RSS Flat For 200 Months (Now Includes July Data)

WoodForTrees.org – Paul Clark – Click the pic to view at source

[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.

WoodForTrees.org – Paul Clark – Click the pic to view at source

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.

Trend1B
Source: WoodForTrees – Paul Clark – click to view at source

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.

WoodForTrees.org – Paul Clark – Click the pic to view at source

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.

Graph 1 and graph 2.

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.

Graph 1 and Graph 2.

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.

Graph 1 and Graph 2.

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.

Graph 1 and Graph 2

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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August 25, 2013 3:46 pm

David W says:
August 25, 2013 at 3:10 pm
“Thus no global cooling…”
For a scientist this post is very poorly worded. It seems to say more about your ideology than anything else.

That your feathers appear ruffled by my comment seems to say something about your ideology.
You did not react to:
justthefactswuwt says:
August 25, 2013 at 10:11 am
I agree, it all seems quite average to me…

James Strom
August 25, 2013 3:57 pm

Werner Brozek says:
August 25, 2013 at 1:38 pm
>>>… the important thing that I wanted to illustrate was that CO2 was steadily climbing while temperatures were not.
This is worth shouting out. Some posters on these threads have the ability to tease out subtle quantitative relations between carefully researched factors, and I admire their skills, but this relation that you mention hits the floor with a clunk. In the approximately seventeen year “pause” in global warming, CO2, the main causal factor, has increased by approximately 8%, without measurable effect. This is strong evidence that CO2 is a less effective driver than thought or that other factors that we haven’t been studying are able to overcome the effect of CO2. Either of these conclusions is bad news for the consensus view.

RossP
August 25, 2013 4:07 pm

I found this paper on another site earlier. Follows the same “line” as Clive Best above.
Interesting conclusions
http://www.ears.nl/user_files/04-Rosema_b.pdf.

Catcracking
August 25, 2013 4:10 pm

“Now if you find out that the rate of return on the investments your financial advisor had described as “accelerating” had actually been reducing for a over decade, how would you describe that person?”
I Love this characterization, can I borrow it and use in my emails to friends?

cba
August 25, 2013 4:21 pm

Personally, I found the graph with the co2 vs T quite interesting. As I understood it, the scales were chosen to indicate the rough range of expected T increase for the given amount of co2 increase. Granted the co2 is a log function but it has diminishing effect with increases so a small section of linear comparison should net a steeper curve of T increase than the overall which should have been at least to go from bottom to top of the graph at that scale. The flatline response shows us nothing happened. Since all of these supposed positive feedbacks are actually temperature based, no increase in temperature means no positive feedback is going to happen at any time scale from this increase – unless there was some temporary and immediate situation that existed which worked against the co2 and kept the T from rising.
I am afraid I encountered the current or next facet of the assault. I attended a training seminar put on by a ‘scientist’ educator who made lots of efforts – like ad hom attacks, straw man arguments, non sequiters, etc to promote the CAGW and that education (and science education) must overcome these deniers and to present a solution currently being tested that dillutes science education more than it already is. Somehow, the claim that the Earth has been warming magically turned into catastrophic anthropogenic global warming. Also, somehow, their solution to educating included the use of pseudo scientific topics to train the students to distinguish between the real and the false, but somehow, while distinguishing between real authorities (true believers?) and non authorities (blasphemers?) was described when talking a bit about the scientific method, there was no mention of analyzing actual data as being an important part of the scientific method.
I am still somewhat traumatized by the recent event and I know that most of the attendees were not prepared to even recognize these things.

August 25, 2013 4:29 pm

David W says:
August 25, 2013 at 3:10 pm
“Thus no global cooling…”
For a scientist this post is very poorly worded. It seems to say more about your ideology than anything else.

There are two camps of alarmists: the CAGW camps and the ‘it’s the Sun, stupid’ camp. One way of interpreting a ‘flat RRS curve’ is note that by colossal coincidence, the effects pushed by the two camps just cancel out Another way is [what I would consider the null-hypothesis] to note that neither effect is operating to any significant degree. Which one do you subscribe to, or what is your ideology?

August 25, 2013 4:41 pm

Reblogged this on CACA and commented:
On six different data sets, there has been no statistically significant warming for between 18 and 23 years, despite record and rapidly increasing ‘carbon pollution’ emissions over the same period ~ settled science?

