1

Open Letter to the Climate Science Community:

Response to “A Climatology Conspiracy?”



Summary

A paper by D.H. Douglass, J.R. Christy, B.D. Pearson, and S.F. Singer, published online in the 

International Journal of Climatology (IJoC) in December 2007, contained a serious error in a 

statistical test.

1

This error led Douglass et al. to make the incorrect claim that modeled and 

observed tropical temperature trends “disagree to a statistically significant extent”. These 

incorrect conclusions received considerable publicity.

The nature of the statistical error is clearly explained in a paper my colleagues and I 

published in the online edition of the IJoC in October 2008.2The statistical flaw is also explained 

in readily-understandable terms in the attached “fact sheet” (see Appendix A below). 

Douglass and Christy have now focused on the selective interpretation of emails stolen 

from the U.K.’s Climatic Research Unit (CRU). Their suggestively-titled article, “A Climatology 

Conspiracy?”, was recently published online in “American Thinker”.3

In “A Climatology Conspiracy?”, Douglass and Christy make a number of allegations 

against the primary authors of the 2008 Santer et al. IJoC paper and against the editor of the 

IJoC. The focus here is on addressing two of the most serious allegations. The first allegation is

that there was a conspiracy to deny Douglass et al. the opportunity to respond to the Santer et 

al. IJoC paper. The second allegation is that there was collusion between the editor of the IJoC

 



This open letter was sent by email to over 150 members of the climate science community on February 3, 2010.

1

Douglass, D.H., J.R. Christy, B.D. Pearson, and S.F. Singer, 2007: A comparison of tropical temperature trends with 

model predictions. International Journal of Climatology, 27: doi:10.1002/joc.1651.

2

Santer, B.D., P.W. Thorne, L. Haimberger, K.E. Taylor, T.M.L. Wigley, J.R. Lanzante, S. Solomon, M. Free, P.J. 

Gleckler, P.D. Jones, T.R. Karl, S.A. Klein, C. Mears, D. Nychka, G.A. Schmidt, S.C. Sherwood, and F.J. Wentz, 

2008: Consistency of modelled and observed temperature trends in the tropical troposphere. International 

Journal of Climatology, 28, 1703-1722. DOI: 10.1002/joc.1756.

3

“A Climatology Conspiracy?”, by David Douglass and John Christy, was published online in “American Thinker” on 

December 20, 2009. See http://www.americanthinker.com/2009/12/a_climatology_conspiracy.html 
2

and some of the authors of the Santer et al. IJoC paper. Douglass and Christy suggest that the 

aim of this collusion was to subvert the normal, rigorous, peer-review process. 

With regard to the first allegation, the authors of the 2008 Santer et al. IJoC paper 

performed a substantial amount of new and original scientific research. It was therefore 

entirely appropriate for the editor of the IJoC to treat the Santer et al. IJoC paper as an 

independent scientific contribution, and to publish Santer et al. as a ‘stand alone’ paper rather 

than simply as a comment on the 2007 Douglass et al. IJoC paper. This editorial decision did not 

– as Douglass and Christy incorrectly allege – deny Douglass et al. the opportunity to respond to 

the scientific issues raised by the Santer et al. IJoC paper. 

Douglass and Christy have had every opportunity to respond to scientific criticism of 

their 2007 IJoC paper, both in the pages of the IJoC and elsewhere. For example, they could 

have contributed a new scientific article to the IJoC, or submitted a comment on the Santer et 

al. IJoC paper. They have not done so. Nor has the Douglass and Christy “American Thinker” 

article adequately addressed concerns regarding the use of a seriously flawed statistical test in 

the Douglass et al. IJoC paper. 

The second major allegation (collusion between the IJoC editor and the authors of the 

Santer et al. IJoC paper) is also baseless. The Santer et al. IJoC paper underwent a normal 

review process, involving two rounds of peer review by two highly-knowledgeable reviewers. 

The authors of the Santer et al. paper provided over 30 pages of detailed responses to the 

review comments. These responses clearly document the rigorous nature of the review 

process, and provide the strongest defense against unfounded “collusion” allegations. To date, 

however, I have not been able to obtain permission from the publishers of the International 

Journal of Climatology to publicly release the responses to the peer review comments on the 

Santer et al. IJoC paper. I am hopeful that this permission will be forthcoming in the near 

future.

As an additional response to the “collusion” charge, I note that our 2008 IJoC paper was 

the first and only paper I have ever submitted to the International Journal of Climatology. I have 

never met the editor of the IJoC (Professor Glenn McGregor), and did not have any 

correspondence or professional interaction with Professor McGregor prior to 2008. 
3

As is clearly shown in the more detailed discussion given below, the “conspiracy” and 

“collusion” allegations – and a number of other claims made in “A Climatology Conspiracy?” –

are simply false.

It is troubling that Professors Douglass and Christy persist in ignoring the serious 

statistical error in their 2007 IJoC paper. I would welcome an independent review by the U.K. 

Royal Meteorological Society4of the scientific issues raised by the Douglass et al. and Santer et 

al. IJoC papers. Such a review would be timely and appropriate. 

 

4

The International Journal of Climatology is published on behalf of the Royal Meteorological Society by Wiley 

InterScience.
4

1. Introduction

In a recently-published commentary entitled “A Climatology Conspiracy?”, Professors D.H. 

Douglass and J.R. Christy have accused me and several of my colleagues of serious professional 

misconduct.5The allegations by Douglass and Christy were made on the basis of emails stolen 

from the University of East Anglia’s Climatic Research Unit (CRU). I am writing this open letter 

to address these allegations. They are baseless and false.

The claims of professional misconduct relate to a paper published by myself and 16 coauthors in the International Journal of Climatology (IJoC), a journal of the U.K. Royal 

Meteorological Society. This paper appeared in the online edition of the IJoC on October 10, 

2008.6I will refer to it below as “S08”.

Many of the stolen CRU emails analyzed by Douglass and Christy were written by me. 

These emails discuss both the S08 IJoC paper and a previously-published 2007 IJoC paper by 

Douglass, Christy, and two of their colleagues.7

Here is a brief history of the genesis of the S08 paper.

