On the retrieval of aerosol optical depth over cryosphere using passive remote sensing
Earth and related Environmental sciences
Aerosol optical depth
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The lack of aerosol information over the cryosphere introduces large uncertainties to our understanding of phenomenon, known as the Arctic Amplification (AA) and its feedback mechanisms. The aerosol optical depth (AOD) describes the optical characteristics of aerosol loading. This paper describes a novel algorithm, which retrieves AOD above snow-covered regions from the measurements of the up-welling radiation at the top of atmosphere, observed by the Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature Radiometer (SLSTR) instruments. The algorithm optimizes the generic eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) approach for longer wavelengths over the cryosphere. The algorithm utilizes the characteristics of solar bidirectional distribution properties of snow and aerosol at wavelength 3.7 μm to derive above-snow-AOD. Since the impact of fine-mode aerosol on 3.7 μm is ignorable, the retrieved AOD in this manuscript represents mainly coarse-mode dominated part. A novel method to extract the solar reflection part at 3.7 μm is presented and used in the surface parameterization. Two aerosol types (sea salt-dominated and dust-dominated) are used and the best-fit type is derived by an iterative procedure, using a Look-Up-Table (LUT) approach. Sensitivity studies of the impact on the retrieved AOD using XBAER algorithm, which investigate the impacts of aerosol type, snow surface emissivity and potential cloud contamination under typical AATSR observation conditions, are presented. The sensitivity studies show that the surface parametrization and aerosol typing are suitable for the retrieval of above-snow-AOD over the Arctic snow-covered region. AOD observations retrieved in this study from AATSR (2002–2012) observation collocated with those from the Aerosol Robotic Network (AERONET) sites over Greenland show good agreement. 72.1% of the match-ups fall into the expected error envelope of (±0.15AOD ± 0.025). The AATSR derived above-snow-AOD at 0.55 μm research product has also been compared with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) aerosol product, the Mineral Aerosols Profiling from Infrared Radiances (MAPIR) derived Infrared Atmospheric Sounding Interferometer (IASI) AOD research product, and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) AOD simulations over Greenland on April 2011. The comparison reveals that all datasets show similar patterns for the AOD above Greenland. The AOD is smaller in central Greenland and larger over the coastline regions. The XBAER derived above-snow-AOD has improved coverage, as compared to that of the existing AATSR aerosol product. The transition between above-snow-AOD and AOD derived over surrounding ocean surfaces does not indicate any systematic errors. Two aerosol transport events have been well-captured by the XBAER derived above-snow-AOD research product. The new algorithm is also applied to the SLSTR onboard Sentinel-3 demonstrating new SLSTR above-snow-AOD data products, and its value for research in the changing AOD during the period of Arctic Amplification.
CitationMei, L.; Vandenbussche, S.; Rozanov, V.; Proestakis, E.; Amiridis, V.; Callewaert, S.; Vountas, M.; Burrows, J.P. (2020). On the retrieval of aerosol optical depth over cryosphere using passive remote sensing. , Remote Sensing of Environment, Vol. 241, A111731, DOI: 10.1016/j.rse.2020.111731.