Air temperature estimation with MODIS data over the Northern Tibetan Plateau
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Time series of MODIS land surface temperature (T s) and normalized difference vegetation index (NDVI) products, combined with digital elevation model (DEM) and meteorological data from 2001 to 2012, were used to map the spatial distribution of monthly mean air temperature over the Northern Tibetan Plateau (NTP). A time series analysis and a regression analysis of monthly mean land surface temperature (T s) and air temperature (T a) were conducted using ordinary linear regression (OLR) and geographical weighted regression (GWR). The analyses showed that GWR, which considers MODIS T s, NDVI and elevation as independent variables, yielded much better results [R2 Adj > 0.79; root-mean-square error (RMSE) = 0.51°C–1.12°C] associated with estimating T a compared to those from OLR (R 2 Adj = 0.40−0.78; RMSE = 1.60°C–4.38°C). In addition, some characteristics of the spatial distribution of monthly T a and the difference between the surface and air temperature (T d) are as follows. According to the analysis of the 0°C and 10°C isothermals, T a values over the NTP at elevations of 4000–5000 m were greater than 10°C in the summer (from May to October), and T a values at an elevation of 3200 m dropped below 0°C in the winter (from November to April). T a exhibited an increasing trend from northwest to southeast. Except in the southeastern area of the NTP, T d values in other areas were all larger than 0°C in the winter.
Key wordsair temperature estimation MODIS land surface temperature geographical weighted regression Northern Tibetan Plateau
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This study was funded by the Chinese Academy of Science “Hundred Talents” program (Dr. Weiqiang MA), the National Natural Science Foundation of China (Grant Nos. 41375009, 91337212, 41275010 and 41522501 and 41661144043), Study on long term changes of surface heat source in northern Tibetan Plateau and its thermal effect on the plateau monsoon system (Dr. Zeyong HU; Grant No. 91537101), the China Meteorological Administration Special Fund for Scientific Research in the Public Interest (Grant No. GYHY201406001), and the EU-FP7 project “CORECLIMAX” (Grant No. 313085).
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