首页|基于集合预报的持续性强降水可预报性评估方法研究

基于集合预报的持续性强降水可预报性评估方法研究

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利用集合预报成员初值误差在大气相空间中增长方向不同的特点，结合模式检验方法，构建持续性强降水可预报性评估指数(Index of Composite Predictability, ICP)，为持续性强降水可预报性及数值预报误差增长机理研究提供科学方法。ICP综合评估指数包括三个数学模型：集合预报成员单一评估指数定义、集合预报成员综合评估指数定义和集合预报成员预报能力定义。利用中国国家气象中心T213全球集合预报资料，选取江淮流域2010年6月17-25日和2011年6月4-12日2次持续性强降水过程，进行ICP综合评估指数应用试验，其中，单一评估指数选取中雨公平成功指数ETS、500 hPa高度场均方根误差分别代表模式降水预报能力和环流形势预报能力。结果显示：可预报性评估指数ICP可有效挑选出预报最好和最差的集合预报成员，两者对持续性强降水过程的大尺度环流系统、中尺度影响系统、降水过程预报差异显著，预报最好成员对影响持续性强降水的大尺度环流形势(阻塞高压、西太平洋副热带高压和东亚大槽)的位置和强度及演变过程、低层中尺度影响系统(如切变线和西南低涡)发生发展过程预报，以及降水发生时间和落区预报与实况更接近，预报更成功，持续性强降水可预报性综合评估指数ICP合理可靠。
A study of evaluation method for predictability of persistent heavy rainfall event based on ensemble forecast
Since initial errors of ensemble members grow toward different directions in atmospheric phase space, within the context of verifi-cation methods of numerical weather prediction, an index of composite predictability (ICP) for persistent heavy rainfall is established, which provides a scientific method for studying predictability and initial error growth. This index (ICP) includes three mathematical models:index of single variable (ISV), index of composite predictability (ICP) and the definition of the ensemble forecasting ability for each member. Verifica-tion of the method is made utilizing T213 global ensemble forecast data for two episodes of persistent heavy rainfall events in Huaihe River ba-sin. The ETS score of rainfall over 10 mm·h-1 and root-mean-square error (RMSE) of 500 hPa geopotential height are selected for ISV evalua-tion to represent the ability to predict precipitation and atmospheric circulation, respectively. The results show that ICP can pick out the best and the poorest ensemble members effectively, which have a marked discrepancy in predicting the persistent heavy rainfall event. As for pre-dicting the location, duration and the movement speed of the large-scale weather systems, such as blocking high, subtropical high and the East Asian trough, good members make much more accurateness forecast than poor members. The same is true for predicting the evolution of mesoscale systems, such as shear line in low level and Southwest Vortex. There exist relative large deviations for the poor members in fore-casting the large scale circulation, mesoscale systems and the location of rain belt. Preliminary results show that the ICP for persistent heavy rainfall is reasonable and reliable.

persistent heavy rainfall (PHR)predictabilityindex of single variable (ISV)index of composite predictability (ICP)ensem-ble prediction forecasts (EPS)

吴志鹏、陈静、张涵斌、陈浩、夏宇

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成都信息工程学院大气科学学院，成都610225

中国气象局数值预报中心，北京100081

南京信息工程大学大气科学学院，南京210044

持续性强降水 可预报性 单一评估指数 综合评估指数 集合预报

国家重点基础研究发展计划973项目国家科技支撑计划中国气象局公益性行业科研专项国家自然科学基金

2012CB4172042009BAC51B00GY-HY20090600741075035

2014

10.3969/j.issn.1004-9045.2014.02.001

暴雨灾害
中国气象局武汉暴雨研究所

暴雨灾害

CSTPCD
影响因子：1.533
ISSN：1004-9045
年,卷(期)：2014.(2)
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