深圳对流尺度集合预报系统在华南暴雨中的应用研究

Application of Shenzhen Storm-Scale Ensemble Forecast System in Heavy Rainfall of South China

作者：

江崟深圳市气象局；深圳南方强天气研究重点实验室深圳 518040
陈训来深圳市气象局；深圳南方强天气研究重点实验室深圳 518040
朱江山中国科学院大气物理研究所北京 100029
王德立深圳市气象局；深圳南方强天气研究重点实验室深圳 518040
陈元昭深圳市气象局；深圳南方强天气研究重点实验室深圳 518040

中文摘要：

针对深圳对流尺度集合预报系统降水预报偏差的特征，开展了基于频率匹配方法的降水偏差订正技术研究，并对华南地区西南季风暴雨和台风暴雨典型过程中的应用试验。分析表明：1）该方法能有效订正深圳对流尺度集合预报的集合平均降水预报的雨量和雨区面积的系统性偏差，订正后降水预报强度和雨区范围得到改善；2）订正后降水预报的ETS和BIAS评分有一定程度的提高，改进了对流尺度集合预报系统对降水预报的空报现象；3）基于目标对象的空间检验方法（MODE）检验结果显示，订正后降水预报的覆盖面积比、质心距离、强度比率等指标都得到改进，与观测更加接近。研究成果也为对流尺度集合预报系统应用及改进提供参考依据。

中文关键词：

频率匹配，集合预报，偏差订正，MODE方法

KeyWords：

frequency matching, ensemble forecast, bias correction, MODE (method for object-based diagnostic evaluation)

Abstract：

By using frequency matching method (FMM), an experiment is performed to correct the precipitation bias from Shenzhen Storm-Scale Ensemble Forecast system (SZ-SSEF). The principle of this method is to use ensemble member based on precipitation frequency to calibrate the simple ensemble mean frequency to correct smoothing effect caused by ensemble averaging. It is applied to experiments of extreme rainfall events in South China induced by southwest monsoon on June 19 and the strong Typhoon Hato on 23 August 2017. The results show that the method can effectively eliminate system biases in precipitation amount and area coverage. Large area of erroneous or spurious rain from model forecasts can be effectively removed, and ETS and BIAS scores for precipitation forecast are significantly improved. The results of MODE (Method for Object-based Diagnostic Evaluation) test indicated that the corrected precipitation is closer to the observations in the precipitation average area ratio, centroid distance separation and the intensity value ratio. This paper aims to provide references for the application and improvement of the SZ-SSEF.