc114dca8e0456b069
created_at: 2023-03-16 14:00:51
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"This section introduces the current climate services landscape, \r\nassesses climate service practices and products related to climate \r\nchange information and associated challenges. Cross-Chapter \r\nBox 12.2 provides concrete examples of climate services. The section \r\nbuilds on the introduction to climate services in Section  1.2.3.3 \r\nand the assessment of regional climate information construction - \r\nincluding storylines  - discussed in Sections 10.3.4.2, 10.5.3 and \r\nCross-Chapter Box 10.3. The Atlas supports the provision of climate \r\ninformation across WGs by providing interactive maps and further \r\ndetails to the material made publicly accessible for use in climate \r\nservices. WGII (Chapter 17) further elaborates on climate services as \r\nenablers for climate risk management."


id: 17446e3c154b013ac13bf3702ffe1639
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"The idea of climate services is not new and has its roots in meteorology \r\nand climatology (Larosa and Mysiak, 2019). It can be traced back to \r\nthe late 1970s and the US National Climate Program Act of 1978 \r\n(Henderson, 2016). The development of the Global Framework for \r\nClimate Services (GFCS) after the World Climate Conference-3 in \r\nGeneva brought international attention and renewed impetus to the \r\nclimate services field (Hewitt et al., 2012). As a result, large investments \r\nhave been made globally and regionally in the development of "


id: 6095ada0456e406d86d7263a48e46ed4
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content:
"climate services shift incentives for climate science away from the \r\npublic interest towards profit-seeking, this will result in less publicly \r\naccessible and transparent climate information and more private \r\nknowledge (Keele, 2019; Tart et al., 2020)."


id: d631d1d47e6fadae664ff57a8cdd1e36
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"activities related to basic knowledge in climate change sciences and \r\nclimate-related risks (De Bruin et al., 2020; Sultan et al., 2020)."


id: 71aa5b6052aac223d0d197ca02df158c
created_at: 2023-03-16 14:00:51
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"Since AR5 and SROCC (Chapter  2) there has been considerable \r\nprogress in understanding climate information user needs (Baztan \r\net  al., 2017; Golding et  al., 2017a, b, 2019; Bruno Soares et  al., \r\n2018a; Hewitt and Golding, 2018; Singh et  al., 2018; Sivakumar \r\nand Lucio, 2018; Bessembinder et  al., 2019; Hewitt et  al., 2020b; \r\nSultan et al., 2020; Y. Wang et al., 2020), better facilitation of user \r\nengagement (Buontempo et al., 2014, 2018; Buontempo and Hewitt, \r\n2018) and an appreciation from climate scientists of the need to \r\ninvolve communication specialists and social scientists to support \r\nthe co-design and co-development process that is fundamental to \r\na successful climate service (Buontempo et al., 2014; Gregow et al., \r\n2016; Damm et al., 2020)."


id: 8adc65d9228ce4d8a2782ab6622565da
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"Information moves from 'useful' to 'usable' only when users \r\neffectively incorporate this information into a  decision process \r\n(Lemos et al., 2012; Bruno Soares and Dessai, 2016; Prokopy et al., \r\n2017; see also WGII, Chapter 17). Climate services include a range \r\nof knowledge brokerage activities such as: identifying knowledge \r\nneeds; dissemination of knowledge; coordinating and networking; \r\ncompiling and translating; building capacity through informed \r\ndecision-making; analysing, evaluating and developing policy; and \r\npersonal consultation (e.g., De Bruin et al., 2020). When analysing \r\nfour European climate services, Reinecke (2015) found that different \r\nclimate services emphasized different knowledge brokerage activities."


