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Forest-based and semi-parametric methods for the postprocessing of rainfall ensemble forecasting
2019
Weather and forecasting
Rainfall ensemble forecasts have to be skillful for both low precipitation and extreme events. We present statistical post-processing methods based on Quantile Regression Forests (QRF) and Gradient Forests (GF) with a parametric extension for heavy-tailed distributions. Our goal is to improve ensemble quality for all types of precipitation events, heavy-tailed included, subject to a good overall performance. Our hybrid proposed methods are applied to daily 51-h forecasts of 6-h accumulated
doi:10.1175/waf-d-18-0149.1
fatcat:5cta7h65rzamtp33m3cphkzfra