2. The Karl et al. CCSP report

Between 2004 and 2006, I acted as Convening Lead Author for one particular chapter of

“Synthesis and Assessment Product 1.1” of the U.S. Climate Change Science Program (CCSP). 

This was the first in a series of 21 reports commissioned by Congress. The aim of the CCSP 

reports was to provide “current evaluations of climate change science to inform public debate, 

policy, and operational decisions”.8Thomas Karl (the Director of the U.S. National Climatic Data 

Center in Asheville, North Carolina) had the overall responsibility for this CCSP report, which

was entitled “Temperature Trends in the Lower Atmosphere: Steps for Understanding and 

 

5

See footnote 3. 

6

See footnote 2.

7

See footnote 1.

8

Karl, T.R., S.J. Hassol, C.D. Miller, and W.L. Murray (eds.), 2006: Temperature Trends in the Lower Atmosphere: 

Steps for Understanding and Reconciling Differences. A Report by the U.S. Climate Change Science Program and 

the Subcommittee on Global Change Research. National Oceanic and Atmospheric Administration, National 

Climatic Data Center, Asheville, NC, USA, 164 pp (the quote is from the unnumbered page immediately before 

the Table of Contents).
5

Reconciling Differences”. The report was published in April 2006. Professor Christy was the 

Convening Lead Author of Chapter 2 of this report.

The Karl et al. CCSP report reached the following conclusion regarding global-scale 

changes in surface and atmospheric temperature:

“Previously reported discrepancies between the amount of warming near the surface 

and higher in the atmosphere have been used to challenge the reliability of climate models and 

the reality of human-induced global warming. Specifically, surface data showed substantial 

global-average warming, while early versions of satellite and radiosonde data showed little or 

no warming above the surface. This significant discrepancy no longer exists because errors in 

the satellite and radiosonde data have been identified and corrected. New data sets have also 

been developed that do not show such discrepancies”.9

In the tropics, however, the Karl et al. CCSP report found that “most observational 

datasets show more warming at the surface than in the troposphere, while most model runs 

have larger warming aloft than at the surface”.10 Although the CCSP report did not reach a 

definitive conclusion about the cause or causes of these tropical discrepancies between models 

and observations, it noted that uncertainties in the observations were very large. Residual 

errors in the weather balloon and satellite data were judged to be the most likely explanation 

for the “discrepancies in the tropics”.

3. The 2006 Douglass et al. GRL paper

Roughly six months after publication of the CCSP report, I received an email from Dr. Chris

Reason, an editor for the scientific journal Geophysical Research Letters.

11 I was asked to review 

a paper by D. H. Douglass, R. Knox, B.D. Pearson, and S.F. Singer entitled “Tropical temperature 

trends during the satellite era: Do model predictions agree with observations?” I will refer to 

this paper below as “D06”. 

 

9

Ibid, abstract, page iii.

10Ibid, page 90.

11The email from Dr. Reason was dated September 10, 2006.
6

I agreed to review the D06 paper, which performed comparisons between observed 

tropical temperature trends (obtained from satellites and weather balloons) and climate model 

results. D06 used the same model and observational data we had employed in both the Karl et 

al. CCSP report and in an earlier paper my colleagues and I had published in 2005 in Science

magazine.12

The bottom-line finding of D06 was that models “fail to reproduce observed trends”, and 

that “these conclusions are in strong contrast with those of recent publications based on the 

same data and models”. It was my professional opinion that the D06 paper had serious 

scientific flaws, particularly with regard to the statistical test used to compare modeled and 

observed temperature trends. In my review of the paper, I recommended rejection. I signed my 

review, and transmitted it to Dr. Reason on September 25, 2006. The D06 paper was not 

published in Geophysical Research Letters.

4. The 2007 Douglass et al. IJoC paper

The next chapter in this story begins on November 30, 2007. On that date, I received an email 

from Mr. Andy Revkin, who until recently worked as a reporter on climate-related issues at the 

New York Times.

13 The email was also sent to Dr. Tony Broccoli and Dr. Carl Mears. Mr. Revkin 

asked us to comment on a paper by Douglass, Christy, Pearson and Singer. The paper was 

entitled “A comparison of tropical temperature trends with model predictions”. As an 

attachment to his email of November 30, 2007, Mr. Revkin appended the page proofs of the 

Douglass et al. paper, which was scheduled to appear shortly in the International Journal of 

Climatology.

 

12Santer, B.D., T.M.L. Wigley, C. Mears, F.J. Wentz, S.A. Klein, D.J. Seidel, K.E. Taylor, P.W. Thorne, M.F. Wehner, 

P.J. Gleckler, J.S. Boyle, W.D. Collins, K.W. Dixon, C. Doutriaux, M. Free, Q. Fu, J.E. Hansen, G.S. Jones, R. Ruedy, 

T.R. Karl, J.R. Lanzante, G.A. Meehl, V. Ramaswamy, G. Russell, and G.A. Schmidt, 2005: Amplification of surface 

temperature trends and variability in the tropical atmosphere. Science, 309, 1551-1556.

13In “A Climatology Conspiracy?”, Douglass and Christy imply that Mr. Revkin and I had engaged in some “prior 

correspondence” regarding the Douglass et al. IJoC paper. This is untrue. No such “prior correspondence” had 

occurred. Douglass and Christy also incorrectly claim that Mr. Revkin sent his email of November 30, 2007, to 

“three team members” (i.e., to three of the authors of the S08 IJoC paper). This, too, is incorrect. Dr. Tony 

Broccoli never was a co-author of the S08 paper. 
7

As noted by Douglass and Christy in “A Climatology Conspiracy?”, the Douglass et al. 

IJoC paper was published online on December 5, 2007.14 I’ll refer to this version of the paper 

below as “D07-online”. The paper quickly received significant publicity. Its finding that “models 

and observations disagree to a statistically significant extent” was highlighted by Fox News. The 

D07-online paper was the centerpiece of a press conference held by one of its co-authors (S.F.

