2014•Journal of Geophysical Research AtmospheresRequires access

Global assessment of OMI aerosol single‐scattering albedo using ground‐based AERONET inversion

Hiren T. Jethva, Omar Torres, Changwoo Ahn

Open publisher page 187 citations

Abstract

Abstract We compare the aerosol single‐scattering albedo (SSA) retrieved by the near‐UV two‐channel algorithm (OMAERUV) applied to the Aura/Ozone Monitoring Instrument (OMI) measurements with an equivalent inversion made by the ground‐based Aerosol Robotic Network (AERONET). A recent upgrade of the OMAERUV algorithm incorporates a modified carbonaceous aerosol model, a Cloud‐Aerosol Lidar with Orthogonal Polarization‐based aerosol height climatology, and a robust aerosol‐type identification. This paper is the first comprehensive effort to globally compare the OMI‐retrieved SSA with that of AERONET using all available sites spanning the regions of biomass burning, dust, and urban pollution. An analysis of the colocated retrievals over 269 sites reveals that about 46% (69%) of OMI‐AERONET matchups agree within the absolute difference of ±0.03 (±0.05) for all aerosol types. The comparison improves to 52% (77%) when only “smoke” and “dust” aerosol types were identified by the OMAERUV algorithm. Regionally, the agreement between the two inversions was robust over the biomass burning sites of South America, Sahel, Indian subcontinent, and oceanic/coastal sites followed by a reasonable agreement over Northeast Asia. Over the desert regions, OMI tends to retrieve higher SSA, particularly over the Arabian Peninsula. Globally, the OMI‐AERONET matchups agree mostly within ±0.03 for the aerosol optical depth (440 nm) and UV‐aerosol index larger than 0.4 and 1.0, respectively. Possible sources of uncertainty in the OMI retrieval can be the subpixel cloud contamination, assumptions of the surface albedo, and spectral aerosol absorption. We expect further refinement in the OMAERUV algorithm which stands uniquely in characterizing aerosol absorption from space.

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What this paper is about

Abstract We compare the aerosol single‐scattering albedo (SSA) retrieved by the near‐UV two‐channel algorithm (OMAERUV) applied to the Aura/Ozone Monitoring Instrument (OMI) measurements with an equivalent inversion made by the ground‐based Aerosol Robotic Network (AERONET). A recent upgrade of the OMAERUV algorithm incorporates a modified carbonaceous aerosol model, a Cloud‐Aerosol Lidar with Orthogonal Polarization‐based aerosol height climatology, and a robust aerosol‐type identification. This paper is the first comprehensive effort to globally compare the OMI‐retrieved SSA with that of AERONET using all available sites spanning the regions of biomass burning, dust, and urban pollution. An analysis of the colocated retrievals over 269 sites reveals that about 46% (69%) of OMI‐AERONET matchups agree within the absolute difference of ±0.03 (±0.05) for all aerosol types. The comparison improves to 52% (77%) when only “smoke” and “dust” aerosol types were identified by the OMAERUV algorithm. Regionally, the agreement between the two inversions was robust over the biomass burning sites of South America, Sahel, Indian subcontinent, and oceanic/coastal sites followed by a reasonable agreement over Northeast Asia. Over the desert regions, OMI tends to retrieve higher SSA, particularly over the Arabian Peninsula. Globally, the OMI‐AERONET matchups agree mostly within ±0.03 for the aerosol optical depth (440 nm) and UV‐aerosol index larger than 0.4 and 1.0, respectively. Possible sources of uncertainty in the OMI retrieval can be the subpixel cloud contamination, assumptions of the surface albedo, and spectral aerosol absorption. We expect further refinement in the OMAERUV algorithm which stands uniquely in characterizing aerosol absorption from space.

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Available abstract

Abstract We compare the aerosol single‐scattering albedo (SSA) retrieved by the near‐UV two‐channel algorithm (OMAERUV) applied to the Aura/Ozone Monitoring Instrument (OMI) measurements with an equivalent inversion made by the ground‐based Aerosol Robotic Network (AERONET). A recent upgrade of the OMAERUV algorithm incorporates a modified carbonaceous aerosol model, a Cloud‐Aerosol Lidar with Orthogonal Polarization‐based aerosol height climatology, and a robust aerosol‐type identification. This paper is the first comprehensive effort to globally compare the OMI‐retrieved SSA with that of AERONET using all available sites spanning the regions of biomass burning, dust, and urban pollution. An analysis of the colocated retrievals over 269 sites reveals that about 46% (69%) of OMI‐AERONET matchups agree within the absolute difference of ±0.03 (±0.05) for all aerosol types. The comparison improves to 52% (77%) when only “smoke” and “dust” aerosol types were identified by the OMAERUV algorithm. Regionally, the agreement between the two inversions was robust over the biomass burning sites of South America, Sahel, Indian subcontinent, and oceanic/coastal sites followed by a reasonable agreement over Northeast Asia. Over the desert regions, OMI tends to retrieve higher SSA, particularly over the Arabian Peninsula. Globally, the OMI‐AERONET matchups agree mostly within ±0.03 for the aerosol optical depth (440 nm) and UV‐aerosol index larger than 0.4 and 1.0, respectively. Possible sources of uncertainty in the OMI retrieval can be the subpixel cloud contamination, assumptions of the surface albedo, and spectral aerosol absorption. We expect further refinement in the OMAERUV algorithm which stands uniquely in characterizing aerosol absorption from space.

Key concepts: AERONET, Aerosol, Single-scattering albedo, Ozone Monitoring Instrument, Environmental science, Albedo (alchemy), Atmospheric sciences, Angstrom exponent

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