To: Rick Piltz <firstname.lastname@example.org>
Subject: Re: FYI--"Phil Jones and Ben Santer respond to CEI and Pat Michaels attack on temperature data record"
Date: Tue, 13 Oct 2009 19:45:45 -0600
Cc: Thomas.R.Karl@noaa.gov, Jim Hansen <email@example.com>, Steve Schneider <firstname.lastname@example.org>, Gavin Schmidt <email@example.com>, Kevin Trenberth <firstname.lastname@example.org>, Michael Mann <email@example.com>, Stefan Rahmstorf <firstname.lastname@example.org>, Phil Jones <P.Jones@uea.ac.uk>, Ben Santer <email@example.com>
You may be interesting in this snippet of information about
Pat Michaels. Perhaps the University of Wisconsin ought to
open up a public comment period to decide whether Pat Michaels,
PhD needs re-assessing?
Michaels' PhD was, I believe, supervised by Reid Bryson. It dealt
with statistical (regression-based) modeling of crop-climate
relationships. In his thesis, Michaels claims that his statistical
model showed that weather/climate variations could explain 95%
of the inter-annual variability in crop yields. Had this been
correct, it would have been a remarkable results. Certainly, it
was at odds with all previous studies of crop-climate relationships,
which generally showed that weather/climate could only explain about
50% of inter-annual yield variability.
How did result come about? The answer is simple. In Michaels'
regressions he included a trend term. This was at the time a common
way to account for the effects of changing technology on yield. It
turns out that the trend term accounts for 90% of the variability,
so that, in Michaels' regressions, weather/climate explains just 5
of the remaining 10%. In other words, Michaels' claim that
weather/climate explains 95% of the variability is completely
Apparently, none of Michaels' thesis examiners noticed this. We
are left with wondering whether this was deliberate misrepresentation
by Michaels, or whether it was simply ignorance.
As an historical note, I discovered this many years ago when working
with Dick Warrick and Tu Qipu on crop-climate modeling. We used a
spatial regression method, which we developed for the wheat belt of
southwestern Western Australia. We carried out similar analyses for
winter wheat in the USA, but never published the results.
Wigley, T.M.L. and Tu Qipu, 1983: Crop-climate modelling using spatial
patterns of yield and climate: Part 1, Background and an example from
Australia. Journal of Climate and Applied Meteorology 22, 1831�1841.
There never was a "Part 2".
Rick Piltz wrote:
> Just posted on Climate Science Watch Website.
> *Phil Jones and Ben Santer respond to CEI and Pat Michaels attack on
> temperature data record*
> /Posted on Tuesday, October 13, 2009
> /Prof. Phil Jones, Director of the Climatic Research Unit at the
> University of East Anglia in the UK and Ben Santer at Lawrence Livermore
> National Laboratory comment in response to a petition to EPA by the
> Competitive Enterprise Institute and Pat Michaels, which misleadingly
> seeks to obstruct EPA�s process in making an �endangerment� finding on
> greenhouse gases. This new CEI tactic is to call into question the
> integrity of the global temperature data record and, by implication, the
> integrity of leading climate scientists.
> /E&E News PM/ reported on October 7 (�CLIMATE: Free-market group attacks
> data behind EPA �endangerment� proposal�):
> The Competitive Enterprise Institute�a vocal foe of EPA�s efforts to
> finalize its �endangerment finding��petitioned the agency this week
> to reopen the public comment period on the proposal, arguing that
> critical data used to formulate the plan have been destroyed and
> that the available data are therefore unreliable.
> At issue is a set of raw data from the Climatic Research Unit at the
> University of East Anglia in Norwich, England, that includes surface
> temperature averages from weather stations around the world�.
> Republican senators also weighed in yesterday, urging EPA to reopen
> the public comment period on the endangerment finding to investigate
> the scientific merit of the research data�.
> We talked with E&E News on this latest maneuver by the ideologues at CEI
> and contrarian scientist Pat Michaels and posted on October 8
> �CEI global warming denialists try another gambit seeking to derail EPA
> �endangerment� finding�
> The process initiated by the CEI petition will, we suppose, produce an
> appropriate response for the record from EPA and relevant members of the
> science community. And while that process drags on, CEI and Michaels no
> doubt will use their petition as a basis for attempting to muddy the
> waters of scientific discourse, while sliming leaders of the
> international climate science community and questioning their motives.
> A few of those leaders have begun to comment on this attempt. We post
> below comments Climate Science Watch has received from Ben Santer at
> Lawrence Livermore National Laboratory and Prof. Phil Jones, Director of
> the Climatic Research Unit at the University of East Anglia in the UK:
> Comment by Benjamin D. Santer
> <http://www-pcmdi.llnl.gov/about/staff/Santer/index.php>, Program for
> Climate Model Diagnosis and Intercomparison, Lawrence Livermore National
> As I see it, there are two key issues here.
> First, the Competitive Enterprise Institute (CEI) and Pat Michaels
> are arguing that Phil Jones and colleagues at the Climatic Research
> Unit at the University of East Anglia (CRU) willfully,
> intentionally, and suspiciously �destroyed� some of the raw surface
> temperature data used in the construction of the gridded surface
> temperature datasets.
> Second, the CEI and Pat Michaels contend that the CRU surface
> temperature datasets provided the sole basis for IPCC �discernible
> human influence� conclusions.