August 25, 2013 4:55 pm

lsvalgaard says:
August 25, 2013 at 4:29 pm
Another way is [what I would consider the null-hypothesis] to note that neither effect is operating to any significant degree.
=========
Another option would be to say there is insufficient evidence. While the later is more likely, co-incidence is not impossible.
humans tend to see things in black and white. we all too often equate long odds with a sure thing. However, Is there any bet more risky than to bet the farm on the “sure thing”?

Nick Stokes
August 25, 2013 5:12 pm

wbrozek says: August 25, 2013 at 3:26 pm
“When we did the Crowdsourcing about 6 months ago, we asked about other sources for this information but found none.”

I am now keeping the all periods, all sources diagrams here updated. For example, here is the RSS plot. You can choose the interval for data display by either clicking on the triangle, or using the controls on the graph. You can choose to display significance levels, t-values etc.

August 25, 2013 5:14 pm

JimS says:
August 25, 2013 at 11:34 am
This can not be. Did not Obama say there has been accelerated warming in the last 10 years? Who is not telling the truth?
===========
Looking at the data there has been a decrease in the rate of warming, so technically there has been accelerated warming, in a negative direction.

Pamela Gray
August 25, 2013 5:24 pm

Dan Pangburn says:
August 25, 2013 at 3:13 pm
“The influence of CO2 is separated from natural influence at…”
No it hasn’t. Solar variations have been shown to be a very poor proxy for temperature trends. In addition you have no mechanism. Therefore your solar connection to the trend is about as good as the fact that I have grown older during the same time period. Therefore I am just as good a candidate as your solar sunspot number is as a driver.

Barry
August 25, 2013 5:46 pm

For those interested in decadal change, is the decade to June 2013 warmer than the preceding decade ending June 2003?

JimF
August 25, 2013 6:46 pm

The CO2 is just reserving its strength, waiting for the opportune moment – probably coinciding with great humungous glob of heat rising, like Leviathan out of the cold ocean depths where it has been dodging ARGO floats and such, to the surface, – to give us a serious roasting. Or not.

kadaka (KD Knoebel)
August 25, 2013 6:47 pm

Barry said on August 25, 2013 at 5:46 pm:

For those interested in decadal change, is the decade to June 2013 warmer than the preceding decade ending June 2003?

http://woodfortrees.org/plot/wti/from:1993.45/to:2003.45/plot/wti/from:1993.45/to:2003.45/trend/plot/wti/from:2003.45/to:2013.45/plot/wti/from:2003.45/to:2013.45/trend
Notation note: Dates include decimal years, June is 0.42, so June 2003 is 2003.42. Call-out uses 0.45 as that’s between June and July and WoodForTrees works with whole months anyway. So 1993.45 to 2003.45 indicates July 1993 to June 2003 inclusive.
Decade ending 6/2013 was warmer than that ending 6/2003, which was expected since there was still warming in the first decade.
But as you can see, in the second decade there was cooling. Whether it was statistically significant or not, eh, who knows.

JimF
August 25, 2013 6:54 pm

I want to coin the term for a great belch of heat from the abyss, if and when it happens: a “Trenberth”.

August 25, 2013 7:35 pm

ferd berple says:
August 25, 2013 at 4:55 pm
Another option would be to say there is insufficient evidence.
You mean to say there is insufficient evidence to say that the warming has stopped?
I’ll go so far as to agree that there is insufficient evidence for anything. Most people would say that if their pet theory is not supported, there clearly is insufficient for the opponents theory.

thingadonta
August 25, 2013 7:41 pm

Unfortunately, some years ago the data became too readily available, and they couldnt make adjustments anymore, strange that the warming stopped at about the same time.

Werner Brozek
August 25, 2013 7:42 pm

Nick Stokes says:
August 25, 2013 at 5:12 pm
Thank you! However I will need time digest it.

August 25, 2013 7:58 pm

kadaka (KD Knoebel) says:
August 25, 2013 at 6:47 pm
But as you can see, in the second decade there was cooling. Whether it was statistically significant or not, eh, who knows.
The SkS site for RSS from 2003.58 to 2013.58 gives a slope of “Trend: -0.047 ±0.409 °C/decade (2σ)”. So it is no where close to being statistically significant. It is not even close at the 1 sigma level which I presume would be +/- 0.205, but I could be wrong here. Perhaps Nick Stokes can figure it out. Perhaps a 54% chance that it is cooling? But I am just guessing here.

