Statistical prediction of summer rainfall and vegetation in the Ethiopian highlands

Abstract

Year-to-year fluctuations of Ethiopia climate are investigated to develop statistical predictions at one-season lead time. Satellite vegetation data from NASA and rainfall from ARC2 are the basis for analysis. The "target" seasons are May-July and August-October, while "predictors" are December-February and March-May, respectively. Global fields of surface temperature, sea level air pressure, and upper and lower level zonal winds are employed in point-to-field correlations. After step-wise multivariate regression, the leading predictors are: surface temperature across Europe (cold-favourable), 850 mb zonal winds over the tropical Atlantic (easterly-favourable), and surface temperature in the tropical Indian Ocean (cold-favourable). Predictive algorithms for early and late rainfall exhibit a consistent r 2 fit of 0.50, while those for vegetation reach 0.65 in late summer, indicating that fluctuations in food resources could be forewarned. © 2014 Mark R. Jury.