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Agricultural yields are highly susceptible to changes in weather system patterns, including annual and sub-annual changes in temperature and precipitation. The impacts of future meteorological variable changes on crop yields have been widely studied in both empirical and process-based models. These changes in future yields can be used in economic models to adjust future crop yields or production functions to reflect the effects of changing weather conditions. This work presents an econometric approach that combines historical weather data with the biophysical growth cycles of maize, winter wheat, and soybean to predict the year-to-year weather-driven yield shocks for rainfed crops. Temperature and modeled soil moisture are taken as predictors, allowing testing of the fitted rainfed model's ability to predict shocks to irrigated yields by assuming irrigation produces the yield-maximizing level of soil moisture …