Statistical climate model downscaling for impact projections in the Midwest United States

For future climate projections to be useful they must be actionable at the local level. In this study, we develop daily temperature and precipitation climate scenarios suitable for use in projections of drought, energy use, water use, and crop production. We investigate the magnitude of future changes to air temperature and precipitation in the Midwest United States in response to three future climate change scenarios. Results are used to assess changes to incidence of precipitation extremes and human comfort (using heat index) associated with the anticipated climate changes in the region. We use self-organizing maps and random forest based techniques to generate daily realizations of temperature and precipitation for 279 weather stations in a region centred on Illinois. We determine that the random forest model performs best for maximum and minimum temperatures, while the self-organizing map performs best for precipitation. Using nine models from the Coupled Model Inter-Comparison Project Phase 5, downscaled daily temperature and precipitation values are generated for low, moderate, and high greenhouse gas emissions scenarios for historical and future periods. Based on recent trends, we focus our results on the high emissions scenario, and show an average increase of 4.3°C in maximum daily air temperature across the region for the 2071–2100 period. Precipitation decreases by up to 15% in the southern half of the study region, with a similar percentage increase in the northern half of the region. The regional environmental changes result in an increase of 5.8° in average summer heat index, and increase of 48% in the number of days likely to produce extreme heat, and a decrease in the average value of the standardized precipitation and evapotranspiration index of 1.9 (indicating increased drought) across the region by 2100.