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Evaluation of directly wind‐coherent near‐inertial surface currents off Oregon using a statistical parameterization and analytical and numerical models
Author(s) -
Kim Sung Yong,
Kosro P. Michael,
Kurapov Alexander L.
Publication year - 2014
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1002/2014jc010115
Subject(s) - inertial frame of reference , meteorology , surface (topology) , environmental science , lagrangian coherent structures , statistical physics , physics , mechanics , mathematics , classical mechanics , turbulence , geometry
Directly wind‐coherent near‐inertial surface currents off the Oregon coast are investigated with a statistical parameterization of observations and outputs of a regional numerical ocean model and three one‐dimensional analytical models including the slab layer, Ekman, and near‐surface averaged Ekman models. The transfer functions and response functions, statistically estimated from observed wind stress at NDBC buoys and surface currents derived from shored‐based high‐frequency radars, enable us to isolate the directly wind‐forced near‐inertial surface currents. Concurrent observations of the wind and currents are crucial to evaluate the directly wind‐forced currents. Thus, the wind stress and surface current fields obtained from a regional ocean model, which simulates variability of the wind and surface currents on scales comparable to those in observations, are analyzed with the same statistical parameterization to derive the point‐by‐point transfer functions and response functions. Model and data comparisons show that the regional ocean model describes near‐inertial variability of surface currents qualitatively and quantitatively correctly. The estimated response functions exhibit decay time scales in a range of 3–5 days, and about 40% of the near‐inertial motions are explained by local wind stress. Among the one‐dimensional analytical models, the near‐surface averaged Ekman model explains the statistically derived wind‐current relationship better than other analytical models.