Hyperspectral Estimation of Aerosol Parameters and Water-Leaving-Radiance in Dusty Atmospheres

Abstract

The scientific aims that motivate our work on this project are: (1) to understand quantitatively the multiple-scattering physics underlying spaceborne hyperspectral and lidar observations of atmospheric aerosols and surface reflectivity; (2) to develop rigorous, stable (i.e., genuinely useful) inverse methods to interpret such observations in terms of geophysical quantities, based on the mathematics of inverse radiative transfer; and (3) to apply such methods to gain otherwise unavailable insight into geophysical interactions of the ocean, the atmosphere, and land surfaces. The specific objectives of this project are: (1) to understand quantitatively how the accuracy of dust parameter and ocean color estimates from hyperspectral data depend on knowledge of vertical aerosol distributions and dust particle absorption; (2) to develop improved methods for estimating dust aerosol properties and water-leaving-radiance (WLR) from hyperspectral and limited vertical profile data, including data from the newest generations of NASA (SeaWIFS, MODIS, MISR, and spaceborne lidar) and DoD (COIS/NEMO) sensors; and (3) to demonstrate the initial use of such methods in investigation of dust outbreaks over littoral seas.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1998
Accession Number
ADA551523

Entities

People

  • Dale P. Winehrenner
  • John Sylvester

Organizations

  • University of Washington

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Acquisition
  • Altitude
  • Applied Mathematics
  • Atmospheres
  • Case Studies
  • Data Acquisition
  • Inverse Scattering
  • Mathematics
  • Observation
  • Optical Properties
  • Physics
  • Physics Laboratories
  • Radiance
  • Radiative Transfer
  • Rayleigh Scattering
  • Scattering
  • Space Systems

Fields of Study

  • Environmental science

Readers

  • Atmospheric Remote Sensing.
  • Systems Analysis and Design