摘要
利用中国气象局模式格点化预报3 h降水数据以及山东省的灾害天气短时临近预报预警业务系统(Severe weather auto-matic nowcast system,简称SWAN)提供的降水估计产品,基于动态融合算法改进权重分配方式,对山东半岛2016—2018年9个降水实例20个时刻点的预报结果进行融合,结果表明:融合后的结果可达到弥补雷达外推漏报、减小模式误报,调整模式极值位置,提高SWAN极值强度的效果;定量评分表明:融合结果在偏差评分和TS评分上总体更优。
Based on the 3-hour model gridded precipitation data from China Meteorological Administration and the precipitation estimation products provided by the severe weather automatic nowcast system(SWAN)of Shandong Province,the weight allocation method is improved based on dynamic fusion algorithm.The prediction results of 20 time-points of 9 precipitation cases in Shandong Peninsula in 2016-2018 are fused.The results show that the blending results can compensate for the miss alarm of radar extrapolation,the reducing of the false alarm of the model,adjusting the extreme position of the model and improving the extreme intensity of the radar extrapolation results.Quantitative scoring analysis showed that the blending results were better in bias score and TS score.
作者
丁锋
陆雪
刘子洲
杨凡
欧衍达
任兆鹏
DING Feng;LU Xue;LIU Zi-zhou;YANG Fan;OU Yan-da;REN Zhao-peng(Qingdao Engineering Technology Research Center for Meteorological Disaster Prevention,Qingdao Meteorological Bureau,Qingdao 266003,China;College of Oceanic and Atmospheric Sciences,Ocean University of China,Qingdao 266100,China)
出处
《海洋湖沼通报》
CSCD
北大核心
2021年第4期68-74,共7页
Transactions of Oceanology and Limnology
基金
中国气象局核心业务发展专项(CMAHX20160209)
山东省气象局预报员专项项目(SDYBY2017-05)
青岛市气象局青年专项(2021qdqxq03)。