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Identifying climatic analogs for Wisconsin under 21st-century climate-change scenarios
Authors:Samuel Veloz  John W Williams  David Lorenz  Michael Notaro  Steve Vavrus  Daniel J Vimont
Institution:1. Department of Geography, Center for Climatic Research, University of Wisconsin, Madison, WI, USA
2. PRBO Conservation Science, Petaluma, CA, USA
3. Center for Climatic Research, University of Wisconsin, Madison, WI, USA
4. Department of Atmospheric and Oceanic Sciences, Center for Climatic Research, University of Wisconsin, Madison, WI, USA
Abstract:There is a deep disconnect between scientific and public concern about climate change. One reason is that global climate change is a fairly abstract concept with little perceived relevance, so a key challenge is to translate climate-change projections into locally concrete examples of potential impacts. Here we use climate analog analyses as an alternative method for identifying and communicating climate-change impacts. Our analysis uses multiple downscaled general circulation models for the state of Wisconsin, at 0.1 decimal degree resolution, and identifies contemporary locations in North America that are the most similar to the projected future climates for Wisconsin. We assess the uncertainties inherent in climate-change projections among greenhouse gas emission scenarios, time windows (mid-21st century vs. late 21st-century) and different combinations of climate variables. For all future scenarios and simulations, contemporary climatic analogs within North America were found for Wisconsin’s future climate. Closest analogs are primarily 200–500 km to the south-southwest of their Wisconsin reference location. Temperature has the largest effect on choice of climatic analog, but precipitation is the greatest source of uncertainty. Under the higher-end emission scenarios, the contemporary climatic analogs for Wisconsin’s end-21st-century climates are almost entirely outside the state. Climate-analog analyses offer a place-based means of assessing climate impacts that is complementary to the species-based approaches of species distributional models, and carries no assumptions about the characterization and conservatism of species niches. The analog method is simple and flexible, and can be readily extended to other regions and other environmental variables.
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