三种再分析资料的气温在东昆仑山北部的适用性评估OA

To evaluate the applicability of air temperature data from three reanalysis datasets(ERA5,JRA-55,and MERRA-2)in the northern part of the Eastern Kunlun Mountains and its different subregions,this study used daily mean temperature observations from 28 national meteorological stations in the northern part of the East Kunlun Mountains during 1980-2023.The air temperature data from the reanalysis datasets were corrected using a lapse-rate correction method.Four evaluation indicators,namely the correlation coefficient(CC),mean bias(MB),root mean square error(RMSE),and mean absolute error(MAE),together with the climatic tenden-cy rate,were used to assess the applicability of annual and seasonal air temperature from the three reanalysis da-tasets at regional and station scales.The results show that:(1)Bilinear interpolation outperformed nearest-neigh-bor interpolation.After lapse-rate correction,the mean absolute value of MB of the three reanalysis datasets de-creased by 0.92～1.81℃,and the RMSE decreased by 0.69～1.34℃.(2)After lapse-rate correction,all three reanalysis datasets reproduced the spatial distribution characteristics of mean air temperature in the study area,namely higher values in the east and lower values in the west,with the lowest values in the northeast,although overestimation occurred in some areas.(3)At the regional scale,ERA5 showed the best applicability.JRA-55 ranked second,while MERRA-2 showed the poorest applicability.Only the spring climatic tendency rate of ERA5 was higher than that of the observations;the remaining values were lower than the observed values.All three datasets showed a warming pattern characterized by stronger warming in summer and weaker warming in winter.(4)At the station scale,JRA-55 showed the best applicability.ERA5 ranked second,while MERRA-2 showed the poorest applicability.The annual and seasonal climatic tendency rates of the observations,ERA5,and JRA-55 were mostly concentrated within 0.30～0.60℃·(10a)-1,whereas those of MERRA-2 were mainly concentrated within 0.15～0.30℃·(10a)-1.Overall,the climatic tendency rates of the three reanalysis datasets were generally lower than those of the observations,and all exhibited a warming pattern of stronger warming in summer and weaker warming in winter.(5)The applicability of the three reanalysis datasets varied among differ-ent subregions.ERA5,JRA-55,and MERRA-2 performed best in the eastern agricultural region,the area around Qinghai Lake,and the Qaidam Basin,respectively.All three datasets captured the subregional warming pattern of stronger warming in summer and weaker warming in winter.The observations showed that the warm-ing trend was ranked as follows:eastern agricultural region,where strong warming occurred at Tongde and Da-tong and the annual and seasonal climatic tendency rates at Tongde were≥0.97℃·(10a)-1,followed by the Qa-idam Basin,where strong warming occurred at Mangya,and then the area around Qinghai Lake.ERA5 showed warming trends closer to the observations in the area around Qinghai Lake and the eastern agricultural region and thus performed the best,followed by JRA-55,while MERRA-2 showed the poorest applicability.(6)For the northern part of the Eastern Kunlun Mountains,ERA5 should be prioritized for regional climate analysis,where-as JRA-55 should be prioritized for refined studies at the station scale.