Ice cores are the accumulation of snow and ice over many years that have recrystallized and have trapped air bubbles from previous time periods. The composition of these ice cores, especially the presence of hydrogen and oxygen isotopes, provides a picture of the climate at the time. Because isotopes of water vapor exhibit a lower vapor pressure, when the temperature falls, the heavier water molecules will condense faster than the normal water molecules. The relative concentrations of the heavier isotopes in the condensate indicate the temperature of condensation at the time, allowing for ice cores to be used in global temperature reconstruction. In addition to the isotope concentration, the air bubbles trapped in the ice cores allow for measurement of the atmospheric concentrations of trace gases, including greenhouse gases carbon dioxide, methane, and nitrous oxide. The air bubbles may also contain traces of aerosols, which are produced in great concentrations during volcanic eruptions.

Coral is similar to trees in that the growth and density of the coral is dependent upon temperature. X-rays of coral cross sections show the relative density and growth over time. High density layers of coral are produced during years of high ocean surface temperatures. Hence, corals can be calibrated to estimate sea surface temperatures.

Principal Component Analysis and the CFR and CPS Methodology

Principal component analysis is a method often used for reducing multidimensional datasets to lower dimensions for analysis. In this context, dimensions refer to the number of distinct variables. The time series proxy data involved are transformed into their principal components, where the first principal component is intended to explain most of the variation present in the variables. Each subsequent principal component explains less and less of the variation. In the methodology of MBH98/99, the first principal component is used in the temperature reconstruction, and also has the highest explained variance. This method is intended for dimension reduction. In most datasets, the first principal component should be the least smooth (because of the higher variance). However, in MBH98, MBH99, the proxy data are incorrectly centered, which inflates the variance of certain proxies and selectively chooses those decentered proxies as the temperature reconstruction.

There are several time series models that exist for the purpose of modeling series with dependence, including autoregressive, moving averages, autoregressive moving average models, and long memory processes. MBH98 and MBH99 focus on simple signal plus superimposed noise models for paleoclimate temperature reconstruction. Because of complex feedback mechanisms involved in climate dynamics, it is unlikely that the temperature records and the data derived from the proxies can be adequately modeled with a simple temperature signal with superimposed noise. We believe that there has not been a serious investigation to model the underlying process structures nor to model the present instrumented temperature record with sophisticated process models.

Two principal methods for temperature reconstructions have been used; CFR* (climate field construction) and CPS (climate-plus-scale). The CFR is essentially a principal component analysis and the CPS is a simple averaging of climate proxies, which are then scaled to actual temperature records. The controversy of Mann's methods lies in that the proxies are centered on the mean of the period 1902-1995, rather than on the whole time period. This mean is, thus, actually decentered low, which will cause it to exhibit a larger variance, giving it preference for being selected as the first principal component. The net effect of this decentering using the proxy data in MBH98 and MBH99 is to produce a "hockey stick" shape. Centering the mean is a critical factor in using the principal component methodology properly. It is not clear that Mann and associates realized the error in their methodology at the time of publication. Because of the lack of full documentation of their data and computer code, we have not been able to reproduce their research. We did, however, successfully recapture similar results to those of MM. This recreation supports the critique of the MBH98 methods, as the offset of the mean value creates an artificially large deviation from the desired mean value of zero.

Findings

In general, we found MBH98 and MBH99 to be somewhat obscure and incomplete and the criticisms of MM03/05a/05b to be valid and compelling. We also comment that they were attempting to draw attention to the discrepancies in MBH98 and MBH99, and not to do paleoclimatic temperature reconstruction. Normally, one would try to select a calibration dataset that is representative of the entire dataset. The 1902-1995 data is not fully appropriate for calibration and leads to a misuse in principal component analysis. However, the reasons for setting 1902-1995 as the calibration point presented in the narrative of MBH98 sounds reasonable, and the error may be easily overlooked by someone not trained in statistical methodology. We note that there is no evidence that Dr. Mann or any of the other authors in paleoclimatology studies have had significant interactions with mainstream statisticians.

In our further exploration of the social network of authorships in temperature reconstruction, we found that at least 43 authors have direct ties to Dr. Mann by virtue of coauthored papers with him. Our findings from this analysis suggest that authors in the area of paleoclimate studies are closely connected and thus 'independent studies' may not be as independent as they might appear on the surface. This committee does not believe that web logs are an appropriate forum for the scientific debate on this issue.

