The Impact of MERRA-2 and CAMS Aerosol Reanalysis Data on FengYun-4B Geostationary Interferometric Infrared Sounder Simulations

Aerosols significantly impact the brightness temperature (BT) in thermal infrared (IR) channels, and ignoring their effects can lead to relatively large observation-minus-background (OMB) bias in radiance calculations. The accuracy of aerosol datasets is essential for BT simulations and bias reduction. This study incorporated aerosol reanalysis datasets from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS) into the Advanced Radiative Transfer Modeling System (ARMS) to compare their impacts on BT simulations from the Geostationary Interferometric Infrared Sounder (GIIRS) and their effectiveness in reducing OMB biases. The results showed that, for a sandstorm event on 10 April 2023, incorporating total aerosol data from the MERRA-2 improved the BT simulations by 0.56 K on average, surpassing CAMS’s 0.11 K improvement. Dust aerosols notably impacted the BT, with the MERRA-2 showing a 0.17 K improvement versus CAMS’s 0.06 K due to variations in the peak aerosol level, thickness, and column mass density. Improvements for sea salt and carbonaceous aerosols were concentrated in the South China Sea and Bay of Bengal, where the MERRA-2 outperformed CAMS. For sulfate aerosols, the MERRA-2 excelled in the Bohai Sea and southern Bay of Bengal, while CAMS was better in the northern Bay of Bengal. These findings provide guidance for aerosol assimilation and retrieval, emphasizing the importance of quality control and bias correction in data assimilation systems.

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Publication Details

Journal
Remote Sensing
Published
2025-02-22
DOI
https://doi.org/10.3390/rs17050761
Citations
4
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
4.42

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article

The Impact of MERRA-2 and CAMS Aerosol Reanalysis Data on FengYun-4B Geostationary Interferometric Infrared Sounder Simulations

Chengzhi Ye, Fuzhong Weng, Weike Peng
4 citations
Remote Sensing
Atmospheric aerosols and clouds
4.42
article

The Impact of MERRA-2 and CAMS Aerosol Reanalysis Data on FengYun-4B Geostationary Interferometric Infrared Sounder Simulations

Chengzhi Ye, Fuzhong Weng, Weike Peng
article en
4 citations

Abstract

Aerosols significantly impact the brightness temperature (BT) in thermal infrared (IR) channels, and ignoring their effects can lead to relatively large observation-minus-background (OMB) bias in radiance calculations. The accuracy of aerosol datasets is essential for BT simulations and bias reduction. This study incorporated aerosol reanalysis datasets from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS) into the Advanced Radiative Transfer Modeling System (ARMS) to compare their impacts on BT simulations from the Geostationary Interferometric Infrared Sounder (GIIRS) and their effectiveness in reducing OMB biases. The results showed that, for a sandstorm event on 10 April 2023, incorporating total aerosol data from the MERRA-2 improved the BT simulations by 0.56 K on average, surpassing CAMS’s 0.11 K improvement. Dust aerosols notably impacted the BT, with the MERRA-2 showing a 0.17 K improvement versus CAMS’s 0.06 K due to variations in the peak aerosol level, thickness, and column mass density. Improvements for sea salt and carbonaceous aerosols were concentrated in the South China Sea and Bay of Bengal, where the MERRA-2 outperformed CAMS. For sulfate aerosols, the MERRA-2 excelled in the Bohai Sea and southern Bay of Bengal, while CAMS was better in the northern Bay of Bengal. These findings provide guidance for aerosol assimilation and retrieval, emphasizing the importance of quality control and bias correction in data assimilation systems.

Remote SensingVol. 17(5)
China Meteorological Administration (CN), Jiangsu Institute of Meteorological Sciences (CN), Chinese Academy of Meteorological Sciences (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hunan Province
Openalex Percentile: Top 7%
Atmospheric aerosols and clouds
4.42
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