id: cbea65bf2b3459ea7707610fb68123e6
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"There are various types of climate service providers and products related \r\nto key sectors and regions, such as those described in Sections 12.3 \r\nand 12.4 (Hewitt et al., 2017b). For instance, studies have described \r\nsectoral climate services in support of agriculture (Falloon et al., 2018; \r\nHansen et al., 2019), health (Jancloes et al., 2014; Lowe et al., 2017), \r\ntourism (Morin et al., 2018; Damm et al., 2020; Matthews et al., 2021), \r\nenergy (Troccoli, 2018b; Goodess  et  al., 2019; Soret et  al.,  2019), \r\ndisaster risk reduction (Golding et al., 2019; Street et al., 2019), water "


id: e8674c12357b248d330227e01e88e629
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content:
"Figure 12.12 | Illustration of different types of climate services. Products, for instance, can focus only on climate-related information or can be designed to integrate \r\nclimate information with other decision-relevant context (vertical axis) and they can be very generic in terms of relevance to a wide range of sectors or stakeholders or \r\ncustomized to fit the needs of a specific sector or stakeholder (horizontal axis). Figure adapted from Visscher et al. (2020)."


id: e78a5fdaa2c9d8c1b0b4e8e59e81a6bd
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"Climate services set new scientific challenges to physical climate \r\nresearch (high confidence). Over at least the last decade, for instance, \r\nmany questions have appeared in terms of optimal estimation of \r\nchanges and uncertainties from projections of model ensembles, \r\nensemble optimization, or adjustment of model biases while preserving \r\nessential information on trends and cross-variable, time and space \r\nconsistencies, downscaling information at the local scale (Benestad \r\net al., 2017; Hewitt et al., 2017b; Marotzke et al., 2017; Hewitt and \r\nLowe, 2018; Knutti, 2019; see also Section  10.5). Other challenges \r\nrelated to climate services are the inter-operability of data (Giuliani \r\net al., 2017), access to data (open/FAIR Guiding principles; Wilkinson \r\net al., 2016; Georgeson et al., 2017), format of data (including moving \r\naway from percentile-based probabilistic forecasts (e.g., Haines, 2019)) \r\nand funding mechanisms (Bruno Soares and Buontempo, 2019)."


id: c15e47fa2d5bc5cb677c1571db92f712
created_at: 2023-03-16 14:00:51
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content:
"Understanding and modelling of weather and climate extremes is of \r\ngreat relevance for climate services and is continuing to set challenges \r\nfor research, such as modelling changes in impact-relevant threshold \r\nexceedance and return periods for a  variety of extremes (Maraun \r\net al., 2015; Sillmann et al., 2017; Hewitt et al., 2021; Schwingshackl \r\net al., 2021; see also Chapter 11). Extreme event attribution has also \r\nbeen used in context of climate services (Philip et al., 2020) as it is \r\nof interest to some stakeholder groups (Sippel et al., 2015; Marjanac \r\nand Patton, 2018; Jezequel et  al., 2019, 2020). The usefulness \r\nor applicability of available extreme event attribution methods \r\n(Section  11.2.4 and Cross-Working Group Box on Attribution in \r\nChapter 1) for assessing climate-related risks remains subject to \r\ndebate (Shepherd, 2016; Mann et al., 2017; Lloyd and Oreskes, 2018)."


id: f1c6f961695f438c9349a4266e75355e
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content:
"Figure 12.12 maps a general categorization of practices and products \r\nthat have emerged from reviewing climate service literature and \r\nuser interviews (Visscher et  al., 2020). The categories range from \r\nvery generic products or expert analysis focused particularly on \r\nclimate information (climate-centric approaches) to more integrated \r\nproducts that include shared open-source products and capacity \r\nbuilding as well as tailored products that treat climate information \r\nas part of a  larger decision-making context (climate-inclusive \r\napproaches). Three specific examples that elaborate in more detail \r\non specific practices and products related to those general categories \r\nare provided in Cross-Chapter Box 12.2."


id: 81222cec93ca6d083be3fbeabd8a9fd4
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"van Huysen et al., 2018); (vii) the lack of trained scientists skilled at \r\nconducting societally relevant research (Rozance et al., 2020)."


