Statistical Downscaling of a High-Resolution Precipitation Reanalysis Using the Analog Ensemble Method

AbstractThis study explores the first application of an analog-based method to downscale precipitation estimates from a regional reanalysis. The utilized analog ensemble (AnEn) approach defines a metric with which a set of analogs, i.e., the ensemble, can be sampled from the observations in the training period. Based on the determined AnEn estimates, also the uncertainty of the generated precipitation time series can easily be assessed. The study investigates tuning parameters of the AnEn such as the choice of predictors or the ensemble size, in order to optimize the performance. The approach is implemented and tuned based on a set of over 700 rain gauges with 6-hourly measurements for Germany and a 6.2km regional reanalysis for Europe which provides the predictors. The obtained AnEn estimates are evaluated against the observations over a 4-year verification period. With respect to deterministic quality, the results show that AnEn is able to outperform the reanalysis itself depending on location and preci...

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