Estimating daytime surface air temperature using multi-source remote sensing and climate reanalysis data at glacierized basins: A case study at Langtang valley, Nepal

Estimate surface air temperature (Ta) accurately in fine scale is very necessary for hydrological simulation, especial in glacierized basins. The purpose of this paper is to present a framework to mapping the Ta using multi-source remote sensing data and reanalysis dataset. The main content includes two parts: (a) filling the gaps in remotely sensed land surface temperature (LST) using spatial-temporal Kriging method and (b) developing a semi-empirical method to relate Ta and LST that is applicable in glacierized basins. The framework is further tested in the Langtang valley, Nepal which is a glacierized basin in the central Hindu-Kush-Himalaya (HKH) region. The validation results show that the estimated Ta has generally good spatial and temporal variations. The RMSE of Ta at Langtang Kyangjin station is 9.1K and 7.7K at 10:30 and 13:30, respectly.

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