Second‐generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance

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  • Robert C. Levy
    Science Systems and Applications Inc. Lanham Maryland USA
  • Lorraine A. Remer
    Laboratory for Atmospheres NASA Goddard Space Flight Center Greenbelt Maryland USA
  • Shana Mattoo
    Science Systems and Applications Inc. Lanham Maryland USA
  • Eric F. Vermote
    Department of Geography University of Maryland College Park Maryland USA
  • Yoram J. Kaufman
    Laboratory for Atmospheres NASA Goddard Space Flight Center Greenbelt Maryland USA

書誌事項

公開日
2007-07-13
権利情報
  • http://onlinelibrary.wiley.com/termsAndConditions#vor
DOI
  • 10.1029/2006jd007811
公開者
American Geophysical Union (AGU)

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説明

<jats:p>Since first light in early 2000, operational global quantitative retrievals of aerosol properties over land have been made from Moderate Resolution Imaging Spectroradiometer (MODIS) observed spectral reflectance. These products have been continuously evaluated and validated, and opportunities for improvements have been noted. We have replaced the surface reflectance assumptions, the set of aerosol model optical properties, and the aerosol lookup table (LUT). This second‐generation operational algorithm performs a simultaneous inversion of two visible (0.47 and 0.66 <jats:italic>μ</jats:italic>m) and one shortwave‐IR (2.12 <jats:italic>μ</jats:italic>m) channel, making use of the coarse aerosol information content contained in the 2.12 <jats:italic>μ</jats:italic>m channel. Inversion of the three channels yields three nearly independent parameters, the aerosol optical depth (<jats:italic>τ</jats:italic>) at 0.55 <jats:italic>μ</jats:italic>m, the nondust or fine weighting (<jats:italic>η</jats:italic>), and the surface reflectance at 2.12 <jats:italic>μ</jats:italic>m. Retrievals of small‐magnitude negative <jats:italic>τ</jats:italic> values (down to −0.05) are considered valid, thus balancing the statistics of <jats:italic>τ</jats:italic> in near zero <jats:italic>τ</jats:italic> conditions. Preliminary validation of this algorithm shows much improved retrievals of <jats:italic>τ</jats:italic>, where the MODIS/Aerosol Robotic Network <jats:italic>τ</jats:italic> (at 0.55 <jats:italic>μ</jats:italic>m) regression has an equation of: y = 1.01x + 0.03, R = 0.90. Global mean <jats:italic>τ</jats:italic> for the test bed is reduced from ∼0.28 to ∼0.21.</jats:p>

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