Literature DB >> 29963346

AERONET-based nonspherical dust optical models and effects on the VIIRS Deep Blue/SOAR over-water aerosol product.

Jaehwa Lee1,2, N Christina Hsu1, Andrew M Sayer1,3, Corey Bettenhausen1,4, Ping Yang5.   

Abstract

Aerosol Robotic Network (AERONET)-based nonspherical dust optical models are developed and applied to the Satellite Ocean Aerosol Retrieval (SOAR) algorithm as part of the Version 1 Visible Infrared Imaging Radiometer Suite (VIIRS) NASA 'Deep Blue' aerosol data product suite. The optical models are created using Version 2 AERONET inversion data at six distinct sites influenced frequently by dust aerosols from different source regions. The same spheroid shape distribution as used in the AERONET inversion algorithm is assumed to account for the nonspherical characteristics of mineral dust, which ensures the consistency between the bulk scattering properties of the developed optical models with the AERONET-retrieved microphysical and optical properties. For the Version 1 SOAR aerosol product, the dust optical models representative for Capo Verde site are used, considering the strong influence of Saharan dust over the global ocean in terms of amount and spatial coverage. Comparisons of the VIIRS-retrieved aerosol optical properties against AERONET direct-Sun observations at three island/coastal sites suggest that the use of nonspherical dust optical models significantly improves the retrievals of aerosol optical depth (AOD) and Ångström exponent by mitigating the well-known artifact of scattering angle dependence of the variables observed when incorrectly assuming spherical dust. The resulting removal of these artifacts results in a more natural spatial pattern of AOD along the transport path of Saharan dust to the Atlantic Ocean; i.e., AOD decreases with increasing distance transported, whereas the spherical assumption leads to a strong wave pattern due to the spurious scattering angle dependence of AOD.

Entities:  

Year:  2017        PMID: 29963346      PMCID: PMC6022739          DOI: 10.1002/2017jd027258

Source DB:  PubMed          Journal:  J Geophys Res Atmos        ISSN: 2169-897X            Impact factor:   4.261


  5 in total

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Journal:  Science       Date:  2013-05-09       Impact factor: 47.728

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  5 in total
  2 in total

1.  Satellite Ocean Aerosol Retrieval (SOAR) algorithm extension to S-NPP VIIRS as part of the 'Deep Blue' aerosol project.

Authors:  A M Sayer; N C Hsu; J Lee; C Bettenhausen; W V Kim; A Smirnov
Journal:  J Geophys Res Atmos       Date:  2017-11-17       Impact factor: 4.261

2.  Evaluation of NASA Deep Blue/SOAR aerosol retrieval algorithms applied to AVHRR measurements.

Authors:  A M Sayer; N C Hsu; J Lee; N Carletta; S-H Chen; A Smirnov
Journal:  J Geophys Res Atmos       Date:  2017-07-20       Impact factor: 4.261

  2 in total

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