By Jim Collins
From agricultural disruptions in Illinois to rising sea levels on the East Coast, changing climate conditions have far-reaching impacts that require local and regional attention.
Armed with more accurate regional climate projections, policymakers and stakeholders will be better equipped to develop adaptation strategies and mitigation measures that address the potential effects of climate change in their backyards.
While global climate models are used to simulate large-scale patterns suitable for weather forecasting and large-area climate trends, they lack the level of detail needed to model conditions at local and regional scales.
With a method called dynamical downscaling, researchers can use outputs from coarse-resolution global models to drive higher-resolution regional climate models. The enhanced resolution allows regional models to better account for topographic details, while also improving the ability to simulate surface variables such as air temperature, precipitation, and wind.
As part of an ongoing study at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility, a research team from Argonne National Laboratory and the University of Chicago is using supercomputing resources to investigate the effectiveness of dynamically downscaled climate models…
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