Search

High-frequency aerosol observation from a new-generation geostationary meteorological satellite is capable to capture and monitor the spatiotemporal dynamic variation of aerosols, which is of vital significance to environmental research and climate studies. Due to the diversity and complexity of land cover, it is a challenge to retrieve aerosol properties with high accuracy over land, especially over heterogeneous land surfaces. In this study, a geometry-discrete minimum reflectance aerosol retrieval algorithm (GeoMRA) has been proposed to retrieve 10-min high temporal resolution aerosol optical depth (AOD) datasets for geostationary Himawari-8 Advanced Himawari Imager (AHI) sensor, aiming at providing universal bidirectional reflectance distribution function (BRDF) descriptions for different land surfaces with different heterogeneous extent. The AOD retrievals from GeoMRA demonstrate good consistency against the ground-based AERONET measurements in East Asia from 2015 to 2020, with a correlation coefficient (${R}$) of 0.883 and approximately 65.6% of matchups falling within the expected error envelope of ±(0.05% +15%). Intercomparison between the GeoMRA retrieved AOD and other operational AOD products shows that the GeoMRA AOD retrievals, which generally possess similar spatial distribution and accuracy as Moderate Resolution Imaging Spectroradiometer (MODIS) AOD products, have better performances than the Japan Aerospace Exploration Agency (JAXA) AOD products by providing more accurate AOD retrievals with higher spatial coverage. Moreover, the AOD bias analyses further demonstrate the robustness of GeoMRA algorithm, and an extreme haze event shows that the continuous GeoMRA AOD images illustrate smoother temporal variations than JAXA AOD products, demonstrating its efficacy and reliability in capturing the process of haze transport and monitoring the continuous spatiotemporal variation of aerosol. The above results suggest the considerable accuracy of GeoMRA algorithm for scientific application requirement and demonstrate the robustness of the proposed BRDF scheme in describing heterogeneous surfaces with diverse reflectance distribution. [ABSTRACT FROM AUTHOR]

One or several aspects of the source, distribution, transport, and optical properties of airborne dust have been characterized using different types of satellite and ground measurements, each with unique advantages. In this study, a dust event that occurred over the East Asia area in May 2017 was exemplified to demonstrate how all the above-mentioned aspects of a dust event can be pictured by combining the advantages of different satellite and ground measurements. The data used included the Himawari-8 satellite Advanced Himawari Imager (AHI) true-colour images, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol vertical profiles, the Aura satellite Ozone Monitoring Instrument (OMI) aerosol index images, and the ground-based Aerosol Robotic Network (AERONET) aerosol properties and the ground station particulate matter (PM) measurements. From the multi-satellite/sensor (AHI, CALIOP, and OMI) time series observations, the dust storm was found to originate from the Gobi Desert on the morning of 3 May 2017 and transport north-eastward to the Bering Sea, eastward to the Korean Peninsula and Japan, and southward to south-central China. The air quality in China deteriorated drastically: the PM 10 (PM < 10 µ m in aerodynamic diameter) concentrations measured at some air quality stations located in northern China reached 4333 µ g m -3. At the AOE_Baotou, Beijing, Xuzhou-CUMT, and Ussuriysk AERONET sites, the maximum aerosol optical depth values reached 2.96, 2.13, 2.87, and 0.65 and the extinction Ångström exponent dropped to 0.023, 0.068, 0.03, and 0.097, respectively. The dust storm also induced unusual aerosol spectral single-scattering albedo and volume size distribution. [ABSTRACT FROM AUTHOR]