Guest Post by Werner Brozek, Edited by Just The Facts
The table below ranks the warmest ten years according to the five data sets I cover. For each of these ten years, the year is given followed by the average anomaly for that year. In all cases, 2016 set a new record. The year 1998 appears on all five data sets as one of the top ten, but 2008 does not appear on any.
Below the second year of data, I give the difference between the record setting year and the second warmest year for that data set. For the satellite data sets, 1998 is the second warmest year. The others have 2015 as the second warmest year.
The margin of error for the average yearly anomaly is about 0.1. This means that to be statistically significant, the difference must be at least 0.1. As can be seen, only the GISS record is statistically significant meaning there is a greater than 95% that 2016 is the real record. For UAH, RSS, HadCRUT4.5 and Hadsst3, we have a statistical tie between the 2016 record and the second place year. However there is still a greater than 50% chance that 2016 is indeed a record. It is something like 57% for HadCRUT4.5 and about 60% for the other three.
The year 2016 started very warm but cooled off at the end. You may find it interesting where the December anomaly would rank if the December anomaly were to be the 2017 average anomaly. Of course, that will not be the case, but just for the fun of it, here are the rankings using the December anomaly on the later table in conjunction with the table above. UAH would be ranked 5th; RSS would be ranked 13th; HadCRUT4.5 would be ranked 3rd; Hadsst3 would be ranked 4th; and GISS would be ranked 3rd.
In the sections below, we will present you with the latest facts. The information will be presented in two sections and an appendix. The first section will show for how long there has been no statistically significant warming on several data sets. The second section will show how 2016 compares with 2015 and the warmest years and months on record so far. For three of the data sets, 2015 also happens to be the warmest year. The appendix will illustrate sections 1 and 2 in a different way. Graphs and a table will be used to illustrate the data.
For this analysis, data was retrieved from Nick Stokes’ Trendviewer available on his website. This analysis indicates for how long there has not been statistically significant warming according to Nick’s criteria. Data go to their latest update for each set. In every case, note that the lower error bar is negative so a slope of 0 cannot be ruled out from the month indicated.
On several different data sets, there has been no statistically significant warming for between 0 and 23 years according to Nick’s criteria. Cl stands for the confidence limits at the 95% level.
The details for several sets are below.
For UAH6.0: Since November 1993: Cl from -0.009 to 1.784
This is 23 years and 2 months.
For RSS: Since July 1994: Cl from -0.005 to 1.768 This is 22 years and 6 months.
For Hadcrut4.5: The warming is statistically significant for all periods above four years.
For Hadsst3: Since March 1997: Cl from -0.003 to 2.102 This is 19 years and 9 months.
For GISS: The warming is statistically significant for all periods above three years.
This section shows data about 2016 and other information in the form of a table. The table shows the five data sources along the top and other places so they should be visible at all times. The sources are UAH, RSS, Hadcrut4, Hadsst3, and GISS.
Down the column, are the following:
1. 15ra: This is the final ranking for 2015 on each data set.
2. 15a: Here I give the average anomaly for 2015.
3. year: This indicates the warmest year on record so far for that particular data set. Note that the satellite data sets have 1998 as the warmest year and the others have 2015 as the warmest year.
4. ano: This is the average of the monthly anomalies of the warmest year just above.
5. mon: This is the month where that particular data set showed the highest anomaly prior to 2016. The months are identified by the first three letters of the month and the last two numbers of the year.
6. ano: This is the anomaly of the month just above.
7. sig: This the first month for which warming is not statistically significant according to Nick’s criteria. The first three letters of the month are followed by the last two numbers of the year.
8. sy/m: This is the years and months for row 7.
9. Jan: This is the January 2016 anomaly for that particular data set.
10. Feb: This is the February 2016 anomaly for that particular data set, etc.
21. ave: This is the average anomaly for all twelve months.
22. rnk: This is the final 2016 rank for each particular data set. All five data sets set a record in 2016.
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 6.0beta5 was used.
For RSS, see: ftp://ftp.ssmi.com/msu/monthly_time_series/rss_monthly_msu_amsu_channel_tlt_anomalies_land_and_ocean_v03_3.txt
For Hadcrut4, see: http://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/time_series/HadCRUT.188.8.131.52.monthly_ns_avg.txt
For Hadsst3, see: https://crudata.uea.ac.uk/cru/data/temperature/HadSST3-gl.dat
For GISS, see:
To see all points since January 2016 in the form of a graph, see the WFT graph below.
As you can see, all lines have been offset so they all start at the same place in January 2016. This makes it easy to compare January 2016 with the latest anomaly.
The thick double line is the WTI which shows the average of RSS, UAH, HadCRUT4.5 and GISS.
In this part, we are summarizing data for each set separately.
For UAH: There is no statistically significant warming since November 1993: Cl from -0.009 to 1.784. (This is using version 6.0 according to Nick’s program.)
The UAH average anomaly for 2016 is 0.505. This sets a new record. 1998 was previously the warmest at 0.484. Prior to 2016, the highest ever monthly anomaly was in April of 1998 when it reached 0.743. The average anomaly in 2015 was 0.261 and it was ranked third but will now be in fourth place.
Presently, for RSS: There is no statistically significant warming since July 1994: Cl from -0.005 to 1.768.
The RSS average anomaly for 2016 is 0.573. This sets a new record. 1998 was previously the warmest at 0.550. Prior to 2016, the highest ever monthly anomaly was in April of 1998 when it reached 0.857. The average anomaly in 2015 was 0.381 and it was ranked third but will now be in fourth place.
For Hadcrut4.5: The warming is significant for all periods above four years.
The Hadcrut4.5 average anomaly for 2016 is 0.774. This sets a new record. Prior to 2016, the highest ever monthly anomaly was in December of 2015 when it reached 1.024. The average anomaly in 2015 was 0.760 and this set a new record at that time.
For Hadsst3: There is no statistically significant warming since March 1997: Cl from -0.003 to 2.102.
The Hadsst3 average anomaly for 2016 is 0.614. This sets a new record. Prior to 2016, the highest ever monthly anomaly was in September of 2015 when it reached 0.725. The average anomaly in 2015 was 0.592 and this set a new record at that time.
For GISS: The warming is significant for all periods above three years.
The GISS average anomaly for 2016 is 0.99. This sets a new record. Prior to 2016, the highest ever monthly anomaly was in December of 2015 when it reached 1.11. The average anomaly in 2015 was 0.87 and it set a new record at that time.
The three hottest years for HadCRUT4.5, HadSST3 and GISS are 2016, 2015 and 2014 in that order. So when people talk about the last three years being the hottest, they are NOT talking about the satellite data. According to the satellite data, 2016 sets a new record with 1998 dropping to second place. However the difference is so small that we could say that 2016 and 1998 are in a statistical tie.
As I indicated in my last post, I had expected HadCRUT4.5 to be very close. As it turned out, HadCRUT4.5 is the only data set of the five that I cover that went up from November to December. The other four went down from November to December. In terms of where December would rank if its anomaly were to hold for 2017, RSS is the odd man out. How long do you think that this will be the case?