
[NOTE: RSS is a satellite temperature data set much like the UAH dataset from Dr. Roy Spencer and John Christy – Anthony]
Image Credit: WoodForTrees.org
Guest Post By Werner Brozek, Edited By Just The Facts
The graphic above shows 3 lines. The long line shows that RSS has been flat from December 1996 to July 2013, which is a period of 16 years and 8 months or 200 months. The other slightly higher flat line in the middle is the latest complete decade of 120 months from January 2001 to December 2010. The other slightly downward sloping line is the latest 120 months prior from present. It very clearly shows it has been cooling lately, however this cooling is not statistically significant.
In my opinion, if you want to find out what the temperatures are doing over the last 10 or 16 years on any data set, you should find the slope of the line for the years in question. However some people insist on saying global warming is accelerating by comparing the decade from 2001 to 2010 to the previous decade. They conveniently ignore what has happened since January 2011. However, when one compares the average anomaly from January 2011 to the present with the average anomaly from January 2001 to December 2010, the latest quarter decade has the lower number on all six data sets that I have been discussing. Global warming is not even decelerating. In fact, on all six data sets, cooling is actually taking place.
The numbers for RSS for example are as follows: From January 2001 to December 2010, the average anomaly was 0.265. For the last 31 months from January 2011 to July 2013, the average anomaly is 0.184. The difference between these is -0.081. I realize that it is only for a short time, but it is long enough that there is no way that RSS, for example, will show a positive difference before the end of the year. In order for that to happen, we can use the numbers indicated to calculate what is required. Our equation would be (0.184)(31) + 5x = (0.265)(36). Solving for x gives 0.767. This is close to the highest anomaly ever recorded on RSS, which is 0.857 from April 1998. With the present ENSO conditions, there is no way that will happen.
A word to the wise: do not even mention accelerated global warming until the difference is positive on all data sets.
I have added rows 23 to 25 to the table in Section 3 with the intention of updating it with every post. This table shows the numbers that I have given for RSS above as well as the corresponding numbers on the other five data sets I have been discussing. Do you feel this would be a valuable addition to my posts?
(Note: If you read my last article and just wish to know what is new with the July data, you will find the most important new things from lines 7 to the end of the table.)
Below we will present you with the latest fact, 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 several data sets. 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 2013 to date compares with 2012 and the warmest years and months on record so far. The appendix will illustrate sections 1 and 2 in a different way. Graphs and a table will be used to illustrate the data.
Section 1
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. 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.
On all data sets below, the different times for a slope that is at least very slightly negative ranges from 8 years and 7 months to 16 years and 8 months.
1. For GISS, the slope is flat since February 2001 or 12 years, 6 months. (goes to July)
2. For Hadcrut3, the slope is flat since April 1997 or 16 years, 4 months. (goes to July)
3. For a combination of GISS, Hadcrut3, UAH and RSS, the slope is flat since December 2000 or 12 years, 8 months. (goes to July)
4. For Hadcrut4, the slope is flat since December 2000 or 12 years, 8 months. (goes to July)
5. For Hadsst2, the slope is flat since March 1997 or 16 years, 4 months. (goes to June) (The July anomaly is out, but it is not on WFT yet.)
6. For UAH, the slope is flat since January 2005 or 8 years, 7 months. (goes to July using version 5.5)
7. For RSS, the slope is flat since December 1996 or 16 years and 8 months. (goes to July) RSS is 200/204 or 98% of the way to Ben Santer’s 17 years.
The next link shows just the lines to illustrate the above for what can be shown. 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 sloped wiggly line shows how CO2 has increased over this period.

When two things are plotted as I have done, the left only shows a temperature anomaly. It goes from 0.1 C to 0.6 C. A change of 0.5 C over 16 years is about 3.0 C over 100 years. And 3.0 C is about the average of what the IPCC says may be the temperature increase by 2100.
So for this to be the case, the slope for all of the data sets would have to be as steep as the CO2 slope. Hopefully the graphs show that this is totally untenable.
The next graph shows the above, but this time, the actual plotted points are shown along with the slope lines and the CO2 is omitted.