Singer) at the U.S. National Press Club. A press release from this conference claimed that the 

Douglass et al. findings represented “an inconvenient truth”, and proved that “Nature rules the 

climate: Human-produced greenhouse gases are not responsible for global warming”.

15 The 

Douglass et al. results were also featured prominently in a report issued by the Heartland 

Institute in March 2008.16

After reading D07-online, it immediately became obvious that the paper contained a 

serious statistical error. The nature of this error is explained in detail below in Appendix A.17 I 

use the word “error” advisedly. This was not simply a difference of opinion between two groups 

of scientists. Douglass et al. had devised and applied what they described as a “robust statistical 

test” to reach their finding of a statistically significant discrepancy between modeled and 

observed tropical temperature trends. The test they devised is inappropriate for comparing 

models and observations. It cannot be used for determining whether or not the data sets 

considered in D07-online (observed and model temperature trends) show significant 

differences. 

This can be demonstrated unequivocally by applying the Douglass et al. test in a 

situation where the answer is known a priori. Such “stochastic simulation” methods rely on 

randomly generated data with known statistical characteristics. With the aid of stochastic 

simulation, it can be shown quite easily that the Douglass et al. “robust statistical test” fails to 

give correct results. In fact, it fails in a very obvious way. In cases where there is no significant 

 

14Douglass, D.H., J.R. Christy, B.D. Pearson, and S.F. Singer, 2007: A comparison of tropical temperature trends with 

model predictions. International Journal of Climatology, 27: doi:10.1002/joc.1651.

15Press release from conference held at U.S. National Press Club, January 2008.

16S. Fred Singer, ed., March 2008: Nature, Not Human Activity, Rules the Climate: Summary for Policymakers of the 

Report of the Nongovernmental International Panel on Climate Change, Chicago, IL: The Heartland Institute, 50 

pp.

17Appendix A consists of a “fact sheet” which was distributed at the time of online publication of the S08 IJoC

paper.
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difference between two data sets, the test frequently yields the incorrect answer that there is a 

significant difference.

18

D07-online relied on “essentially the same data”

19 used in Chapter 5 of the 2006 Karl et 

al. CCSP report20 and in the 2005 Santer et al. Science paper, yet reached very different 

conclusions from either of those previous publications. In my opinion, it was incumbent on the 

authors of D07-online to ask why they had reached radically different findings from previous 

work, and to investigate whether their statistical test was appropriate. They did not attempt to 

explain why their results differed from those previously published, nor did they attempt to 

show that the test they used was suitable for their task.

5. The 2008 Santer et al. IJoC paper

Given the serious nature of the statistical flaw in D07-online, the incorrect claims being made 

on the basis of the paper, and the widespread publicity that it had received, I decided that it 

was necessary to conduct an independent scientific assessment of the methods and results in 

D07-online. This decision was taken after discussions with a number of my colleagues at LLNL

and at scientific institutions around the world. I sought the advice and guidance of experts in 

climate modeling, statistical analysis, and the development of observational temperature 

datasets.

My colleagues and I quickly reached the conclusion that we needed to do more than 

simply write a short note identifying the statistical flaw in the D07-online paper. Although the 

error in the paper could be easily demonstrated, the issue of statistical significance testing was 

too complex to cover in a short comment on D07-online. Furthermore, we decided that it 

would be much more illuminating to do the significance testing21 properly, with several 

 

18These tests with randomly-generated data were performed in Section 6 of the S08 IJoC paper.

19This quote is from the abstract of D07-online.

20Santer, B.D., J.E. Penner, P.W. Thorne, W.D. Collins, K.W. Dixon, T.L. Delworth, C. Doutriaux, C.K. Folland, C.E. 

Forest, J.R. Lanzante, G.A. Meehl, V. Ramaswamy, D.J. Seidel, M.F. Wehner, and T.M.L. Wigley, 2006: How well 

can the observed vertical temperature changes be reconciled with our understanding of the causes of these 

changes? In: Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling 

Differences. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change 

Research [Karl, T.R., S.J. Hassol, C.D. Miller, and W.L. Murray (eds.)]. National Oceanic and Atmospheric 

Administration, National Climatic Data Center, Asheville, NC, USA, pp. 89-108.

21Of differences between modeled and observed temperature trends.
9

different statistical tests, and with some discussion of how these tests performed under 

controlled conditions.

22 We also concluded that if we were going to invest substantial effort in a 

“do over” of the Douglass et al. significance testing strategy, we should use a wide range of 

observational temperature datasets. Many of the datasets we eventually used in the S08 IJoC

paper were new, and had not been available to us at the time of our work on the 2006 Karl et 

al. CCSP report.

The bottom line is that the authors of the S08 IJoC paper performed a substantial 

amount of new and original research. S08 was not simply a brief comment on the statistical 

error in the D07-online paper – it was much more than this. This distinction should be obvious 

to anyone who has read S08. When substantial new research is performed, and a paper based 

on that research is submitted to a peer-reviewed scientific journal, it is customary for the 

journal to treat the new research as a ‘stand-alone’ paper – not to classify it as a ‘comment’. It 

was therefore entirely appropriate for the editor of the IJoC to regard our paper as an 

independent contribution to the IJoC, and not to treat it as a comment on D07-online.

6. The ‘preventing a response’ allegation

In “A Climatology Conspiracy?”, Douglass and Christy (based on their analysis of the stolen CRU 

emails) assert that I tried to prevent them “from providing what is considered normal in the 

peer-reviewed literature: an opportunity to respond to... critique.” This is untrue. Douglass and 

Christy have had every opportunity to comment on S08, to defend their own “robust statistical 

test”, and to criticize the statistical tests we applied to compare modeled and observed 

temperature trends. In particular, they have had every opportunity to try to explain why their 

test fails to perform correctly when applied to randomly-generated data, or why it fails when

applied to climate model data only.

23 To date, such explanations have not been forthcoming.

 

22With randomly-generated data having known statistical characteristics.

23To illustrate how the use of the Douglass et al. statistical test could lead to incorrect inferences, S08 applied the 

test to climate model data only. The temperature trend in each of the 19 models used by S08 was tested in turn 

against the average trend calculated from the remaining 18 models. The Douglass et al. statistical test provided the 

bizarre result that more than half of the 19 models were inconsistent with the average model trend! A test which 

rejects more than half of the population of samples on which it is based is clearly flawed.
10

They are certainly not available in the “scientific discussion” provided by Douglass and Christy in 

“A Climatology Conspiracy?”.

24

No one has prevented Douglass and Christy from submitting a comment on S08 to the 

IJoC. Nor has anyone prevented Douglass and Christy from performing substantive new 

research, and submitting a ‘stand-alone’ paper to the IJoC. In fact, in one of the stolen email 

excerpts that Douglass and Christy reproduced, I explicitly stated that “Douglass et al. should 

have the opportunity to respond to our contribution, and we should be given the chance to 

reply. Any response and reply should be published side-by-side, in the same issue of the IJC”. 

These are clearly not the words of someone intent on advancing a sinister conspiracy to 

suppress scientific debate. Nor do these words sound like the words of someone who would 

“fear a response” from Douglass et al.

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7. The “strategy of delaying” allegation

The S08 paper was published in the online edition of the IJoC on October 10, 2008 – ten months

after the online publication of the Douglass et al. paper on December 5, 2007. As noted above, 

the D07-online paper garnered considerable attention in the 10 months following its 

publication. Extraordinary – and incorrect – claims were made on the basis of D07-online (see 

section 4 above). The paper received high-level attention within the U.S. Department of Energy 

and the National Oceanic and Atmospheric Administration.

Douglass and Christy claim that there was a “strategy of delaying” publication of 

Douglass et al. They make this claim because the print version of their paper was published on 

November 15, 2008 – some 11 months after its first online publication. The print version of the 

S08 paper was also published on November 15, 2008 (36 days after its online publication). 

The decision to publish the print versions of the Douglass et al. and Santer et al. IJoC

papers on the same date was an editorial decision. It was not my decision. In view of the 

serious statistical flaw in Douglass et al., I believe that the editor’s decision to publish the 

 

24This is “Climate Conspiracy Appendix A” in the Douglass and Christy “American Thinker” article.

25The “fear a response” quote is from Douglass and Christy, “A Climatology Conspiracy?”
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Douglass et al. and Santer et al. papers side-by-side (in the “hardcopy” version of the journal) 

was entirely appropriate.

The “strategy of delaying” allegation is baseless. In the scientific world, most journals 

now publish papers online before they appear in hardcopy form. The online publication is 

generally considered to be the publication of record, and attracts the majority of the scientific 

and media attention – as was the case with D07-online. The relevant point here is that the 

online version of the Douglass et al. IJoC paper was released 10 months prior to the appearance 

of S08-online. Any (imagined or imaginary) conspiracy to delay publication of Douglass et al. 

would therefore have to be judged remarkably unsuccessful. 

8. The ‘bias in review process’ allegation 

Douglass and Christy imply that the review process for the S08 IJoC paper was irregular, and 

that unusual favors were extended to Santer et al. by the editor of the International Journal of 

Climatology. This allegation is baseless. Let me briefly review the facts relevant to this 

allegation.

First, the time from submission to online publication of the S08 paper was just under 4 

months. For the Douglass et al. paper, the submission to online publication time was very 

similar (just over 4 months). The Santer et al. paper did not, therefore, receive an unusually

‘quick turn-around’ in the review process.

Second, the S08 paper was thoroughly and comprehensively examined by two 

reviewers. The review process consisted of two separate rounds. Our response to the first set 

of review comments was finalized on June 3, 2008. The response is 27 pages long. Our 7-page 

response to the second set of review comments was completed on July 16, 2008. These 

responses clearly document that the Santer et al. IJoC paper was rigorously reviewed. It was not 

given a free pass. The responses also document how thoroughly and professionally we 

addressed the comments of the two reviewers.

In my opinion, public release of the detailed responses to the review comments on the 

S08 paper would provide the strongest refutation of the “bias in review process” allegations 
12

made by Douglass and Christy. To date, however, I have not been able to obtain permission 

from the publishers of the International Journal of Climatology to publicly release these

responses. Should this permission be forthcoming in the future, I am very willing to provide 

(upon request) our responses to the anonymous reviews of the Santer et al. IJoC paper.

9. Response to allegations regarding neglect of weather balloon datasets

Douglass and Christy make the serious allegation that I intentionally withheld weather balloon 

data “that does not support his view.”

26 This allegation is false. The S08 paper analyzed 7 

different weather balloon datasets. It showed weather balloon results from both the Hadley 

Centre and IUK datasets – datasets Douglass and Christy accuse me of intentionally ignoring. 

Douglass and Christy also state that I “cut off” observational datasets in 1999. Again, the 

implication is that I am guilty of intentionally withholding inconvenient data. This allegation is 

false.

All of the comparisons between climate model and observational data in S08 are made 

over the 21-year period from 1979 to 1999. This is because most of the climate model 

experiments examined by both S08 and Douglass et al. end in 1999. The model experiments are 

attempts to simulate 20th century climate changes. In these simulations, many of the models 

incorporated estimates of historical changes in both human-caused climate “forcings” (like 

changes in atmospheric levels of greenhouse gases) and in natural “forcings” (like changes in 

the Sun’s energy output, or the amount of volcanic dust in the atmosphere). Such changes in 

human and natural forcings influence surface and atmospheric temperature. To facilitate 

meaningful comparisons between models and observations, it is important to compare the two 

over the same period of time – which is exactly what we did in S08.27

 

26In other words, “my view”.

27Note, however, that in the Supporting Material for the S08 paper (which was available online from IJoC), my 

colleagues and I did “extend” observational datasets beyond 1999, making the necessary assumption that the 

model temperature trends and trend uncertainties were the same over a longer period of time (such as 1979 to 

2006) as they were over the shorter period 1979 to 1999. This sensitivity test enabled us to look at the issue of 

whether tests of modeled and observed temperature trends were sensitive to the length of the observational 

record. Douglass and Christy fail to mention that we performed such tests.
13

10. Response to allegations regarding the 2008 Thorne Nature paper

In May 2008, Dr. Peter Thorne (one of the co-authors of the S08 IJoC paper), published a “News 

and Views” piece in the journal “Nature Geosciences”.28 A News and Views piece is not a 

scientific paper, although Douglass and Christy refer to it as a “paper”. As the “News and Views” 

title suggests, Dr. Thorne’s contribution was actually a commentary on a scientific paper 

published by Dr. R.J. Allen and Dr. S.C. Sherwood in the same issue of Nature Geosciences.

29

The 2008 Thorne contribution (referred to below as “T08”) briefly referenced the S08 

IJoC paper. T08 did not reference any papers by Professor Douglass. As described in “A

Climatology Conspiracy?”, Douglass wrote to me on May 27, 2008 (two days after publication of 

T08), requesting a copy of our IJoC paper, which at that point had not yet been accepted for

publication by IJoC.

30 I declined. I was hesitant to release a version of the paper that was still 

undergoing revision31 and had not yet been accepted for publication.32

11. Concluding remarks

I have addressed above the major allegations made by Professors Douglass and Christy in “A 

Climatology Conspiracy?” There was no “conspiracy”, and no attempt to interfere with the 

ability of Douglass and Christy to explain and defend why they applied a flawed statistical test 

 

28Thorne, P.W., 2008: The answer is blowing in the wind. Nature Geosciences, 1, 347-348. 

29Allen, R.J. and S.C. Sherwood, 2008: Warming maximum in the tropical upper troposphere deduced from thermal 

winds. Nature Geosciences, 1, 399-403.

30The S08 IJoC paper was not formally accepted for publication until July 20, 2008.

31As noted above in Section 9, our responses to the first set of review comments on S08 were not finalized until 

June 3, 2008. Our responses to the second set of review comments on S08 were not completed until July 16, 

2008.

32Douglass and Christy also imply that Professor Douglass voluntarily provided me with a pre-publication copy of 

D07-online, and that – as a kind of scientific quid pro quo – I should have voluntarily provided them with a prepublication copy of our S08 IJoC paper. In fact, Douglass never gave me a pre-publication copy of D07-online. I 

received a preprint of the D07-online paper from Andy Revkin of the New York Times – not from Professor 

Douglass. I received this preprint only five days before the paper’s online publication in the IJoC. Additionally, 

Douglass and Christy attempt to argue that I already had an advance copy of their D07-online paper, since I had 

been a reviewer of the D06 GRL paper. They maintain that that the version of the paper they finally published 

online in IJoC in December 2007 was “only slightly changed” relative to the D06 version. This claim is also 

incorrect. The two papers are noticeably different. Even the cast of authors is different. R. Knox (an author on 

D06) is not an author on D07-online. Professor Christy (who is not an author on D06) is an author on D07-

online.
14

in the 2007 Douglass et al. IJoC paper. Nor was there a “conspiracy” to subvert the normal peer 

review process for the 2008 Santer et al. IJoC paper which identified this statistical flaw. 

It is of concern that Douglass and Christy have (to date) failed to acknowledge the 

existence of any error in the “robust statistical test” they used to compared modeled and 

observed temperature trends, despite the fact that their test was clearly incorrect. Because of 

this concern, and in view of the extraordinary nature of the claims made on the basis of the 

2007 Douglass et al. IJoC paper (one of its coauthors asserted that the paper “clearly falsifies 

the hypothesis of anthropogenic greenhouse warming”),

33 I believe it would be timely and 

appropriate for the U.K. Royal Meteorological Society (on whose behalf the International 

Journal of Climatology is published) to investigate the scientific issues raised by the 2007 

Douglass et al. and 2008 Santer et al. IJoC papers. 

In summary, the emails stolen from the University of East Anglia’s Climatic Research 

Unit have been used by Douglass, Christy, and others to claim that there is a conspiracy to 

suppress scientific views critical of a “discernible human influence” on global climate. Yet the 

fact remains that the 2007 Douglass et al. IJoC paper was not suppressed. It was published, 

despite the authors’ use of an incorrect statistical test. The energy Douglass and Christy have 

now expended in searching for a non-existent conspiracy could have been more productively 

directed towards understanding and correcting errors in their IJoC paper. 

Benjamin D. Santer

John D. and Catherine T. MacArthur Fellow

San Ramon, California

February 2, 2010&

 

33S. F. Singer, op cit. 16.

&

These remarks reflect the personal opinions of Benjamin D. Santer. They do not represent the official views of 

Lawrence Livermore National Laboratory or the U.S. Department of Energy.
15

Timeline of key events related to the publication of the Douglass et al. 

and Santer et al. International Journal of Climatology papers

November 30, 2007 I receive a preprint of the Douglass et al. International Journal of 

Climatology paper from Andy Revkin, a New York Times reporter.

December 5, 2007 Douglass et al. International Journal of Climatology paper is published 

online. The paper claims that “models and observations disagree to a 

statistically significant extent”.

January 2008 S. Fred Singer holds a press conference at the U.S. National Press 

Club. A press release from this conference claims that the Douglass et 

al. paper proves that “Nature rules the climate: Human-produced 

greenhouse gases are not responsible for global warming”.

March 2008 Heartland Institute Report (“Nature, not human activity, rules the 

climate: Summary for Policymakers of the Report of the 

Nongovernmental International Panel on Climate Change”) is 

published. The Douglass et al. paper is featured prominently in this 

Report.

October 10, 2008 Santer et al. International Journal of Climatology paper is published 

online. It identifies a serious statistical error in the Douglass et al.

paper.

November 15, 2008 Douglass et al. and Santer et al. papers are published in the print 

version of the International Journal of Climatology.

November 2009 Over 1,000 personal emails are stolen from the Climatic Research 

Unit of the U.K.’s University of East Anglia. The stolen emails are 

publicly disseminated via the internet.

