ECMWF地表太阳辐射数据在我国的误差及成因分析

利用2000-2009年中国气象局（CMA）地表太阳辐射台站资料,对欧洲中期天气预报中心（ECMWF）地表太阳下行短波辐射产品进行多时间尺度的计算与分析,检验ECMWF地表辐射产品对于中国地区太阳辐射特征的表现。本文通过聚类分析将中国地区分为8个区域,考虑到ECMWF大气因素对ECMWF地表辐射的影响和大气因子分布的空间异质性,引入地理探测器对ECMWF再分析辐射产品的时空误差进行定量分析,来判明影响ECMWF辐射精度的主要大气因子。结果表明：总体上看,ECMWF地表太阳辐射要高于地面观测数据,月均偏差为18.28W/m²;ECMWF地表太阳辐射表现出季节性差异,夏秋季节明显好于春冬季节,相对偏差较大的数据集中分布在12、1、2和3月,相对偏差较小的数据集中分布在6、7、8和9月;不同区域在冬季和夏季的主导大气影响因子不同,夏季中国西北（1区）、高原（3区）、西南（4区）和四川盆地（5区）地区主导影响因子都是气溶胶,东南（6区）地区的主导影响因子是地表反照率和气溶胶,中东部地区（7区）的主导影响因子是云覆盖率和气溶胶,但是因子解释较小,分别为0.0228和0.0202,东北地区（8区）4个因子均未通过显著性系数检验,因子对相对偏差的变化影响不显著;冬季中国西北（1区）、高原（3区）、中东（7区）、东北（8区）和四川盆地（5区）地区的主导影响因子都是云覆盖率,西南（5区）和东南（6区）地区的辐射主要受到气溶胶的影响。

Error Analysis of ECMWF Surface Solar Radiation Data in China

Comparison of surface radiation data of ECMWF (European Centre for Medium-Range Weather Forecasts) reanalysis data and data from station observation (China Meteorological Administration) is conducted at different time scales to check whether reanalysis data can reflect the characteristics of surface solar radiation over China. Based on the cluster analysis method, China is divided into 8 regions in order to study the regional differences of the surface radiation products of the ECMWF reanalysis data in China. Taking into account the influence of atmospheric factors on the earth's surface radiation and the spatial stratified heterogeneity of the atmospheric distribution, the geographical detector is used to find the causes of errors in different sites of reanalysis data. Overall, ECMWF is higher than the ground observation station data and the monthly deviation is 18.2835W/m². ECMWF shows seasonal difference, greater deviation in spring and winter, less deviation in summer and autumn. Large relative deviation of the data mainly distributed in December, January, February and March while minor relative deviation of the data mainly concentrated in July, June, August and September. The dominant atmospheric factors in different regions are different in winter and summer. In summer, from zone 1 to 5 the dominant factors are aerosols and the power of determinant is larger. The dominant factors of the zone 6 are albedo and aerosol. The dominant factors of the zone 7 are cloud cover and aerosol but the power of determinant is small, merely 0.0228 and 0.0202, respectively. Failing significance test indicates that the four factors had no significant effect on the relative deviation in the zone 8. In winter, the dominant factors of zone 4, 6, 8 and zone 1, 3, 5, 7 are aerosol and cloud coverage, respectively.