id: d3546004a960e0aac24e1527793a2070
created_at: 2023-03-16 14:00:51
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"Other challenges related to governance and dealing with complex \r\nsystems are sometimes acknowledged but less well described in the \r\nclimate services domain (Hewitt et al., 2020a). Importantly, decision \r\ncontexts are strongly rooted in past practice (which often does not \r\neven make optimal use of past climate information), stakeholder \r\nexperience, and history. Even important emerging concepts of \r\nco-production, entry points, and champions do not always fall \r\nnaturally into these realities without significant effort. The social \r\nsciences have an important role in helping understand and tackle \r\nthese challenges (Bruno Soares and Buontempo, 2019)."


id: 6623ffa028adda777f323919c2b2090c
created_at: 2023-03-16 14:00:51
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"Contributing Authors: Suraje Dessai (United Kingdom/Portugal), Jana Sillmann (Norway/Germany), Carlo Buontempo (United \r\nKingdom/Italy), Cecilia Conde (Mexico), Aida Diongue-Niang (Senegal), Francisco J. Doblas-Reyes (Spain), Christopher Jack (South \r\nAfrica), Richard Jones (United Kingdom), Benjamin Lamptey (Niger/Ghana), Xianfu Lu (United Kingdom/China), Douglas Maraun \r\n(Austria/Germany), Ben Orlove (United States of America), Roshanka Ranasinghe (Netherlands/Sri Lanka/Australia), Alex C. Ruane \r\n(United States of America), Anna Steynor (South Africa), Bart van den Hurk (Netherlands), Robert Vautard (France)"


id: 3da77b1b20bc82f7858f61f4e09f8f8
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"The diversity of climate services practices and products is illustrated here using three case studies each representing one of the \r\nbroad categories of user -provider engagement (Cross-Chapter Box 12.2, Figure 1)."


id: 169ac2949f8d90b32f69b0e0d06e018d
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"The Copernicus Climate Change Service (C3S) provides free and open access to climate data, tools and information through a website. \r\nIt also includes demonstration projects that show how C3S data can be used in practice through case studies, training sessions and \r\nworkshops (Thepaut et al., 2018). A large audience of the service is composed of intermediate users, loosely defined as the community \r\nof operators in one of the intermediate steps between the primary producers of climate data and the ultimate beneficiaries."


id: f51692e641f46282680a8f1f903961eb
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"C3S also facilitates the tailoring process, by providing a series of working open-source, cloud-based demonstrators which show how \r\nclimate data can be transformed into actionable information to meet specific user requirements. This tailoring process covers the chain \r\nbetween the definition of key indicators all the way to the user interface. The definition and production of C3S products involve scientists \r\nthat produced and assessed the data. A variety of potential users are involved in the definition of indicators and other products."


id: f949182e2c9ef05d50e5d4456505e8b3
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"Through its quality assurance process and demonstrators, C3S provides a basic evaluation of all climate data; it provides access, and it \r\nencourages the users to develop their own case-specific analysis within the C3S infrastructure. Trustworthiness and relevance of such \r\nan analysis are substantially strengthened through a distillation process, co-designed by the user and data provider, and drawing upon \r\nmultiple lines of evidence and process-based evaluation of model fitness (Section 10.5)."


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"Science-application engagement is extremely challenging, especially in critically important but complex contexts such as rapidly \r\ngrowing cities in developing nations (Culwick and Patel, 2017). The publicly funded Future Resilience for African CiTies And Lands \r\n(FRACTAL) project was conceived and designed in response to extensive and strong evidence and experience that useful and useable \r\nclimate services require strong mutual relationships across the science-application interface that can be built using supportive \r\nprocesses and structures (A. Taylor et al., 2017)."


id: e07beeb9daf3cf4498810ac245de7afd
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"Informed by this understanding, FRACTAL was grounded in a very reflexive and context-guided approach with city decision-making \r\nat its core (A. Taylor et al., 2017). Representatives from selected southern African cities were included in the proposal design and, \r\nthroughout the project, a core principle was to allow the city partners to lead and guide the process."


