Land Surface Temperature Derived from the MSG-SEVIRI Data

Computer Science – Performance

Scientific paper

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Scientific paper

We have developed a physical-based split-window algorithm for retrieving the land surface temperature (LST) from SEVIRI/MSG1 (Spinning Enhanced Visible and Infrared Imager/ Meteosat Second Generation1) data in two thermal infrared bands (IR 10.8 and IR 12.0). The proposed algorithm takes into account the SEVIRI angular dependence. MODTRAN3 code has been used to derive synthetic data which have allowed to obtain the numerical values of the split-window algorithm from a statistical regression method. The new LST algorithm has been tested with simulated SEVIRI/MSG1 data over a wide range of atmospheric and surface conditions. Comprehensive sensitivity and error analyses have been undertaken to evaluate the performance of the proposed algorithm and its dependence on surface properties, atmospheric conditions and on the noise-equivalent temperature difference. The results show that the algorithm is capable of producing LST with a standard deviation lower than 1.5K for viewing zenith angles lower than 50 degrees.

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