Aerosol data assimilation using data from Himawari‐8, a next‐generation geostationary meteorological satellite

Himawari‐8, a next‐generation geostationary meteorological satellite, was launched on 7 October 2014 and became operational on 7 July 2015. The advanced imager on board Himawari‐8 is equipped with 16 observational bands (including three visible and three near‐infrared bands) that enable retrieval of...

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Veröffentlicht in:Geophysical research letters 2016-06, Vol.43 (11), p.5886-5894
Hauptverfasser: Yumimoto, K., Nagao, T.M., Kikuchi, M., Sekiyama, T.T, Murakami, H., Tanaka, T.Y., Ogi, A., Irie, H., Khatri, P., Okumura, H., Arai, K., Morino, I., Uchino, O., Maki, T.
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Sprache:eng
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Zusammenfassung:Himawari‐8, a next‐generation geostationary meteorological satellite, was launched on 7 October 2014 and became operational on 7 July 2015. The advanced imager on board Himawari‐8 is equipped with 16 observational bands (including three visible and three near‐infrared bands) that enable retrieval of full‐disk aerosol optical properties at 10 min intervals from geostationary (GEO) orbit. Here we show the first application of aerosol optical properties (AOPs) derived from Himawari‐8 data to aerosol data assimilation. Validation of the assimilation experiment by comparison with independent observations demonstrated successful modeling of continental pollution that was not predicted by simulation without assimilation and reduced overestimates of dust front concentrations. These promising results suggest that AOPs derived from Himawari‐8/9 and other planned GEO satellites will considerably improve forecasts of air quality, inverse modeling of emissions, and aerosol reanalysis through assimilation techniques. Key Points Next‐generation geostationary meteorological satellite Himawari‐8 launched on 7 October 2014 Himawari‐8 provides full‐disk aerosol optical properties at 10 min intervals from geostationary orbit Promising results of aerosol assimilation experiment on Himawari‐8 retrievals
ISSN:0094-8276
1944-8007
DOI:10.1002/2016GL069298