Surface-latent heat(LE)and sensible heat(SH)fluxes play a pivotal role in governing hydrological,biological,geochemical,and ecological processes on the land surface in the Tibetan Plateau.However,to accurately assess ...Surface-latent heat(LE)and sensible heat(SH)fluxes play a pivotal role in governing hydrological,biological,geochemical,and ecological processes on the land surface in the Tibetan Plateau.However,to accurately assess and understand the spatial distribution of LE and SH fluxes across different underlying surfaces,it is crucial to verify the validity and reliability of ERA-5,GLDAS,and MODIS data against ground measurements obtained from the Flux Net micrometeorological tower network.This study analyzed the spatial patterns of LE and SH over the Tibetan Plateau using data from ERA-5,GLDAS,and MODIS.The results were compared with ground measurements from Flux Net tower observations on different underlying surfaces,and five statistical parameters(Pearson's r,LR slope,RMSE,MBE,and MAE)were used to validate the data.The results showed that:(1)MODIS LE data and ERA-5 SH data exhibited the closest agreement with ground observations,as indicated by their lowest root mean square error and mean bias area values.(2)The accuracy of ERA-5 SH was the highest in meadows and steppes,while GLDAS SH performed optimally in shrublands.Notably,MODIS LE consistently outperformed the other datasets across all vegetation types.(3)The spatial distribution of LE and SH displayed considerable heterogeneity,contingent upon the specific data sources and underlying surfaces.Notably,there was a contrasting trend between GLDAS and ERA-5,as well as MODIS,in terms of SH distribution in the shrubland.In shrublands and meadows,MODIS SH and LE exhibited more pronounced changes than ERA-5 and GLDAS.Additionally,ERA-5 SH demonstrated the opposite variation in meadow and steppe regions compared to GLDAS and MODIS.展开更多
地球重力场的变化是导致陆地水储量变化的重要因素之一,利用GRACE(Gravity Recovery and Climate Experiment)重力场恢复与气候实验重力卫星数据,结合GLDAS(Global Land Data Assimilation Systems)全球陆面数据同化系统和实测地下水位...地球重力场的变化是导致陆地水储量变化的重要因素之一,利用GRACE(Gravity Recovery and Climate Experiment)重力场恢复与气候实验重力卫星数据,结合GLDAS(Global Land Data Assimilation Systems)全球陆面数据同化系统和实测地下水位数据,反演和田地区克里雅河流域11年间四季和田地区的陆地水储量动态变化,模拟计算地下水等效水高变化趋势,构建了地下水水位估算模型。研究结果表明:和田地区春、夏两季的陆地水储量呈现出增加趋势,而秋、冬两季出现亏损状态;GRACE地球重力卫星所反演的陆地水储量比GLDAS同化系统所模拟的水资源变化更为剧烈,但2类数据的动态变化拟合度很高;GLDAS水资源等效水高二阶微分、GLDAS水资源变化倒数一阶微分、GRACE陆地水储量变化倒数变化、地下水储量变化一阶微分的敏感程度最高,构建的多元逐步回归模型明显优于线性函数,且水位深度越浅,该估算模型的适用性越高。展开更多
基金funded by the West Light Scholar of the Chinese Academy of Sciences(xbzg-zdsys-202202)the Natural Science Foundation of Henan(Grant No.232300420165)Integrated Scientific Investigation of the North-South Transitional Zone of China(2017FY100900)。
文摘Surface-latent heat(LE)and sensible heat(SH)fluxes play a pivotal role in governing hydrological,biological,geochemical,and ecological processes on the land surface in the Tibetan Plateau.However,to accurately assess and understand the spatial distribution of LE and SH fluxes across different underlying surfaces,it is crucial to verify the validity and reliability of ERA-5,GLDAS,and MODIS data against ground measurements obtained from the Flux Net micrometeorological tower network.This study analyzed the spatial patterns of LE and SH over the Tibetan Plateau using data from ERA-5,GLDAS,and MODIS.The results were compared with ground measurements from Flux Net tower observations on different underlying surfaces,and five statistical parameters(Pearson's r,LR slope,RMSE,MBE,and MAE)were used to validate the data.The results showed that:(1)MODIS LE data and ERA-5 SH data exhibited the closest agreement with ground observations,as indicated by their lowest root mean square error and mean bias area values.(2)The accuracy of ERA-5 SH was the highest in meadows and steppes,while GLDAS SH performed optimally in shrublands.Notably,MODIS LE consistently outperformed the other datasets across all vegetation types.(3)The spatial distribution of LE and SH displayed considerable heterogeneity,contingent upon the specific data sources and underlying surfaces.Notably,there was a contrasting trend between GLDAS and ERA-5,as well as MODIS,in terms of SH distribution in the shrubland.In shrublands and meadows,MODIS SH and LE exhibited more pronounced changes than ERA-5 and GLDAS.Additionally,ERA-5 SH demonstrated the opposite variation in meadow and steppe regions compared to GLDAS and MODIS.
文摘地球重力场的变化是导致陆地水储量变化的重要因素之一,利用GRACE(Gravity Recovery and Climate Experiment)重力场恢复与气候实验重力卫星数据,结合GLDAS(Global Land Data Assimilation Systems)全球陆面数据同化系统和实测地下水位数据,反演和田地区克里雅河流域11年间四季和田地区的陆地水储量动态变化,模拟计算地下水等效水高变化趋势,构建了地下水水位估算模型。研究结果表明:和田地区春、夏两季的陆地水储量呈现出增加趋势,而秋、冬两季出现亏损状态;GRACE地球重力卫星所反演的陆地水储量比GLDAS同化系统所模拟的水资源变化更为剧烈,但2类数据的动态变化拟合度很高;GLDAS水资源等效水高二阶微分、GLDAS水资源变化倒数一阶微分、GRACE陆地水储量变化倒数变化、地下水储量变化一阶微分的敏感程度最高,构建的多元逐步回归模型明显优于线性函数,且水位深度越浅,该估算模型的适用性越高。
