Predicting agricultural impacts of large-scale drought: 2012 and the case for better modeling
Produced as part of the Adaptation to climate change and human development CCCEP research programme theme
Working Paper 111
The 2012 growing season saw one of the worst droughts in a generation in much of the United States and cast a harsh light on the need for better analytic tools and a comprehensive approach to predicting and preparing for the effects of extreme weather on agriculture. We present an example of a simulation-based forecast for the 2012 US maize growing season produced as part of a high-resolution multi-scale predictive mechanistic modeling study designed for decision support, risk management, and counterfactual analysis. We estimate national average yields of 7.507 t/ha for 2012, 24.6% below the expected value based on increasing trend yield alone, with an interval based on resampled forecasts errors stretching from 5.586 to 8.967 t/ha. On average, the median yield simulations deviate from NASS observations by 8.3% from 1979 to 2011.
Joshua Elliot, Michael Glotter, Neil Best, Ken Boote, Jim Jones, Jerry Hatfield, Cynthia Rozenweig, Leonard A. Smith and Ian Foster