Section 2
For this analysis, data was retrieved from SkepticalScience.com. This analysis indicates for how long there has not been statistically significant warming according to their criteria. The numbers below start from January of the year indicated. Data go to their latest update for each set. In every case, note that the magnitude of the second number is larger than the first number so a slope of 0 cannot be ruled out. (To the best of my knowledge, SkS uses the same criteria that Phil Jones uses to determine statistical significance.)
The situation with GISS, which used to have no statistically significant warming for 17 years, has now been changed with new data. GISS now has over 18 years of no statistically significant warming. As a result, we can now say the following: On six different data sets, there has been no statistically significant warming for between 18 and 23 years.
The details are below and are based on the SkS Temperature Trend Calculator:
For RSS the warming is not statistically significant for over 23 years.
For RSS: +0.120 +/-0.129 C/decade at the two sigma level from 1990
For UAH the warming is not statistically significant for over 19 years.
For UAH: 0.141 +/- 0.163 C/decade at the two sigma level from 1994
For Hadcrut3 the warming is not statistically significant for over 19 years.
For Hadcrut3: 0.091 +/- 0.110 C/decade at the two sigma level from 1994
For Hadcrut4 the warming is not statistically significant for over 18 years.
For Hadcrut4: 0.092 +/- 0.106 C/decade at the two sigma level from 1995
For GISS the warming is not statistically significant for over 18 years.
For GISS: 0.104 +/- 0.106 C/decade at the two sigma level from 1995
For NOAA the warming is not statistically significant for over 18 years.
For NOAA: 0.085 +/- 0.102 C/decade at the two sigma level from 1995
If you want to know the times to the nearest month that the warming is not statistically significant for each set to their latest update, they are as follows:
RSS since August 1989;
UAH since June 1993;
Hadcrut3 since August 1993;
Hadcrut4 since July 1994;
GISS since January 1995 and
NOAA since June 1994.
Section 3
This section shows data about 2013 and other information in the form of a table. The table shows the six data sources along the top and bottom, namely UAH, RSS, Hadcrut4, Hadcrut3, Hadsst2, and GISS. Down the column, are the following:
1. 12ra: This is the final ranking for 2012 on each data set.
2. 12a: Here I give the average anomaly for 2012.
3. year: This indicates the warmest year on record so far for that particular data set. Note that two of the data sets have 2010 as the warmest year and four have 1998 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 two 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.
8. sig: This is the whole number of years for which warming is not statistically significant according to the SkS criteria. The additional months are not added here, however for more details, see Section 2.
9. Jan: This is the January, 2013, anomaly for that particular data set.
10. Feb: This is the February, 2013, anomaly for that particular data set, etc.
21. ave: This is the average anomaly of all months to date taken by adding all numbers and dividing by the number of months. However if the data set itself gives that average, I may use their number. Sometimes the number in the third decimal place differs by one, presumably due to all months not having the same number of days.
22. rnk: This is the rank that each particular data set would have if the anomaly above were to remain that way for the rest of the year. Of course it won’t, but think of it as an update 30 or 35 minutes into a game. Due to different base periods, the rank may be more meaningful than the average anomaly.
23.new: This gives the average anomaly of the last 31 months on the six data sets I have been discussing, namely from January 2011 to the latest number available.
24.old: This gives the average anomaly of the 120 months before that on the six data sets I have been discussing. The time goes from January 2001 to December 2010.
25.dif: This gives the difference between these two numbers.
Note that in every single case, the difference is negative. In other words, from the previous decade to this present one, global warming is NOT accelerating. As a matter of fact, cooling is taking place.
