Ensemble-based Regional Climate Prediction: Political Impacts

Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.