Estimation And Distribution Of Near-surface Meteorological Elements Over Complex Terrains

Meteorological elements,such as near-surface air temperature(Ta),vapour pressure deficit(VPD),and atmospheric pressure(P),are important indicators for measuring climate change and the hydrological cycle and are also the basis for various meteorological services.However,the distribution of meteorological stations in some areas is sparse and uneven due to factors such as the economic development level and population distribution characteristics.The meteorological data of existing stations is insufficient for application to the agricultural production and animal husbandry sectors,and in supporting the research of local epidemic disease dissemination warnings,climate change,forest fire detection,and so on.Moreover,the existing near-surface meteorological element estimation methods have certain deficiencies in the application of complex terrain and sparse areas,such as the Tibetan Areas of West Sichuan Province and the Northwestern District of China.For example,the spatial interpolation methods are limited by the number and distribution of stations,and the accuracy is low when the station is sparse and the distribution uniformity is poor;the methods of estimating nearsurface meteorological elements based on remote sensing data is limited by the current remote sensing observation technology,and the accuracy is also low when applied in remote sensing blind areas or complex terrain areas.Due to the mismatch between"demand" and "supply",it is necessary to explore suitable methods for accurately obtaining meteorological data in areas with complex terrains and sparse stations.Using the Tibetan Areas of West Sichuan Province and the Northwestern District of China as an example,this study examined the estimation methods for Ta,VPD,and P and their distribution characteristics in areas with complex terrains and sparse stations.An improved satellite-based approach,combining an artificial neural network and inverse distance weighting(ANN-IDW),is proposed for estimating Ta and VPD with highaccuracy under all weather conditions from Moderate Resolution Imaging Spectroradiometer(MODIS)data.The data of 41 meteorological stations in Tibetan Areas of West Sichuan Province and its adjacent areas and the data of 135 meteorological stations in Northwestern District of China were used for the training and validation of the ANN-IDW.For Ta and VPD,the mean absolute errors(MAEs)of the ANN-IDW applied in Tibetan Areas of West Sichuan Province are 1.45? to 2.15? and 0.54 hPa to 0.87 hPa respectively;the MAE in Northwestern District of China are 1.81? to 2.65? and 1.19 hPa to 1.50 hPa respectively.Also,the detailed features of the distribution of the estimated Ta and VPD are prominent and closely related to the terrain.The accuracy of the methods was also verified indirectly.In addition to the Ta and VPD,the improved method based on the existing method was applied for estimating P.The results confirm that:1)the ANN-IDW is suitable for estimating Ta and VPD in areas with complex terrain and sparse stations under all weather conditions;2)the improved method is more suitable for estimating P at high-elevation.Moreover,the distribution characteristics of meteorological elements were also analysed in the Tibetan Areas of West Sichuan Province and the Northwestern District of China.These elements guide agricultural production and animal husbandry and have a high application value.The results further show that topography and elevation range are important factors affecting the distribution of meteorological elements of region.However,there are some differences in the intensity of their effects in different regions and seasons.