Land surface temperature and emissivity estimation based on the two-temperature method: sensitivity analysis using simulated MSG/SEVIRI data

Abstract

A feasibility study of land surface temperature (LST) and land surface emissivity (LSE) estimation is presented using METEOSAT Second Generation (MSG)/Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, based on the two-temperature method (TTM). The performance of TTM was assessed by taking into consideration the noise in SEVIRI channels IR 10.8 and IR 12.0 as well as the errors in the atmospheric profiles. Imposed errors due to uncertainties on atmospheric information were generated based on the background error covariance matrix used in the assimilation scheme of the European Centre for Medium-Range Weather Forecasts (ECMWF) Global Circulation Model. TTM has provided LST values with averaged error bias [root-mean square error (RMSE)] ranging from 0.0 to 0.5 K (from 0.8 to 2.5 K) for geographical–seasonal model atmospheres stored in MODTRAN4 with water vapor content varying between 0.85 and 4.11 g cm −2. Obtained results suggest that TTM may be used as a complementary method to split-window (SW) algorithms over areas where LSE is not well known a priori.