Nick Boyce
August 25, 2013 8:28 pm

Genghis says:
August 25, 2013 at 10:38 am
I just have two unimportant, trivial questions. What is the absolute Global average temperature today and what was it fifty years ago?
Approximate decadal absolute global surface air temperatures, correct to 1dp
August 1953 to July 1963, 13.9(+0.4, -0.7)°C
August 2003 to July 2013, 14.5(+0.4, -0.7)°C
(1) The figures of 13.9, and 14.5 are as per GISTEMP’s “LOTI”.
http://data.giss.nasa.gov/gistemp/tabledata_v3/GLB.Ts+dSST.txt
(2) The assymetric error estimates, (+0.4, -0.7), are as per GISTMP’s “The elusive absolute surface air temperature”, which is one of the most remarkable, and subversive, documents in climatology. If you’ve not read it already, I urge you to read it.
http://data.giss.nasa.gov/gistemp/abs_temp.html
(3) The temperature for 08/1953 to 07/1963 could have been as high as 14.3°C.
(4) The temperature for 08/2003 to 07/2013 could have been as low as 13.8°C.

climatologist
August 25, 2013 8:29 pm

Wasn’t there a period between 1944 and 1976 when the global temperature was flat or even falling slightly?

rgbatduke
August 25, 2013 8:36 pm

I will make the adjustment in the next report. I agree that if one wants to compare apples to oranges, one cannot be too quantitative in this case. I should have been more qualitative in my description and said that while the oranges (CO2) were rising, the apples (temperature anomalies) were not rising. Thank you very much for the correction!
Not a problem. A second suggestion. You, like everybody else in the known universe, present not the absolute values of the quantities in question, but the so-called “anomalies”. If you want to see something very, very instructive, plot them in their actual units — parts per million (for example) for CO_2, degrees kelvin for temperature.
There are a number of reasons this is basically never done. One is that on a 300 degree kelvin (give or take a hair) scale, in a figure perhaps 300 to 600 pixels high total, the entire thermometric climate record is pretty much a single totally flat line — at most it varies over a single pixel in height. If you plotted it in absolute units and included error bars, the error bars would be several pixels thick everywhere but in the very last tiny bit, pretty much the stretch from the 1970s to the present, and the line would get thicker fast as one proceeds into the past from there. If you presented this in any public forum, it would be rather difficult to convince people that the world is at risk. The CO_2, on the other hand, has increased by 1/3 over the last seventy years — a substantial change, it would show up on any graph.
It is presenting the CO_2 change next to the temperature change presented as an anomaly measured only from 1870 to the present — that is, from the Dalton minimum and functional end of the Little Ice Age to the present — that provides the illusion of a “good” correlation. If you present the over longer intervals, the natural range of variation becomes apparent, and the LACK of good correlation between CO_2 and temperature over even the last 140 years becomes equally obvious — it warmed almost as much from 1870 to 1950 as it did from 1950 to the present, enough to make it very, very difficult to be able to discern the CO_2 linked fraction of any temperature changes that might or might not have occurred across this interval. This both weakens and strengthens your argument. It strengthens in that it shows that natural variation is sufficient to explain all or most of the observed late 20th century warming as the Earth is demonstrably capable of warming substantially and rapidly without CO_2 forcing; it weakens it because the flip side of that coin is that even if CO_2 is indeed acting as a GHG that “should” be making it warmer all things being equal, natural variation could be cancelling all or most of the warming because all things are NOT, actually equal. That does not mean, however, that when the natural cooling cycle ends that warming will not resume.
I generally dislike arguments that attempt to prove something about the climate on the basis of correlation or a lack thereof, because post hoc ergo propter hoc is a logical fallacy whichever way you swing it. Correlation between CO_2 increases and temperature increases does not prove CAGW, and a lack of correlation between CO_2 increases and the temperature does not disprove it. The only safe thing to say, as I said, is that is certainly not good evidence for the proposition. Otherwise, you can take any generally increasing monotonic quantity and claim it is the “cause” of the generally increasing temperature post 1870, or get involved in the arcane numerology of fitting planetary cycles or misreported sunspots or possibly miscalculated solar magnetic field strength data (known by means of proxies) to temperature data (ignoring the error bars in the latter, as usual).
There was an op ed on CNN recently where the writer was defending Al Gore’s Category 6 hurricane invention (and carefully sidestepping the facts that Pielke, Jr presented to congress recently, that there is no statistically observable trend in strength, frequency, or normalized damage of any kind of extreme weather over ANY time interval that makes a hash of Gore’s entire, oft-repeated, untrue assertions to the contrary). The writer then went on (after asserting that “even category one hurricanes can be very damaging”, well duh, but there isn’t any evidence of the slightest anthropogenic influence on the frequency or damage of even category one hurricanes) to assert that we are sure to get 3 to 6 feet of SLR by the end of the century.
Say what? This is Hansen’s old argument and its associated egregious claims, now with an independent life of its own. It is directly contradicted both the tide gauge data and the new (and still somewhat shaky) satellite data. Even Trenberth no longer claims anything like this in public (IIRC, his claim is currently for perhaps 15″, which is high but not completely insanely unreasonable). I replied, and was immediately told that I was wrong because (for example) the rate over the last 15 years was 3.3 mm/year while its average rate from 1870 to 1995 or so was less than 2 mm/year, proof that it is “accelerating”. I pointed out that if you look at the actual tide gauge data on SLR from 1870 to the present, there are four distinct periods of a decade or longer where the rise rate was 3.3mm/year or even more — including a decade at the very beginning of the 20th century and the twenty years from 1930 to 1950 (both of which are pre-CO_2). It is no more reasonable to look at the last 15 years as evidence of acceleration or a linearly extrapolatable 15″ by 2100 than it would have been to look at 1930 to 1950 and conclude that the ocean should be several inches higher now than it is, or to look at an interval from e.g. 1910 to 1920 (IIRC) where SLR was almost perfectly flat and conclude that THIS was an extrapolatable trend.
