Spatial Downscaling and Simulation of TRMM Data at High Altitudes — A Case Study of Lhasa River

Abstract

As measured precipitation data are often lacking at high altitudes,remote sensing data by satellites could compensate for the shortage of traditional observation.This paper takes the Lhasa River basin as the study area and makes an in-depth analysis of the relationship between precipitation,vegetation,and temperature in this basin.On this basis,the multiple linear regression,residual analysis,and inverse distance weighting (IDW) of spatial interpolation are employed to spatially downscale the TRMM 3B43V7 data that overestimates the precipitation in the study area by about 29% and has a spatial resolution of 0.25°×0.25° to 0.05°×0.05°.Given the measured data of stations,the downscaled data is further revised.The accuracy of the final high-quality precipitation dataset is greatly improved in most regions of the Lhasa River basin,and the dataset can provide basic statistical support for research on hydrology and water resources at high altitudes.

Keywords

• high-altitude areas
• TRMM
• NDVI
• temperature
• Lhasa River