基于对流尺度集合预报方法对一次暴雨过程预报的分析

Analysis of the forecast performance of a rainstorm process based on a convective scale ensemble prediction system

为了更加直观和深入地理解对流尺度集合预报中的降水集合预报产品,以便进一步向预报员推广应用,本文开展了基于对流尺度集合预报方法对2021年8月28—29日的一次暴雨过程的预报性能分析,对集合预报的暴雨和大暴雨量级降水预报技巧进行了综合分析。结果表明:(1)不同集合成员降水预报结果的差异随着降水量级的增大越发明显,预报最优和最差的成员的TS评分相差0.3以上。(2)概率匹配平均预报对于暴雨和大暴雨量级降水的预报技巧优于控制预报,也优于集合平均。集合平均由于集合成员预报的平滑作用导致其对极端降水不敏感,因此,简单的集合平均不适合于大暴雨以上量级的极端降水预报。(3)从最小值预报到最大值预报,随着集合百分位的增大,命中率、空报率和频率偏差均逐渐增大,70%或者80%集合百分位预报的预报技巧最优,且优于集合平均和概率匹配平均预报。(4)对于重庆东北部偏西地区出现的大暴雨量级降水,较长预报时效集合概率预报均预报出了一定的降水概率,最长提前60 h,相应的最优的集合成员的降水预报与实况也较为接近。

In order to understand more comprehensively the ensemble forecast results of rainfall with the convective scale ensemble prediction system and thus to further recommend them to the weather forecasters,this study carried out the analysis of the forecast performance of a rainstorm process with a convective scale ensemble prediction system.The results show that:(1)The forecast difference of each ensemble member increases with precipitation magnitude,and the threat score difference between the best and worst performed ensemble member is more than 0.3.(2)Probability-matched mean forecast performs better than control forecast and ensemble mean forecast for both rainstorm and heavy rainstorm precipitation.Ensemble mean is insensitive to extreme precipitation due to the smoothing effect of ensemble member forecast.Therefore,ensemble mean is not suitable for extreme precipitation forecast.(3)From the minimum forecast to the maximum forecast,with the increase of ensemble percentile,the probability of detection,false alarm rate,and frequency bias gradually increase.The forecast at 70%or 80%ensemble percentile performs the best,and it is better than the ensemble mean and probability-matched mean forecast.(4)For the heavy rainstorm precipitation in the west part of northeastern Chongqing,the long-time ensemble probability forecasts with leading-times up to 60 h all successfully predict certain precipitation probability of rainstorm,and the forecasted precipitation from the corresponding best performed ensemble member is close to the observation.