Complementary vertical sensitivity unlocks full-column thermodynamics from combined ground and space microwave observations - Disong Fu; Qinghui Sun; Fa Tao; Xiangao Xia; Yunjie Xia; Zijue Song; Dazhi Yang; Hongrong Shi; Jiajia Mao; Ziqiang Zhu; Peng Zhang (Atmospheric Research, 2026)

FAMdust: Fast Adaptive Machine-Learning Framework for Global Martian Dust Optical Depth Retrieval—Applied to HOPE/EMIRS Thermal Infrared Observations - Disong Fu; Minqiang Zhou; Minzheng Duan; Xuehua Fan; Yiyuan Li; Li Dong; Juanjuan Liu; Hongrong Shi; Xiangao Xia (Advances in Atmospheric Sciences, 2026)

The synergy of active and passive satellite sensors for robust sea-fog detection: A two-stage machine-learning model with constraints from ICOADS - Luyu Yan; Xuehua Fan; Disong Fu; Hongrong Shi; Lin Chen; Bo Li; Zhuhui Jiang; Xiaoqiong Zhen; Xiaoguang Sun; Xiangao Xia (Atmospheric Research, 2026)

Revealing the lifecycle evolution of hail-producing deep convective clouds by synergy of multi-source data - Qiang Li; Hongrong Shi; Yurui Xie; Rubin Jiang; Chaoying Wang; Yupeng Teng; Shuo Jia; Jianwei Wen; Disong Fu; Jiefan Yang; Xuehua Fan; Jinqiang Zhang; et al. (Atmospheric Research, 2026)

Optimal spatio-temporal interpolation of aerosol optical depth over China using fixed rank kriging - Yu Kong; Bai Liu; Dazhi Yang; Disong Fu; Hongrong Shi; Yun Chen; Guoming Yang; Yong Chen; Jiaqi Chen; Yanbo Shen; Xiang’ao Xia (Atmospheric Research, 2026)

Conditional Generative Adversarial Networks Enhance Atmospheric Thermodynamic Profile Retrieval from Ground-Based Microwave Radiometer Measurements - Disong Fu; Xia Li; Jingmiao Zhu; Dazhi Yang; Ruiting Liu; Hongrong Shi; Guangyu Gao; Xinlei Han; Xiang’ao Xia; Yunjie Xia; Maoling Ayitikan; Kai Cheng; et al. (Journal of Meteorological Research, 2025)

Evaluating and Enhancing Fengyun AGRI Cloud Detection with the Ensemble Learning Algorithm - Meijia Xiao; Disong Fu; Hongrong Shi; Guocheng Wang; Hengchi Lei; Xinlei Han; Xiang’ao Xia (Advances in Atmospheric Sciences, 2025)

Joint Retrieval of PM2.5 Concentration and Aerosol Optical Depth over China Using Multi-Task Learning on FY-4A AGRI - Bo Li; Disong Fu; Ling Yang; Xuehua Fan; Dazhi Yang; Hongrong Shi; Xiang’ao Xia (Advances in Atmospheric Sciences, 2025)

A Thorough Evaluation of the Passive Microwave Radiometer Measurements onboard Three Fengyun-3 Satellites - Xinran Xia; Wenying He; Shengli Wu; Disong Fu; Wei Shao; Peng Zhang; Xiangao Xia (Journal of Meteorological Research, 2023)

Corrigendum to “Validation of the improved GOES-16 aerosol optical depth product over North America” [Atmos. Environ. 298 (2023) 119642] - Disong Fu; Christian A. Gueymard; Xiangao Xia (Atmospheric Environment, 2023)

Validation of the improved GOES-16 aerosol optical depth product over North America - Disong Fu; Christian A. Gueymard; Xiangao Xia (Atmospheric Environment, 2023)

Improving aerosol optical depth retrievals from Himawari-8 with ensemble learning enhancement: Validation over Asia - Disong Fu; Christian A. Gueymard; Dazhi Yang; Yu Zheng; Xiangao Xia; Jianchun Bian (Atmospheric Research, 2023)

Data-driven Estimation of Cloud Effects on Surface Irradiance at Xianghe, a Suburban Site on the North China Plain - Mengqi Liu; Jinqiang Zhang; Hongrong Shi; Disong Fu; Xiang’ao Xia (Advances in Atmospheric Sciences, 2022)

Fengyun-4 Geostationary Satellite-Based Solar Energy Nowcasting System and Its Application in North China - Chunlin Huang; Hongrong Shi; Ling Gao; Mengqi Liu; Qixiang Chen; Disong Fu; Shu Wang; Yuan Yuan; Xiang’ao Xia (Advances in Atmospheric Sciences, 2022)

Estimation of PM2.5 Mass Concentration from Visibility - Denghui Ji; Zhaoze Deng; Xiaoyu Sun; Liang Ran; Xiangao Xia; Disong Fu; Zijue Song; Pucai Wang; Yunfei Wu; Ping Tian; Mengyu Huang (Advances in Atmospheric Sciences, 2020)
Aerosols in the atmosphere not only degrade visibility, but are also detrimental to human health and transportation. In order to develop a method to estimate PM 2.5 mass concentration from the widely measured visibility, a field campaign was conducted in Southwest China in January 2019. Visibility, ambient relative humidity (RH), PM 2.5 mass concentrations and scattering coefficients of dry particles were measured. During the campaign, two pollution episodes, i.e., from 4–9 January and from 10–16 January, were encountered. Each of the two episodes could be divided into two periods. High aerosol hygroscopicity was found during the first period, when RH was higher than 80% at most of the time, and sometimes even approached 100%. The second period experienced a relatively dry but more polluted condition and aerosol hygroscopicity was lower than that during the first period. An empirical relationship between PM 2.5 mass concentration and visibility (ambient aerosol extinction) under different RH conditions could thus be established. Based on the empirical relationship, PM 2.5 mass concentration could be well estimated from visibility and RH. This method will be useful for remote sensing of PM 2.5 mass concentration.