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

Abstract

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.

Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China

“…The center of Himawari-8 is 140.7 • E over equator, and the observation area is located from 80 • E to 160 • W and from 60 • N to 60 • S [28]. Himawari-8 can provide AODs at 500 nm and Ångström exponents with 10 min intervals and 5 km coverage over about one-third of the Earth (i.e., Western Pacific Ocean, East and Southeast Asia, and Oceania) [25,26]. The AODs were subjected to quality assurance with four confidence levels, namely, "very good," "good," "marginal," and "no confidence" (or "no retrieval").…”

Aerosol Optical Depth Retrieval over East Asia Using Himawari-8/AHI Data

“…Himawari-8 is the next-generation geostationary meteorological satellite [25,26]. The observational bands in visible and near-infrared wavelengths of Himawari-8 are sensitive to aerosol scattering and absorption, which is an attractive characteristic for aerosol research.…”

“…The AHI is equipped with 16 observational bands from visible to infrared with a spatial resolution of 0.5-2 km and temporal resolution of 10 min (six full-disk images per hour) [26,29]. images per hour) [26,29]. Table 1 shows the detailed spectral bands of AHI (source: http://www.jmanet.go.jp/msc/en/), and their corresponding channel response functions are plotted in Figure 1.…”

“…It carries an Advanced Himawari Imager with improved spectral, temporal, and radiometric resolution. The AHI is equipped with 16 observational bands from visible to infrared with a spatial resolution of 0.5-2 km and temporal resolution of 10 min (six full-disk images per hour) [26,29]. images per hour) [26,29].…”

Improving PM<sub>2. 5</sub> forecast over China by the joint adjustment of initial conditions and source emissions with an ensemble Kalman filter

“…Peng et al: Improving PM 2.5 forecast over China et al, 2010a, b;Pagowski and Grell, 2012;Dai et al, 2014;Rubin et al, 2016;Ying et al, 2016;Yumimoto et al, 2016) and the hybrid variational-ensemble DA approach (Schwartz et al, 2014) have also been applied to aerosol predictions. All these studies have shown that DA is one of the most effective ways of improving aerosol forecasting through assimilating aerosol observations from multiple sources (e.g.…”