4.7 Article

Observed and modeled drifters at a tidal inlet

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JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
卷 120, 期 7, 页码 4825-4844

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AMER GEOPHYSICAL UNION
DOI: 10.1002/2014JC010541

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资金

  1. NSF
  2. ONR [N00014-13-1-0120]
  3. ASD (R+E)
  4. Division Of Ocean Sciences
  5. Directorate For Geosciences [1357060] Funding Source: National Science Foundation

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Material transport and dispersion near the mouth of a tidal inlet (New River Inlet, NC) are investigated using GPS-tracked drifters and numerical models. For ebb tide releases, velocities are largest (> 1 ms(-1)) in two approximately 30 m wide channels that bisect the 1-3 m deep ebb shoal. In the channels, drifter and subsurface current meter velocities are similar, consistent with strong vertical mixing and 2-D hydrodynamics. Drifters were preferentially entrained in the channelized jets where drifter cluster lateral spreading rates mu(in) were small (mu(in) approximate to 0.5 m(2) s (1)). At the seaward edge of the ebb shoal, jet velocities decrease linearly with distance (to <= 0.2 ms(-1), about 1 km from shore), and cluster spreading rates are larger with mu(out) approximate to 3 m(2) s(-1). Although the models COAWST and NearCom generally reproduce the observed trajectory directions, certain observed drifter properties are poorly modeled. For example, modeled mean drifter velocities are smaller than observed, and upon exiting the inlet, observed drifters turn north more than modeled drifters. The model simulations do reproduce qualitatively the spreading rates observed in the inner inlet, the flow deceleration, and the increase in mu(out) observed in the outer inlet. However, model spreading rates increase only to mu(out) < 1 m(2) s(-1). Smaller modeled than observed mu(out) may result from using unstratified models. Noncoincident (in space) observations show evidence of a buoyant plume (Delta rho = 1 kg m(-3)) in the outer inlet, likely affecting drifter lateral spreading. Generally, drifter-based model performance is good within the inlet channels where tidal currents are strongest, whereas model-data differences are significant farther offshore.

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