CLDAS温湿风产品在乌昌地区的适用性评估OA

This study evaluates the performance of 5-km hourly fused analysis products from the China Meteorological Administration Land Data Assimilation System(CLDAS)against ground meteorological station observations in the Urumqi-Changji Region from January to December 2023.Using bilinear interpolation for spatial matching,key statistical metrics,including the Correlation Coefficient(COR),Mean Error(ME),Mean Absolute Error(MAE),Mean Relative Error(MRE),and Root Mean Square Error(RMSE),were calculated.The spatial heterogeneity of errors in temperature,relative humidity,and wind speed products was further analyzed using Moran's I index and local indicators of spatial association(LISA)cluster analysis.The main findings are as follows:(1)Diurnal variations of CLDAS temperature,relative humidity,and wind speed exhibit high consistency with station observations,indicating strong capability in capturing spatiotemporal patterns under synoptic-scale weather conditions.(2)On an hourly scale,temperature(COR>0.95)and relative humidity(COR>0.88)show significant correlations with observations,whereas wind speed shows weaker correlations(COR=0.65-0.83),particularly in southern mountainous areas where terrain-induced parameterization limitations result in large errors(RMSE≥1.56 m/s).(3)Temperature products demonstrate reliability over plains(MAE≤0.76℃),while higher independent validation errors(ME=0.53-0.67℃)suggest insufficient adaptability to local microclimates.Relative humidity products systematically underestimate values in oasis irrigation zones(ME=-0.83%to-1.24%),likely due to insufficient evapotranspiration coupling.(4)Spatially,temperature errors are minimal in the Junggar Basin,relative humidity errors are prominent in the southwestern mountainous and oasis areas,and wind speed errors rise significantly in urban and complex terrain regions.CLDAS products can effectively support macroscale meteorological analysis in the Urumqi-Changji Region.