North African climate variability. Part 3: Resource prediction

SummaryTropical north Africa depends on rain-fed agriculture as the main economic driver. The variability of climate-sensitive resources is investigated with a goal to develop statistical long-lead prediction models with reasonable skill. Climate data from NCEP is analysed in conjunction with agricultural and economic production in various sectors, in addition to the traditional climatic indices: temperature and rainfall. Key predictors for statistical models include the lower-level zonal wind over the Atlantic and Pacific Oceans. These exhibit a ‘memory’ that is consistent with sea surface temperatures (SST) through equatorial upwelling dynamics. Kinematic predictors outperform SST in hindcast fit by an average 33% with respect to various tropical north African resource indices. A multi-decadal oscillation induces long-term trends in rainfall that contribute to apparently skilful forecasts based on the interaction of Pacific ENSO and the Atlantic zonal overturning circulation. The skill of statistical forecasts is lower when the drying trend is removed.

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