Four months ago I wrote a post about how several speakers at the AGU 2012 Fall Meeting suggested that the IPCC may be systematically underestimating several key climate change-related parameters (total anthropogenic GHG emissions, Arctic ice melt rates, sea level rise projections). Sure enough, one of those speakers is co-author on a new paper that proposes there is a systematic trend towards ‘erring on the side of least drama’, i.e., of backing off from scientifically-rigorous predictions that could be interpreted as alarming:
Brysse, K.; Oreskes, N.; O’Reilly, J.; Oppenheimer, M. Climate change prediction: Erring on the side of least drama? Global Environmental Change 2013, 23, 327–337.
At about the same time this was published, the Economist came out with a very different article suggesting just the opposite, that global climate models are currently over-predicting temperature increases because estimates of climate sensitivity to CO2 emissions are too high. Check out DotEarth blog or Yale 360 for additional technical discussions of the issue. For the record, while the article in the Economist is extremely interesting, I find its dismissive tone troubling- even if climate change is coming in on the low end of the prediction range, it’s still serious enough to warrant a much greater effort towards mitigation and adaptation than humanity is currently making.
That being said, for a lively rebuttal of the Brysse et al. 2013 article, check out http://rogerpielkejr.blogspot.com/2013/02/science-is-shortcut.html (Disclaimer- this blog post is what led me to the paper in the first place). After having read the article in its entirety, I have to say that I think Dr. Pielke’s harsh critique is on-point, and that Brysse et al. 2013 is characterized by cursory analysis, anecdotal reasoning, and tendencies toward proof by assertion and appeal to authority (Disclaimer 2- I’m not a social scientist, so my standards of what constitutes legitimate reasoning or convincing arguments might be fundamentally different than that of the authors). The hypothesis presented, that scientists have more incentive to bias their work towards under-estimation of the severity of environmental impacts than towards over-estimation, is entirely reasonable and worthy of analysis. However, the article unfortunately offers little actual analysis: it cites only a small number (5) of previous assessments (none of which is more current than 4 years old, even though more recent critical reports are available), makes no systematic attempt at quantitative analysis of the results, has no mention of statistics (perhaps unsurprising given the small sample size), and offers not even a single figure or table to help organize their thoughts or help the reader follow their critique of those multiple studies. The article goes on to present some anecdotal case studies of past instances where scientists have been taken to task for over-predicting certain environmental impacts, and ends with a far-ranging discussion (which I found genuinely interesting) of how skepticism of new theories is inherent in modern science, with references to Darwin, Lyell, and Kuhn. Interesting stuff to be sure, though I remain unmoved by their overall conclusions.
PS– One of the authors of the Brysse 2013 study will be lecturing at CSU on Thursday. I’m very curious what she will have to say!