Yang et al. (2026) CACM-Net++: FY-4B AGRI Day and Night Cloud Mask Algorithm Modeling

Identification

• Journal: IEEE Transactions on Geoscience and Remote Sensing
• Year: 2026
• Date: 2026-01-01
• Authors: Jingyuan Yang, Zhongfeng Qiu, Dongzhi Zhao, Na Xu, Yu Wang, Kailin Li
• DOI: 10.1109/tgrs.2026.3670024

Research Groups

[Information not available in the provided text.]

Short Summary

This paper models a new cloud mask algorithm, CACM-Net++, for the FY-4B Advanced Geosynchronous Radiation Imager (AGRI) instrument, designed for effective cloud detection under both day and night conditions.

Objective

• To develop and model a robust cloud mask algorithm (CACM-Net++) for the FY-4B AGRI instrument that performs effectively under both day and night conditions.

Study Configuration

• Spatial Scale: Global or hemispheric coverage as provided by a geostationary satellite instrument (FY-4B AGRI). Specific resolution or coverage area not detailed in the provided text.
• Temporal Scale: Continuous monitoring, covering both day and night periods. Specific temporal resolution not detailed in the provided text.

Methodology and Data

• Models used: CACM-Net++ (a cloud mask algorithm, likely involving machine learning or deep learning given the "Net++" nomenclature).
• Data sources: Satellite observation data from the FY-4B Advanced Geosynchronous Radiation Imager (AGRI).

Main Results

[Information not available in the provided text.]

Contributions

• Development of a novel cloud mask algorithm (CACM-Net++) specifically tailored for the FY-4B AGRI instrument.
• Enhancement of cloud detection capabilities for both day and night conditions using the new algorithm.

Funding

[Information not available in the provided text.]

Citation

@article{Yang2026CACMNet,
  author = {Yang, Jingyuan and Qiu, Zhongfeng and Zhao, Dongzhi and Xu, Na and Wang, Yu and Li, Kailin},
  title = {CACM-Net++: FY-4B AGRI Day and Night Cloud Mask Algorithm Modeling},
  journal = {IEEE Transactions on Geoscience and Remote Sensing},
  year = {2026},
  doi = {10.1109/tgrs.2026.3670024},
  url = {https://doi.org/10.1109/tgrs.2026.3670024}
}