id: 629d208a90d3cabeba298634a8a6515b
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"This case study emphasizes the positive contributions of the fit, tailoring and contextualization of climate information with respect \r\nto the specific decision-making needs of particular users (Section 10.5; AR6 WGII Section 17.4.4.2.2), the importance of participatory \r\nplanning for risk management in urban areas (AR6 WGII Sections 6.3.3.3 and 6.4.2) and the importance of networks and organizations \r\nwhich link researchers, policymakers and end-users to promote adaptation in African cities (AR6 WGII Box 9.4). Upscaling this type \r\nof interactive activity to cater for the large number of user demands remains a challenge."


id: 511e648d60c23cfe1ddebf3023d36245
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content:
"Cross-Chapter Box 12.2, Figure 2 | Climate Risk Narrative infographic developed through the FRACTAL Windhoek Learning Lab process. Figure \r\nadapted from Jack et al. (2020)."


id: 69988c468b5bcb5d02de24e112a357b4
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"This broad category involves one-to-one engagement between a provider and a user with very specific needs. One such user is the \r\nAsian Development Bank (ADB), which has committed to making all its investments climate resilient by implementing a climate \r\nrisk management framework (ADB, 2014, 2018; Lu, 2019). The climate risk management framework mandates all climate-sensitive \r\ninvestment projects undertake a climate risk and adaptation assessment, to identify material risks of a changing climate to the proposed \r\nproject and potential adaptive measures to be incorporated into project design, implementation, maintenance and/or monitoring. \r\nTypically, loan project processing teams procure consulting services for a bespoke climate risk and adaptation assessment (CRA) "


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"for a  specific project. The user-provider engagement is highly targeted and goal-oriented. An example of such a  focused user-\r\nprovider engagement is the CRA carried out as part of an investment project in Vietnam, the Water Efficiency Improvement in Drought\u0002Affected Provinces (WEIDAP) project."


id: f6c4f96ac8bc1356e1b5fb08e50b1649
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"This case study illustrates that climate information distillation including a sustained iterative engagement between climate information \r\nusers, producers and translators can improve the quality of the information and the decision-making (Section 10.5; WGII Section 17.4.4.2.2)."


id: 920aec77ed60cd9c35adeeca837fefa2
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"Cross-Chapter Box 12.2, Table 1 | Summary of annual province-level changes in temperature, precipitation and evapotranspiration under the \r\nthree broad scenarios in southern Vietnam. Scenario 1: warm-and-wet; Scenario 2: hot-and-wet; Scenario 3: hotter. Source: Table 3 in ADB (2020)."


id: 3e29265b5f3449aaaca3e8ab0b859af0
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"science community and practitioners/stakeholders on the ground. \r\nCo-development of CID index definitions with impact scientists \r\nor stakeholders helps ensure their salience and utility (Sections \r\n12.1, 12.2, 12.3 and 12.6)."


id: 38026403cc9c57f1881e141910ca7f5
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"The assessment in this chapter is based on a rapidly growing body of \r\nnew evidence from the peer-reviewed literature, direct calculations \r\nof  climate projections from several new model ensembles, and \r\nresults from other AR6 WGI chapters. Although a large amount a new \r\ninformation on CID changes and their uptake in climate services \r\nhas become available since AR5, some challenges still remain. This \r\nsection summarizes some of these main challenges, with a view to \r\nfacilitating improved assessments in future. The section is organized \r\nfollowing the order of chapter sections and consolidated according \r\nto key assessment components."


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"projections challenge a uniformly robust assessment across all \r\nCIDs and regions of the world (Sections 12.4 and 12.5)."


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"A climatic impact-driver is a physical climate condition that directly affects society or ecosystems. Climatic impact\u0002drivers may represent a long-term average condition (such as the average winter temperatures that affect indoor \r\nheating requirements), a common event (such as a frost that kills off warm-season plants), or an extreme event \r\n(such as a coastal flood that destroys homes). A single climatic impact-driver may lead to detrimental effects \r\nfor one part of society while benefiting another, while others are not affected at all. A climatic impact-driver \r\n(or its change caused by climate change) is therefore not universally hazardous or beneficial, but we refer to it \r\nas a 'hazard' when experts determine it is detrimental to a specific system."


