DEVELOPMENT AND VALIDATION OF LAND SURFACE TEMPERATURE RETRIEVAL ALGORITHM FROM MTSAT-1R DATA

Land surface Temperature (LST) is a very useful surface parameter for the wide range of applications, such as agriculture, numerical and climate modelling community. Whereas operational observation of LST is far from the needs of application community in the spatial Itemporal resolution and accuracy. So, we developed split-window type LST retrieval algorithm to estimate the LST from MTSAT-IR data. The coefficients of split-window algorithm were obtained by means of a statistical regression analysis from the radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, satellite zenith angle and lapse rate conditions including the surface inversions. The sensitivity analysis showed that the LST algorithm reproduces the LST with a reasonable quality. However, the LST algorithm overestimates and underestimates for the strong surface inversion and superadiabatic conditions especially for the warm temperature, respectively. And the performance of LST algorithms is superior when satellite zenith angle is small. The accuracy of the retrieved LST has been evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The validation results showed that the correlation coefficients and RMSE are about 0.83${\sim}$0.98 and 1.38${\sim}$4.06, respectively. And the quality of LST is significantly better during night and winter time than during day and summer. The validation results showed that the LST retrieval algorithm could be used for the operational retrieval of LST from MTSAT-IR and COMS(Communication, Ocean and Meteorological Satellite) data with some modifications.