12B.4 Statistical Downscaling over Illinois Using Self-Organizing Maps

Thursday, 10 January 2019: 9:15 AM
North 122BC (Phoenix Convention Center - West and North Buildings)
Andrew Polasky, The Pennsylvania State Univ., University Park, PA; and H. L. Hamilton, J. L. Evans, and J. D. Fuentes

Statistical downscaling of climate model projections enables greater understanding of the likely impacts of climate change in a given region. We use self organizing maps (SOMs) to produce downscaled daily estimates of temperature and precipitation over the state of Illinois. In addition to producing these daily time series of downscaled values, we employ a modified form of the same SOM technique to produce estimates of the frequency of extreme events in both temperature and precipitation. At present, the daily estimates are fed into a crop model, to provide estimates of agricultural production in alternative climate regimes. Future work will include incorporation of downscaled information on extreme events. This work is undertaken as part of an interdisciplinary project investigating ways of reducing household energy and water use. Results from the climate downscaling will be included in a role-playing game aimed at highlighting the outcomes of household-level changes in consumption patterns.
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