Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors - MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea-United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84-0.93) and low RMSE (0.12-0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. Highaccuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18-21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0:5 0:5 grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.
|Number of pages||23|
|Journal||Atmospheric Measurement Techniques|
|Publication status||Published - 2019 Aug 30|
Bibliographical noteFunding Information:
This research has been supported by the National Strategic Project-Fine Particle of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), the Ministry of Environment (ME), and the Ministry of Health and Welfare (MOHW) (grant no. NRF- 2017M3D8A1092021) and the NASA ROSES-2013 Atmospheric Composition: Aura Science Team program and NASA Headquarter Directed Research and Technology Development Task (grant no. NNN13D455T). We thank all principal investigators and their staff for establishing and maintaining the AERONET and SONET sites used in this investigation. We also thank the MODIS, MISR, and VIIRS science teams for providing valuable data for this research. This research was supported by the National Strategic Project-Fine Particle of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), the Ministry of Environment (ME), and the Ministry of Health andWelfare (MOHW; NRF-2017M3D8A1092021). Some research tasks were supported by the NASA ROSES-2013 Atmospheric Composition: Aura Science Team program and NASA Headquarter Directed Research and Technology Development Task (grant number: NNN13D455T, manager: Kenneth W. Jucks and Richard S. Eckman). A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The editor and two anonymous reviewers are thanked for numerous useful comments, which improved the content and clarity of the manuscript.
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All Science Journal Classification (ASJC) codes
- Atmospheric Science