A statistical downscaling procedure for improving multi-model ensemble probabilistic precipitation forecasts
A statistical downscaling solution is proposed and tested here to improve skill and reliability of multi-model ensembles verified when against high-resolution analyses. Point by point, the multi-model ensemble members (and/or deterministic forecasts) are compared against precipitation analyses upscaled to the same grid. A list of dates is generated which represents the dates with the most similar past weather. An ensemble of the deviations of the fine-scale precipitation analyses from their upscaled mean is then multiplied by the ensemble of forecast precipitation amounts, thereby producing a much-higher resolution precipitation forecast with implicit statistical downscaling. At the conference, the impact of this method on precipitation forecast skill and reliability over the US will be discussed.