Abstract:The traditional precipitation skill scores are affected by the well-known double penalty problem caused by slight spatial or temporal mismatches between forecast and observations. The FSS (Fraction skill score) as a popular scientific and diagnostic spatial technique has been proposed for deterministic simulations, while it shows significant advantage in solving this problem. With the ensemble forecast resolution increasing, ensemble precipitation forecasts also have similar problems with deterministic forecasts. In this paper, a new ensemble precipitation verification skill score with spatial technique EFSS (Ensemble Fraction Skill Score) is developed based on extending FSS from deterministic into ensemble forecasts. Using daily forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts and QPE products from national meteorological information center during June and August in 2018, the scoring consistency and the difference with traditional skill score in operational application have been analyzed. It shows that EFSS is not affected by the ensemble members and the consistent evaluation conclusions can be obtained. By comparison with EETS (Ensemble Equitable Threat Score), which is suitable for ensemble forecasting extending from deterministic traditional skill score, it shows that the traditional skill scoring is limited by low skill to effectively assess the different characteristics of heavy precipitation processes. However, EFSS can effectively improve the identification of heavy precipitation forecast verification.