December 20, 2009 Based primarily on their analysis of these emails, David Douglass and 

John Christy publish “A Climatology Conspiracy?” in “American 

Thinker”, and falsely allege that I am guilty of serious professional 

misconduct. 
16

APPENDIX A#

Fact Sheet for “Consistency of Modelled and Observed Temperature 

Trends in the Tropical Troposphere”, by B.D. Santer et al.

34

Abstract

Using state-of-the-art observational datasets and results from a large archive of 

computer model simulations, a consortium of scientists from 12 different

institutions has resolved a long-standing conundrum in climate science – the

apparent discrepancy between simulated and observed temperature trends in the 

tropics. Research published by this group indicates that there is no fundamental 

discrepancy between modeled and observed tropical temperature trends when 

one accounts for: 1) the (currently large) uncertainties in observations; 2) the 

statistical uncertainties in estimating trends from observations. These results 

refute a recent claim that model and observed tropical temperature trends 

“disagree to a statistically significant extent”. This claim was based on the 

application of a flawed statistical test and the use of older observational datasets.

Ben Santer, Peter Thorne, Leo Haimberger, Karl Taylor, Tom Wigley, John Lanzante, Susan 

Solomon, Melissa Free, Peter Gleckler, Phil Jones, Tom Karl, Steve Klein, Carl Mears, Doug 

Nychka, Gavin Schmidt, Steve Sherwood, and Frank Wentz

October 6, 2008

 

#

Appendix A was written in October 2008. It was prepared to provide a simple, non-technical introduction 

to some of the scientific issues raised by the Douglass et al. and Santer et al. International Journal of 

Climatology papers.

34This paper will be published online in the International Journal of Climatology during the week of Oct. 6-

10, 2008.
17

QUESTION 1: What is the scientific context for the research published in the Santer et 

al. International Journal of Climatology paper?

Our paper compares modeled and observed atmospheric temperature changes in the 

tropical troposphere.

35 We were interested in this region because of an apparent 

inconsistency between computer model results and observations. Since the late 1960s, 

scientists have performed experiments in which computer models of the climate system 

are run with human-caused increases in atmospheric concentrations of greenhouse 

gases (GHGs).36 These experiments consistently showed that increases in atmospheric 

concentrations of GHGs should lead to pronounced warming, both at the Earth's surface 

and in the troposphere. The models also predicted that in the tropics, the warming of the 

troposphere should be larger than the warming of the surface.37

Observed estimates of surface temperature changes are in good agreement with 

computer model results, confirming the predicted surface warming.38 Until several years 

ago, however, most available estimates of tropospheric temperature changes obtained 

from satellites and weather balloons (radiosondes) implied that the tropical troposphere 

had actually cooled slightly over the last 20 to 30 years (in sharp contrast to the 

computer model predictions, which show tropospheric warming).

For nearly a decade, this apparent disconnect between models and reality has been 

used by some scientists and politicians to argue that:

 The surface thermometer record is wrong;

 The Earth has not experienced any surface or tropospheric warming since the 

beginning of satellite measurements of atmospheric temperature in 1979;

 Human-caused changes in greenhouse gases have no effect on climate;

 

35The troposphere is the lowest layer of the atmosphere, where most weather phenomena take place. In 

the tropics, the troposphere extends from the surface to a height of about 10 miles (16 km) above the 

Earth’s surface.

36Both climate models and the experiments performed with them have become more realistic over time. 

Since the mid 1990s, many climate model experiments have incorporated not only human-caused 

changes in GHGs, but also changes in other “forcing agents” that have effects on global or regional 

climate. Examples include human-caused changes in various aerosol particles (such as sulfate and soot 

aerosols), and natural changes in the Sun’s energy output and the amount of volcanic dust in the 

atmosphere. 

37This prediction of larger warming aloft than at the surface holds for all factors that tend to warm the 

surface of the Earth – it is not unique to human-caused changes in GHGs. 

38This agreement between models and observations was also found for complex geographical patterns of 

surface temperature changes – not simply for trends in temperature changes averaged over very large 

areas (such as the tropics).
18

 Computer models have no skill in simulating the observed temperature changes 

in the tropics, and therefore cannot be used to predict the climatic “shape of 

things to come” in response to further increases in greenhouse gases.

Our paper attempts to determine whether there is indeed a real and statistically 

significant discrepancy between modeled and observed temperature changes in the 

tropics, as was claimed in a paper published online in December 2007 in the 

International Journal of Climatology. As discussed in QUESTION 9, we find that this 

claim is incorrect.

QUESTION 2: What arguments were made to support this claim?

David Douglass, John Christy, Benjamin Pearson, and S. Fred Singeridevised a 

statistical test to determine whether modeled and observed atmospheric temperature 

trends in the tropical troposphere were significantly different. They applied this test in 

several different ways. First, they considered temperature trends in two different layers

of the troposphere (the lower troposphere and the mid- to upper troposphere). In each 

of these layers, their test suggested that the modeled warming trends were larger than 

and significantly different from the warming trends estimated from satellite data. 

Second, they compared trends in the temperature differences between the surface and 

the lower troposphere – a measure of the “differential warming” of the surface and lower 

atmosphere. Once again, their test pointed towards the existence of statistically 

significant differences in modeled and observed trends.

The bottom-line conclusion of Douglass et al. was that “models and observations 

disagree to a statistically significant extent”. As discussed in QUESTIONS 6-8, we show 

that this statistical test is flawed, and that the conclusions reached by Douglass et al. 

are incorrect.

QUESTION 3: But hadn’t the scientific community already resolved this issue?

The community had already achieved a partial resolution of this issue in a 2006 Report 

issued by the U.S. Climate Change Science Program (CCSP)ii. The CCSP Report

concluded that, when one examined temperature changes at the global scale, newer 

satellite and weather balloon datasets showed “no significant discrepancy” between 

surface and tropospheric warming trends, and were therefore consistent with computer 

model results. But the same CCSP Report noted that it was not possible (in 2006) to 

reconcile modeled and observed temperature changes in the tropics, where “most 
19

observational datasets show more warming at the surface than in the troposphere, while 

most model runs have larger warming aloft than at the surface”.

