著者
YOSHIDA Mayumi KIKUCHI Maki NAGAO Takashi M. MURAKAMI Hiroshi NOMAKI Tomoyuki HIGURASHI Akiko
出版者
Meteorological Society of Japan
雑誌
気象集誌. 第2輯 (ISSN:00261165)
巻号頁・発行日
pp.2018-039, (Released:2018-04-15)
被引用文献数
17

We develop a common retrieval algorithm of aerosol properties such as aerosol optical thickness, single-scattering albedo, and Ångström exponent for various satellite sensors over both land and ocean. The three main features of this algorithm are as follows: (1) automatic selection of the optimum channels for aerosol retrieval by introducing a weight for each channel to the object function, (2) setting common candidate aerosol models over land and ocean, and (3) preparation of lookup tables for every 1 nm in the range from 300 to 2500 nm of wavelength and weighting the radiance using the response function for each sensor. This method was applied to the Advanced Himawari Imager (AHI) on board the Japan Meteorological Agency’s geostationary satellite Himawari-8, and the results depicted an approximately continuous estimate of aerosol optical thickness over land and ocean. Further, the aerosol optical thickness estimated using our algorithm was generally consistent with the products from Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET). Additionally, we applied our algorithm to MODIS on board the Aqua satellite and then compared the retrieval results to those that were obtained using AHI. The comparisons of the aerosol optical thickness retrieved from different sensors with different viewing angles on board the geostationary and polar-orbiting satellites suggest an underestimation of aerosol optical thickness at the backscattering direction (or overestimated in other directions). The retrieval of aerosol properties using a common algorithm allows us to identify a weakness in the algorithm, which includes the assumptions in the aerosol model (e.g. sphericity or size distiribution).
著者
YUMIMOTO Keiya TANAKA Taichu Y. YOSHIDA Mayumi KIKUCHI Maki NAGAO Takashi M. MURAKAMI Hiroshi MAKI Takashi
出版者
Meteorological Society of Japan
雑誌
気象集誌. 第2輯 (ISSN:00261165)
巻号頁・発行日
pp.2018-035, (Released:2018-04-08)
被引用文献数
5

The Japan Meteorological Agency (JMA) launched a next-generation geostationary meteorological satellite (GMS), Himawari-8, on October 7, 2014 and began its operation on July 7, 2015. The Advanced Himawari Imager (AHI) onboard Himawari-8 has 16 observational bands that enable the retrieval of full-disk maps of aerosol optical properties (AOPs), including aerosol optical thickness (AOT) and the Ångström exponent (AE) with unprecedented spatial and temporal resolution. In this study, we combined an aerosol transport model with the Himawari-8 AOT using the data assimilation method, and performed aerosol assimilation and forecasting experiments on smoke from an intensive wildfire that occurred over Siberia between May 15 and 18, 2016. To effectively utilize the high observational frequency of Himawari-8, we assimilated 1-h merged AOTs generated through the combination of six AOT snapshots taken over 10-min intervals, three times per day. The heavy smoke originating from the wildfire was transported eastward behind a low-pressure trough, and covered northern Japan from May 19 to 20. The southern part of the smoke plume then traveled westward, in a clockwise flow associated with high pressure. The forecast without assimilation reproduced the transport of the smoke to northern Japan; however, it underestimated AOT and the extinction coefficient compared with observed values, mainly due to errors in the emission inventory. Data assimilation with the Himawari-8 AOT compensated for the underestimation and successfully forecasted the unique C-shaped distribution of the smoke. In particular, the assimilation of the Himawari-8 AOT during May 18 greatly improved the forecast of the southern part of the smoke flow. Our results indicate that the inheritance of assimilation cycles and the assimilation of more recent observations led to better forecasting in this case of a continental smoke outflow.