Guest Post by Werner Brozek, Edited by Just The Facts
Image Credit: Ken’s Kingdom
Image Credit: RSS
As can be seen in the above graphs, the south polar region has been cooling for the whole satellite record. The cooling is not statistically significant, however over the complete time span of the satellite record of almost 37 years, it should not be happening if we have global warming. Since the cooling is over the whole satellite record, it could be much longer if we had earlier records.
It is understandable that if carbon dioxide is really the control knob, that all places on Earth would not warm at the same rate. It is also understandable that for short periods of time, there may be cooling in some areas where other factors have a stronger influence than carbon dioxide.
It is also understandable that if carbon dioxide goes from 0.028% to 0.040%, that the effect would be greatest at the poles where the additional carbon dioxide does not have to compete with 2% to 4% water vapor as may be the case in the tropics. Since very cold temperatures can hold very small amounts of water vapor, the relative affect of more carbon dioxide should be largest in the polar regions. But why are just the northern polar regions showing larger amounts of warming? It is not as if the carbon dioxide is upside down in the south. ☺
The time of almost 37 years is also significant. Sometimes, climate is defined as to what happened over the last 30 years. And some may feel that the global standstill of almost 19 years is not enough time to draw the correct conclusions. Since 37 years is above 30 years, this cooling over a relatively large part of the Earth requires an explanation. By the way, Ken’s Kingdom and RSS also show several other time periods of no slope for different parts of the Earth.
In the sections below, as in previous posts, we will present you with the latest facts. The information will be presented in three sections and an appendix. The first section will show for how long there has been no warming on some data sets. At the moment, only the satellite data have flat periods of longer than a year. The second section will show for how long there has been no statistically significant warming on several data sets. The third section will show how 2015 so far compares with 2014 and the warmest years and months on record so far. For three of the data sets, 2014 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.
This analysis uses the latest month for which data is available on WoodForTrees.com (WFT). All of the data on WFT is also available at the specific sources as outlined below. We start with the present date and go to the furthest month in the past where the slope is a least slightly negative on at least one calculation. So if the slope from September is 4 x 10^-4 but it is – 4 x 10^-4 from October, we give the time from October so no one can accuse us of being less than honest if we say the slope is flat from a certain month.
1. For GISS, the slope is not flat for any period that is worth mentioning.
2. For Hadcrut4, the slope is not flat for any period that is worth mentioning.
3. For Hadsst3, the slope is not flat for any period that is worth mentioning.
4. For UAH, the slope is flat since May 1997 or 18 years and 4 months. (goes to August using version 6.0)
5. For RSS, the slope is flat since January 1997 or 18 years and 8 months. (goes to August)
The next graph shows just the lines to illustrate the above. Think of it as a sideways bar graph where the lengths of the lines indicate the relative times where the slope is 0. In addition, the upward sloping blue line at the top indicates that CO2 has steadily increased over this period.
Note that the UAH5.6 from WFT needed an offset to show the slope is zero for UAH6.0.
When two things are plotted as I have done, the left only shows a temperature anomaly.
The actual numbers are meaningless since the two slopes are essentially zero. No numbers are given for CO2. Some have asked that the log of the concentration of CO2 be plotted. However WFT does not give this option. The upward sloping CO2 line only shows that while CO2 has been going up over the last 18 years, the temperatures have been flat for varying periods on the two sets.
For this analysis, data was retrieved from Nick Stokes’ Trendviewer available on his website <a href=”http://moyhu.blogspot.com.au/p/temperature-trend-viewer.html”. 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 11 and 22 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 December 1992: Cl from -0.014 to 1.694
This is 22 years and 9 months.
For RSS: Since February 1993: Cl from -0.010 to 1.633
This is 22 years and 7 months.
For Hadcrut4.4: Since December 2000: Cl from -0.013 to 1.326
This is 14 years and 9 months.
For Hadsst3: Since October 1995: Cl from -0.017 to 1.888
This is 19 years and 11 months.
