Crop models can be run with seasonal climate forecasts to make predictions of crop yield for the upcoming season. Skillful predictions of crop yield could reduce the humanitarian and socio-economic impacts of crop failure and allow improved management of the food surplus in favorable years.
Kathryn Nicklin has developed and tested a yield forecasting system for groundnut and sorghum in West Africa. The system uses the GLAM crop model together with ECMWF seasonal forecasts. Crop failures and bumper yields can be predicted reasonably well. Further improvements to increase the skill of the system would be expected to occur as part of operationalisation.
Kathryn has also used GLAM to model maize yields in East Africa with a view to running the model with seasonal forecasts. This work developed methods for improving input data quality and was part of the EU funded projects EUPORIAS and SPECS.
Challinor AJ; Koehler AK; Ramirez-Villegas J; Whitfield S; Das B (2016) Current warming will reduce yields unless maize breeding and seed systems adapt immediately, Nature Climate Change, 6, pp.954-958. doi: 10.1038/nclimate3061
Challinor, A. J., T. Osborne, A. Morse, L. Shaffrey, T. Wheeler, H. Weller, Vilale, P.L (2009). Methods and resources for climate impacts research: achieving synergy. Bulletin of the American Meteorological Society, 90 (6), 836-848. .doi.10.1175/2008BAMS2403.1
Challinor, A. J., F. Ewert, S. Arnold, E. Simelton and E. Fraser (2009). Crops and climate change: progress, trends, and challenges in simulating impacts and informing adaptation. Journal of Experimental Botany, 60 (10), 2775-2789. doi: 10.1093/jxb/erp062