Introduction
The dataset is a colltection of FY-4A REGC AGRI AOD retrieved with transfer learning method (see details in the paper:A deep-learning and transfer-learning hybrid aerosol retrieval algorithm for FY4-AGRI: Development and verification over Asia). The AGRI AOD is built with 5min/4km. The dataset in this category is provided in 1 hour.
Due to the cloud mask before March 12th being derived from a simplified empirical algorithm, there is a difference in data quality between the AOD data before and after March 12th. If the author requires a dataset with a 5-minute time resolution, please contact Dr. Dong Fu (fudisong@mail.iap.ac.cn). If you use this dataset, please cite this dataset and the related article.
Citation
Disong Fu, Hongrong Shi, Christian A. Gueymard, Dazhi Yang, Yu Zheng, Huizheng Che, Xuehua Fan, Xinlei Han, Lin Gao, Jianchun Bian, Minzheng Duan, Xiangao Xia, A Deep-Learning and Transfer-Learning Hybrid Aerosol Retrieval Algorithm for FY4-AGRI: Development and Verification over Asia, Engineering, 2024, https://doi.org/10.1016/j.eng.2023.09.023.
Acknowledgments
The work was supported by the National Natural Science of Foundation of China (41852011, 42030608, 42105128, and 42075079), the Opening Foundation of Key Laboratory of Atmospheric Sounding, the China Meteorological Administration and the CMA Research Center on Meteorological Observation Engineering Technology (U2021Z03). The AERONET and CARSNET staff and participants are thanked for their successful effort in establishing and maintaining the sites. The authors are grateful to the European Centre for Medium-Range Weather Forecasts (ECMWF) for the reanalysis products, Japan Aerospace Exploration Agency for AHI AOD, and NASA for its MODIS products.
Source Data
The FY-4A datasets are obtained from http://data.nsmc.org.cn. The retrieved AGRI AOD in 2018 can be accessed at https://doi.org/10.57760/sciencedb.12395. More information of the re-trieved AGRI AOD can also be requested by contacting Disong Fu (fudisong@mail.iap.ac.cn).