Global Warming – Temperature Data

This research topic has occupied a lot of my attention since 2002. I have numerous papers in the area already and I am still working on some new ones. There are also related papers filed under Global Warming/Model Testing. 

BERKELEY EARTH STUDY REFEREE REPORTS: On September 8 2011 I was asked by Journal of Geophysical Research to be a reviewer for a paper by Charlotte Wickham et al. presenting the 
Berkeley Earth Surface Temperature ("BEST") analysis of the effect of urbanization on land surface temperatures. This work is mainly associated with Richard Muller and his various coauthors.  I submitted my review just before the end of September 2011, outlining what I saw were serious shortcomings in their methods and arguing that their analysis does not establish valid grounds for the conclusions they assert. I suggested the authors be asked to undertake a major revision. 
   In October 2011, despite the papers not being accepted, Richard Muller launched a major international publicity blitz announcing the results of the "BEST" project. I wrote to him and his coauthor Judy Curry objecting to the promotional initiative since the critical comments of people like me were locked up under confidentiality rules, and the papers had not been accepted for publication. Richard stated that he felt there was no alternative since the studies would be picked up by the press anyway. Later, when the journal turned the paper down and asked for major revisions, I sought permission from Richard to release my review. He requested that I post it without indicating I was a reviewer for JGR. Since that was not feasible I simply kept it confidential. 
   On March 8 2012 I was asked by JGR to review a revised version of the Wickham et al. paper. I submitted my review at the end of March. The authors had made very few changes and had not addressed any of the methodological problems, so I recommended the paper not be published. I do not know what the journal's decision was, but it is 4 months later and I can find no evidence on the BEST website that this or any other BEST project paper has been accepted for publication. [Update July 30: JGR told me "This paper was rejected and the editor recommended that the author resubmit it as a new paper."] 
   On July 29 2012 Richard Muller launched another publicity blitz (e.g. here and here) claiming, among other things, that "In our papers we demonstrate that none of these potentially troublesome effects [including those related to urbanization and land surface changes] unduly biased our conclusions." Their failure to provide a proper demonstration of this point had led me to recommend against publishing their paper. This places me in an awkward position since I made an undertaking to JGR to respect the confidentiality of the peer review process, but I have reason to believe Muller et al.'s analysis does not support the conclusions he is now asserting in the press. 
   I take the journal peer review process seriously and I dislike being placed in the position of having to break a commitment I made to JGR, but the "BEST" team's decision to launch another publicity blitz effectively nullifies any right they might have had to confidentiality in this matter. So I am herewith releasing my referee reports. The first, from September 2011, is here and the second, from March 2012 is here. 


PAPER CONFIRMING CONTAMINATION OF SURFACE TEMPERATURE DATA: In 2007 I published a paper with Pat Michaels showing evidence that CRU global surface temperature data used by the IPCC are likely contaminated due to socioeconomic development and variations in data quality. In 2009 Gavin Schmidt published a paper in the International Journal of Climatology claiming our results, as well as those of de Laat and Maurellis who independently found the same things we did, were spurious. My rebuttal, coauthored with Nicolas Nierenberg, has been accepted at The Journal of Economic and Social Measurement. 

Data/Code archive here. The paper provides a complete and thorough refutation of Schmidt's critique. Why JESM? First, because it is a journal that focuses on the critical evaluation of policy-relevant databases, and its editors and reviewers have considerable econometric depth, and this paper is fundamentally an application of econometrics to the evaluation of data quality. Second, we submitted the paper to the IJOC in April 2009, on the assumption that, having published Schmidt's paper, they were interested in the topic. Evidently their interest only extends to analyses that support IPCC views. After 10 months we found out that IJOC was rejecting our paper on the basis of some inane referee reports to which Nico and I were not given a chance to reply. We did anyway, and if anyone thinks the rejection by IJOC amounts to a knock against our paper, please read our response letter for some perspective. Whether or not the IJOC editors read it, they refused to reconsider our paper. Interestingly, we learned from the Climategate release that Schmidt's paper, which focuses on defending Phil Jones' CRU data against its various critics, was sent by the IJOC Editors to be reviewed by Phil Jones of the CRU. As you can imagine his review was shallow and uncritical, but evidently impressed the editors of IJOC. They didn't ask deLaat or me to supply a review, nor did they invite us to contribute a response. Every interaction I have had over the years with the IJOC has left me very unimpressed. 




SURFACE TEMPERATURES REVIEW: 3 lines of inquiry merged on this topic. I have been assembling material on the construction of surface temperature data for my own research. And a law firm involved in cases concerning the EPA endangerment finding asked me to write up some explanatory information for them. And I was asked by a think-tank in Germany to write a report on climate change. I put a paper together compiling notes and info, and posted it for comments and corrections, of which I received many. The report can be accessed as an SSRN Working Paper



ATMOSPHERIC CIRCULATIONS: In 2008 wrote a working paper about claims in the IPCC 4th Assessment Report that the strong correlation between spatial warming patterns and the spatial pattern of industrialization is a fluke due to atmospheric circulations. The IPCC made this claim without supporting evidence, and used it to sweep aside evidence that their fundamental temperature data are contaminated with a strong warm bias. My paper shows their claim is false. After a long strange trip, and several revisions, my paper has been accepted for publication at a new applied statistics journal.
The zipped data and code archive is here.

