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Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
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Atmospheric correction over case 2 waters with an iterative fitting algorithm: relative humidity effects.

P E Land1, J D Haigh

  • 1Department of Space and Atmospheric Physics, Imperial College, London SW7 2BZ, United Kingdom.

Applied Optics
|February 12, 2008
PubMed
Summary
This summary is machine-generated.

This study improves atmospheric correction algorithms for satellite ocean color data. By accounting for aerosol components and humidity, it better separates water and aerosol spectral signals, enhancing accuracy over Case 2 waters.

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Area of Science:

  • Earth and Atmospheric Sciences
  • Remote Sensing
  • Oceanography

Background:

  • Standard atmospheric correction algorithms for satellite imagery often assume a simple Angström power law for aerosol optical depth, which is insufficient for complex environments.
  • This assumption can lead to errors in ocean color data, misattributing water spectral properties to aerosol variations, particularly in Case 2 waters.

Purpose of the Study:

  • To enhance atmospheric correction algorithms for satellite ocean color imagery.
  • To improve the retrieval of aerosol properties and spectral unmixing of water constituents in Case 2 waters.
  • To address limitations of the Angström power law assumption in aerosol spectral variation.

Main Methods:

  • Developed an iterative fitting algorithm that calculates spectral optical depth based on aerosol type and relative humidity.
  • Treated aerosols as mixtures of components (e.g., soot) rather than broad types (e.g., urban).
  • Attempted to retrieve relative humidity alongside aerosol type.

Main Results:

  • The improved algorithm demonstrated enhanced performance over previous methods using simulated Case 1 and Case 2 data.
  • The new approach better distinguishes spectral effects caused by water constituents from those caused by aerosols.
  • The retrieval of relative humidity was not successfully achieved in this study.

Conclusions:

  • The refined algorithm offers a more accurate method for atmospheric correction of ocean color imagery, especially in optically complex Case 2 waters.
  • Modeling aerosols as component mixtures and incorporating relative humidity improves spectral unmixing.
  • Further research is needed to successfully retrieve relative humidity for even more robust atmospheric correction.