The point being that reason is almost entirely absent at this point from the entire climate debate, on both sides. Post hoc ergo propter hoc has become the foundation of all arguments, and any claim, no matter how outrageous, now has an effectively infinite lifetime in the public debate. How do you refute the assertion that SLR will rise six feet by 2100? Point out that six feet is 72 inches, so that the ocean would have to rise an average of an inch a year where it is currently rising at an eighth of that rate in what could easily be an entirely natural rate fluctuation? Point out that in order for this to occur Greenland and Antarctica would both have to lose a rather large fraction of their land-based glacial icepacks in a matter of a few decades, where there isn’t any real evidence that they are losing ice at all, or at most are contributing significantly less than 1 mm of the current SLR (even according to climate scientists looking for that “warming signal”, which one can interpret as open season on cherrypicking any or all data that supports it). Point out that every year that the rate of SLR peskily persists at 3 mm/year means that it has to rise even faster than an inch a year later on? Point out that the only basis for believing this is an “ensemble” result obtained by averaging GCMs most of which individually would fail a bone-simple statistical hypothesis test when compared to the actual climate data at the 95% confidence level or more, and adding in a dose of voodoo magic because it would take a few centuries to melt a significant fraction of the icepacks of either greenland or antarctica assuming that the climate DID warm by a couple of degrees by the end of the century?
Which brings us around to your top post, which quite correctly demonstrates — again, since this is hardly secret knowledge — that there has been no discernible warming trend since the 1997-1998 Super El Nino. Or cooling trend. One can play games and cherrypick intervals a bit this way and show some cooling, a bit that way and show some warming, but the really important divergence isn’t between CO_2 on some arbitrary scale and a temperature anomaly on an even more arbitrary scale across an arbitrary interval it is the divergence between the GCM predictions from 1998 to the present and reality.
That’s not a matter of cherrypicking a start. The GCM predictions were made at a (set of) definite times. Most GCMs ran, at that time, an ensemble of possible futures given continuously increasing CO_2 (as it has in fact continued). The actual performance of the climate is outside of the range of 95% or more of the ensemble predictions over almost the entire interval. Worse, if one tracks the individual trajectories themselves, none of them behaved at all like the climate for most of the models — at least the ones I can see e.g. reported in AR5 or AR4. Typically the models make future trajectories that oscillate up and down, oscillate differently per run but still over a wide range, and the observed climate is at the bottom of the envelope of these oscillatory outcomes. This isn’t really failure at the 95% confidence level — per model — it is failure of the model, the kind of failure that one doesn’t even question, it is “certain failure” at more than 99%, an amount so much more that is difficult to calculate. That is, if you compared each model-generated trajectory to the actual data, you would instantly say “nope, no, not that one, not even close…” one at a time for all of the trajectories. The best thing one could say is that some comparatively small fraction of them descend to spend some small fraction of their time down close to the observational data.
That is one of several reasons that the AR4 summary for policy makers is egregious statistical fraud, and I’m very much afraid that AR5 is set up to make exactly the same mistake. It might not even be “deliberate” — not many people are competent in statistics, and by plotting the composite envelope (which in some cases barely catches the data on the bottom) one is misled into believing that it is this envelope that determines the variance of the models overall, rather than the fraction of time any given model trajectory spends anywhere near the observational data, per model.
I repeat — this is not cherrypicking an interval, it is comparing a prediction made at a certain time to the only data we have that follows. Yes, the models were built to fit the prior data, so fitting it is not a surprise or an endorsement of the predictive power of the models. It is how the models do at actually predicting the future that matters.
This final step is the constructive one. Suppose that you are the keeper of a GCM, and you honestly appraise your model’s performance over the last 16 to 20 years. You note that — let’s be blunt — your model fails to predict this interval, not at any “confidence” level but at the level of pretty much certainty. You can then go into your model and try adjusting its adjustable parameters to improve the model. For example, you could turn the climate sensitivity way down, completely retune the way water vapor is handled, allow for a lot more natural variation that (if you are honest) you cannot predict and do not even understand as your model does not hindcast any of it, try to once again fit it to the trial set pre-1998 (or whenever) and see if it can fit the actual data THEN.
This is the kind of thing those of us in the predictive modeling game for actual money call “training and testing a predictive model”, and when there is money on the line, you dasn’t fail or you go broke. If a major wall street investment company sold its clients a bull market prediction that went up like CAGW was supposed to go up, and the market turned flat to bearish for 16 years (where that investment firm kept going back to its clients, year after year, and claimed “the market is about to go up, look at our models, they are sky high, we have found a secret pathway where money has been diverted into rails and has been building up and the market will come roaring back, any day now”) how many clients would they still have? Would “zero” be a reasonable guess, given that all of its clients would by now be bankrupt from shorting themselves into a supposedly rising market?
