{"title":"基于改进表面反射率的多角度气溶胶光学深度反演方法","authors":"Lijuan Chen, Ren Wang, Ying Fei, Peng Fang, Yong Zha, Haishan Chen","doi":"10.5194/amt-2023-204","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> Retrieval of terrestrial aerosol optical depth (AOD) has been a challenge for satellite Earth observations, mainly due to the difficulty of estimating surface reflectance caused by land-atmosphere coupling. Current satellite AOD retrieval products have low spatial resolution under complex surface processes. In this study, based on our previous studies of AOD retrieval, we further improved the estimation method of surface reflectance by establishing an error correction model and then obtained a more accurate AOD. A lookup table is constructed using the Second Simulation of Satellite Signal in the Solar Spectrum (6S) to obtain high-precision retrieval of AOD. The retrieval accuracy of the algorithm is verified by AERONET (Aerosol Robotic Network) observations. The results indicate that the retrieved AOD based on the improved method of this study has advantages in fewer missing AOD pixels and finer spatial resolution, as compared to the MODIS AOD product and our previous estimation method. Among the nine MISR angles, the optimal correlation coefficient (R) of retrieved AOD and observed AOD can reach 0.89. Root mean square error (RMSE) and relative mean bias (RMB) can reach a minimum values of 0.20 and 0.32, respectively. This study will help to further improve the accuracy of retrieving multi-angle AOD at large spatial scales and long time series.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"12 3","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-angle aerosol optical depth retrieval method based on improved surface reflectance\",\"authors\":\"Lijuan Chen, Ren Wang, Ying Fei, Peng Fang, Yong Zha, Haishan Chen\",\"doi\":\"10.5194/amt-2023-204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> Retrieval of terrestrial aerosol optical depth (AOD) has been a challenge for satellite Earth observations, mainly due to the difficulty of estimating surface reflectance caused by land-atmosphere coupling. Current satellite AOD retrieval products have low spatial resolution under complex surface processes. In this study, based on our previous studies of AOD retrieval, we further improved the estimation method of surface reflectance by establishing an error correction model and then obtained a more accurate AOD. A lookup table is constructed using the Second Simulation of Satellite Signal in the Solar Spectrum (6S) to obtain high-precision retrieval of AOD. The retrieval accuracy of the algorithm is verified by AERONET (Aerosol Robotic Network) observations. The results indicate that the retrieved AOD based on the improved method of this study has advantages in fewer missing AOD pixels and finer spatial resolution, as compared to the MODIS AOD product and our previous estimation method. Among the nine MISR angles, the optimal correlation coefficient (R) of retrieved AOD and observed AOD can reach 0.89. Root mean square error (RMSE) and relative mean bias (RMB) can reach a minimum values of 0.20 and 0.32, respectively. This study will help to further improve the accuracy of retrieving multi-angle AOD at large spatial scales and long time series.\",\"PeriodicalId\":8619,\"journal\":{\"name\":\"Atmospheric Measurement Techniques\",\"volume\":\"12 3\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2023-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Measurement Techniques\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/amt-2023-204\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Measurement Techniques","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/amt-2023-204","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
Multi-angle aerosol optical depth retrieval method based on improved surface reflectance
Abstract. Retrieval of terrestrial aerosol optical depth (AOD) has been a challenge for satellite Earth observations, mainly due to the difficulty of estimating surface reflectance caused by land-atmosphere coupling. Current satellite AOD retrieval products have low spatial resolution under complex surface processes. In this study, based on our previous studies of AOD retrieval, we further improved the estimation method of surface reflectance by establishing an error correction model and then obtained a more accurate AOD. A lookup table is constructed using the Second Simulation of Satellite Signal in the Solar Spectrum (6S) to obtain high-precision retrieval of AOD. The retrieval accuracy of the algorithm is verified by AERONET (Aerosol Robotic Network) observations. The results indicate that the retrieved AOD based on the improved method of this study has advantages in fewer missing AOD pixels and finer spatial resolution, as compared to the MODIS AOD product and our previous estimation method. Among the nine MISR angles, the optimal correlation coefficient (R) of retrieved AOD and observed AOD can reach 0.89. Root mean square error (RMSE) and relative mean bias (RMB) can reach a minimum values of 0.20 and 0.32, respectively. This study will help to further improve the accuracy of retrieving multi-angle AOD at large spatial scales and long time series.
期刊介绍:
Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere.
The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.