The CCSP Report relied almost exclusively on published literature. At the time of its 

publication in 2006, there were no peer-reviewed studies on the formal statistical 

significance of differences between modeled and observed tropical temperature trends. 

The Douglass et al. paper attempted to assess the statistical significance of the modelversus-observed tropical trend differences noted in the CCSP Report.

QUESTION 4: What was the thrust of your new research?

Our primary goal was to determine whether the findings of Douglass et al. were sound. 

As noted above, Douglass et al. reported that “models and observations disagree to a 

statistically significant extent”. They interpreted their results as evidence that computer 

models are seriously flawed, and that the projections of future climate change made 

with such models are untrustworthy. If Douglass et al. were right, this would imply that 

there was some fundamental flaw – not only in all state-of-the-art climate models, but 

also in our basic theoretical understanding of how the climate system should respond to 

increases in GHGs. We wanted to know whether such a fundamental flaw really existed.

QUESTION 5: What specific issues did you focus on?

We focused on two issues. First, Douglass et al. claimed that they had applied a “robust 

statistical test” to identify statistically significant differences between modeled and 

observed temperature trends. We sought to understand whether their test was indeed 

“robust” and appropriate. Second, Douglass et al. claimed to be using the “best 

available updated observations” for their study. We did not believe that this claim was 

accurate. 

We decided to check their analysis by applying a variety of different statistical tests to 

modeled and observed temperature trends, and by employing temperature data from 

more recent observational datasets – datasets that were either unavailable to Douglass 

et al. at the time of their study, or which were available, but had not been used by them.

QUESTION 6: What did you learn about the appropriateness of the Douglass et al. test?

We found that there was a serious flaw in the “robust statistical test” that Douglass et al. 

had used to compare models and observations. Their test ignored the effects of natural 

climate “noise” on observed temperature trends, and the resulting statistical uncertainty 
20

in estimating the “signal component” of these trends (see QUESTION 7 for a definition 

of the “signal component”). 

QUESTION 7: Why was this a problem?

We know that in the real world, changes in temperatures are due to a combination of 

human effects and natural factors. The “natural factors” can be things like volcanic 

eruptions or changes in the Sun’s energy output. Another type of “natural factor” is 

referred to as “internal variability”, which is unrelated to changes in the Sun or volcanic 

dust, and involves phenomena like El Niños, La Niñas, and other natural climate 

oscillations. In the tropics in particular, El Niños and La Niñas have a substantial effect 

on surface and atmospheric temperature. They introduce climate “noise”, which 

complicates the separation of human and natural effects on temperature.

Douglass et al. effectively assumed that the observed surface and tropospheric 

temperature trends were perfectly-known, and that these trends were purely due to 

human-caused changes in greenhouse gases39. The inappropriateness of this 

assumption is immediately obvious by looking at any observed temperature time series, 

such as the surface and tropospheric temperature time series shown below.

 

39In their paper, Douglass et al. claim to be testing “the proposition that greenhouse model simulations

and observations can be reconciled”. The model simulations of 20th century climate change that they used 

to test this proposition, however, include a variety of different human and natural forcing factors, such as 

changes in sulfate and soot aerosols, volcanic dust, the Sun’s energy output, and land surface properties. 

These so-called “20CEN” experiments are not just driven by human-caused increases in GHGs. Douglass 

et al.’s proposition that they are only testing the response of climate models to GHG increases is simply 

incorrect.
21

Figure Caption: Estimates of observed temperature changes in the tropics (30°N-30°S). Changes are 

expressed as departures from average conditions over 1979 to 2006. The top panel shows results for the 

surface40 and lower troposphere.

41 The thin red and black lines in the top panel are 12-month running 

averages of the temperature changes for individual months. The thick straight lines are trends that have 

been fitted to the time series of surface and tropospheric temperature changes. The warming trend is 

larger in the tropospheric temperature data than in the surface temperature record, in accord with 

computer model results. The bottom panel shows a commonly-used index of El Niño and La Niña activity, 

consisting of sea-surface temperature changes averaged over the so-called Niño 3.4 region of the tropical 

Pacific. The bottom panel shows that much of the year-to-year variability in surface and lower 

tropospheric temperatures is related to changes in El Niños and La Niñas. 

This Figure illustrates that both tropical surface and tropospheric temperatures have 

gradually warmed since 1979. Superimposed on this overall warming is climate “noise”, 

which in this case arises primarily from El Niños and La Niñas. When temperatures are 

averaged over the tropics (and indeed, over the globe), El Niños tend to warm the 

surface and lower atmosphere, and La Niñas tend to cool these regions.

42 As is visually 

 

40Surface data are from version 3 of the Extended Reconstructed Sea Surface Temperature Dataset 

(ERSST) produced by the National Oceanic and Atmospheric Administration (NOAA).

41Lower tropospheric temperatures are from version 3.0 of the TLT retrieval produced by Remote Sensing 

Systems in Santa Rosa, California.

42For example, 1998 was unusually warm because of the effects of a very large El Niño.
22

obvious, El Niños and La Niñas introduce considerable year-to-year variability in surface 

and tropospheric temperature. 

Because of the climate noise introduced by El Niños and La Niñas, there is uncertainty 

in estimating any underlying temperature trend, such as that arising from slow, humancaused increases in GHGs. In the real world and in many model simulations of 20th

century climate change, this underlying trend in temperature is not caused by GHG 

increases alone – it results from the combined changes in GHGs and other external 

forcing factors, and is partly masked by climate noise. 

The underlying “signal trend” is what we really want to compare in climate models and 

observations. Any meaningful statistical test of the differences between modeled and 

observed temperature trends must therefore account for the statistical uncertainty in 

estimating this “signal trend” from noisy observational data. The Douglass et al. test did 

not account for this uncertainty.

QUESTION 8: What were the consequences of the flaw in the Douglass et al. test?

The primary consequence was that Douglass et al. reached incorrect conclusions about 

the true statistical significance of differences between modeled and observed 

temperature trends in the tropics. When we applied modified versions of their test –

versions that properly accounted for uncertainties in estimating the “signal component” 

of observed temperature trends – we obtained results that were strikingly different from 

theirs. Like Douglass et al., we applied our tests to modeled and observed temperature 

trends:

 In individual layers of the troposphere;

 In the trend difference between surface and tropospheric warming rates. 