| Source | UAH | RSS | Had4 | Had3 | Sst2 | GISS |
|---|---|---|---|---|---|---|
| 1. 12ra | 9th | 11th | 9th | 10th | 8th | 9th |
| 2. 12a | 0.161 | 0.192 | 0.448 | 0.406 | 0.342 | 0.57 |
| 3. year | 1998 | 1998 | 2010 | 1998 | 1998 | 2010 |
| 4. ano | 0.419 | 0.55 | 0.547 | 0.548 | 0.451 | 0.66 |
| 5. mon | Ap98 | Ap98 | Ja07 | Fe98 | Au98 | Ja07 |
| 6. ano | 0.66 | 0.857 | 0.829 | 0.756 | 0.555 | 0.93 |
| 7. y/m | 8/7 | 16/8 | 12/8 | 16/4 | 16/4 | 12/6 |
| 8. sig | 19 | 23 | 18 | 19 | 18 | |
| Source | UAH | RSS | Had4 | Had3 | Sst2 | GISS |
| 9. Jan | 0.504 | 0.441 | 0.450 | 0.390 | 0.283 | 0.63 |
| 10.Feb | 0.175 | 0.194 | 0.479 | 0.424 | 0.308 | 0.50 |
| 11.Mar | 0.183 | 0.205 | 0.405 | 0.384 | 0.278 | 0.58 |
| 12.Apr | 0.103 | 0.219 | 0.427 | 0.400 | 0.354 | 0.48 |
| 13.May | 0.077 | 0.139 | 0.498 | 0.472 | 0.377 | 0.56 |
| 14.Jun | 0.269 | 0.291 | 0.451 | 0.426 | 0.304 | 0.66 |
| 15.Jul | 0.118 | 0.222 | 0.514 | 0.490 | 0.468 | 0.54 |
| Source | UAH | RSS | Had4 | Had3 | Sst2 | GISS |
| 21.ave | 0.204 | 0.244 | 0.459 | 0.427 | 0.339 | 0.564 |
| 22.rnk | 6th | 8th | 9th | 8th | 10th | 10th |
| 23.new | 0.158 | 0.184 | 0.436 | 0.385 | 0.314 | 0.562 |
| 24.old | 0.187 | 0.265 | 0.483 | 0.435 | 0.352 | 0.591 |
| 25.dif | -.029 | -.081 | -.047 | -.050 | -.038 | -.029 |
If you wish to verify all of the latest anomalies, go to the following links, For UAH, version 5.5 was used since that is what WFT used,, RSS, Hadcrut4, Hadcrut3, Hadsst2,and GISS.
To see all points since January 2012 in the form of a graph, see the WFT graph below.

Appendix
In this section, we summarize the data for each set separately.
RSS
The slope is flat since December 1996 or 16 years and 7 months. (goes to June) RSS is 199/204 or 97.5% of the way to Ben Santer’s 17 years.
For RSS the warming is not statistically significant for over 23 years.
For RSS: +0.122 +/-0.131 C/decade at the two sigma level from 1990.
The RSS average anomaly so far for 2013 is 0.248. This would rank 7th if it stayed this way. 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 2012 was 0.192 and it came in 11th.
Following are two graphs via WFT. Both show all plotted points for RSS since 1990. Then two lines are shown on the first graph. The first upward sloping line is the line from where warming is not statistically significant according to the SkS site criteria. The second straight line shows the point from where the slope is flat.
The second graph shows the above, but in addition, there are two extra lines. These show the upper and lower lines using the SkS site criteria. Note that the lower line is almost horizontal but slopes slightly downward. This indicates that there is a slight chance that cooling has occurred since 1990 according to RSS.
UAH
The slope is flat since July 2008 or 5 years, 0 months. (goes to June)
For UAH, the warming is not statistically significant for over 19 years.
For UAH: 0.139 +/- 0.165 C/decade at the two sigma level from 1994
The UAH average anomaly so far for 2013 is 0.219. This would rank 4th if it stayed this way. 1998 was the warmest at 0.419. The highest ever monthly anomaly was in April of 1998 when it reached 0.66. The anomaly in 2012 was 0.161 and it came in 9th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to UAH.
Hadcrut4
The slope is flat since November 2000 or 12 years, 7 months. (goes to May.)
For Hadcrut4, the warming is not statistically significant for over 18 years.
For Hadcrut4: 0.093 +/- 0.107 C/decade at the two sigma level from 1995
The Hadcrut4 average anomaly so far for 2013 is 0.450. This would rank 9th if it stayed this way. 2010 was the warmest at 0.547. The highest ever monthly anomaly was in January of 2007 when it reached 0.829. The anomaly in 2012 was 0.448 and it came in 9th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut4.
Hadcrut3
The slope is flat since April 1997 or 16 years, 2 months (goes to May, 2013)
For Hadcrut3, the warming is not statistically significant for over 19 years.
