摘要
提出一种基于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;提出一种改进的Brier评分法,该方法兼顾了降水落区的大小和降水量,降低评分对样本数据数量多少的敏感性;根据两种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。试验部分通过Brier等评分验证表明,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。
A new method for probabilistic precipitation forecasts with dynamic weights is proposed.First,a scoring model for weight distribution is established and the forecast accuracy calculated from radar extrapolation and numerical model prediction is evaluated.Second,an improved method based on the Brier scoring is presented,which takes into account the size of the precipitation area and precipitation,and reduces the sensitivity to the number of samples.Third,according to the scores of different lead times,the weights of two kinds of forecasting methods are dynamically allocated in different forecast lead time.In the experimental part,the Brier and other ratings show that the prediction of each lead time is similar to the radar extrapolation or the numerical model,and even has a higher technical score.
出处
《气象科技》
北大核心
2017年第6期1036-1042,共7页
Meteorological Science and Technology
基金
国家自然科学基金项目(41276033)
南京气象雷达开放实验室研究基金(BJG201105)资助
关键词
融合预报
降水概率预报
雷达外推
光流法
数值模式
blending nowcasting
probabilistic precipitation forecast
radar extrapolation
optical flow
numerical weather prediction
