Climate science needs professional statisticians | Environment - The CT Mirror

Editor’s Note: This opinion piece is the part of a larger series exploring how Connecticut and the nation are grappling with the effects of climate change.

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Climate science needs its own specialized 'climostatisticians' as integral members of multidisciplinary research teams, according to Daniel Cooley, Department of Statistics, Colorado State University and Michael Wehner, Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley.

Photo: Samuel Mann - Flickr

“Climate is what you expect; weather is what you get!”

This old cliché rings true, for climate is the distribution of weather. Weather’s distribution depends on season, location, internal variability, and external influences, both natural and human. As it is weather, not climate, that is observable and measurable, any study of climate is inherently statistical in nature.

Climate change is one of the most important social issues of our time. The climate science community faces the immediate, important task of informing difficult decisions that must be made regarding our economic, environmental, and public health systems. Confidence in the effectiveness of these decisions derives from confidence in the underlying climate science. Appropriate statistical analyses can increase such confidence...

Integration of statisticians into climate science does not have the long history that biostatistics has. However, there are many important and successful examples of joint work between statisticians and climate scientists, and some of this work has influenced policy at the federal government level. In one such example, statisticians played a role in producing and reviewing the 2006 National Research Council report on paleoclimate reconstructions [North et al., 2006], which aimed to reconcile the “hockey stick” controversy arising from the congressional inquiry into the work of Mann et al. [1998].

Another example of collaboration between climate scientists and statisticians that should influence climate science practice is that of Paciorek et al. [2018]. This research shows that in the context of event attribution—that is, attributing the occurrence or severity of specific weather events to climate change —naïvely implemented (but commonly used) statistical bootstrap techniques quantify uncertainty poorly, particularly when estimating the small probabilities associated with attributing causes to individual events.
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Source: The CT Mirror