An Improved Aerosol Retrieval Algorithm for FY-4A/AGRI Data Based on the GRASP Framework
文献类型：期刊论文
| 作者 | Wang, Huaxuan5,6; Fan, Meng6; Jiao, Sunxin4,6; Yan, Huanhuan3; Xu, Benben6; Liu, Xu2; Wang, Yang1; Tao, Jinhua6; Chen, Liangfu6 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2025 |
| 卷号 | 63页码:4103517 |
| 关键词 | Aerosols Sea surface Spatial resolution Monitoring MODIS Atmospheric modeling Reflectivity Instruments Accuracy Land surface Advanced Geostationary Radiation Imager (AGRI) aerosol optical depth (AOD) Fengyun-4A (FY-4A) generalized retrieval of atmosphere and surface properties (GRASP) optimal estimation method |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2025.3546614 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Accurate satellite-derived aerosol optical depth (AOD) with high temporal resolution is crucial for monitoring diurnal aerosol variations and understanding their impacts on atmospheric processes and air quality. The Advanced Geostationary Radiation Imager (AGRI) aboard the Fengyun 4A (FY-4A) satellite offers high spatiotemporal resolution, making it suitable for continuous atmospheric aerosol monitoring. In this study, an improved AOD retrieval algorithm is proposed for FY-4A/AGRI based on the generalized retrieval of atmosphere and surface properties (GRASP) framework. The algorithm incorporates multitemporal and multispectral FY-4A/AGRI observations within a 30-min window to enhance observational constraints for AOD retrieval. Reasonable prior information from Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) products and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) aerosol components is introduced, enabling hourly AOD retrievals with high accuracy and robustness. Compared with AOD derived from the single-temporal strategy with fixed BRDF and aerosol models, results of validation against aerosol robotic network (AERONET) AOD measurements over Beijing-Tianjin-Hebei (BTH) region indicate that our improved FY-4A/AGRI AOD retrievals increase the R from 0.543 to 0.864, and reduce root-mean-square error (RMSE) from 0.149 to 0.09, with the percentage of data falling within the expected error (EE) range rising from 46.1% to 69.9%. In Asia, such advancements led to significant improvements in AOD retrieval performance in 2021, with validation results demonstrating a strong correlation (R =0.826 for hourly retrievals and R =0.891 for daily means) and high accuracy (RMSE =0.118 for hourly retrievals and RMSE =0.09 for daily means) against ground-based AOD measurements from 32 AERONET sites. Comparative analyses reveal that FY-4A/AGRI AOD retrievals outperform Himawari-8/AHI products and are comparable to MODIS multiangle implementation of atmospheric correction (MAIAC) data, particularly in capturing diurnal variations and spatial distributions of aerosols. The algorithm also demonstrates robustness across diverse land cover types and vegetation densities. Our AOD retrieval strategy provides a scalable approach for geostationary satellite aerosol retrieval, with implications for regional air quality monitoring and climate studies. |
| URL标识 | 查看原文 |
| WOS关键词 | OPTICAL-PROPERTIES ; PRODUCTS ; LAND |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001447530000009 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/213351]  |
| 专题 | 生态系统网络观测与模拟院重点实验室_外文论文 |
| 通讯作者 | Fan, Meng |
| 作者单位 | 1.Fujian Normal Univ, Sch Geog Sci, Fuzhou 350117, Peoples R China 2.Tianfu Yongxing Lab, Chengdu 610213, Peoples R China; 3.Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China; 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China; 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 6.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Remote Sensing & Digital Earth, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Wang, Huaxuan,Fan, Meng,Jiao, Sunxin,et al. An Improved Aerosol Retrieval Algorithm for FY-4A/AGRI Data Based on the GRASP Framework[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2025,63:4103517. |
| APA | Wang, Huaxuan.,Fan, Meng.,Jiao, Sunxin.,Yan, Huanhuan.,Xu, Benben.,...&Chen, Liangfu.(2025).An Improved Aerosol Retrieval Algorithm for FY-4A/AGRI Data Based on the GRASP Framework.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,63,4103517. |
| MLA | Wang, Huaxuan,et al."An Improved Aerosol Retrieval Algorithm for FY-4A/AGRI Data Based on the GRASP Framework".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 63(2025):4103517. |
入库方式： OAI收割
来源：地理科学与资源研究所
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