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Over the past two decades, skeptics of the reality and significance of anthropogenic climate change have frequently accused climate scientists of “alarmism”: of over-interpreting or overreacting to evidence of human impacts on the climate system. However, the available evidence suggests that scientists have in fact been conservative in their projections of the impacts of climate change. In particular, we discuss recent studies showing that at least some of the key attributes of global warming from increased atmospheric greenhouse gases have been under-predicted, particularly in IPCC assessments of the physical science, by Working Group I. We also note the less frequent manifestation of over-prediction of key characteristics of climate in such assessments. We suggest, therefore, that scientists are biased not toward alarmism but rather the reverse: toward cautious estimates, where we define caution as erring on the side of less rather than more alarming predictions. We call this tendency “erring on the side of least drama (ESLD).” We explore some cases of ESLD at work, including predictions of Arctic ozone depletion and the possible disintegration of the West Antarctic ice sheet, and suggest some possible causes of this directional bias, including adherence to the scientific norms of restraint, objectivity, skepticism, rationality, dispassion, and moderation. We conclude with suggestions for further work to identify and explore ESLD. ⺠Climate scientists are not alarmists but have underestimated recent climate changes. ⺠We identify a directional bias toward erring on the side of least drama (ESLD). ⺠ESLD is an internal pressure arising from norms of objectivity, restraint, etc. ⺠ESLD may cause scientists to underpredict or downplay future climate changes.
"In science, generally, the burden of proof is on those who wish to change prevailing views and approaches, be they theoretical, explanatory, or methodological. Philosopher of science Thomas S. Kuhn described this phenomenon in the 1960s; he called it (in uncharacteristically prosaic terms) "resistance to change" (Kuhn, 1962, pp. 151-152). Established knowledge is the default position, until sufficient evidence is developed to dislodge it."
"A version of erring on the side of least drama can be found in what statisticians call Type 1 and Type 2 errors. As most scientists know, a Type 1 error involves thinking an effect is real when it is not; a Type 2 error means missing effects that are actually there. Making a Type 1 error can be thought of as being naïve, credulous, or gullible; making a Type 2 error can be interpreted as being excessively skeptical or overly cautious. Interestingly, conventional statistics is set up to be deeply skeptical and to avoid Type 1 errors, by placing a very high statistical bar on claims for statistical significance. The use of a 95% or even 99% confidence limit in many scientific experiments reflects a scientific worldview in which skepticism is a virtue and credulity is not. (...) It is telling that professional statisticians generally regard Type 1 errors as more important to avoid than Type 2; social scientists would argue that each case should be judged on its own merits: which is worse depends upon what kind of damage ensues from the Type 1 versus the Type 2 error in that particular case."
"Assuming such a bias operates, model runs which suggest very different results may tend to be discounted. For example, the outcome of a distributed computing experiment using large ensembles of runs of simplified climate models (Stainforth et al., 2005) yielded a probability of nearly 5% that steady-state climate sensitivity exceeds 8 °C. However, the physical implications of such high sensitivities were not pursued much in AR4. The most comprehensive effort to examine the social and ecological impacts resulting from high sensitivity focused on a warming of 4 °C (New et al., 2011). Yet if the climate system were highly sensitive, a much larger warming would be plausible and the implications would be dramatic and worrisome (Piani et al., 2005).
"...the precautionary principle (...) is interpreted in the context of climate change to mean that action in the face of potentially serious and/or irreversible climate risks should not have to wait for complete scientific certainty to be attained (an impossibility in any event)."
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