For Hadcrut3: 0.091 +/- 0.110 C/decade at the two sigma level from 1994
The Hadcrut3 average anomaly so far for 2013 is 0.414. This would rank 9th if it stayed this way. 1998 was the warmest at 0.548. The highest ever monthly anomaly was in February of 1998 when it reached 0.756. One has to go back to the 1940s to find the previous time that a Hadcrut3 record was not beaten in 10 years or less. The anomaly in 2012 was 0.405 and it came in 10th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to Hadcrut3.
Hadsst2
For Hadsst2, the slope is flat since March 1, 1997 or 16 years, 2 months. (goes to April 30, 2013).
The Hadsst2 average anomaly for the first four months for 2013 is 0.306. This would rank 11th if it stayed this way. 1998 was the warmest at 0.451. The highest ever monthly anomaly was in August of 1998 when it reached 0.555. The anomaly in 2012 was 0.342 and it came in 8th.
Sorry! The only graph available for Hadsst2 is this.
GISS
The slope is flat since February 2001 or 12 years, 5 months. (goes to June)
For GISS, the warming is not statistically significant for over 18 years.
For GISS: 0.105 +/- 0.110 C/decade at the two sigma level from 1995
The GISS average anomaly so far for 2013 is 0.57. This would rank 9th if it stayed this way. 2010 was the warmest at 0.66. The highest ever monthly anomaly was in January of 2007 when it reached 0.93. The anomaly in 2012 was 0.56 and it came in 9th.
Following are two graphs via WFT. Everything is identical as with RSS except the lines apply to GISS. Graph 1 and Graph 2
Conclusion
So far in 2013, there is no evidence that the pause in global warming has ended. As well, all indications are that RSS will reach Santer’s 17 years in three or four months. The average rank so far is 8.5 on the six data sets discussed here. ENSO has been neutral all year so far and shows no signs of changing. The sun has been in a slump all year and also shows no sign of changing. As far as polar ice is concerned, the area that the north is losing is close to what the south is gaining. So the net effect is that there is little overall change and this also shows no sign of changing.
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RSS Flat For 200 Months (Now Includes July Data)
Thus no global cooling…
lsvalgaard says: August 25, 2013 at 10:06 am
RSS Flat For 200 Months (Now Includes July Data)
Thus no global cooling…
I agree, it all seems quite average to me…
Sorry for going OT here but I have a question. Does anybody know the global average SST vs the global average air temperature over the oceans? If the former is lower, how can heat transfer (net) from atmosphere to ocean?
Intesting overview.
May be more appropriate to show log CO2 (probably not possible in the challenged limitations of WTF website) , also why the offset?
So for this to be the case, the slope for all of the data sets would have to be as steep as the CO2 slope. Hopefully the graphs show that this is totally untenable.
No, this is not the case. For so very many reasons it is difficult to cover them all. First of all, you are comparing apples to oranges when you compare anomaly slopes. Second of all, there is obviously a constant (needed just to change the UNITS!) between the two quantities, and the value of this constant determines the comparative steepness of slope. Third, the problem with this SORT of analysis is that one cannot separate out the “natural climate variation” and the “CO_2 caused climate variation” and the “feedback caused climate variation” and the “anthropogenic but also warming or cooling or both factors” such as aerosols and soot and the “influence of water vapor” — so asserting a simple linear dependence of one on another either way is absurd. CAGW could easily be correct and the current flat trend is natural noise that will eventually be overwhelmed by the CO_2 forced signal, or CAGW could easily be incorrect, and the current flat trend is mostly natural and UNDERWHELMED by any CO_2 forced signal. Or any of a slew of other alternatives.
The best conclusion one can draw from the curves you present above is “this data does not support the assertion that the increase in CO_2 over the last 16 years has caused additional warming”. That’s all that the data really means, and all it will ever mean until we can reliably separate causal components contributing to the climate that probably cannot be separated in a complex nonlinear system.
rgb
Yes, your normalised CO2 is pretty meaningless and hence misleading. How about you normalise the temps too ? 😉
If you plot the log of CO2 conc over the same period it’s probably almost as flat, though technically non-zero.
