Sea surface wind speed estimation from space-based lidar measurements

Yongxiang Hu,K. Stamnes,M. Vaughan,J. Pelon,C. Weimer,Dong L. Wu,M. Cisewski,Wenbo Sun,Ping Yang,B. Lin,A. Omar,D. Flittner,C. Hostetler,C. Trepte,D. Winker,G. Gibson,M. Santa-Maria

Published 2008 in Atmospheric Chemistry and Physics

ABSTRACT

Global satellite observations of lidar backscatter measurements acquired by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission and collocated sea surface wind speed data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), are used to investigate the relation between wind driven wave slope variance and sea surface wind speed. The new slope variance – wind speed relation established from this study is similar to the linear relation from Cox-Munk (1954) and the log-linear relation from Wu (1990) for wind speed larger than 7 m/s and 13.3 m/s, respectively. For wind speed less than 7 m/s, the slope variance is proportional to the square root of the wind speed, assuming a two dimensional isotropic Gaussian wave slope distribution. This slope variance – wind speed relation becomes linear if a one dimensional Gaussian wave slope distribution and linear slope variance – wind speed relation are assumed. Contributions from whitecaps and subsurface backscattering are effectively removed by using 532 nm lidar depolarization measurements. This new slope variance – wind speed relation is used to derive sea surface wind speed from CALIPSO single shot lidar measurements (70 m spot size), after correcting for atmospheric attenuation. The CALIPSO wind speed result agrees with the collocated AMSR-E wind speed, with 1.2 m/s rms error. Ocean surface with lowest atmospheric loading and moderate wind speed (7–9 m/s) is used as target for lidar calibration correction.

PUBLICATION RECORD

  • Publication year

    2008

  • Venue

    Atmospheric Chemistry and Physics

  • Publication date

    2008-07-08

  • Fields of study

    Geology, Physics, Environmental Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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