For GISS: Since September 2004: Cl from -0.065 to 2.023
This is exactly11 years.
This section shows data about 2015 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. 14ra: This is the final ranking for 2014 on each data set.
2. 14a: Here I give the average anomaly for 2014.
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 2014 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. 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. y/m: This is the longest period of time where the slope is not positive given in years/months. So 16/2 means that for 16 years and 2 months the slope is essentially 0. Periods of under a year are not counted and are shown as “0”.
8. 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.
9. sy/m: This is the years and months for row 8. Depending on when the update was last done, the months may be off by one month.
10. Jan: This is the January 2015 anomaly for that particular data set.
11. Feb: This is the February 2015 anomaly for that particular data set, etc.
18. ave: This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months.
19. rnk: This is the rank that each particular data set would have for 2015 without regards to error bars and assuming no changes. Think of it as an update 40 minutes into a game.
If you wish to verify all of the latest anomalies, go to the following:
For UAH, version 6.0beta3 was used. Note that WFT uses version 5.6. So to verify the length of the pause on version 6.0, you need to use Nick’s program.
For Hadsst3, see: http://www.cru.uea.ac.uk/cru/data/temperature/HadSST3-gl.dat
For GISS, see:
To see all points since January 2015 in the form of a graph, see the WFT graph below. Note that UAH version 5.6 is shown. WFT does not show version 6.0 yet. Also note that Hadcrut4.3 is shown and not Hadcrut4.4, which is why the last few months are missing for Hadcrut.
As you can see, all lines have been offset so they all start at the same place in January 2015. This makes it easy to compare January 2015 with the latest anomaly.
In this part, we are summarizing data for each set separately.
The slope is flat since January 1997 or 18 years, 8 months. (goes to August)
For RSS: There is no statistically significant warming since February 1993: Cl from -0.010 to 1.633.
The RSS average anomaly so far for 2015 is 0.313. This would rank it as 6th place. 1998 was the warmest at 0.55. The highest ever monthly anomaly was in April of 1998 when it reached 0.857. The anomaly in 2014 was 0.255 and it was ranked 6th.
The slope is flat since May 1997 or 18 years and 4 months. (goes to August using version 6.0beta3)
For UAH: There is no statistically significant warming since December 1992: Cl from -0.014 to 1.694. (This is using version 6.0 according to Nick’s program.)
The UAH average anomaly so far for 2015 is 0.223. This would rank it as 3rd place. 1998 was the warmest at 0.483. The highest ever monthly anomaly was in April of 1998 when it reached 0.742. The anomaly in 2014 was 0.188 and it was ranked 5th.
The slope is not flat for any period that is worth mentioning.
For Hadcrut4: There is no statistically significant warming since December 2000: Cl from -0.013 to 1.326.
The Hadcrut4 average anomaly so far for 2015 is 0.693. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.832. The anomaly in 2014 was 0.564 and this set a new record.
For Hadsst3, the slope is not flat for any period that is worth mentioning. For Hadsst3: There is no statistically significant warming since October 1995: Cl from -0.017 to 1.888.
The Hadsst3 average anomaly so far for 2015 is 0.537. This would set a new record if it stayed this way. The highest ever monthly anomaly was in August of 2014 when it reached 0.644. This is prior to 2015. The anomaly in 2014 was 0.479 and this set a new record. The August 2015 anomaly of 0.664 also sets a new record.
The slope is not flat for any period that is worth mentioning.
For GISS: There is no statistically significant warming since September 2004: Cl from -0.065 to 2.023.
The GISS average anomaly so far for 2015 is 0.81. This would set a new record if it stayed this way. The highest ever monthly anomaly was in January of 2007 when it reached 0.97. The anomaly in 2014 was 0.75 and it set a new record.
Different regions of the Earth are either warming at different rates or even cooling. Then the various regions contradict each other as to what is really occurring. With so much uncertainty, perhaps we should wait to really see what is really occurring before spending trillions on a problem that may not even exist?