> Both of these arguments are incorrect. First, there was no
> intentional destruction of the primary source data. I am sure that,
> over 20 years ago, the CRU could not have foreseen that the raw
> station data might be the subject of legal proceedings by the CEI
> and Pat Michaels. Raw data were NOT secretly destroyed to avoid
> efforts by other scientists to replicate the CRU and Hadley
> Centre-based estimates of global-scale changes in near-surface
> temperature. In fact, a key point here is that other
> groups�primarily at the NOAA National Climatic Data Center (NCDC)
> and at the NASA Goddard Institute for Space Studies (GISS), but also
> in Russia�WERE able to replicate the major findings of the CRU and
> UK Hadley Centre groups. The NCDC and GISS groups performed this
> replication completely independently. They made different choices in
> the complex process of choosing input data, adjusting raw station
> data for known inhomogeneities (such as urbanization effects,
> changes in instrumentation, site location, and observation time),
> and gridding procedures. NCDC and GISS-based estimates of global
> surface temperature changes are in good accord with the HadCRUT data
> The second argument�that �discernible human influence� findings are
> like a house of cards, resting solely on one observational
> dataset�is also invalid. The IPCC Third Assessment Report (TAR)
> considers MULTIPLE observational estimates of global-scale
> near-surface temperature changes. It does not rely on HadCRUT data
> alone�as is immediately obvious from Figure 2.1b of the TAR, which
> shows CRU, NCDC, and GISS global-mean temperature changes.
> As pointed out in numerous scientific assessments (e.g., the IPCC
> TAR and Fourth Assessment Reports, the U.S. Climate Change Science
> Program Synthesis and Assessment Report 1.1 (Temperature trends in
> the lower atmosphere: Steps for understanding and reconciling
> differences), and the state of knowledge report, Global Climate
> Change Impacts on the United States, rigorous statistical
> fingerprint studies have now been performed with a whole range of
> climate variables�and not with surface temperature only. Examples
> include variables like ocean heat content, atmospheric water vapor,
> surface specific humidity, continental river runoff, sea-level
> pressure patterns, stratospheric and tropospheric temperature,
> tropopause height, zonal-mean precipitation over land, and Arctic
> sea-ice extent. The bottom-line message from this body of work is
> that natural causes alone CANNOT plausibly explain the climate
> changes we have actually observed. The climate system is telling us
> an internally- and physically-consistent story. The integrity and
> reliability of this story does NOT rest on a single observational
> dataset, as Michaels and the CEI incorrectly claim.
> I have known Phil for most of my scientific career. He is the
> antithesis of the secretive, �data destroying� character the CEI and
> Michaels are trying to portray to the outside world. Phil and Tom
> Wigley have devoted significant portions of their scientific careers
> to the construction of the land surface temperature component of the
> HadCRUT dataset. They have conducted this research in a very open
> and transparent manner�examining sensitivities to different gridding
> algorithms, different ways of adjusting for urbanization effects,
> use of various subsets of data, different ways of dealing with
> changes in spatial coverage over time, etc. They have thoroughly and
> comprehensively documented all of their dataset construction
> choices. They have done a tremendous service to the scientific
> community�and to the planet�by making gridded surface temperature
> datasets available for scientific research. They deserve medals�not
> the kind of deliberately misleading treatment they are receiving
> from Pat Michaels and the CEI.
> (Santer has received several honors, awards and fellowships including
> the Department of Energy Distinguished Scientist Fellowship
> the E.O. Lawrence Award, and the �Genius Award� by the MacArthur
> Comment by Prof. Phil Jones
> <http://www.cru.uea.ac.uk/cru/people/pjones/>, Director, Climatic
> Research Unit (CRU), and Professor, School of Environmental Sciences,
> University of East Anglia, Norwich, UK:
> No one, it seems, cares to read what we put up
> <http://www.cru.uea.ac.uk/cru/data/temperature/> on the CRU web
> page. These people just make up motives for what we might or might
> not have done.
> Almost all the data we have in the CRU archive is exactly the same
> as in the Global Historical Climatology Network (GHCN) archive used
> by the NOAA National Climatic Data Center [see here
> <http://www.ncdc.noaa.gov/oa/climate/ghcn-monthly/index.php> and
> here <http://www.ncdc.noaa.gov/oa/climate/research/ghcn/ghcngrid.html>].
> The original raw data are not �lost.� I could reconstruct what we
> had from U.S. Department of Energy reports we published in the
> mid-1980s. I would start with the GHCN data. I know that the effort
> would be a complete waste of time, though. I may get around to it
> some time. The documentation of what we�ve done is all in the
> If we have �lost� any data it is the following:
> 1. Station series for sites that in the 1980s we deemed then to be
> affected by either urban biases or by numerous site moves, that were
> either not correctable or not worth doing as there were other series
> in the region.
> 2. The original data for sites for which we made appropriate
> adjustments in the temperature data in the 1980s. We still have our
> adjusted data, of course, and these along with all other sites that
> didn�t need adjusting.
> 3. Since the 1980s as colleagues and National Meteorological
> Services <http://www.wmo.int/pages/members/index_en.html> (NMSs)
> have produced adjusted series for regions and or countries, then we
> replaced the data we had with the better series.
> In the papers, I�ve always said that homogeneity adjustments are
> best produced by NMSs. A good example of this is the work by Lucie
> Vincent in Canada. Here we just replaced what data we had for the
> 200+ sites she sorted out.
> The CRUTEM3 data for land look much like the GHCN and NASA Goddard
> Institute for Space Studies data
> <http://data.giss.nasa.gov/gistemp/> for the same domains.
> Apart from a figure in the IPCC Fourth Assessment Report (AR4)
> showing this, there is also this paper from Geophysical Research
> Letters in 2005 by Russ Vose et al.
> Figure 2 is similar to the AR4 plot.
> I think if it hadn�t been this issue, the Competitive Enterprise
> Institute would have dreamt up something else!