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Systematic Scatterometer Wind Errors Near Coastal Mountains.

Thomas Kilpatrick1, Shang-Ping Xie1, Hiroki Tokinaga2

  • 1Scripps Institution of Oceanography University of California San Diego California USA.

Earth and Space Science (Hoboken, N.J.)
|January 3, 2020
PubMed
Summary
This summary is machine-generated.

Satellite scatterometers show wind errors near coasts. Ambiguity removal during processing causes these errors, impacting wind vector accuracy in complex coastal mountain regions.

Keywords:
lee vortexorographic windremote sensingscatterometer

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Area of Science:

  • Oceanography
  • Remote Sensing
  • Meteorology

Background:

  • Satellite scatterometers are crucial for observing ocean surface wind vectors globally.
  • Coastal regions present unique challenges for remote sensing due to complex wind patterns.

Purpose of the Study:

  • To identify and demonstrate systematic errors in satellite scatterometer wind products near coastal mountains.
  • To investigate the cause of these errors, specifically related to ambiguity removal in scatterometer data processing.

Main Methods:

  • Comparison of scatterometer-derived wind climatologies (JPL, RSS) with in-situ data (ICOADS ship data, aircraft observations).
  • Analysis of specific case studies: lee vortices near Hawaii's Big Island and the Catalina Eddy in the Southern California Bight.
  • Examination of the ambiguity removal process in scatterometer wind retrieval.

Main Results:

  • Absence of observed counter-rotating lee vortices near Hawaii's Big Island in scatterometer wind climatologies.
  • Similar underrepresentation of transient Catalina Eddy events in Southern California Bight scatterometer data.
  • Attribution of these errors to the non-uniqueness of scatterometer wind solutions and the ambiguity removal step.

Conclusions:

  • Systematic scatterometer wind errors occur near coastal mountains, impacting the accuracy of wind vector observations.
  • The ambiguity removal process is a likely source of these errors, particularly where small-scale wind reversals are common.
  • Strategies are needed to improve ambiguity selection for more accurate coastal wind remote sensing.