Abstract:Statistical post-processing of ensemble forecasts could effectively improve their accuracy and reliability. In this study, three typical post-processing methods including equal weight (EW), model output statistics (MOS) and Bayesian model averaging (BMA) were applied to the raw multi-model runoff forecasts during the flood period (from 1 June to 30 September) of 2010-2013, and the processed results were compared and analyzed. It is shown that BMA is a promising post-processing method with highest accuracy, but… Show more
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