I think Derek Lowe has it about right.
A third issue I want to comment on are the problems with the data and its analysis. I have deep sympathy for the fellow who tried to reconcile the various poorly documented and conflicting data sets and buggy, unannotated code that the CRU has apparently depended on. And I can easily see how this happens. I’ve been on long-running projects, especially some years ago, where people start to lose track of which numbers came from where (and when), where the underlying raw data are stored, and the history of various assumptions and corrections that were made along the way. That much is normal human behavior. But this goes beyond that.
Those of us who work in the drug industry know that we have to keep track of such things, because we’re making decisions that could eventually run into the tens and hundreds of millions of dollars of our own money. And eventually we’re going to be reviewed by regulatory agencies that are not staffed with our friends, and who are perfectly capable of telling us that they don’t like our numbers and want us to go spend another couple of years (and another fifty or hundred million dollars) generating better ones for them. The regulatory-level lab and manufacturing protocols (GLP and GMP) generate a blizzard of paperwork for just these reasons.
But the stakes for climate research are even higher. The economic decisions involved make drug research programs look like roundoff errors. The data involved have to be very damned good and convincing, given the potential impact on the world economy, through both the possible effects of global warming itself and the effects of trying to ameliorate it.
I don’t think the emails are much of a big deal, except as they indicate any lawbreaking. Even wanting to stay out of “tainted” journals makes sense if you assume the analogy of evolutionary scientists wanting to avoid journals that have been coopted by Intelligent Design cranks or other creationists. But to assume that you have to assume that climate science is as settled as evolution.
Evolution is the only theory for speciation and there are no competing theories. There is a lot of evidence for AGW but much of the data is lost, and there are competing hypotheses. The climate is a complex system, and the computer models of it are clunky (as revealed by the CRU data dump) and rely on iffy data sets. The data sets in support of evolution are many (fossils take second place to DNA evidence) and nothing in modern biology makes any sense except in light of evolution. The same cannot yet be said for any climate hypothesis. (I see nothing that’s risen yet to the standard of a theory because there aren’t any good and tested predictions.)
So to the deliberately offensive who want to call skeptics “deniers”, using a deliberately political term, I say knock it off and show proper respect. While it’s true that some of the anti-AGW noise out there is ideologically-driven any honest person would have to admit that the same is just as true, if not more so, on the pro AGW side.
Scientists are humans, not saints. They’re supposed to show disciplined thought, so they get held to a higher standard, but they are not immune to making mistakes.
A commenter on another post sent this abstract.
Policymakers need to know whether prediction is possible and if so whether any proposed forecasting method will provide forecasts that are substantively more accurate than those from the relevant benchmark method. Inspection of global temperature data suggests that it is subject to irregular variations on all relevant time scales and that variations during the late 1900s were not unusual. In such a situation, a “no change” extrapolation is an appropriate benchmark forecasting method. We used the U.K. Met Office Hadley Centre’s annual average thermometer data from 1850 through 2007 to examine the performance of the benchmark method. The accuracy of forecasts from the benchmark is such that even perfect forecasts would be unlikely to help policymakers. For example, mean absolute errors for 20- and 50-year horizons were 0.18°C and 0.24°C. We nevertheless demonstrate the use of benchmarking with the example of the Intergovernmental Panel on Climate Change’s 1992 linear projection of long-term warming at a rate of 0.03°C-per-year. The small sample of errors from ex ante projections at 0.03°C-per-year for 1992 through 2008 was practically indistinguishable from the benchmark errors. Validation for long-term forecasting, however, requires a much longer horizon. Again using the IPCC warming rate for our demonstration, we projected the rate successively over a period analogous to that envisaged in their scenario of exponential CO2 growth—the years 1851 to 1975. The errors from the projections were more than seven times greater than the errors from the benchmark method. Relative errors were larger for longer forecast horizons. Our validation exercise illustrates the importance of determining whether it is possible to obtain forecasts that are more useful than those from a simple benchmark before making expensive policy decisions.
And the indispensable Derb has a great column on why, even with all of this, we should trust science.
Well, of course we all do trust science. We trust Bernoulli’s Principle every time we get on a plane; we trust celestial mechanics when we take the kids outside to watch a scheduled lunar eclipse; we trust subatomic physics when we relax with an iPod; we trust the laws of chemistry every time we strike a match; we trust the theories of Special and General Relativity when we consult a GPS gadget; we trust natural selection when we fret about drug-resistant disease strains or pesticide-resistant crop infestations; we trust molecular biology every time we pop a pill. Our trust in science is well-nigh unbounded. We hardly draw a breath without trusting science.
Derb’s not up on his aeronautics and doesn’t know that Bernoulli accounts for only a small portion of lift, but his point is valid. Yuval Levin concurs.
…it shows, as Derb notes, that science is a human endeavor, and therefore highly prone to corruptions of all sorts. I do think it’s fair to say, though, that science is less prone to them (or better equipped to correct for them) than most great human endeavors.
As we say around the shop, trust the process.