EGU24-14190, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Characteristics and Results of Cloud Retrieval Algorithm for Geostationary Environment Monitoring Spectrometer

Bo-Ram Kim1, Gyuyeon Kim2, Minjeong Cho2, and Yong-Sang Choi2
Bo-Ram Kim et al.
  • 1Korea Aerospace Research Institute, National Satellite Operation and Application, Korea, Republic of (
  • 2Ewha Womans University, Seoul, Republic of Korea

The cloud retrieval algorithm used by the Geostationary Environment Monitoring Spectrometer (GEMS) to monitor atmospheric conditions over East Asia is presented in this paper. In the UV-VIS range, cloud increase radiance and shorten the beam bath length. We defined cloud products as the effective cloud fraction, which represents the reflecting impact of clouds, and the cloud centroid pressure, which indicates the height at which clouds reflect. The absorption in the O2-O2 absorption band, which results from collisions of oxygen molecules in the atmosphere with generally constant concentrations, is used by the algorithm to determine the characteristics of clouds. Input data include observed radiance, irradiance, observation geometry, and surface information (reflectance and pressure). We evaluate the algorithm’s sensitivity to each input data. Moreover, we perform a monthly comparison and analysis of the actual cloud retrieval products acquired from GEMS with TROPOMI (Tropospheric Monitoring Instrument), investigating the algorithm's seasonality. Additionally, events showcasing prominent cloud features, such as high concentrations of air pollutants, typhoons, and sea fog, are chosen for performance evaluation through comparisons between GEMS results and those from TROPOMI, Advanced Meteorology Imager, and Cloud-Aerosol Lidar with Orthogonal Polarization. In comparing GEMS cloud retrieval results with those of other satellites, distinct variations based on land and ocean surfaces were observed, overshadowing the impact of seasonal differences. However, the CCP exhibited reduced accuracy during thick cloud in the summer season. This feature was consistently seen in event analysis, especially in cases of typhoons with diverse cloud shapes. In thin-cloud regions, CCP was comparable to other satellites; in thick-cloud regions, significant differences were seen. Besides, the investigation showed that GEMS had a tendency to identify clouds over highly reflective, low-altitude sea fog, resulting in CCP values that were comparable to surface pressure. This special quality made it possible to accurately characterize the characteristics of sea fog.

How to cite: Kim, B.-R., Kim, G., Cho, M., and Choi, Y.-S.: Characteristics and Results of Cloud Retrieval Algorithm for Geostationary Environment Monitoring Spectrometer, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14190,, 2024.