Improvements of COMS Land Surface Temperature Retrieval Algorithm by considering diurnal variations of boundary layer temperature

Abstract:

National Meteorological Satellite Centre in Republic of Korea retrieves operationally land surface temperature (LST) by applying the split-window LST algorithm (CSW_v1.0) from Communication, Ocean, and Meteorological Satellite (COMS) data. In order to improve COMS LST accuracy, Cho et al. (2015) developed six types of LST retrieval equations (CSW_v2.0) by considering temperature lapse rate and water vapor/aerosol effect. Similar to CSW_v1.0, the LST retrieved by CSW_v2.0 had a correlation coefficient of 0.99 with the prescribed LST and the root mean square error (RMSE) improved from 1.41 K to 1.39 K. However, CSW_v2.0 showed relatively poor performance, in particular, the temperature lapse rate is certainly large (superadiabatic cases during daytime or strong inversion cases during early morning). In this study, we upgraded the CSW_v2.0 by considering diurnal variations of boundary layer temperature to reduce the relatively large errors under the large lapse rate conditions. To achieve the goals, the diurnal variations of air temperature along with the land surface temperature are included during radiative transfer simulations for the generation of the pseudo-match-up database. The preliminary analysis results showed that RMSE and bias are reduced from 1.39K to 1.14K and from -0.03K to -0.01K. In this presentation, we will show the detailed results of LST retrieval using new algorithms according to the viewing geometry, temperature lapse rate condition, and water vapour amount along with the intercomparison results with MODIS LST data.