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Simulation reveals that aerosol effects reduce observation-minus-background errors in FY‐4B GIIRS measurements, indicating improved temperature retrieval accuracy.
In the past, impacts of aerosol scattering and absorption were often neglected in simulating the hyperspectral infrared sounder (HIS) measurements and can lead to larger observation‐minus‐background (OMB) errors in satellite data assimilation. To quantify the aerosol effects on OMB, we utilized the Modern‐Era Retrospective Analysis for Research and Applications, Version 2 (MERRA‐2) data to calculate the mass densities of different aerosol types (dust, organics, sulfates, and carbonates). These parameters are then incorporated into the advanced radiative transfer modeling system (ARMS) to simulate the brightness temperatures (BT) and Jacobians for the longwave channels of the FengYun‐4B (FY‐4B)/GIIRS. For a sandstorm event on 9 April 2023, simulation results indicate a positive correlation between OMB and aerosol optical parameters (e.g., aerosol mass density, particle size, and aerosol optical depth). The inclusion of aerosols generally results in smaller OMBs. In particular, the bias in GIIRS is reduced by 1.11 K when the dust aerosols are included. In general, both JT and JQ are sensitive to the changes in dust aerosol. Simulated BT sensitivity is most responsive to the temperature of aerosol and particulate layers. Moreover, accounting for the effects of dust aerosols in the one‐dimensional variational retrieval (1D‐VAR) system significantly enhanced the accuracy of temperature profile retrievals in dust‐affected regions. Compared to retrievals that did not consider aerosol effects and the GIIRS Level‐2 product, the temperature retrieval results were improved, especially in aerosol peak layers. The root mean square error (RMSE) improved by about 0.01 K, and the mean bias improved by about 0.7 K.
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Peng et al. (2025) studied this question.
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