摘要
利用2007年6月8日—8月31日东亚地区TIGGE集合预报资料中欧洲中期天气预报中心（European Centre for Medium-range Weather Forecasts,ECMWF）和英国气象局（United Kingdom Met Office,UKMO）两个中心的地面2 m气温资料进行集合成员优选研究。结果表明,对于24-96 h预报,集合成员优选方法能够较好地选出预报技巧较高和预报技巧较低的集合成员。个例分析表明,在极端天气出现的地区,优选集合平均的预报优势较为明显。对比ECMWF和UKMO的集合成员优选结果发现,ECMWF的预报效果优于UKMO的预报效果。
This study uses a ranking method to select some good and bad ensemble members from ensemble forecasts of the 2 m temperature above the ground in East Asia provided by European Centre for Medium-range Weather Forecasts（ ECMWF） and United Kingdom Met Office（ UKMO）. The ensemble forecast products are taken from TIGGE archive for the period from June 8,2007 to August 31,2007.The results showthat the optimal selection method may reasonably select the ensemble members with higher and lower forecast skills for 24—96 h forecasts. Case study shows that the ensemble mean forecast of the optimally selected ensemble members may predict the extreme temperature quite well,and it performs better than the ensemble mean of all ensemble members. The forecast skill of the ECMWF ensemble forecast is higher than that of UKMO forecast in terms of the root-mean-square errors of the surface air temperature forecasts.
出处
《大气科学学报》
CSCD
北大核心
2015年第3期414-420,共7页
Transactions of Atmospheric Sciences
基金
公益性行业(气象)科研专项(GYHY200906009)
江苏高校优势学科建设工程资助项目(PAPD)
关键词
TIGGE资料
集合平均
最优集合成员
均方根误差
TIGGE dataset
ensemble mean
optimally selected ensemble members
root-meansquare error
