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Evaluation of quantitative precipitation forecasts by TIGGE ensembles for south China during the presummer rainy season

Based on The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) data set, this study evaluates the ability of global ensemble prediction systems (EPSs) from the European Centre for Medium‐Range Weather Forecasts (ECMWF), U.S. National Centers for Environmental Prediction, Japan Meteorological Agency (JMA), Korean Meteorological Administration, and China Meteorological Administration (CMA) to predict presummer rainy season (April–June) precipitation in south China. Evaluation of 5 day forecasts in three seasons (2013–2015) demonstrates the higher skill of probability matching forecasts compared to simple ensemble mean forecasts and shows that the deterministic forecast is a close second. The EPSs overestimate light‐to‐heavy rainfall (0.1 to 30 mm/12 h) and underestimate heavier rainfall (>30 mm/12 h), with JMA being the worst. By analyzing the synoptic situations predicted by the identified more skillful (ECMWF) and less skillful (JMA and CMA) EPSs and the ensemble sensitivity for four representative cases of torrential rainfall, the transport of warm‐moist air into south China by the low‐level southwesterly flow, upstream of the torrential rainfall regions, is found to be a key synoptic factor that controls the quantitative precipitation forecast. The results also suggest that prediction of locally produced torrential rainfall is more challenging than prediction of more extensively distributed torrential rainfall. A slight improvement in the performance is obtained by shortening the forecast lead time from 30–36 h to 18–24 h to 6–12 h for the cases with large‐scale forcing, but not for the locally produced cases.