Guest Post by Werner Brozek, Edited by Just The Facts:
First of all, I wish to draw your attention to the graph of UAH6.0beta5 with a mean of 12. (Yes, WoodForTrees.org has finally been updated, at least for UAH6.0beta5 and Hadcrut4.4 and WTI!)
On the graph, it can be seen that the mean 2016 values are pretty even with the 1998 values to this point. The average for the first 8 months of 1998 was 0.574 and the average for the first 8 months of 2016 was 0.566. The final average for 1998 with all 12 months was 0.484 so further drops are needed in 2016 if the 1998 record is to stand. In 1998, the January to December period was the highest 12 month period to 3 decimal places. This 0.484 average was narrowly beaten by the 12 month period from September 2015 to August 2016 where the average was 0.496. However since the margin of error for a 12 month period for UAH6.0beta5 is 0.1, the extra 0.012 is within the margin of error so it would be more accurate to say that the latest average is statistically tied with 1998. Whatever happens for the rest of the year, I believe it is safe to say that 2016 will be statistically tied with 1998 since the difference will not be more than 0.1.
Now for some comments on the ENSO numbers, which are from NOAA’s Climate Prediction Center. The period of time where we had El Nino conditions around 1998 was 13 months. In contrast, the period of time in the present case was 19 months. The highest average value was 2.3 in both cases. For all of the months from January to August, the 1998 numbers were lower than the 2016 numbers. The difference was not much most of the time with the exception of the July average. In 1998, it was in La Nina territory at -0.7. This time, it is in neutral territory at -0.3 which is 0.4 warmer. There was much speculation as to whether or not we would have a strong La Nina soon. At the moment, the drops in ENSO numbers have greatly slowed down. They only dropped from -0.6 to -0.7 over about 6 weeks. I still expect the average UAH6.0beta5 anomalies to drop over the rest of 2016, however they did rise over the last 2 months. This contest between 1998 and 2016 may go right down to the wire.
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 so far 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. All data sets except Hadcrut4.4 go to August.
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 August 1993: Cl from -0.006 to 1.810
This is 23 years and 1 month.
For RSS: Since December 1993: Cl from -0.008 to 1.746 This is 22 years and 9 months.
For Hadcrut4.4: The warming is statistically significant for all periods above three years.
For Hadsst3: Since December 1996: Cl from -0.022 to 2.162 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.
17. ave: This is the average anomaly of all months to date.
18. rnk: This is the rank that each particular data set would have for 2016 without regards to error bars and assuming no changes to the current average anomaly. Think of it as an update 35 minutes into a game.
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 6.0beta5 was used.
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.
I am very happy to note that WFT has been updated for the latest Hadcrut4 version as well as allowing UAH6.0beta5 to be seen. The thick double line is the WTI which shows the average of RSS, UAH6.0beta5, Hadcrut4.4 and GISS.
In this part, we are summarizing data for each set separately.
For UAH: There is no statistically significant warming since August 1993: Cl from -0.006 to 1.810. (This is using version 6.0 according to Nick’s program.)
The UAH average anomaly so far for 2016 is 0.566. This would set a record if it stayed this way. 1998 was 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 3rd.
For RSS: There is no statistically significant warming since December 1993: Cl from -0.008 to 1.746.
The RSS average anomaly so far for 2016 is 0.645. This would set a record if it stayed this way. 1998 was 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 0.358 and it was ranked 3rd.
For Hadcrut4: The warming is significant for all periods above three years.
The Hadcrut4 average anomaly so far is 0.874. This would set a record if it stayed this way. Prior to 2016, the highest ever monthly anomaly was in December of 2015 when it reached 1.010. The average anomaly in 2015 was 0.746 and this set a new record.
For Hadsst3: There is no statistically significant warming since December 1996: Cl from -0.022 to 2.162.
The Hadsst3 average anomaly so far for 2016 is 0.651. This would set a record if it stayed this way. 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.
For GISS: The warming is significant for all periods above three years.
The GISS average anomaly so far for 2016 is 1.05. This would set a record if it stayed this way. Prior to 2016, the highest ever monthly anomaly was in December of 2015 when it reached 1.10. The average anomaly in 2015 was 0.86 and it set a new record.
It would appear that when considering ENSO numbers and the length of time they were high, that 2016 would be significantly higher than 1998. In addition, there is significantly more carbon dioxide in the air now than was the case in 1998, i.e. according to Economist, “The world added roughly 100 billion tonnes of carbon to the atmosphere between 2000 and 2010. That is about a quarter of all the CO₂ put there by humanity since 1750.” Thus if 2016 edges out 1998 on UAH6.0beta5, how much of the reason should be attributed to the length and strength of the El Niño and how much can be attributed to additional carbon dioxide in the atmosphere?