Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean

The atmosphere over the ocean is an important research field that involves multiple aspects such as climate change, atmospheric pollution, weather forecasting, and marine ecosystems. It is of great significance for global sustainable development. Satellites provide a wide range of measurements of marine aerosol optical properties and are very important to the study of aerosol characteristics over the ocean. In this study, aerosol optical depth (AOD) data from seventeen AERONET (Aerosol Robotic Network) stations were used as benchmark data to comprehensively evaluate the data accuracy of six aerosol optical thickness products from 2013 to 2020, including MODIS (Moderate-resolution Imaging Spectrometer), VIIRS (Visible Infrared Imaging Radiometer Suite), MISR (Multi-Angle Imaging Spectrometer), OMAERO (OMI/Aura Multi-wavelength algorithm), OMAERUV (OMI/Aura Near UV algorithm), and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) in the East Asian Ocean. In the East Asia Sea, VIIRS AOD products generally have a higher correlation coefficient (R), expected error within ratio (EE within), lower root mean square error (RMSE), and median bias (MB) than MODIS AOD products. The retrieval accuracy of AOD data from VIIRS is the highest in spring. MISR showed a higher EE than other products in the East Asian Ocean but also exhibited systematic underestimation. In most cases, the OMAERUV AOD product data are of better quality than OMAERO, and OMAERO overestimates AOD throughout the year. The CALIPSO AOD product showed an apparent underestimation of the AOD in different seasons (EE Below = 58.98%), but when the AOD range is small (0 < AOD < 0.1), the CALIPSO data accuracy is higher compared with other satellite products under small AOD range. In the South China Sea, VIIRS has higher data accuracy than MISR, while in the Bohai-Yellow Sea, East China Sea, Sea of Japan, and the western Pacific Ocean, MISR has the best data accuracy. MODIS and VIIRS show similar trends in R, EE within, MB, and RMSE under the influence of AOD, Angstrom exponent (AE), and precipitable water. The study on the temporal and spatial distribution of AOD in the East Asian Ocean shows that the annual variation of AOD is different in different sea areas, and the ocean in the coastal area is greatly affected by land-based pollution. In contrast, the AOD values in the offshore areas are lower, and the aerosol type is mainly clean marine type aerosol. These findings can help researchers in the East Asian Ocean choose the most accurate and reliable satellite AOD data product to better study atmospheric aerosols' impact and trends.

Investigation of June 2020 giant Saharan dust storm using remote sensing observations and model reanalysis

This paper investigates the characteristics and impact of a major Saharan dust storm during June 14th–19th 2020 on atmospheric radiative and thermodynamics properties over the Atlantic Ocean. The event witnessed the highest ever aerosol optical depth for June since 2002. The satellites and high-resolution model reanalysis products well captured the origin and spread of the dust storm. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measured total attenuated backscatter and aerosol subtype profiles, lower angstrom exponent values (~ 0.12) from Modern-Era Retrospective Analysis for Research and Application—version 2 (MERRA-2) and higher aerosol index value from Ozone monitoring instrument (> 4) tracked the presence of elevated dust. It was found that the dust AOD was as much as 250–300% higher than their climatology resulting in an atmospheric radiative forcing ~ 200% larger. As a result, elevated warming (8–16%) was observed, followed by a drop in relative humidity (2–4%) in the atmospheric column, as evidenced by both in-situ and satellite measurements. Quantifications such as these for extreme dust events provide significant insights that may help in understanding their climate effects, including improvements to dust simulations using chemistry-climate models.

Recent Increase in Winter Hazy Days over Central India and the Arabian Sea

Indian subcontinent is greatly vulnerable to air pollution, especially during the winter season. Here, we use 15 years (2003-2017) of satellite and model reanalysis datasets over India and adjoining Seas to estimate the trend in hazy days (i.e. days with high aerosol loading) during the dry winter season (November to February). The number of hazy days is increasing at the rate of ~2.6 days per year over Central India. Interestingly, this is higher than over the Indo-Gangetic Plain (~1.7 days/year), a well known global hotspot of particulate pollution. Consistent increasing trends in absorbing aerosols are also visible in the recent years. As a result, the estimated atmospheric warming trends over Central India are two-fold higher than that over Indo-Gangetic Plain. This anomalous increment in hazy days over Central India is associated with the relatively higher increase in biomass burning over the region. Moreover, the trend in aerosol loading over the Arabian Sea, which is located downwind to Central India, is also higher than that over the Bay of Bengal during the dry winter season. Our findings not only draw attention to the rapid deteriorating air quality over Central India, but also underline the significance of increasing biomass burning under the recent climate change.

Validation of MODIS-Aqua Aerosol Products C051 and C006 over the Beijing-Tianjin-Hebei Region

The recently released MODerate resolution Imaging Spectroradiometers (MODIS) Collection 6(C006) includes several significant improvements, which are expected to do well in analyzing aerosols and using the observations for air pollution application. The C006 Aerosol Optical Depth (AOD) retrievals should be validated completely before they will be applied to specific research. However, the validation of C006 AOD retrievals at a regional scale is limited. Therefore, this study evaluated the performance of the MODIS-Aqua Collection 51 (C051) and C006 AOD retrievals over the Beijing-Tianjin-Hebei region in China from 2006 to 2015 using ground-based Sun photometers. The algorithms of the AOD product include Dark Target (DT) and Deep Blue (DB). The results indicated that the improvements in DT C006 were slight, as the expected error (EE) increased by almost 9% over the two sites, and the DT C051 and DT C006 AOD were overestimated for both sites. DB C006 presented an improvement over DB C051, and a better correlation was observed between the collocated DB C006 retrievals and Sun photometer data (R ranged from 0.9343–0.9383). There was an increase in the frequency from DT C051 to DT C006, in the range 0.6–1.5, over the two sites; moreover, the AOD from the DB retrievals had a very narrow range (0.1–0.3). The spatial distribution of the AOD values was high (AOD > 0.7) over the southeastern region and low (AOD < 0.3) over the northwestern region. Changes in the DT C006 algorithm resulted in an increased AOD (0.085) for the region. The AOD values in spring and summer were higher than those in fall and winter. By subtracting the C051 AOD from the corresponding C006 values, greater positive changes (~0.2) were found in the southeastern areas during summer, presumably as the updated cloud-masking allowed heavy smoke retrievals. The accuracy of the AOD retrievals depended on the assumptions of surface reflectance and the selection of the aerosol model. The use of the DB C006 algorithm is recommended for the Beijing and Xianghe sites. Because of the limitations of the DT algorithm over sparsely vegetated surfaces, the DT C006 product is recommended for Xianghe.

Utilization of O4 slant column density to derive aerosol layer height from a spaceborne UV-Visible hyperspectral sensor: Sensitivity and case study

The sensitivities of oxygen-dimer (O₄) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the Linearlized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O₄ SCD by 10⁴⁰ molecules²cm^-5, to aerosol types and optical properties are also evaluated and compared. Among the O₄ absorption bands at 340, 360, 380, and 477 nm, the O₄ absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80% of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.