薛一迪,黄向宇,卢冰,陈敏,夏宇. 2024. 一种基于分数技巧评分定义的降水预报跳跃指数及其应用. 气象学报,82(X):1-17. DOI: 10.11676/qxxb2024.20230097
引用本文: 薛一迪,黄向宇,卢冰,陈敏,夏宇. 2024. 一种基于分数技巧评分定义的降水预报跳跃指数及其应用. 气象学报,82(X):1-17. DOI: 10.11676/qxxb2024.20230097
Xue Yidi, Huang Xiangyu, Lu Bing, Chen Min, Xia Yu. 2024. A Fraction Skill Score-based precipitation forecast jumpiness index and its application. Acta Meteorologica Sinica, 82(X):1-17. DOI: 10.11676/qxxb2024.20230097
Citation: Xue Yidi, Huang Xiangyu, Lu Bing, Chen Min, Xia Yu. 2024. A Fraction Skill Score-based precipitation forecast jumpiness index and its application. Acta Meteorologica Sinica, 82(X):1-17. DOI: 10.11676/qxxb2024.20230097

一种基于分数技巧评分定义的降水预报跳跃指数及其应用

A Fraction Skill Score-based precipitation forecast jumpiness index and its application

  • 摘要: 基于CMA-BJ系统提供的2021年8月9日2套降水预报结果(业务数值预报模式和同化试验结果)和2022年6月4日、2023年9月17日的业务数值预报模式结果,结合定性分析,利用4种客观评价指标(不确定度、均方根误差、不一致指数和基于分数技巧评分(FSS)定义的预报跳跃指数)对该系统降水预报不一致特征进行了定量评估。3次降水过程的分析结果显示:预报跳跃指数不仅可以识别出2021年8月9日和2022年6月4日业务数值预报模式结果中降水量预报明显减小的3个预报时次,而且对于降水过程预报相对稳定的个例(2021年8月9日同化试验和2023年9月17日业务预报结果),随着预报时次逐渐临近最新预报,该指数整体呈现波动上升或者数值较大、波动较小的特征,表明15个连续降水预报特征逐渐与最新预报趋于一致或者大体相似,与定性分析结果相对吻合。其他3种指数对于降水预报不一致问题的表征存在不足,不确定度和均方根误差显著受到预报降水量的影响,同时不确定度不能反映预报不一致的时间特征,不一致指数随预报时次逐时滚动变化较大,确定的预报不一致时次较多,与定性分析结果存在明显偏差。

     

    Abstract: Based on two sets of precipitation forecast results of the CMA-BJ model (operational and assimilated forecast) on 9 August 2021 and operational results on 4 June 2022 and 17 September 2023, combined with subjective analysis, four objective evaluation indexes (uncertainty, root-mean-square error, inconsistency index and forecast jumpiness index based on FSS) are used to quantitatively evaluate the inconsistency characteristics of precipitation forecast. The analysis of the above three precipitation processes shows that the FSS-based forecast jumpiness index can not only identify the three forecast moments at which the precipitation forecast decreased significantly in the operational results on 9 August 2021 and 4 June 2022, but also distinguish them from the cases in which precipitation forecast is relatively stable based on the assimilated forecast on 9 August 2021 and the operational result on 17 September 2023. As the forecast moment gradually approaches the latest forecast, the jumpiness index either increases or maintains a large value and small fluctuation on the whole, indicating that the 15 continuous precipitation forecast results gradually converge or are roughly similar to the latest forecast, which is relatively consistent with the results of subjective analysis. Since the forecast jumpiness index focuses on precipitation probability in the selected time window, it is not affected by the value, and thus it can more directly reflect spatial distribution characteristics of precipitation forecast in the continuous forecast results of the model. This makes it have a unique advantage for analyzing the overall evolution characteristics of precipitation process. The other three indexes are insufficient to characterize the inconsistency of precipitation forecast. For example, the uncertainty and the root-mean-square error are significantly affected by the value of precipitation forecast, and the uncertainty is not able to reflect temporal characteristics of the forecast inconsistency. The inconsistency index changes greatly as the forecast time rolls from time to time. According to the criteria of the inconsistency index, many jumpiness cases that deviate from results of the subjective analysis are identified.

     

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