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Atmospheric Correction for the NPP VIIRS Ocean Color EDRs

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Title: Atmospheric Correction for the NPP VIIRS Ocean Color EDRs


1
 Atmospheric Correction for the NPP VIIRS Ocean
Color EDRs 
  • Menghua Wang
  • University of Maryland Baltimore County
  • NASA Goddard Space Flight Center, Code
    970.2Greenbelt, MD 20771, USA
  • NPP Science Team Meeting
  • November 4-6, 2003, Annapolis, Maryland  

2
Atmospheric Correction
Atmospheric Correction Algorithm (Gordon Wang,
1994)
  • rw is the desired quantity in ocean color
    remote sensing the VIIRS ocean color EDRs.
  • Trg is the sun glint contribution
    avoided/masked and residual contamination is
    corrected.
  • trwc is the whitecap reflectance computed from
    wind speed.
  • rr is the scattering from molecules computed
    using the Rayleigh lookup tables.
  • ?A ra rra is the aerosol and Rayleigh-aerosol
    contributions estimated using aerosol models.

3
Examples of the TOA Reflectance
4
Validation Results from SeaWiFS
http//seawifs.gsfc.nasa.gov/SEAWIFS
5
Chlorophyll Results from SeaWiFS
http//seawifs.gsfc.nasa.gov/SEAWIFS
6
EDR/CDR List
  • The spectrum of water-leaving radiances (the
    ocean color EDRs).
  • The necessary vicarious calibration technique for
    the ocean color EDRs.
  • The band ratio values of the water-leaving
    radiance spectrum that are used for deriving the
    chlorophyll concentration and other ocean
    bio-optical EDRs.
  • Possibly look into the chlorophyll and ocean
    optical property EDRs.
  • Aerosol optical property data over ocean, which
    are derived as by-products from the atmospheric
    correction (results may be useful for evaluation
    of the aerosol EDRs).

7
Roles of PI and Co-I
  • Menghua Wang will assume the overall
    responsibility for the project, and may get an
    assistant for helps in data analyses.
  • radiative transfer modeling, ocean color remote
    sensing, remote retrievals and in situ
    measurements of aerosol optical and microphysical
    properties, calibration and validation
    techniques, and data merging methods for various
    satellite remote sensors.
  • Interested in and welcome collaborations from NPP
    PIs and Co-Is, and Northrop Grumman Space
    Technologies (NGST).

8
Approach
  • Assessment of spatial and temporal uncertainties
    of the ocean color EDRs that are processed using
    the VIIRS atmospheric correction algorithm.
    These include evaluation of the algorithm for
  • the instrument polarization sensitivity
  • algorithm performance in the coastal regions
    (e.g., absorbing aerosols, Case-II waters)
  • effects of ancillary data variability
  • solar-sensor geometry (e.g., high latitude
    regions, Earth curvature effects)
  • and some other effects, e.g., aerosol models
  • Evaluation of the vicarious calibration with
    various spatial and temporal uncertainties and
    some other effects.

9
Resources Offered/Requested
  • Studies will be carried out using both the
    simulated and satellite data, e.g., measurements
    from MODIS and SeaWiFS. Experiences and lessons
    learned from the MODIS and SeaWiFS ocean color
    missions are extremely useful for the NPP
    project.
  • In situ data from the SeaBAS (SeaWiFS Bio-Optical
    Archive and Storage System) and from other data
    sources are planned for use.
  • The data analyses for SeaWiFS and MODIS can be
    achieved using the SeaDAS (SeaWiFS Data Analysis
    System) software, which is freely available and
    widely distributed.
  • Assume computer resources and necessary supplies
    are provided through NASA/GSFC.

10
Contribution to Deliverables
  • It is expected that all analysis results,
    algorithm sensitivity studies, and proposed
    algorithm improvements will be published in
    peer-reviewed journals and/or in technical
    reports.
  • Studies using the MODIS and SeaWiFS data are
    particularly important and useful.
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