Editorial Type:
Article
Article Type:
Research Article

Bulk versus Spectral Wave Parameters: Implications on Stokes Drift Estimates, Regional Wave Modeling, and HF Radars Applications

Nirnimesh Kumar Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

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Douglas L. Cahl School of the Earth, Ocean and Environment, University of South Carolina, Columbia, South Carolina

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Sean C. Crosby Integrative Oceanography Division, Scripps Institution of Oceanography, La Jolla, California

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George Voulgaris School of the Earth, Ocean and Environment, University of South Carolina, Columbia, South Carolina

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Print Publication:
01 Jun 2017
DOI:
https://doi.org/10.1175/JPO-D-16-0203.1
Page(s):
1413–1431
Restricted access

Abstract

Accurate estimates of Stokes drift are necessary to quantify Lagrangian transport and upper-ocean mixing. These can be estimated from directional wave spectra. Here, a methodology for the reconstruction of such spectra is developed using partitioned bulk wave parameters provided by global wave models. These reconstructed spectra agree well with global wave model–simulated full spectra. Regional wave model simulations with reconstructed spectra as open boundary conditions lead to more accurate estimates of bulk wave parameters in the coastal ocean. Furthermore, the reconstructed directional spectra can be used to improve high-frequency (HF) radar–derived surface Lagrangian current estimates. Stokes drift vertical profiles from complete directional spectra are more accurate, and therefore coupled ocean circulation and wave models should incorporate spectral estimates for wave–current interaction studies. Based on model simulations conducted here, it is recommended that regional wave modeling studies use partitioned rather than bulk wave parameter products from global wave simulations to reconstruct complete directional spectra for open boundary conditions. Finally, this study shows that inclusion of the peak spectral energy for each partition improves the ability to reconstruct more accurately directional spectra and surface Stokes drift. It is recommended that the global wave model hindcast/forecast include this additional bulk parameter.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: N. Kumar, nirni@uw.edu

Abstract

Accurate estimates of Stokes drift are necessary to quantify Lagrangian transport and upper-ocean mixing. These can be estimated from directional wave spectra. Here, a methodology for the reconstruction of such spectra is developed using partitioned bulk wave parameters provided by global wave models. These reconstructed spectra agree well with global wave model–simulated full spectra. Regional wave model simulations with reconstructed spectra as open boundary conditions lead to more accurate estimates of bulk wave parameters in the coastal ocean. Furthermore, the reconstructed directional spectra can be used to improve high-frequency (HF) radar–derived surface Lagrangian current estimates. Stokes drift vertical profiles from complete directional spectra are more accurate, and therefore coupled ocean circulation and wave models should incorporate spectral estimates for wave–current interaction studies. Based on model simulations conducted here, it is recommended that regional wave modeling studies use partitioned rather than bulk wave parameter products from global wave simulations to reconstruct complete directional spectra for open boundary conditions. Finally, this study shows that inclusion of the peak spectral energy for each partition improves the ability to reconstruct more accurately directional spectra and surface Stokes drift. It is recommended that the global wave model hindcast/forecast include this additional bulk parameter.

Denotes content that is immediately available upon publication as open access.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: N. Kumar, nirni@uw.edu
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