Hong, KO, Suh, MS, Kang, JH (2009). Development of a Land Surface Temperature-Retrieval Algorithm from MTSAT-1R Data. ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES, 45(4), 411-421.
Land surface temperature (LST) is a useful surface parameter for a wide range of applications, such as agriculture and the numerical and climate-modeling community. As a result, operational observations of LST on various scales are gaining increased scientific interest. In this study, we developed a split window-type LST retrieval algorithm to estimate the LST from MTSAT-1R data. The coefficients of the split-window algorithm were obtained by means of a statistical regression analysis using a synthetic match-up database. The database was made through radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, spectral emissivity, satellite zenith angle (SZA), and various lapse-rate conditions, including surface inversions. The sensitivity analysis showed that the LST algorithm reproduces LST with a reasonable quality. However, the algorithm has a tendency to overestimate and underestimate for surface inversion and superadiabatic conditions, respectively, especially for warm temperatures, and its performance is superior when the SZA is small and the lapse rate is neutral. Validation results using Moderate-Resolution Imaging Spectroradiometer (MODIS) LST data showed that the correlation coefficients and RMSE are about 0.83 similar to 0.99 and 1.09 similar to 4.06 K, respectively. The quality of retrieved LST is significantly better at nighttime than at the daytime and in vegetated areas rather than barren areas. The validation results showed that the LST retrieval algorithm developed in this study could be used for operational retrieval of LST from data compiled by MTSAT-1R and Korea's Communication, Ocean and Meteorological Satellite (COMS), with some modifications.