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吴志鹏, 周国兵, 张亚萍, 刘德, 何军. 2020: 基于风暴尺度模式产品的暴雨最优升尺度概率预报方法研究. 暴雨灾害, 39(4): 372-381. DOI: 10.3969/j.issn.1004-9045.2020.04.007
引用本文: 吴志鹏, 周国兵, 张亚萍, 刘德, 何军. 2020: 基于风暴尺度模式产品的暴雨最优升尺度概率预报方法研究. 暴雨灾害, 39(4): 372-381. DOI: 10.3969/j.issn.1004-9045.2020.04.007
WU Zhipeng, ZHOU Guobing, ZHANG Yaping, LIU De, HE Jun. 2020: Study on the optimal neighborhood area to generate probabilistic prediction of heavy rainfall based on deterministic convection-allowing model. Torrential Rain and Disasters, 39(4): 372-381. DOI: 10.3969/j.issn.1004-9045.2020.04.007
Citation: WU Zhipeng, ZHOU Guobing, ZHANG Yaping, LIU De, HE Jun. 2020: Study on the optimal neighborhood area to generate probabilistic prediction of heavy rainfall based on deterministic convection-allowing model. Torrential Rain and Disasters, 39(4): 372-381. DOI: 10.3969/j.issn.1004-9045.2020.04.007

基于风暴尺度模式产品的暴雨最优升尺度概率预报方法研究

Study on the optimal neighborhood area to generate probabilistic prediction of heavy rainfall based on deterministic convection-allowing model

  • 摘要: 基于ARPS3DVAR+WRF(Advanced Regional Prediction and 3-dimensional variational System)快速同化模式对西南地区近几年发生的4次强降水过程进行模拟试验,对12 h降水预报结果采用升尺度方法,计算邻域平均预报、站点概率预报,最终形成邻域概率预报,并细致分析了这三种预报的特点与效果,讨论了升尺度窗区尺度给不同量级降水带来的影响,最后结合AROC评分与邻域空间检验FSS讨论业务概率预报应用的最佳尺度。结果表明:升尺度邻域平均预报在小雨与大暴雨量级降水上表现不稳定,对中雨的预报提高不明显,但是对大雨与暴雨预报有较好的改善效果;站点概率预报具有一定的误导性,而邻域概率预报可以弥补其缺憾,越高分辨率的模式有更多的降水样本,在降水不确定性上能给出更好的概率分级信息;相对邻域平均的升尺度预报TS检验结果,基于邻域概率的FSSAROC分析有更好的预报技巧指导意义;36 km升尺度窗区既能消除一定程度的强降水预报不确定性,同时也可以保留适当的对流尺度特征,为最佳升尺度窗区。

     

    Abstract: The ARPS3DVAR+WRF (Advanced Regional Prediction and 3-dimensional variational System)rapid assimilation model is used to simulate several heavy rainfall events in Sichuan and Chongqing areas occurred in recent years. Focusing on the strongest precipitation within 12 h. Neighborhood approach is adopted to the SSRAFS (Storm-Scale Rapid Assimilation and Forecast System)products to perform Neighborhood Mean(NM) forecast, Station Probability(SP) forecast and Neighborhood Probability(NP) forecast in the ranges of different upscale radius. Then the characteristics and effects are respectively analyzed, and the effect of increasing upscale window area to the precipitation forecast is particularly discussed. Finally, the optimum radius of the operational forecast is found by combining traditional and spatial verification results. The results show that the performance of the NM forecast is not stable in light rain and downpour. The improvementof the moderate rain is not obvious, However, it has a good effect on the prediction of heavy rainfall. The singlestation probability may be misleading, but NP forecast could serve as a remedy, by giving better classification information on the uncertainty of heavy rainfall prediction, and provide better reference to improve the capability of short-term operational forecast. FSS and AROC verification results based on NP prediction has a better consistency guidance than TS scores of NM prediction. It reveals that the size of 36 km upscale could eliminate the uncertainty of heavy precipitation to a certain extent while retaining the characteristics of convective feature, which should be selected as the optimal window region.

     

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