We evaluate the regional-level agricultural impacts of climate change in the Northern Great Plains. We first estimate a non-linear yield-weather relationship for all major commodities in the area: corn, soybeans, spring wheat and alfalfa. We separately identify benevolent and harmful temperature thresholds for each commodity, and control for severe-to-extreme dry/wet conditions in our yield models. Analyzing all major commodities in a region extends the existing literature beyond just one crop, most typically corn yields. Alfalfa is particularly interesting since it is a legume-crop that is substitutable with grasses as animal feed and rotated with other row-crops for nitrogen-fixation of soils. Our model includes trend-weather and soil-weather interaction terms that extend the existing yield-weather models in the literature. Results suggest that temporal adaptations have not mitigated the negative impacts of weather stressors in the past, and that the spatial soil profile only weakly influences weather impacts on crop yields. We estimate yield-weather elasticities and find that historical weather patterns in the region have benefited corn and soybeans (spring wheat) the most (least). We expand our analysis to formally evaluate the role of short-run weather fluctuations in determining land-use decisions. We utilize decomposed crop yield estimates due to trend and weather in order to model crop acreage shares. Our preliminary results suggest that short-run weather fluctuations are an important factor for decisions on soybeans and spring wheat shares, however only yield trends drive corn shares.