id: 73cae4b0bc18db6bd97c156bf602099c
created_at: 2023-03-16 14:00:51
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vector_id: 15833
content:
"Many aspects of our daily lives, businesses and natural systems depend on weather and climate, and there is \r\ngreat interest in anticipating the impacts of climate change on the things we care about. To meet these needs, \r\nscientists engage with companies and authorities to provide climate services - meaningful and possibly actionable \r\nclimate information designed to assist decision-making. Climate science and services can focus on CIDs that \r\nsubstantially disrupt systems to support broader risk management approaches. A single CID change can have \r\ndramatically different implications for different sectors or even elements of the same sector, so engagement \r\nbetween climate scientists and stakeholders is important to contextualize the climate changes that will come. \r\nClimate services responding to planning and optimization of an activity can focus on more gradual changes in \r\noperating climate conditions."


id: 4cf4b439aad76f5f8c0b825f3b019fa3
created_at: 2023-03-16 14:00:51
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vector_id: 9531
content:
"A climatic impact-driver (CID) is a climate condition that directly affects elements of society or ecosystems.\r\nClimatic impact-drivers and their changes can lead to positive, negative, or inconsequential outcomes (or a mixture)."


id: d82be2869a0bc89d3e4cafca62dde803
created_at: 2023-03-16 14:00:51
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content:
"Climatic thresholds tell us about the tolerance of society and ecosystems so that we can better scrutinize the types \r\nof climate changes that are expected to impact things we care about. Many systems have natural or structural \r\nthresholds. If conditions exceed those thresholds, the result can be sudden changes or even collapses in health, \r\nproductivity, utility or behaviour. Adaptation and risk management efforts can change these thresholds, altering \r\nthe profile of climate conditions that would be problematic and increasing overall system resilience."


id: f465f8d942497fd5ed8709eb80f6d327
created_at: 2023-03-16 14:00:51
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content:
"Decision makers have long observed that certain weather and climate conditions can be problematic, or \r\nhazardous, for things they care about (i.e., things with socio-economic, cultural or intrinsic value). Many elements \r\nof society and ecosystems operate in a suitable climate zone selected naturally or by stakeholders considering \r\nthe expected climate conditions. However, as climate change moves conditions beyond expected ranges, they \r\nmay cross a climatic 'threshold' - a level beyond which there are either gradual changes in system behaviour or \r\nabrupt, non-linear and potentially irreversible impacts."


id: 4044f911f655a93a821be8d980e25563
created_at: 2023-03-16 14:00:51
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content:
"Climatic thresholds can be associated with either natural or structural tolerance levels. Natural thresholds, for \r\ninstance, include heat and humidity conditions above which humans cannot regulate their internal temperatures \r\nthrough sweat, drought durations that heighten competition between species, and winter temperatures that \r\nare lethal for pests or disease-carrying vector species. Structural thresholds include engineered limits of drainage \r\nsystems, extreme wind speeds that limit wind turbine operation, the height of coastal protection infrastructure, \r\nand the locations of irrigation infrastructure or tropical cyclone sheltering facilities."


id: d017cfac2d08af97e6216e2aa7a55113
created_at: 2023-03-16 14:00:51
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content:
"Thresholds may be defined according to raw values (such as maximum temperature exceeding 35degC) or percentiles \r\n(such as the local 99th percentile daily rainfall total). They also often have strong seasonal dependence \r\n(see FAQ 12.3). For example, the amount of snowfall that a deciduous tree can withstand depends on whether \r\nthe snowfall occurs before or after the tree sheds its leaves. Most systems respond to changes in complex ways, \r\nand those responses are not determined solely or precisely by specific thresholds of a single climate variable. \r\nNonetheless, thresholds can be useful indicators of system behaviours, and an understanding of these thresholds \r\ncan help inform risk management decisions."


