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东亚海域多卫星气溶胶光学厚度产品的评估与比较

Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean.

作者信息

Cao Zhaoxiang, Luan Kuifeng, Zhou Peng, Shen Wei, Wang Zhenhua, Zhu Weidong, Qiu Zhenge, Wang Jie

机构信息

College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China.

Estuarine and Oceanographic Mapping Engineering Research Center of Shanghai, Shanghai 200123, China.

出版信息

Toxics. 2023 Sep 26;11(10):813. doi: 10.3390/toxics11100813.

Abstract

The atmosphere over the ocean is an important research field that involves multiple aspects such as climate change, atmospheric pollution, weather forecasting, and marine ecosystems. It is of great significance for global sustainable development. Satellites provide a wide range of measurements of marine aerosol optical properties and are very important to the study of aerosol characteristics over the ocean. In this study, aerosol optical depth (AOD) data from seventeen AERONET (Aerosol Robotic Network) stations were used as benchmark data to comprehensively evaluate the data accuracy of six aerosol optical thickness products from 2013 to 2020, including MODIS (Moderate-resolution Imaging Spectrometer), VIIRS (Visible Infrared Imaging Radiometer Suite), MISR (Multi-Angle Imaging Spectrometer), OMAERO (OMI/Aura Multi-wavelength algorithm), OMAERUV (OMI/Aura Near UV algorithm), and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) in the East Asian Ocean. In the East Asia Sea, VIIRS AOD products generally have a higher correlation coefficient (R), expected error within ratio (EE within), lower root mean square error (RMSE), and median bias (MB) than MODIS AOD products. The retrieval accuracy of AOD data from VIIRS is the highest in spring. MISR showed a higher EE than other products in the East Asian Ocean but also exhibited systematic underestimation. In most cases, the OMAERUV AOD product data are of better quality than OMAERO, and OMAERO overestimates AOD throughout the year. The CALIPSO AOD product showed an apparent underestimation of the AOD in different seasons (EE Below = 58.98%), but when the AOD range is small (0 < AOD < 0.1), the CALIPSO data accuracy is higher compared with other satellite products under small AOD range. In the South China Sea, VIIRS has higher data accuracy than MISR, while in the Bohai-Yellow Sea, East China Sea, Sea of Japan, and the western Pacific Ocean, MISR has the best data accuracy. MODIS and VIIRS show similar trends in R, EE within, MB, and RMSE under the influence of AOD, Angstrom exponent (AE), and precipitable water. The study on the temporal and spatial distribution of AOD in the East Asian Ocean shows that the annual variation of AOD is different in different sea areas, and the ocean in the coastal area is greatly affected by land-based pollution. In contrast, the AOD values in the offshore areas are lower, and the aerosol type is mainly clean marine type aerosol. These findings can help researchers in the East Asian Ocean choose the most accurate and reliable satellite AOD data product to better study atmospheric aerosols' impact and trends.

摘要

海洋上空的大气是一个重要的研究领域,涉及气候变化、大气污染、天气预报和海洋生态系统等多个方面。它对全球可持续发展具有重要意义。卫星提供了大量有关海洋气溶胶光学特性的测量数据,对研究海洋上空的气溶胶特征非常重要。在本研究中,来自17个AERONET(气溶胶机器人网络)站点的气溶胶光学厚度(AOD)数据被用作基准数据,以全面评估2013年至2020年期间东亚海域六种气溶胶光学厚度产品的数据准确性,这些产品包括MODIS(中等分辨率成像光谱仪)、VIIRS(可见红外成像辐射仪套件)、MISR(多角度成像光谱仪)、OMAERO(OMI/Aura多波长算法)、OMAERUV(OMI/Aura近紫外算法)和CALIPSO(云气溶胶激光雷达和红外探路者卫星观测)。在东亚海域,VIIRS AOD产品的相关系数(R)通常较高,比率内预期误差(EE within)较低,均方根误差(RMSE)和中位数偏差(MB)低于MODIS AOD产品。VIIRS的AOD数据在春季的反演精度最高。MISR在东亚海域的EE高于其他产品,但也表现出系统性低估。在大多数情况下,OMAERUV AOD产品数据质量优于OMAERO,OMAERO全年高估AOD。CALIPSO AOD产品在不同季节明显低估AOD(EE Below = 58.98%),但当AOD范围较小时(0 < AOD < 0.1),在小AOD范围内CALIPSO数据准确性高于其他卫星产品。在南海,VIIRS的数据准确性高于MISR,而在渤海-黄海、东海、日本海和西太平洋,MISR的数据准确性最佳。在AOD、埃斯特朗指数(AE)和可降水量的影响下,MODIS和VIIRS在R、EE within、MB和RMSE方面呈现相似趋势。对东亚海域AOD时空分布的研究表明,不同海域AOD的年变化不同,沿海地区的海洋受陆源污染影响较大。相比之下,近海区域的AOD值较低,气溶胶类型主要是清洁海洋型气溶胶。这些发现可以帮助东亚海域的研究人员选择最准确可靠的卫星AOD数据产品,以更好地研究大气气溶胶的影响和趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/856b/10611072/b526ff9cc14a/toxics-11-00813-g001.jpg

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