一种基于雷达外推与数值模式的动态融合降水概率预报方法-气象研究与应用

文章信息/Info

Title:: Dynamic Blending Probabilistic Precipitation Forecasts Method based on Radar Extrapolation and Numerical Weather Prediction

作者:: 薛峰¹; 王兴²; 苗春生²; 吴双²; 张琳焓²; 1. 国家气象中心预报系统开放实验室, 北京 100081;
2. 南京信息工程大学大气科学学院, 江苏南京 210044

Author(s):: XUE Feng¹; WANG Xing²; MIAO chunsheng²; WU Shuang²; ZHANG Linhan²; 1. National Meteorological Centre, Beijing 100081, China;
2. School of Atmospheric Science, Nanjing University of Information Science & Technology, Nanjing 210044, China

Keywords:: Blending Nowcasting; Probabilistic Precipitation Forecasts; Radar Extrapolation; Optical Flow; Numerical Weather Prediction

摘要:: 提出一种动态权重的降水概率融合预报方法。首先建立一个适用于权重分配的评分模型,对基于雷达光流外推的降水概率预报和基于数值模式经反射率换算后的降水概率预报的预报准确率分别加以评估,再根据各自在不同预报时效的评分,动态地分配两种预报方法在不同预报时效的权重。实验部分通过Brier等评分表明,融合后各个预报时效的预报都表现出与雷达外推或数值模式相近甚至更高的技术评分。

Abstract:: A new method for probabilistic precipitation forecasts with dynamic weights is proposed. Firstly, a scoring model for weight distribution should be established to evaluate the forecast accuracy calculated from radar extrapolation and numerical model prediction. Secondly, according to the scores of different lead times, the weight of two kinds of forecasting methods is dynamically allocated in different forecasting time. In the experimental part, the Brier and other ratings show that the prediction of each forecast time is similar to the radar extrapolation or numerical model, and even higher technical score.