The thing is, building a predictive model for a complex, nonlinear, multivariate system like the climate or the stock market is goddamn difficult! Or rather, it is stunningly easy, with readily available tools. It is building one that works that is difficult, no matter what tools and how much insight you bring to bear. For example, the performance of the stock market is almost certainly tied not only to the actual climate (in many ways) but at this point it is tied into the public perception of the climate in as many or even more ways! And for all of that, this is only a possible/probable causal factor that can easily be swamped my many, many other things acting singly or collectively — the cost of money, how many wars we are fighting, and where, whether or not the next major public scandal involving corporations acting like banks illegally or banks acting like banks stupidly is ready to fling shit at the fan, monetary policy and unemployment in Greece, the rate that the Chinese are modernizing, and mere weather events like Sandy that can shut the market down and make a few tens of billions of dollars disappear overnight.
How the hell do you model that?
The climate is really not much simpler, for all that we can in principle describe the physics of each parcel of atmosphere and water and land and the sun down to a stunningly fine resolution, although with a number of approximations and attendant errors that are very difficult to estimate. That is because the climate system is chaotic, nonlinear, and highly multivariate.
All that is really missing in climate science is honesty. I was on jury duty a few days ago with an area meteorologist, and while we were debating the Bayesian merits of the evidence in the criminal case at hand he made a comment that I — correctly — interpreted as his being highly dissatisfied with climate science. After the verdict was in, we chatted about the weather and climate for almost an hour before finally going home. He pointed out that the one really sad thing about climate science isn’t that the science that is being done isn’t terribly good, that the GCMs are failing and so on. It is a goddamn hard problem, one expects to fail. It is the lack of honesty, the assertion of results from failed models as if it were reality, even in the face of a reality that directly contradicts those predictions!
It is not too late for AR5, even now. All they need to do is publicly acknowledge what almost all the scientists involved already know as a most inconvenient, uncomfortable truth. The GCMs upon which predictions of future catastrophe rely have more or less failed, and the statistical relevance of those predictions has been erroneously computed and horrendously misrepresented in previous AR reports. This doesn’t mean that AGW is an incorrect hypothesis, and it does not disprove even CAGW, but it does mean our certainty of the magnitude of AGW past, present and future is a lot less than has been asserted.
A tiny bit of honesty, and it would make all of the difference in the world. It would enable science to be carried out that for once was not trying to verify CAGW (so that it could get funded at all). It would allow world leaders to come back to sanity and back off on the expensive and pointless attack on Demon Carbon and instead concentrate on constructive things, such as supporting research and development of e.g. PV solar not to Save The World but because it will ultimately save US taxpayers money as the price per watt continues to plummet. I communicated today with a chance-met slashdot person who sells PV solar systems, and he tells me that they sell PV solar full retail with warranty for $0.69/watt. That is down by almost $0.30 in only three or four years. He’s installed it for himself at break even to win a bit in Toronto, driven not by any desire to “be green” but because energy prices plus regular inflation make it a decent investment even that far north. Power companies can get wholesale cells at $0.50/watt for large scale installations.
We are thus within a hair of making solar energy not just a positive ROI (without subsidy) investment. We are within two hairs of it becoming a no-brainer, the next gold rush as every household puts PV solar on the roof. Just as natural gas caused the US to actually reduce its carbon footprint not because it is saving the environment but because it is cheap and methane is one carbon per four hydrogens so a lot of the energy comes from burning hydrogen, not carbon, PV solar will reduce its carbon footprint still further not because it is saving the environment but because there is something dazzlingly attractive about paying out about the same amount that I just paid for three household air conditioners and never have to pay for the electricity to run them again!
It would let coastal communities STOP preparing for meter-plus SLR that will start — honestly, trust me — any day now (as if it will all happen overnight, so we need to go ahead and spend a fortune now because it is certain). It would let Europe stop building windmills that — curiously — don’t generate power when the wind doesn’t blow, which is a lot of the time in most places. It would let third world countries build coal-burning power plants without spending two or three times their normal cost trying to control CO_2 as a “pollutant”, which in turn will save countless lives and improve the living conditions of millions of people right now, not in 80 years. And yeah, in ten more years they too can benefit as the price of solar continues to drop, allowing them to eke out a coal burning generator during peak daylight demand when air conditioners are most needed, when most manufacturing takes place, when water can be purified and pumped without burning coal at all not to save the Earth but to save money.
Perhaps it will be saving the Earth, perhaps not. It’s hard to say at this point. We really don’t know. We have some reason to think that it would be wiser not to pump up atmospheric CO_2 more than we have to in order to bring the world up to a uniform degree of civilization as rapidly as possible, but we also have some excellent reasons not to let the fact that building up civilization quickly and inexpensively (still) requires the burning of oil and coal stop us from doing it, at least until the science is a lot clearer than it is at the moment. By which time, as I said, the issue might well be moot. We are almost to the point where mere engineering will lead to the utter dominance of PV solar (that is, nuclear energy once removed) supplemented by natural gas and, perhaps, eventually, by nuclear energy, and there are a couple of technological game changers that could happen literally overnight (or not). Invention of a viable, cost-effective long distance energy transmission scheme — something that could move power from Arizona to Maine, or from the Negev to the Netherlands. Development of a scalable technology that would permit solar power to be “banked” for overnight delivery, e.g. pumping up underground caves with compressed air and using the air to run a conventional generator during the night and to buffer power fluctuations. Reduce solar costs to $0.25/watt, or $0.10/watt, and we’ll have power to (not) burn, so to speak — we could afford to put 3 GW of generation in where we only need 1 and bank 2 to get us through the night.
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kadaka (KD Knoebel)
August 25, 2013 8:43 pm

