摘要
利用中国大陆区域2231个国家气象观测站的月平均气温和降水资料为参照,以欧洲中期天气预报中心的再分析产品ERA5和美国再分析产品CFSR作为对比评估对象,应用三角剖分线性插值方法将格点数据与站点数据进行插值,分别计算了偏差、标准差比值、相关系数、均方根误差和模式技巧,从月平均气温和降水在空间分布及时间变化方面对比评估了中国第一代陆面再分析(CRA40/Land)产品在中国大陆的适用性。评估结果表明:CRA40、ERA5和CFSR资料都能反映出中国大陆区域月平均气温和降水的时空分布特征,同时都表现为东部地区优于西部地区,冬季(1月)优于夏季(7月),三种再分析月平均气温资料的误差基本控制在2℃以内,CRA40和ERA5略优于CFSR。而对于月平均降水,3套再分析资料的误差差异较大,在三套再分析资料中CRA40的误差最小,在中国的适用性最高。
The applicability of first-generation of Chinese land surface reanalysis dataset(CRA40/Land)has been evaluated with the observations from 2231 national meteorological stations and further compared with the ERA5 and CFSR datasets in terms of the spatial and temporal variations of monthly air temperature and precipitation.Triangulation linear interpolation is used to interpolate grid data into stations,and station data into grid.The China mainland is divided into four regions according to the stations distribution and topographic features.The bias,standard deviation ratio,root mean square error(RMSE),correlation coefficient and model skill of the 3 reanalysis datasets in four regions are computed to compare the accuracy and evaluate the application.The comparative results suggest that the CRA40,ERA5 and CFSR datasets can reproduce similar spatio-temporal distribution patterns of the monthly air temperature and precipitation with the observations in Mainland of China.In particular,they all show much better performance in the eastern China than in western China and in winter than in summer.For the monthly air temperature,the mean errors of the 3 reanalysis datasets are generally within 2℃,with slightly better performance for the CRA40 and ERA5 datasets.For the monthly precipitation,the errors of the 3 reanalysis datasets show large differences,the CRA40 performs the best and shows the highest applicability over Mainland of China among the 3 datasets.
作者
王彩霞
黄安宁
郑鹏
刘凯
侯敏
WANG Caixia;HUANG Anning;ZHENG Peng;LIU Kai;HOU Min(Tianjin Binhai New Area Bureau of Meteorology,Tianjin 300457,China;School of Atmospheric Sciences,Nanjing University,Nanjing 210023,Jiangsu,China;College of Oceanic and Atmospheric Sience,Ocean University of China,Qingdao 266100,Shandong,China;Shandong Shouxin Project Management Co.Ltd.,Dezhou 253000,Shandong,China)
出处
《高原气象》
CSCD
北大核心
2022年第5期1325-1334,共10页
Plateau Meteorology
基金
国家自然科学基金项目(42006154,41975081)
中科院“西部之光”项目(E129030101,Y929641001)
天津市气象局一般项目(202211ybxm05)。
