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. Reliable drought prediction is fundamental for water resource managers todevelop and implement drought mitigation measures. Considering that droughtdevelopment is closely related to the spatial–temporal evolution oflarge-scale circulation patterns, we developed a conceptual prediction modelof seasonal drought processes based on atmospheric and oceanic standardizedanomalies (SAs). Empirical orthogonal function (EOF) analysis is firstapplied to drought-related SAs at 200 and 500 hPa geopotential height (HGT)and sea surface temperature (SST). Subsequently, SA-based predictors arebuilt based on the spatial pattern of the first EOF modes. This droughtprediction model is essentially the synchronous statistical relationshipbetween 90-day-accumulated atmospheric–oceanic SA-based predictors and SPI3(3-month standardized precipitation index), calibrated using a simplestepwise regression method. Predictor computation is based on forecastatmospheric–oceanic products retrieved from the NCEP Climate Forecast SystemVersion 2 (CFSv2), indicating the lead time of the model depends on that ofCFSv2. The model can make seamless drought predictions for operational useafter a year-to-year calibration. Model application to four recent severeregional drought processes in China indicates its good performance inpredicting seasonal drought development, despite its weakness in predictingdrought severity. Overall, the model can be a worthy reference for seasonalwater resource management in China.

hydrology and earth system sciences

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China