Unlike Douglass et al., however, we found that most of our tests involving temperature 

trends in individual layers of the troposphere did not show statistically significant 

differences between models and observations. This result was relatively insensitive to 

which model or satellite dataset we chose for the trend comparison.

The situation was a little more complex for tests involving the trend difference between 

surface and tropospheric warming rates. In this case, the statistical significance of the 

differences between models and observations was sensitive to our choice of 

observational datasets. When we used a satellite-based tropospheric temperature 
23

dataset developed at Remote Sensing Systems (RSS) in Santa Rosa, California, we 

found that the warming in the tropical troposphere was always larger than the warming 

at the surface.43 This behavior is consistent with the behavior of the climate models and 

with our understanding of the physical processes that govern tropospheric temperature 

profiles. It is contrary to the findings of Douglass et al.

However, when we used a satellite-based tropospheric temperature dataset developed 

at the University of Alabama at Huntsville (UAH)44, the tropospheric warming was less

than the surface warming. But even when we employed UAH data, our statistical test 

showed that the observed difference between surface and tropospheric warming trends 

was not always significantly different from the trend difference in model simulations. 

Whether or not trend differences were statistically significant was dependent on the 

choice of model and the choice of observed surface dataset used in the test.

45

QUESTION 9: So what is the bottom line of your study?

The bottom line is that we obtained results strikingly different from those of Douglass et 

al. The “robust statistical test” that they used to compare models and observations had 

at least one serious flaw – its failure to account for any uncertainty in the “signal 

component” of observed temperature trends (see QUESTION 7). This flaw led them to 

reach incorrect conclusions. We showed this by applying their test to randomly 

generated data with the same statistical properties as the observed temperature data, 

but without any underlying “signal trend”. In this “synthetic data” case, we knew that 

significant differences in temperature trends could occur by chance only, and thus 

would happen infrequently. When we applied the Douglass et al. test, however, we 

found that even randomly generated data showed statistically significant trend 

differences much more frequently than we would expect on the basis of chance alone. A 

test that fails to behave properly when used with random data – when one knows in 

advance what results to expect – cannot be expected to perform reliably when applied 

to real observational and model data. 

Q10: Final question: Have you reconciled modeled and observed temperature trends in 

the tropics? 

 

43Irrespective of which one of four different observational datasets was used to characterize changes in 

tropical surface temperatures. 

44Developed by John Christy (one of the co-authors of the Douglass et al. paper), Roy Spencer, and 

colleagues.

45See Table V in our paper. 
24

We’ve gone a long way towards such a reconciliation. There are at least two reasons for 

this.46 The first reason is that we have now applied appropriate statistical tests for 

comparing modeled and observed temperature trends in the tropics. Unlike the 

Douglass et al. test, our test properly accounts for uncertainty in estimating the “signal 

component” of observed temperature trends. Results from these more appropriate tests 

do not support the claim that there are fundamental, pervasive, and statistically 

significant differences between modeled and observed tropical temperature trends. This 

claim is not tenable for temperature trends in individual layers of the troposphere. Nor is 

it tenable for the differences in the warming rates of the surface and troposphere. 

Second, we now have many more estimates of recent temperature changes. These 

have been produced by a number of different research groups, often using completely 

independent methods. 

Research groups involved in the development of newer sea surface temperature 

datasets have reported improvements in the treatment of information from buoys and 

satellites. This has led to slightly reduced estimates of the warming of the tropical ocean 

surface (relative to the warming in the earlier surface temperature datasets used by 

Douglass et al. and in the CCSP Report). Additionally, newly-developed satellite and 

radiosonde datasets now show larger warming of the tropical troposphere than was 

apparent in the datasets used by Douglass et al. The enhanced tropospheric warming is

due to improvements in our ability to identify and adjust for biases introduced by 

changes over time in the instruments used to measure temperature.47

Access to such a rich variety of independently produced datasets has provided us with 

a valuable perspective on the inherent uncertainty in observed estimates of recent 

climate change. Based on our current best estimates of these observational 

uncertainties, there is no fundamental discrepancy between modeled and observed 

tropical temperature trends. In fact, many of the recently-developed observational 

datasets now show tropical temperature changes that are larger aloft than at the surface 

– behavior that is entirely consistent with climate model results.

 

46A third reason is that several studies published within the last 12 months provide independent evidence 

for substantial warming of the tropical troposphere. These studies have documented pronounced 

increases in surface specific humidity and atmospheric water vapor that are in accord with tropospheric 

warming.

47Several of the newer radiosonde and satellite datasets that exhibit pronounced tropospheric warming 

are based on novel approaches to the construction of homogeneous datasets. These approaches often 

involve bringing in data from new sources (such as hitherto unused satellite data, or data on the physical 

relationship between temperature and wind) in order to better constrain uncertainties in estimated 

tropospheric temperature changes.
25

One of the lessons from this work is that even with improved datasets, there are still 

important uncertainties in observational estimates of recent tropospheric temperature 

trends. These uncertainties may never be fully resolved, and are partly a consequence 

of historical observing strategies, which were geared towards weather forecasting rather 

than climate monitoring. We should apply what we learned in this study toward 

improving existing climate monitoring systems, so that future model evaluation studies 

are less sensitive to observational ambiguity.

 

i Douglass DH, Christy JR, Pearson BD, Singer SF. 2007. A comparison of tropical temperature 

trends with model predictions. International Journal of Climatology 27: 

doi:10.1002/joc.1651.

ii Karl TR, Hassol SJ, Miller CD, Murray WL (eds). 2006. Temperature Trends in the Lower 

Atmosphere: Steps for Understanding and Reconciling Differences. A Report by the U.S. 

Climate Change Science Program and the Subcommittee on Global Change Research. 

National Oceanic and Atmospheric Administration, National Climatic Data Center, 

Asheville, NC, 164 pp.