It is important to note the isolation of the paleoclimate community; even though they rely heavily on statistical methods they do not seem to be interacting with the statistical community. Additionally, we judge that the sharing of research materials, data and results was haphazardly and grudgingly done. In this case we judge that there was too much reliance on peer review, which was not necessarily independent. Moreover, the work has been sufficiently politicized that this community can hardly reassess their public positions without losing credibility. Overall, our committee believes that Mann's

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The CFR methodology is essentially the methodology used in the MBH98/99 papers, but the terminology was not used until later.

assessments that the decade of the 1990s was the hottest decade of the millennium and that 1998 was the hottest year of the millennium cannot be supported by his analysis.

Recommendations

Recommendation 1. Especially when massive amounts of public monies and human lives are at stake, academic work should have a more intense level of scrutiny and review. It is especially the case that authors of policy-related documents like the IPCC report, Climate Change 2001: The Scientific Basis, should not be the same people as those that constructed the academic papers.

Recommendation 2. We believe that federally funded research agencies should develop a more comprehensive and concise policy on disclosure. All of us writing this report have been federally funded. Our experience with funding agencies has been that they do not in general articulate clear guidelines to the investigators as to what must be disclosed. Federally funded work including code should be made available to other researchers upon reasonable request, especially if the intellectual property has no commercial value. Some consideration should be granted to data collectors to have exclusive use of their data for one or two years, prior to publication. But data collected under federal support should be made publicly available. (As federal agencies such as NASA do routinely.)

Recommendation 3. With clinical trials for drugs and devices to be approved for human use by the FDA, review and consultation with statisticians is expected. Indeed, it is standard practice to include statisticians in the application-for-approval process. We judge this to be a good policy when public health and also when substantial amounts of monies are involved, for example, when there are major policy decisions to be made based on statistical assessments. In such cases, evaluation by statisticians should be standard practice. This evaluation phase should be a mandatory part of all grant applications and funded accordingly.

Recommendation 4. Emphasis should be placed on the Federal funding of research related to fundamental understanding of the mechanisms of climate change. Funding should focus on interdisciplinary teams and avoid narrowly focused discipline research.

1. INTRODUCTION

Global warming is an issue that has gathered much public, legislative, national and international attention. Uncertainty about magnitude and consequences of global warming has caused considerable friction among governments and among their citizens. The Intergovernmental Panel on Climate Change (IPCC) report (Intergovernmental Panel on Climate Change, 2001) entitled, Climate Change 2001: Third Assessment Report, featured alarming statistics concerning the rapid rise in global temperatures during the decade of the 1990s and suggested that this rapid rise was due principally to anthropogenicly generated greenhouse gas emissions, specifically carbon dioxide. This document was taken to be a strong justification for the Kyoto Accord. Featured prominently in the IPCC report was the work of Dr. Michael Mann, Dr. Raymond Bradley, and Dr. Malcolm Hughes (Mann et al., 1998, 1999) [MBH98, MBH99]. These papers featured temperature reconstructions going back as far as 1000 years. The methodology found in Mann et al. employed a statistical technique known as principal components analysis (PCA). Challenges to the way in which PCA was used have arisen from McIntyre and McKitrick (2003, 2005a, 2005b) [MM03, MM05a, MM05b]. The challenges are based on rather subtle mathematical nuances. The discussion and evaluation of the use of PCA to some extent has degenerated in to the battle of competing web blogs: http://www.climateaudit.org, http://www.climate2003.org, http://www.realclimate.org.

and

The Chairman of the House Committee on Energy and Commerce along with Chairman of the Subcommittee of Oversight and Investigations have been interested in discovering whether or not the criticisms of Mann et al. are valid and if so, what are the implications. To this end, Committee staff asked for advice as to the validity of the complaints of McIntyre and McKitrick [MM] and related implications. Dr. Wegman formed an ad hoc Committee (Drs. Edward J. Wegman – George Mason University, David W. Scott - Rice University, and Yasmin H. Said The Johns Hopkins University). The Committee was organized with our own initiative as a pro bono committee.

We have attempted to address several broad issues. We have sought to reproduce the results of MM in order to determine whether their criticisms are valid and have merit. We will also comment on whether issues raised by those criticisms discussed in McIntyre and McKitrick (2005a, 2005b) raise broader questions concerning the assessment of Mann et al. (1998, 1999) in peer review and the IPCC and whether such science assessments involving work of a statistical nature require some type of strengthening to provide reliable guidance for policy makers.

Prior to the work of our committee and independently of our committee, Chairman Barton and Chairman Whitfield wrote letters to Drs. Michael Mann, Raymond Bradley, and Malcolm Hughes as well as to the Intergovernmental Panel on Climate Change and the National Science Foundation. All three of the authors responded, but as lead author Dr. Mann's responses were most extensive. Dr. Mann's responses had something of a confrontational tone. No member of our Committee participated in the design or structure of the questions to Dr. Mann. However, based on his responses and the extensive