id: bd53648ec824081bc34104c27637ba12
created_at: 2023-03-16 14:00:51
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content:
"Adaptation and other changes in societies and environment can shift climatic thresholds by modifying vulnerability \r\nand exposure. For example, adaptation efforts may include breeding new crops with higher heat tolerance levels \r\nso that corresponding dangerous thresholds occur less frequently. Likewise, increasing the height of a flood \r\nembankment protecting a given community can increase the level of river flow that may be tolerated without \r\nflooding, reducing the frequency of damaging floods. Stakeholders therefore benefit from climate services that \r\nare based on a co-development process, with scientists identifying system-relevant thresholds and developing \r\ntailored climatic impact-driver indices that represent these thresholds (FAQ 12.1). These thresholds help focus the \r\nprovision of action-relevant climate information for adaptation and risk management. "


id: f5e41ac0c8926ef59bc703775c1115bc
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 36201
content:
"Many systems have thresholds that can lead to sudden changes, if climate conditions exceed them. \r\nAdaptation and risk management efforts can increase overall system resilience by identifying and \r\nchanging tolerance thresholds."


id: bac2974f43ff1b9ecb77a1ec204221db
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 26924
content:
"FAQ 12.2, Figure 1 | Crop response to maximum temperature thresholds. Crop growth rate responds to daily maximum temperature increases, \r\nleading to reduced growth and crop failure as temperatures exceed critical and limiting temperature thresholds, respectively. Note that changes in other \r\nenvironmental factors (such as carbon dioxide and water) may increase the tolerance of plants to increasing temperatures."


id: a820f4b89eca3f81d2bbc2601b1057e5
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 23967
content:
"Human-driven climate change can alter the regional characteristics of a climate hazard by changing the magnitude \r\nor intensity of the climate hazard, the frequency with which it occurs, the duration that hazardous conditions \r\npersist, the timing when the hazard occurs, or the spatial extent threatened by the hazard. By examining each \r\nof these aspects of a hazard's profile change, climate services may provide climate risk information that allows \r\ndecision makers to better tailor adaptation, mitigation and risk management strategies."


id: 9889e47471c397b89115f5e070abcf4c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 21512
content:
"A climate hazard is a climate condition with the potential to harm natural systems or society. Examples include \r\nheatwaves, droughts, heavy snowfall events and sea level rise. Climate scientists look for patterns in climatic \r\nimpact-drivers to detect the signature of changing hazards that may influence stakeholder planning (FAQ 12.1). \r\nClimate service providers work with stakeholders and impacts experts to identify key system responses and \r\ntolerance thresholds (FAQ 12.2) and then examine historical observations and future climate projections to \r\nidentify associated changes to the characteristics of a regional hazard's profile. Climate change can alter at least \r\nfive different characteristics of the hazard profile of a region (FAQ 12.3, Figure 1):"


id: 1b9710e9ef795cefb34787ac850700eb
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 1800
content:
"Magnitude or intensity is the raw value of a climate hazard, such as an increase in the maximum yearly temperature \r\nor in the height of flooding that results from a coastal storm with a 1% change of occurring each year."


id: 5f89efc47ce8f065be018805bcb1e617
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 12605
content:
"Frequency is the number of times that a climate hazard reaches or surpasses a threshold over a given period. \r\nFor example, increases to the number of heavy snowfall events, tornadoes, or floods experienced in a year or in \r\na decade."


id: 744a5c05990c7094b28876d004efad3
created_at: 2023-03-16 14:00:51
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vector_id: 15892
content:
"Duration is the length of time over which hazardous conditions persist beyond a threshold, such as an increase \r\nin the number of consecutive days where maximum air temperature exceeds 35degC, the number of consecutive \r\nmonths of drought conditions, or the number of days that a tropical cyclone affects a location."


id: 85b52b6fca6e7fa8f7a7cde9c41ce744
created_at: 2023-03-16 14:00:51
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content:
"Timing captures the occurrence of a hazardous event in relation to the course of a day, season, year, or other \r\nperiod in which sectoral elements are evolving or co-dependent (such as the time of year when migrating animals \r\nexpect to find a seasonal food supply). Examples include a shift towards an earlier day of the year when the last \r\nspring frost occurs or a delay in the typical arrival date for the first seasonal rains, the length of the winter period \r\nwhen the ground is typically covered by snow, or a reduction in the typical time needed for soil moisture to move \r\nfrom normal to drought conditions."


