Statistical models of crop yields are widely-used to predict the agricultural impacts of climate change scenarios. As a result, they are difficult to test without observing the future. Mathematical models of crop yield processes (process-based models) are simulated “futures” that can be exploited as test-bed for statistical models. Harshil will discuss these models, and some of their strengths and limitations as they relate to his research.
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