Bad data analysis by University of Alabama scientists set old myth in motion
Denier talking points are harder to kill than vampires. They keep rising from the dead no matter how many times scientists try to drive a stake through their heart.
Sometimes they take on a slightly different form, like a relentless, indestructible liquid-metal android assassin from the future that constantly switches appearance in an effort to fulfill its mission of ruining life on this planet for homo “sapiens.”
And so it is with one of the most enduring denier myths, that the satellite data didn’t show the global warming that the surface temperature data did. When this myth was exposed as bad data analysis by scientists at the University of Alabama in Huntsville, it morphed into a narrower claim about supposed discrepancies between the modeled and observed rate of warming in the tropical troposphere — a claim which itself was quickly debunked (see “They blinded me with bad science“). But since that debunking did not come in a peer-reviewed publication, the myth lived on for hard-core deniers.
The fatal blow has come in the form of a new paper, “Consistency of modelled and observed temperature trends in the tropical troposphere,” ($ub. req’d, RealClimate post here, and a fact sheet with everything you could possibly want to know about the study in laymen’s language here [PDF]). The International Journal of Climatology article has 17 authors, including some of the top climate scientists in the country. Its bottom line:
Using state-of-the-art observational datasets and results from a large archive of computer model simulations, a consortium of scientists from 12 different institutions has resolved a long-standing conundrum in climate science — the apparent discrepancy between simulated and observed temperature trends in the tropics. Research published by this group indicates that there is no fundamental discrepancy between modeled and observed tropical temperature trends when one accounts for: 1) the (currently large) uncertainties in observations; 2) the statistical uncertainties in estimating trends from observations. These results refute a recent claim that model and observed tropical temperature trends “disagree to a statistically significant extent”. This claim was based on the application of a flawed statistical test and the use of older observational datasets.
I would say “Ouch” or “D’oh” but since the “et al” in the original flawed Douglass et al paper included the likes of John Christy and S. Fred Singer, the more appropriate one word response is probably “Duh.”
The fact sheet has a very interesting figure:
Estimates of observed temperature changes in the tropics (30Â°N-30Â°S). Changes are expressed as departures from average conditions over 1979 to 2006. The top panel shows results for the surface and lower troposphere. The thin red and black lines in the top panel are 12-month running averages of the temperature changes for individual months. The thick straight lines are trends that have been fitted to the time series of surface and tropospheric temperature changes. The warming trend is larger in the tropospheric temperature data than in the surface temperature record, in accord with computer model results. The bottom panel shows a commonly-used index of El NiÃ±o and La NiÃ±a activity, consisting of sea-surface temperature changes averaged over the so-called NiÃ±o 3.4 region of the tropical Pacific. The bottom panel shows that much of the year-to-year variability in surface and lower tropospheric temperatures is related to changes in El NiÃ±os and La NiÃ±as.
In short, “El NiÃ±os and La NiÃ±as introduce considerable year-to-year variability [or noise] in surface and tropospheric temperature” superimposed on the underlying warming trend. The authors note:
The underlying “signal trend” is what we really want to compare in climate models and observations. Any meaningful statistical test of the differences between modeled and observed temperature trends must therefore account for the statistical uncertainty in estimating this “signal trend” from noisy observational data. The Douglass et al. test did not account for this uncertainty.
Ouch D’oh Duh.
The Real Climate post ends by noting:
Taking a slightly larger view, I think this example shows quite effectively how blogs can play a constructive role in moving science forward (something that we discussed a while ago). Given the egregiousness of the error in this particular paper (which was obvious to many people at the time), having the initial blog posting up very quickly alerted the community to the problems even if it wasn’t a comprehensive analysis. The time in-between the original paper coming out and this new analysis was almost 10 months. The resulting paper is of course much better than any blog post could have been and in fact moves significantly beyond a simple rebuttal. This clearly demonstrates that there is no conflict between the peer-review process and the blogosphere. A proper paper definitely takes more time and gives generally a better result than a blog post, but the latter can get the essential points out very quickly and can save other people from wasting their time.
Kudos to Gavin Schmidt and all of the authors of this excellent paper. Jeers to the climate