A COMBINED VERIFICATION METHOD FOR PREDICTABILITY OF PERSISTENT HEAVY RAINFALL EVENTS OVER EAST ASIA BASED ON ENSEMBLE FORECAST

IF 1.5 4区 地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES
Wu Zhi-peng, Chen Jing, Zhang Han-bin, Chen Fa-jing, Zhuang Xiao-ran
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引用次数: 1

Abstract

Persistent Heavy Rainfall (PHR) is the most influential extreme weather event in Asia in summer, and thus it has attracted intensive interests of many scientists. In this study, operational global ensemble forecasts from China Meteorological Administration(CMA) are used, and a new verification method applied to evaluate the predictability of PHR is investigated. A metrics called Index of Composite Predictability (ICP) established on basic verification indicators, i. e., Equitable Threat Score(ETS) of 24h accumulated precipitation and Root Mean Square Error(RMSE) of Height at 500hPa, are selected in this study to distinguish“good”and“poor”prediction from all ensemble members. With the use of the metrics of ICP, the predictability of two typical PHR events in June 2010 and June 2011 is estimated. The results show that the“good member”and“poor member”can be identified by ICP and there is an obvious discrepancy in their ability to predict the key weather system that affects PHR.“Good member”shows a higher predictability both in synoptic scale and mesoscale weather system in their location, duration and the movement. The growth errors for “poor” members is mainly due to errors of initial conditions in northern polar region. The growth of perturbation errors and the reason for better or worse performance of ensemble member also have great value for future model improvement and further research.
基于集合预报的东亚持续强降雨事件可预测性联合验证方法
持续性强降雨(PHR)是亚洲夏季最具影响力的极端天气事件,引起了许多科学家的高度关注。本文利用中国气象局(CMA)全球综合预报资料,探讨了一种新的PHR可预测性评价方法。在基本验证指标(即24小时累积降水的公平威胁得分(ETS)和500hPa高度的均方根误差(RMSE))的基础上,本研究选择了一个称为综合可预测性指数(ICP)的指标来区分所有集合成员的“好”和“差”预测。利用ICP指标,估算了2010年6月和2011年6月两个典型PHR事件的可预测性。结果表明,ICP可以识别“好成员”和“差成员”,对影响PHR的关键天气系统的预测能力存在明显差异。“好成员”展示了一个更高的可预测性在天气尺度和中尺度天气系统的位置,持续时间和运动。“贫穷”成员的增长误差主要是由于北极地区初始条件的误差。微扰误差的增长以及集合成员性能好坏的原因对未来模型的改进和进一步研究也具有重要的价值。
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来源期刊
热带气象学报
热带气象学报 METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
1.80
自引率
8.30%
发文量
2793
审稿时长
6-12 weeks
期刊介绍: Information not localized
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