Climate models are sophisticated computer programs that incorporate as many details about the complex workings of the environment as possible. Hundreds of dynamic processes, such as ocean currents, cloud formations, vegetation cover and the increase in atmospheric greenhouse gases, are included. The models produce data of the net effects for square-shaped plots over the Earth's surface. The smaller these squares are, the better the resolution the model can provide.
A model must factor in so many changing variables that a full analysis can require months of nonstop computational effort. The Rosen Center for Advanced Computing on Purdue's campus provided the powerful computing required for this study.
Jeremy Pal, one of the lead developers of the regional climate model used in this study and a co-author of the paper, said the regional climate model offers the most detailed picture available today of what is happening across the United States.
The regional model divides the landmass of the United States into a grid of cells spaced 25 kilometers, or 15.6 miles, apart and provides information about the conditions occurring for each cell. This adds detailed information to the data from the global models.
"For example, for Indiana the regional model gives information for specific counties, while a global model would have one set of average data for the entire state," said Pal, who also is a professor of civil engineering at Loyola Marymount University and a member of the Intergovernmental Panel on Climate Change and the Abdus Salam International Centre for Theoretical Physics in Trieste, Italy. "The regional model has a higher resolution and provides information on the tens-of-miles scale. Global models give data on the hundreds-of-miles scale. The use of four different models in this study makes the results more robust."
Trapp said the next step is to use eve
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