中国区域ERA5和MERRA-2再分析资料计算T_(m)的精度分析

Accuracy Analysis of T_(m) Calculated by ERA5 and MERRA-2 Reanalysis Data over China

以中国区域89个探空站2017年资料为参考值,对ERA5和MERRA-2再分析资料积分计算的T_(m)的精度进行评估,并分析2种资料计算的T_(m)的bias和RMSE的时空变化特性。结果表明:1)以探空站资料为参考值,ERA5和MERRA-2再分析资料计算的T_(m)的年均bias分别为0.41K和0.10K,年均RMSE分别为1.26K和1.34K。2)2种资料计算的T_(m)的bias和RMSE具有相似的时空变化特性,时间上总体表现为夏季精度高、冬季精度稍低,但ERA5再分析资料计算的T_(m)的bias在全年均表现为正值,而MERRA-2再分析资料计算的T_(m)的bias在夏季表现为负值,其余时间表现为正值;在空间上,2种资料计算的T_(m)的bias和RMSE在高程上无明显变化特性,但在纬度上RMSE均表现出随纬度增加而逐渐变大的趋势,总体保持在2.5K以内。

We evaluate the performance of T_(m) derived from ERA5 and MERRA-2 reanalysis data over China using 89 radiosonde stations data in 2017,and analyze the temporal and spatial variation characteristics of bias and RMSE of T_(m) calculated from ERA5 and MERRA-2 reanalysis data.The results show that:1)The T_(m) calculated by ERA5 and MERRA-2 reanalysis data have the annual bias of 0.41 K and 0.10 K,and annual RMSE of 1.26 K and 1.34 K when compared with T_(m) derived from radiosonde stations,respectively.2)The bias and RMSE of T_(m) calculated from ERA5 and MERRA-2 reanalysis data show similar temporal and spatial variation characteristics.For the characteristics of temporal variation,the bias and RMSE of T_(m) calculated from two reanalysis data generally show high precision in summer but low precision in winter.Moreover,T_(m) calculated from ERA5 reanalysis data shows positive bias in the whole year,while the MERRA-2 reanalysis data shows negative bias in summer and positive bias in other time.For the characteristics of spatial variation,there is no obvious variation characteristics in altitude.However,the RMSE shows an increasing trend with the increase of latitude,and generally remain in 2.5 K.