AHI/Himawari-8 Yonsei Aerosol Retrieval (YAER): Algorithm, Validation and Merged Products

Abstract

Himawari-8, a next-generation geostationary meteorological satellite, was successfully launched by the Japanese Meteorological Agency (JMA) on 7 October 2014 and has been in official operation since 7 July 2015. The Advanced Himawari Imager (AHI) onboard Himawari-8 has 16 channels from 0.47 to 13.3 µm and performs full-disk observations every 10 min. This study describes AHI aerosol optical property (AOP) retrieval based on a multi-channel algorithm using three visible and one near-infrared channels (470, 510, 640, and 860 nm). AOPs were retrieved by obtaining the visible surface reflectance using shortwave infrared (SWIR) data along with normalized difference vegetation index shortwave infrared (NDVI SWIR ) categories and the minimum reflectance method (MRM). Estimated surface reflectance from SWIR (ESR) tends to be overestimated in urban and cropland areas. Thus, the visible surface reflectance was improved by considering urbanization effects. Ocean surface reflectance is obtained using MRM, while it is from the Cox and Munk method in ESR with the consideration of chlorophyll-a concentration. Based on validation with ground-based sun-photometer measurements from Aerosol Robotic Network (AERONET) data, the error pattern tends to the opposition between MRMver (using MRM reflectance) AOD and ESRver (Using ESR reflectance) AOD over land. To estimate optimal AOD products, two methods were used to merge the data. The final aerosol products and the two surface reflectances were merged, which resulted in higher accuracy AOD values than those retrieved by either individual method. All four AODs shown in this study show accurate diurnal variation compared with AERONET, but the optimum AOD changes depending on observation time.

Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign

“…AHI MRM and ESR show the least difference overall over most areas and this is related to the highest selection ratio of AHI products for fusion AOD. An interesting feature is that positivenegative pattern is the opposite between MRM and ESR over most grids, which was found to agree with improved accuracy in AHI when these two products are merged in Lim et al (2018). The narrow swath of MISR leads to a broad gap between paths, and the discontinuity of the MISR L2 AOD data is noticeable along the swath boundary.…”

“…Then, the co-located AHI IR cloud information is applied to the GOCI at 500 m spatial resolution between the original cloud masking step and the pixel aggregation step to 6 km. Details of the full AHI IR cloud masking procedure for aerosol retrieval are described by Lim et al (2018). On 22 May 2016, thin cloud was detected over Manchuria (44-48 • N, 125-140 • E) and southern ocean of Japan (30-34 • N, 128-140 • E) from the GOCI true color image (Fig.…”

“…The AHI YAER algorithm provides two versions of 550 nm AOD with a 6 km ×6 km spatial resolution. Details of the AHI YAER algorithm are presented by Lim et al (2018). The full-disk area is measured by AHI in 10 segments from north to south.…”

“…Global net radiative cooling or heating is determined partially by interactions for which the level of understanding is still low and varies significantly with geographic region. Additionally, ambient particulate matter (PM) at the ground level adversely affects human health through pulmonary and respiratory transport, resulting in heart disease, stroke, and lung cancer (Gao et al, 2015;Lim et al, 2012). Many developing countries in East Asia have both large anthropogenic emission sources and natural aerosol sources, such as the Taklamakan and Gobi deserts and wildfire regions.…”

New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)

“…Aerosol properties have been observed extensively by a number of LEO satellite instruments, including Moderate Resolution Imaging Spectroradiometer (MODIS; Levy et al 2013) and Visible Infrared Imaging Radiometer Suite (VIIRS; Jackson et al 2013). High-temporal-and high-spatial-resolution observations of aerosol properties have been available from geostationary Earth orbit (GEO) instruments: the Meteorological Imager (MI) and the Geostationary Ocean Color Imager (GOCI) on board the Geostationary Korea Multi-Purpose Satellite (GK)-1, also known as Communication, Oceanography and Meteorology Satellite (COMS), and, more recently, from the AHI over Asia (Kim et al 2008;Kim et al 2016;Choi et al 2016;Choi and Ho 2015;Lim et al 2018). Long-term validation of the GOCI aerosol optical depth (AOD) indicates good agreement with ground-based Aerosol Robotic Network (AERONET) measurements, with correlation coefficients of ~0.9 (M. Choi et al 2018).…”