Himawari-8 (H8), as a geostationary satellite, observing the full disk image of the earth per 10 min, is a very powerful tool to investigate atmospheric aerosol temporal variations. The advanced himawari imager (AHI) onboard H8 has several spectral bands similar with those of Moderate Resolution Imaging Spectroradiometer (MODIS). Aerosol optical depth (AOD) is thus possible to be retrieved from AHI data using the dark target (DT) method of MODIS. Based on a statistics study of infrared bands of these two satellite instruments, we found that the difference of shortwave infrared bands between AHI (2.3 μm) and MODIS (2.12 μm) in DT area can be ignored for our purpose. Meanwhile, for AHI sensor, the normalized difference vegetation index (NDVI) calculated from 0.86 μm (instead of traditional 1.24 μm) and 2.3 μm can also be a good indicator of surface spectral reflectance. Therefore, first, a new NDVI of AHI sensor is proposed in this paper to improve the estimation of surface reflectance based on DT retrieval method. Then, AOD over DT area was retrieved using a lookup table strategy and tested based on AHI observation over China region from August 2015 to July 2016. All retrieved results are validated against ground-based measurements of the aerosol robotic network and the sun-sky radiometer observation network. The coincident AOD results between AHI retrieval- and ground-based network measurements show good agreements with R² of 0.81. The intercomparison between AHI and MODIS DT AOD products also shows a good agreement with R² of 0.92.

Toward the Kashi region in northwest of China, the Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) retrievals from Collection 6 (C6) MYD, Collection 6.1 (C6.1) MOD, and C6.1 MYD during 2016–2017 are compared with ground‐based measurements from the Sun‐sky Radiometer Network (SONET), and the first comprehensive evaluation of the Dark Target (DT) and Deep Blue (DB) retrievals with a 10‐km spatial resolution in the latest C6.1 MYD AOD data set during 2016–2018 is presented. In general, C6.1 MYD AOD products (both of DT and DB algorithm) are the most effective in Kashi of the three collections, and there is an overall underestimation of DB AOD, while DT AOD that slightly outperformed DB AOD in Kashi is overestimated on the whole. As to the factors that influence the accuracy of MODIS AOD, for DB algorithm, the overestimations of the surface reflectance and Single Scattering Albedo that DB aerosol model assumed can cause underestimation of DB AOD retrievals over Kashi, while the ones for DT algorithm are opposite. Besides, the coarse dust particles with lower veracity are predominant in Kashi region, which illustrated that the errors of particle size assumption in C6.1 MYD DT and DB algorithms will make large inversion error of MODIS AOD. Moreover, whatever DB or DT algorithm, the accuracy of AOD is diminished as the aerosol loading increases. The more realistic aerosol models and surface characterizations are necessary during the process of generating the MODIS aerosol retrievals in Kashi region.

The fine-mode fraction (FMF) of aerosol optical depth (AOD) is a key optical parameter that represents the proportion of fine particles relative to total aerosols in the atmosphere. However, in comparison to ground-based measurements, the FMF is still difficult to retrieve from satellite observations, as attempted by a Moderate-resolution Imaging Spectroradiometer (MODIS) algorithm. In this paper, we introduce the retrieval of FMF based on Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from a Lidar (PARASOL) data. This method takes advantage of the coincident multi-angle intensity and polarization measurements from a single satellite platform. In our method, we use intensity measurements to retrieve the total AOD and polarization measurements to retrieve the fine-mode AOD. The FMF is then calculated as the ratio of the retrieved fine-mode AOD to the total AOD. The important processes in our method include the estimation of the surface intensity and polarized reflectance by using two semi-empirical models, and the building of two sets of aerosol retrieval lookup tables for the intensity and polarized measurements via the 6SV radiative transfer code. We apply this method to East Asia, and comparisons of the retrieved FMFs for the Beijing, Xianghe and Seoul_SNU sites with those of the Aerosol Robotic Network (AERONET) ground-based observations produce correlation coefficients (R²) of 0.838, 0.818, and 0.877, respectively. However, the comparison results are relatively poor (R² = 0.537) in low-AOD areas, such as the Osaka site, due to the low signal-to-noise ratio of the satellite observations.