Deriving a global and hourly data set of aerosol optical depth over land using data from four geostationary satellites: goes-16, msg-1, msg-4, and himawari-8

• Published in: IEEE Transactions on Geoscience and Remote Sensing
• Main Authors: Xie, Yanqing, Xue, Yong, Guang, Jie, Mei, Linlu, She, Lu, Li, Ying, Che, Yahui, Fan, Cheng
• Other Authors: China University of Mining and Technology, XuzhouChina, State Key Laboratory of Remote Sensing Science, University of Bremen, Bremen, Germany, Ningxia University, Yinchuan, China, University of Derby
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: IEEE 2019
• Subjects: Big Data; Aerosols; Monitoring; Geostationary satellites; Remote sensing; Earth; Optical sensors; Aerosol Robotic Network
• Online Access: https://doi.org/10.1109/TGRS.2019.2944949; https://repository.derby.ac.uk/download/b430d8874206767801e43cdb9b9243fae2222e4ae144d1c9edcc1d879ee7b680/1980/license.txt; https://repository.derby.ac.uk/download/29f994acac6baf2a6025172a35a071d06633d22f33b2212e2324531ac88b0957/908/license_rdf

Due to the limitations in the number of satellites and the swath width of satellites (determined by the field of view and height of satellites), it is impossible to monitor global aerosol distribution using polar orbiting satellites at a high frequency. This limits the applicability of aerosol optical depth (AOD) data sets in many fields, such as atmospheric pollutant monitoring and climate change research, where a high-temporal data resolution may be required. Although geostationary satellites have a high-temporal resolution and an extensive observation range, three or more satellites are required to achieve global monitoring of aerosols. In this article, we obtain an hourly and global AOD data set by integrating AOD data sets from four geostationary weather satellites [Geostationary Operational Environmental Satellite (GOES-16), Meteosat Second Generation (MSG-1), MSG-4, and Himawari-8]. The integrated data set will expand the application range beyond the four individual AOD data sets. The integrated geostationary satellite AOD data sets from April to August 2018 were validated using Aerosol Robotic Network (AERONET) data. The data set results were validated against: the mean absolute error, mean bias error, relative mean bias, and root-mean-square error, and values obtained were 0.07, 0.01, 1.08, and 0.11, respectively. The ratio of the error of satellite retrieval within ±(0.05 + 0.2 x AODAERONET) is 0.69. The spatial coverage and accuracy of the MODIS/C61/AOD product released by NASA were also analyzed as a representative of polar orbit satellites. The analysis results show that the integrated AOD data set has similar accuracy to that of the MODIS/AOD data set and has higher temporal resolution and spatial coverage than the MODIS/AOD data set.