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Yan, H, Zhang, JH, Hou, YY, He, YB (2009). Estimation of air temperature from MODIS data in east China. INTERNATIONAL JOURNAL OF REMOTE SENSING, 30(23), 6261-6275.

Air temperature, T-a, with high spatial and temporal resolution is desired for global change, agricultural disaster, land surface studies, and modelling applications. A statistical algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS) data is developed for daytime T-a retrievals over east China at a resolution of 0.05 degrees x 0.05 degrees. The approach first applies a statistical regression of the first guess, i.e. the preliminary estimate, of T-a to MODIS 11 mu m and 12 mu m brightness temperature (T-11 mu m and T-12 mu m) and site data (longitude, latitude and altitude) for east China. Then the first guess of T-a is further corrected with a series of bias equations for different latitude zones in east China. Further quantitative validation with measured T-a using 335 synoptic weather stations for the whole of 2006 indicates that the algorithm performs well with overall statistics of R = 0.96, RMSE = 3.23 degrees C, and bias = -0.09 degrees C. 75% of the estimated T-a is within 3 degrees C of the actual T-a and 92% of the estimated T-a is within 5 degrees C of the actual T-a. This bias correction algorithm can be applied to other geostationary and sun-synchronous satellite instruments for T-a retrieval.



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