Climategate (Part II)
A sequel as ugly as the original.
Dec 12, 2011, Vol. 17, No. 13 • By STEVEN F. HAYWARD
In fact, the emails display candid glimpses of concern inside the CRU circle. Peter Thorne of NOAA (National Oceanographic and Atmospheric Administration), who earned his Ph.D. in climate science at East Anglia in 2001, wrote Phil Jones in a 2005 message, “I also think the science is being manipulated to put a political spin on it which for all our sakes might not be too clever in the long run.” An appeal to “context,” which the climate campaigners say is crucial to understanding why excerpts such as this one are unimportant, does quite the opposite, and only points to the problems the climate change campaigners have brought upon themselves by their tribalism.
This exchange between Thorne and Jones, along with numerous similar threads in the new cache, is concerned with what should and shouldn’t be included in a chapter of the IPCC’s 2007 fourth assessment report—a chapter for which Jones was the coordinating lead author along with another key Climategate figure, Kevin Trenberth. The complete chapter (if you’re keeping score at home, it’s Chapter 3 of Working Group I, “Observations: Surface and Atmospheric Climate Change”) lists 10 “lead authors” and 66 “contributing authors” in addition to Jones and Trenberth. One of Jones’s emails from 2004 displays how explicitly political the process of assembling the IPCC report is: “We have a very mixed bag of LAs [lead authors] in our chapter. Being the basic atmos obs. one, we’ve picked up number of people from developing countries so IPCC can claim good geographic representation. This has made our task harder as CLAs [contributing lead authors] as we are working with about 50% good people who can write reasonable assessments and 50% who probably can’t.”
The final chapter was amended along lines Thorne recommended, but several other objections and contrary observations (one in particular from Roger Pielke Jr. about extreme weather events that has been subsequently vindicated) were scornfully dismissed. And appeals to context avoid the question: Is this “science-by-committee” a sensible way to sort out contentious scientific issues that hold immense public policy implications? Perhaps a politicized, semi-chaotic process like the IPCC is unavoidable in a subject as wide-ranging and complex as climate change; future historians of science can debate the issue. But the high stakes involved ought to compel a maximum of open debate and transparency. Instead, the IPCC process places a premium on gatekeepers and arbiters who control what goes in and what doesn’t, and it is exactly in its exercise of the gatekeeping function that the CRU circle has shredded its credibility and trustworthiness.
One thing that emerges from the new emails is that, while a large number of scientists are working on separate, detailed nodes of climate-related issues (the reason for dozens of authors for every IPCC report chapter), the circle of scientists who control the syntheses that go into IPCC reports and the national climate reports that the U.S. and other governments occasionally produce is quite small and partial to particular outcomes of these periodic assessments. The way the process works in practice casts a shadow over one of the favorite claims of the climate campaign—namely, that there exists a firm “consensus” about catastrophic future warming among thousands of scientists. This so-called consensus reflects only the views of a much smaller subset of gatekeepers.
Beyond additional bad news for the hockey stick graph, is there anything new in these emails about scientific aspects of the issue? This will take time to sort out, but I suspect anyone with the patience to go through the weeds of all 5,300 messages and cross check them against published results may well discover troubling new aspects of how climate modeling is done, and how weak the models still are on crucial points (such as cloud behavior). Some of the new emails frankly acknowledge such problems. There are arcane discussions about how to interpolate gaps in the data, how to harmonize different data sets, and how to resolve the frequent and often inconvenient (because contradictory) anomalies in modeling results. Definite examples of political influence have emerged already from a first pass over a sample of the massive cache.
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