The correlated k-distribution (CKD) is a fast radiative transfer model and is often used in atmospheric absorption simulation. In the paper, we apply two automatic CKD methods to satellite brightness… Click to show full abstract
The correlated k-distribution (CKD) is a fast radiative transfer model and is often used in atmospheric absorption simulation. In the paper, we apply two automatic CKD methods to satellite brightness temperature simulations from the Fengyun 4A Advanced Geostationary Radiation Imager (AGRI) in infrared channels, namely, the finding point method (FPM) and the re-optimized method (ROM). In the calculation, we used Radiative Transfer for the Television Observation Satellite Operational Vertical Sounder (RTTOV) as the comparison, and we use line-by-line (LBL) integration as the reference. Compared with LBL in the brightness temperature simulation of real profiles, the errors of FPM in 7.1 µm and 13.5 µm channels are 0.22 K, -0.13K for mean error and 0.3128 K, 0.2184 K for root mean square error (RMSE), respectively, which are larger than that of RTTOV, with 0.16 K, 0.02 K, 0.2144 K, and 0.1226 K, respectively. In the other channels, the results show that of ROM has the highest accuracy and RTTOV has the lowest accuracy. In general, FPM and ROM can achieve very good accuracy in satellite infrared remote sensing.
               
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