Aggregation of Gridded Emulated Rainfed Crop Yield Projections at the National or Regional Level

Abstract

To estimate the impact of climate change on yields, researchers traditionally use process-based models or statistical models. To benefit from the capabilities of processed-based models while preserving the application simplicity of statistical models, Blanc and Sultan (2015) and Blanc (2017) provide an ensemble of statistical tools emulating crops yields from global gridded crop models at the grid cell level using a simple set of environmental variables. This paper and companion code provide a tool for researcher to use those statistical emulators and estimate crop yields of rainfed maize, rice, soybean and wheat at the regional level. Crop yields estimates for various regional delineations can them simply be used as input into a variety of numerical equilibrium models and other analyses.