Deep Learning at the Interface of Agricultural Insurance Risk and Spatio-Temporal Uncertainty in Weather Extremes

Challenges in risk estimation for agricultural insurance bring to the fore statistical problems of modeling complex weather and climate dynamics, analyzing massive multi-resolution, multi-source data. Nonstationary space-time structure of such data also introduces greater complexity when assessing the highly nonlinear relationship between weather events and crop yields. In this setting, conventional parametric statistical and actuarial models...