MM2004&07 PAPERS: Temperature data around the world is collected for meteorological purposes. Climate data is something different, and has to be produced by a model, using temperature data as an input. The model is intended to “fix” known sources of contamination due to land use changes, inconsistent quality control etc. Yet the validity of the models used to produce climate data has been subject to little formal testing, and what testing has been done points to serious problems. My 2004 work with Pat Michaels showed that the “corrections” being commonly applied do not correct the contamination, and leave a strong warming bias in the global land record. 
Since I publish my data and code along with the papers, these results were heavily scrutinized. A blogger found a small numerical error: I omitted to convert the latitude measure to radians (from degrees) prior to computing the cosine. This had only a trivial effect, but many climate scientists dismissed or ignored all the results largely on the basis of rumours that the results had been undermined. We published an Erratum right away, putting the before and after results side-by-side so people could see how small the changes were. The Erratum is posted at:

There was also a strange comment on our work submitted to Climate Research. It was not peer-reviewed, instead the Editor just told us to write a response and, after editing, he published it with the comment. The author found that if he discarded half the data he got weaker results. Well surprise surprise. Here’s our response.

After that paper was published we extended the study to a global sample, and I built a new socioeconomic data base, adding new covariates and going to a complete coverage of the available land surface. The new results fully confirm the old ones: the global land-based surface data set is heavily contaminated by extraneous ‘signals’ arising from land-surface modifications and variations in quality control. In a new paper we estimate the overall impact on measured warming over land and discuss the implications for understanding climate data. It’s high time for a much deeper re-examination of basic climate data sets.

CRU DATA: I have been contacted by several people, including a reporter, asking for supporting information regarding my July 2009 request for the raw data used in the CRU gridded temperature products. This has arisen in part because of Pat Michael's NRO article The Dog Ate Global Warming. The documentation of my request is here. 

A while ago I saw a fascinating essay by Joe D'Aleo on the sudden loss of measurement sites around 1990. I graphed it up and the graph has since been used by a number of other authors, including Marlo Lewis in his book 'A Skeptics Guide to Global Warming'. A detailed explanation of that graph and its origins is here:
 
In Taken By Storm Chris Essex and I explained in informal terms why there’s no such thing as a “global temperature.” We spelled out the theoretical argument in this paper:
The implications are very important. The notion of a planet “warming” or “cooling” is ill-posed, at least in the context of the global warming discussion. Talking about a trend in a temperature average over a non-equilibrium system as if it is denotes “warming” (i.e. an increase in a number known to be a temperature) is scientific hand-waving and short cut-taking that conceals nontrivial physical problems. Every field (including economics) has to take short-cuts, but eventually when the discrepancies are piling up all around, someone has to go back and see where the wrong turn was. I figure people in the climate field will come looking for this paper in about 10 years.

AMPLIFICATION RATIOS: I was drawn into the dispute between Gavin Schmidt and Klotzbach et al. (see Pielke Sr.) over the latter paper's conclusion that the surface temperature record over land has a warm bias for the purpose of measuring global warming. I was cited in Klotzbach et al. as the source of a claim that the GISS model exhibits amplification over land of about 1.2. I should not have been cited, since all I did was report in an email to John Christy the average trop/surf trend in Gavin Schmidt's own GISS data pertaining to my 2007 surface temperature analysis. The information source, in other words, was Schmidt himself, not me; and in any case I did not provide it as a personal communication for the purpose of a journal article (which I did not know was being written). Phil Klotzbach and his coauthors have issued a correction on this point. In subsequent correspondence with Gavin Schmidt he reported to me that he had corrected an error his original IJOC archive and also that the GISS model classifies land differently than CRU so some of the 440 grid cells are actually over ocean in his model. He supplied me with the GISS landmask. I have recomputed the original results using the corrected data and the GISS landmask. The cosine-weighted amplification ratio over land is about 1.106 and over ocean is 1.602, where 'land' and 'ocean' are according to the GISS landmask applied to the 440 grid cells used in my 2007 paper. 

This next article was invited by the late Kirill Kondratiev. I apply some basic econometrics to temperature data to show that inference about trends (i.e. deciding whether a trend is significant or not) requires some careful testing and estimation. This topic was also waved away by the IPCC (at issue was the work of some others who examined long term persistence in temperature records). It’s a worthwhile expository paper for people who want to see how to apply some time series methods to temperature data.
  • *McKitrick, Ross R. (2002). "Inference About Trends in Temperature Data After Controlling for Serial Correlation and Heteroskedastic Variance." Invited Paper, Proceedings of the Russian Geographical Society 164(3) pp. 16-24. (English version)