CFSv2模式产品在汛期海南热带气旋频数预测模型中的应用  

Application of CFSv2 products in tropical cyclone frequency prediction model in Hainan during flood season

作　　者：邢彩盈[1,2] 吴慧[1,2] 胡德强[1,2] 吴胜安[1,2] 

机构地区：[1]海南省气候中心,海口570203 [2]海南省南海气象防灾减灾重点实验室,海口570203

出　　处：《气象科学》2017年第5期666-672,共7页Journal of the Meteorological Sciences

基　　金：中国气象局气象关键技术集成与应用项目(CMAGJ2013M39);海南省气象局科研项目(HNQXZD201402);海南省气象局面上项目(HNQXMS201403)

摘　　要：利用1982—2014年汛期影响海南的热带气旋频数、NCEP/NCAR逐月再分析资料和CFSv2模式历史回报数据,分析了热带气旋频数特征及同期环流特征,并利用逐步回归构建基于模式有效预测信息的热带气旋频数预测模型。结果表明:汛期影响海南热带气旋频数的异常与同期大尺度环流变化密切相关,且CFSv2模式对其环流影响关键区具有较好的预测技巧,包括南海到热带太平洋的海平面气压、500 h Pa位势高度场、低层风及热带太平洋纬向风切变。据此,利用逐步回归构建热带气旋频数预测模型,其26 a交叉检验中实况与预测相关为0.88,距平同号率达88%;6 a预测试验仅2 a预测与观测反号,可见模型具有良好的稳定性和预测技巧,可为汛期热带气旋频数预测提供依据。Based on the Tropical Cyclone （TC） frequency data during flood seasons in Hainan, NCEP/NCAR monthly reanalysis data and CFSv2 model historical return data, the characteristics of TC frequency and the corresponding atmospheric circulation were analyzed, moreover, the TC frequency pre- diction model was built based on the effective information of CFSv2 by using stepwise regression. Results show that TC frequency anomaly during flood seasons in Hainan is closely related to the large scale circu- lation during the corresponding period, and CFSv2 model has a great prediction skill on the key influence areas of circulation fields, including sea level pressure, geopotential height field at 500 hPa, low level wind field from the South China Sea to tropical Pacific, and zonal wind shear in the tropical Pacific. On these grounds, the correlation of TC frequency prediction model between observation and prediction of 26 years cross-validation is 0. 88, and the rate of same anomalies between them reaches 88% ; there are only two years that the predicted anomaly is contrary to the observed one in six years predictive testing. It can see that the prediction model has a good stability and prediction skill, which can provide effective basis for the TC frequency prediction of Hainan during flood seasons.

关 键 词：汛期 热带气旋频数 CFSv2模式 预测模型 海南省 

分 类 号：P466[天文地球—大气科学及气象学]