id: 8315bd32c9abe7e97b2e01ca9ff070cd
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 18153
content:
"Spatial extent is the region in which a hazardous condition is expected, such as the area currently threatened by \r\ntropical cyclones, geographical areas where the coldest day of the year restricts a particular pest or pathogen, \r\nterrain where permafrost is present, the area that would flood following a common storm, zones where climate \r\nconditions are conducive to outdoor labour, or the size of a marine heatwave."


id: d5dc68797ad0d34185ff914e7bc7c165
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 31163
content:
"Hazard profile changes are often intertwined or stem from related physical changes to the climate system. For \r\nexample, changes in the frequency and magnitude of extreme events are often directly related to each other \r\nas a result of atmospheric dynamics and chemical processes. In many cases, one aspect of hazard change is more \r\napparent than others, which may provide a first emergent signal indicating a larger set of changes to come \r\n(FAQ 1.2)."


id: a8cfd5eb92abc449161af87c8b0db40
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 24089
content:
"Information about how a hazard has changed or will change helps stakeholders prioritize more robust adaptation, \r\nmitigation and risk management strategies. For example, allocation of limited disaster relief resources may be \r\ndesigned to recognize that tropical cyclones are projected to become more intense even as the frequency of \r\nthose storms may not change. Planning may also factor in the fact that even heatwaves that are not record\u0002breaking in their intensity can still be problematic for vulnerable populations when they persist over a long \r\nperiod. Likewise, firefighters recognize new logistical challenges in the lengthening of the fire weather season \r\nand an expansion of fire conditions into parts of the world where fires were not previously a great concern. \r\nStrong engagement between climate scientists and stakeholders therefore helps climate services tailor and \r\ncommunicate clear information about the types of changing climate hazards to be addressed in resilience efforts."


id: f00eef9f12150904856c012a756de61f
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 35275
content:
"Climate change can alter the intensity and magnitude, frequency, duration, timing and spatial extent of a region's \r\nclimate hazards. "


id: 9018b80598c5de356f2dddb35aa113e8
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 20204
content:
"FAQ 12.3, Figure 1 | Types of changes to a region's hazard profile. The first five panels illustrate how climate changes can alter a hazard's intensity \r\n(or magnitude), frequency, duration, and timing (by seasonality and speed of onset) in relation to a hazard threshold (horizontal grey line, marked 'H'). The \r\ndifference between the historical climate (blue) and future climate (red) shows the changing aspects of climate change that stakeholders will have to manage. \r\nThe bottom right-hand panel shows how a given climate hazard (such as a current once-in-100-year river flood, geographic extent in blue) may reach new \r\ngeographical areas under a future climate change (extended area in red)."


id: 5f34ad0fe8b090c2eeb3b77e7e5d065c
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
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vector_id: 12544
content:
"Jose Manuel Gutierrez (Spain), Richard G. Jones (United Kingdom), Gemma Teresa Narisma \r\n(Philippines)"


id: 3145c41286d76b0f37ab6c56c421237a
created_at: 2023-03-16 14:00:51
updated_at: 2023-03-16 14:00:51
content_type: text
index: climate_gpt_only_giec
vector_id: 5172
content:
"Lincoln M. Alves (Brazil), Muhammad Amjad (Pakistan), Irina V. Gorodetskaya (Portugal/\r\nBelgium, The Russian Federation), Michael Grose (Australia), Nana Ama Browne Klutse (Ghana), \r\nSvitlana  Krakovska (Ukraine), Jian Li (China), Daniel Martinez-Castro (Cuba, Peru/Cuba), \r\nLinda O. Mearns (United States of America), Sebastian H. Mernild (Denmark, Norway/Denmark), \r\nThanh Ngo-Duc (Vietnam), Bart van den Hurk (The Netherlands), Jin-Ho Yoon (Republic of Korea)"


