Development of Himawari-8/Advanced Himawari Imager (AHI) Land Surface Temperature Retrieval Algorithm

• Published in: Remote sensing (Basel, Switzerland) Vol. 10; no. 12; p. 2013
• Main Authors: Choi, Youn-Young, Suh, Myoung-Seok
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2018
• Subjects: Air temperature; Algorithms; Atmosphere; Bias; Brightness temperature; Cold season; Computer simulation; Correlation coefficient; Correlation coefficients; Diurnal; Diurnal variations; Emissivity; Himawari-8; Land surface temperature; Lapse rate; Meteorological satellites; MODIS; Radiance; Radiative transfer; Radiometers; Remote sensing; Response functions; Retrieval; Root-mean-square errors; Seasons; Sensors; Spectra; Spectral emissivity; Spectral sensitivity; Spectroradiometers; split-window method; Studies; Synchronous satellites; Temperature; Temperature effects; Temperature gradients; Time of use; Vegetation; Water vapor; East Asia; Asia; United States > US; China; Japan
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs10122013

We developed land surface temperature (LST) retrieval algorithms based on the time of day and water vapor content using the Himawari-8/AHI (Advanced Himawari Imager) data, which is the Japanese next generation geostationary satellite. To develop the LST retrieval algorithms, we simulated the spectral radiance using the radiative transfer model (MODTRAN4) by applying the atmospheric profiles (SeeBor), diurnal variation of LST and air temperature, spectral emissivity of land surface, satellite viewing angle, and spectral response function of Himawari-8/AHI. To retrieve the LST from Himawari-8 data, a linear type of split-window method was used in this study. The Himawari-8 LST algorithms showed a high correlation coefficient (0.996), and a small bias (0.002 K) and root mean square error (RMSE) (1.083 K) between prescribed LSTs and estimated LSTs. However, the accuracy of LST algorithms showed a slightly large RMSE when the lapse rate was larger than 10 K, and the brightness temperature difference was greater than 6 K. The cross-validation of Himawari-8/AHI LST using the MODIS (Terra and Aqua Moderate Resolution Imaging Spectroradiometer) LST showed that annual mean correlation coefficient, bias, and RMSE were 0.94, +0.45 K, and 1.93 K, respectively. The performances of LST algorithms were slightly dependent on the season and time of day, generally better during the night (warm season) than during the day (cold season).