主办单位：中国气象局沈阳大气环境研究所
国际刊号：ISSN 1673-503X
国内刊号：CN 21-1531/P
气象与环境学报

气象与环境学报 ›› 2023, Vol. 39 ›› Issue (3): 40-46.doi: 10.3969/j.issn.1673-503X.2023.03.005

• 论文 • 上一篇    下一篇

基于邻域法的区域模式环渤海短时强降水预报评估

贾旭轩1,2,3(),张立鹏3,王赛頔4,周天娇5,梁军3,*()   

  1. 1. 中国气象局沈阳大气环境研究所, 辽宁沈阳 110166
    2. 东北冷涡研究重点开放实验室, 辽宁沈阳 110166
    3. 大连市气象台, 辽宁大连 116001
    4. 辽宁省气象服务中心, 辽宁沈阳 110166
    5. 大连市气象服务中心, 辽宁大连 116001
  • 收稿日期:2021-11-16 出版日期:2023-06-28 发布日期:2023-07-25
  • 通讯作者: 梁军 E-mail:jiaxxmail@126.com;qinldj@163.com
  • 作者简介:贾旭轩, 男, 1984年生, 高级工程师, 主要从事灾害性天气机理及相关研究, E-mail: jiaxxmail@126.com
  • 基金资助:
    环渤海区域科技创新基金(QYXM202011);环渤海区域科技创新基金(QYXM202108);中国气象局沈阳大气环境研究所和东北冷涡研究重点开放实验室联合开放基金(2021SYIAEKFMS01)

Prediction and evaluation of short-term heavy precipitation around the Bohai Sea by a regional model based on the neighborhood method

Xu-xuan JIA1,2,3(),Li-peng ZHANG3,Sai-di WANG4,Tian-jiao ZHOU5,Jun LIANG3,*()   

  1. 1. Institute of Atmospheric Environment, China Meteorological Administration, Shenyang 110166, China
    2. Key Opening Laboratory for Northeast China Cold Vortex Research, Shenyang 110166, China
    3. Dalian Meteorological Observatory, Dalian 116001, China
    4. Liaoning Meteorological Service Center, Shenyang 110166, China
    5. Dalian Meteorological Service Center, Dalian 116001, China
  • Received:2021-11-16 Online:2023-06-28 Published:2023-07-25
  • Contact: Jun LIANG E-mail:jiaxxmail@126.com;qinldj@163.com

RichHTML

8

PDF (PC)

150

摘要：

利用2020年5—9月Grapes_3km、华东、华北、东北中尺度区域模式降水预报资料和中国气象局陆面数据同化系统产品数据集1 h降水资料, 基于邻域法对副热带高压外围850 hPa切变线、东北冷涡、500 hPa高空槽、台风、台风外围500 hPa高空槽和850 hPa切变线5类影响系统下环渤海区域的短时强降水预报(≥20 mm·h-1)进行检验评估。结果表明: 5 km邻域时, 各区域模式在环渤海区域短时强降水预报的FSS和命中率都很低, 随着邻域增大, 从50 km邻域开始, 检验结果给出了当预报存在位移偏差时有价值的评分结果。第5类影响系统下的短时强降水, Grapes_3km和华东区域模式分数技巧评分(FSS)分别于250 km和300 km邻域达到了最低预报技巧, 其他区域模式各邻域均未达到最低预报技巧。其他影响系统下的短时强降水, 4种模式各邻域FSS均未达到最低预报技巧, 在各邻域华北区域模式对于第2、3、4类影响系统下的短时强降水预报FSS高于其他模式, Grapes_3km对于第1类影响系统下的短时强降水预报FSS高于其他模式。根据命中率和空报率的检验结果, Grapes_3km对于第1、3、5类影响系统下短时强降水预报, 华北区域模式对于第2、3、4类影响系统下短时强降水预报, 华东区域模式对于第5类影响系统下短时强降水预报效果优于其他模式。

关键词: 影响系统, 分数技巧评分, 命中率, 空报率

Abstract:

Using Grapes_3km, mesoscale regional model precipitation forecast data over East, North, and Northeast China and 1 h precipitation data set of Land surface Data assimilation System of China Meteorological Administration (CLDAS) from May to September of 2020, the short-term heavy precipitation forecast (≥20 mm·h-1) around the Bohai Sea under the influence system of 850 hPa shear line outside the subtropical high, Northeast Cold Vortex, 500 hPa upper trough, typhoon, 500 hPa upper trough outside typhoon and 850 hPa shear line was tested and evaluated based on the neighborhood method.The results show that the FSS (fractions skill score) and hit ratio of each regional model are very low in the forecast of short-term heavy precipitation around the Bohai Sea when the neighborhood is 5 km.With the increase of the neighborhood, the test results give the score results that are valuable when there is displacement deviation in the forecast starting from the 50 km neighborhood.Grapes_3km and East China regional model FSS receives the minimum forecast skills in the 250 km and 300 km neighborhood, respectively, for the short-time heavy precipitation under the Category 5 influence system, whereas the other regional models do not receive the minimum forecast skills in the neighborhood.For the short-time heavy precipitation under other affected systems, the FSS of the four models in each neighborhood does not receive the minimum prediction skill, and the FSS of the North China model for the type 2, 3, and 4 affected systems is higher than that of the other models.The FSS of Grapes_3km for the type 1 affected system is higher than that of the other models.According to the test results of hit and false alarm ratios, Grapes_3km, the North China model and the East China model have better prediction effects for short-term heavy precipitation under type 1, 3, and 5 influence systems, type 2, 3, and 4 influence systems, and type 5 influence systems, respectively.

Key words: Influence system, Fractions skill score, Probability of detection, False alarm ratio

中图分类号: