基于累加气候概率的FSS检验方法对多模式短时暴雨预报的评估

Forecast Evaluation of Short-Term Heavy Precipitation from Operational Models by the Fractions Skill Score Method Based on the Cumulative Climatological Probability

为深入认识数值天气模式强降水精细化预报性能,本文以短时强降水多发的浙江省2019年5到10月降水为例,采用分数技巧评分(Fractions Skill Score,简称FSS)邻域检验方法,评估了6个业务模式短时降水预报准确性,重点探讨了各模式短时暴雨预报能力及天气背景的影响。结果表明:(1)基于站点降水的累加气候概率,确定了短时小雨、中雨、大雨、暴雨和大暴雨的预报技巧评分阈值各为0.583、0.522、0.506、0.502和0.500,改进并实现了FSS方法对长时间序列各等级降水预报技巧尺度的综合评估。(2)只有上海中尺度区域数值预报业务系统和浙江中尺度区域数值预报业务系统的暴雨预报平均评分达到预报技巧,相应技巧尺度为159、159和183 km;这3个产品共有约6成预报达到技巧评分,其技巧尺度累积频率从3 km至183 km可增幅近50%,这种尺度选择性评价可为不同尺度下产品应用提供参考。(3)不同天气背景下各模式预报性能差异明显。台风类、梅雨类和弱天气尺度强迫类短时暴雨预报的最优模式分别是欧洲中期天气预报中心全球预报模式、上海中尺度区域数值预报业务系统和浙江中尺度区域数值预报业务系统,各技巧尺度为27、99和135 km,模式产品使用中需分类区别对待。

In this paper,to gain insight into the performance of numerical weather prediction models on refined heavy rainfall,a neighborhood verification method named Fractions Skill Score(FSS)is introduced to explore the capability of six operational models on 3-h accumulated precipitation during the warm season in 2019 in Zhejiang Province,with an emphasis on short-term torrential rain and the impacts of different weather backgrounds.(1)According to the cumulative climatological probability of 3-h accumulated precipitation at the station,the FSS method is improved by determining the skill score thresholds for 5-grade precipitation with thresholds of 0.1,3.0,10.0,20.0,and 50.0 mm/3 h to be 0.583,0.522,0.506,0.502,and 0.500,respectively,and applied in the evaluation of their prediction skill scales in the long time series.(2)The regional models perform better than the global ones in heavy rain forecasts,and only the mean scores of the Shanghai Regional Numerical Weather Prediction System and Zhejiang Regional Numerical Weather Prediction System realize the forecast skills for torrential rain,and their corresponding skill scales are 159,159,and 183 km,respectively.There are approximately 60% of forecasts in these models that achieve the prediction skills,and the cumulative frequency of the skill scale is increased by nearly 50%from 3 to 183 km.These scale-selective evaluation results can provide guidance for the application of model products on different scales.(3)There are evident differences in the model performance of precipitation forecasts under various weather backgrounds.The best models for predicting torrential rains under the backgrounds of tropical cyclones,Meiyu fronts,and weak synoptic forcing are the Global Forecast Model from the European Centre for Medium-Range Weather Forecasts(EC-GFS),Shanghai Regional Numerical Weather Prediction System,and Zhejiang Regional Numerical Weather Prediction System,with skill scales of 27,99,and 135 km,respectively.Therefore,the application of model products should be treated differently in terms of weather background type.