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The selection of atmospheric sample profiles is one of the key factors affecting the accuracy of the fast simulation of satellite channels, but the mechanism of the influence has not been conclusively established. In this paper, the mechanism of atmospheric sample profile selection and its contribution in the forward modeling are discussed through the analysis of the role of transmittance predictors in RTTOV model. The CO2 absorption channel at 15 μm in the infrared band of FY-3C IRAS (InfraRed Atmospheric Sounder) is used as the study object, and the IRAS laminar channel transmittance factor is established based on the TIGR43 profile database. The comparison tests between the profile temperature anomaly and simulation accuracy in the cold and warm scenarios show that the root mean square error (RMSE) of the simulation for the IRAS temperature detection channel is 0.2 K when all the profiles are involved in the regression calculation, compared with the simulation results of LBL. Within the detection height range of the selected CO2 detection channels, there is a strong linear correlation between the profile temperature anomaly and the simulation accuracy in the warm scenario due to the higher order residual term in the Taylor expansion, and more significant accuracy improvement can be obtained if the profile with larger temperature anomaly is removed from the forward modeling.
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