From wbrozek on August 25, 2013 at 7:58 pm:

The SkS site for RSS from 2003.58 to 2013.58 gives a slope of “Trend: -0.047 ±0.409 °C/decade (2σ)”. So it is no where close to being statistically significant.

Except my link was for the WoodForTrees Temperature Index (WTI). The SkS trendy toy doesn’t do WTI.
So do you know if the WTI cooling trend is statistically significant?

Werner Brozek
August 25, 2013 8:49 pm

climatologist says:
August 25, 2013 at 8:29 pm
Wasn’t there a period between 1944 and 1976 when the global temperature was flat or even falling slightly?
Of course RSS does not go back that far, but Hadcrut3 shows a negative slope from 1940 to 1976. See:
http://www.woodfortrees.org/plot/hadcrut3gl/from:1850/plot/hadcrut3gl/from:1940/to:1976/trend

August 25, 2013 9:00 pm

kadaka (KD Knoebel) says:
August 25, 2013 at 8:43 pm
So do you know if the WTI cooling trend is statistically significant?
WTI is a combination of Hadcrut3, GISS, RSS and UAH. They discontinued Hadcrut3 very recently, but they do have Hadcrut4 which has a slightly lower slope, but even so, the numbers are no where close to being statistically significant over the last 10 years. Here are the 4 numbers for Hadcrut4, GISS, RSS and UAH:
Trend: -0.055 ±0.219 °C/decade (2σ)
Trend: -0.019 ±0.243 °C/decade (2σ)
Trend: -0.047 ±0.409 °C/decade (2σ)
Trend: 0.040 ±0.412 °C/decade (2σ)