Leif,
the RSS trend 2001-2013 is – 0.08. Probably not a big deal (no new Ice Age in sight), but cooling nevertheless.
Woodfortrees is being abused by overanalysis by “chartists” playing with their PCs.
The criteria for statistical significance is vastly abused. It amounts to looking at an elephant with an electron microscope.
Northern hemisphere glaciers began melting naturally before 1800.
Satellite radiometers show no significant warming since 1979. An anomaly of 0.2 degrees is not significant.
Rejecting UHI contaminated surface temps leaves a few good surface station data.
The remaining good data show show zero waming. eg Antarctica.
The long term temp trend is visible when looking at longer term temp data.
Using Best data with satellite data added to show the UHI contaminated data since 1980.
http://www.woodfortrees.org/plot/best/scale:1/plot/rss-land
I just have two unimportant, trivial questions. What is the absolute Global average temperature today and what was it fifty years ago?
The half way trends are a good idea.
There may be no overall warming but there sure is a change from warming to cooling centred on 2005, which Willis pointed out some time ago appears to be a ‘regime change’.
A change from +ve to -ve slope is also called a decelleration.
GISS flat for 294 months, eh?
That’s what you get for artificially increasing your temperatures to make things look more dangerous. But, of course, Hansen does have an answer.
If he simply confesses to a few of his little tricks and lowers the temperatures over the last three years, he will magically have a rising graph again. I wonder if he’ll do that?
A similar peak was shown in Dr Maue’s hurricane data.
HADCRUT4 is also out now for July.
http://notalotofpeopleknowthat.wordpress.com/2013/08/23/global-temperature-reportjuly-2013/
12-month average is still below the 10-year average.
What’s “RSS”? We’re not all undergrads at Weather U.
Ivan says:
August 25, 2013 at 10:32 am
the RSS trend 2001-2013 is – 0.08. Probably not a big deal (no new Ice Age in sight), but cooling nevertheless.
-0.08 is not statistically different from zero or even +0.08 for that matter.
I do like the subtle poking of fun at Michael Mann with the upside down grapth you show. It’s OK to turn a graph with a flat line upside down. The result is the same. Unlike Mann’s Tiljander effort.
@Greg: Actually, the log of CO2 for 1996-2013, increased 25% faster than for 1980-1996. WFT can’t calculate such things, but you can click on the link to download the data and do it yourself.
So, the heat is still busy hiding in the depths of the oceans and/or hopscotching around the globe, playing hide-and-seek. C02 heat is tricky that way.
This can not be. Did not Obama say there has been accelerated warming in the last 10 years? Who is not telling the truth?
(oh, it’s the climate models you say…)
Well, sorry if I am wrong, but I don’t see an explanation of the meaning of RSS at the start of the post.
According to the glossary RSS means ‘remote sensing system’ but I have the feeling in this post is means something different, temperature data.
What is more, In the paragraph Climate Science Abbreviations of the glossary there is no RSS.
So what is the exact meaning of RSS in this post?
Let’s not lose sight of the big picture which is that this flat line temperature data does not in any way match up with the IPCC temperature predictions/projections for the first two decades as published with fanfare in their 5 year reports.
Thus their AGW conjecture fails once again.
Have you started using the “Mann” trick of upside down data in chart 3??
I noticed that the CO2 concentration graph appears to show a trend that is very linear. If the anthropogenic contribution to the overall concentration is significant, would this not imply that the trend of this component alone also be linear? I understand that a method of smoothing has been applied to create the graph, yet I am still inclined to think that some variation in the human CO2 output should reflected in the slope in this graph.
mpcraig (August 25, 2013 at 10:14 am) asks: “Does anybody know the global average SST vs the global average air temperature over the oceans? If the former is lower, how can heat transfer (net) from atmosphere to ocean?”
Don’t know of a data source, but your logic only holds if atmosphere to ocean heat transfer is linear. But we know it is quite nonlinear. For example, the trade winds during neutral and La Nina conditions are able to move warmer surface water west in the Pacific and then down into deeper ocean out there. Another example is downwelling areas in Arctic and Antarctic are very efficient at transferring heat into the ocean even with relatively colder ocean temperatures in those locations.
Third graph upside down, it seems.
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