Monday, 11 January 2016
Himawari-8, a Japanese new generation geostationary meteorological satellite launched in October 2014, is equipped with a 16-channel multispectral imager, which includes three visible (RGB) bands and three near-infrared (NIR) bands with 1-km horizontal and 10-minute temporal resolutions covering East Asia, Southeast Asia, Oceania, and the western Pacific. The RGB and NIR band imager allows us to retrieve aerosol optical depth (AOD) and particle size information with the unprecedented temporal resolution and spatial coverage. The Himawari-8 aerosol products are promising data to improve numerical aerosol predictions if they are coupled with a high-performance aerosol simulation model and a state-of-the-art data assimilation scheme.
We have been developing an aerosol-forecast-oriented data assimilation system using a global aerosol simulation model (called MASINGAR) and the local ensemble transform Kalman filter (LETKF) with polar orbit satellite-borne imager (MODIS) AOD data or satellite-borne lidar (CALIPSO/CALIOP) data. In this study, we attempted to assimilate the Himawari-8 AOD data and forecast aerosol distributions in East Asia using the MASINGAR-LETKF data assimilation system. The data assimilation experiments showed the advantage of the Himawari-8 aerosol product over MODIS and CALIPSO/CALIOP data in aerosol predictions. The Himawari-8 aerosol data assimilation system will be operationally used for Asian dust predictions by the Japan Meteorological Agency (JMA) in 2018.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner