Comparison of forms of the viscous shallow-water equations in the boundary-fitted coordinates

Romanenkov, Dmitriy A.; Androsov, A.A.; Voltzinger, N.

doi:10.1016/s1463-5003(01)00008-7

Cited by 6 publications

(3 citation statements)

References 23 publications

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“…The formation of oceanic convection cells due to local cooling at the surface can be simulated by a numerical hydrostatic/nonhydrostatic convection model, following the approach of Mahadevan et al [1996], Androsov et al [2001], Romanenkov et al [2001], and Androsov et al [2002]. The model implemented at the University of Hamburg, which is called GNOM (General Nonhydrostatic Ocean Model), is a high‐resolution, nonlinear, three‐dimensional hydrostatic/nonhydrostatic model.…”

Section: Interpretation Of Radar Signatures Of Oceanic and Atmospherimentioning

confidence: 99%

On the remote sensing of oceanic and atmospheric convection in the Greenland Sea by synthetic aperture radar

Romeiser¹,

Ufermann

Androssov³

et al. 2004

J. Geophys. Res.

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[1] In this paper we discuss characteristic properties of radar signatures of oceanic and atmospheric convection features in the Greenland Sea. If the water surface is clean (no surface films or ice coverage), oceanic and atmospheric features can become visible in radar images via a modulation of the surface roughness, and their radar signatures can be very similar. For an unambiguous interpretation and for the retrieval of quantitative information on current and wind variations from radar imagery with such signatures, theoretical models of current and wind phenomena and their radar imaging mechanisms must be utilized. We demonstrate this approach with the analysis of some synthetic aperture radar (SAR) images acquired by the satellites ERS-2 and RADARSAT-1. In one case, an ERS-2 SAR image and a RADARSAT-1 ScanSAR image exhibit pronounced cell-like signatures with length scales on the order of 10-20 km and modulation depths of about 5-6 dB and 9-10 dB, respectively. Simulations with a numerical SAR imaging model and various input current and wind fields reveal that the signatures in both images can be explained consistently by wind variations on the order of ±2.5 m/s, but not by surface current variations on realistic orders of magnitude. Accordingly, the observed features must be atmospheric convection cells. This is confirmed by visible typical cloud patterns in a NOAA AVHRR image of the test scenario. In another case, the presence of an oceanic convective chimney is obvious from in situ data, but no signatures of it are visible in an ERS-2 SAR image. We show by numerical simulations with an oceanic convection model and our SAR imaging model that this is consistent with theoretical predictions, since the current gradients associated with the observed chimney are not sufficiently strong to give rise to significant signatures in an ERS-2 SAR image under the given conditions. Further model results indicate that it should be generally difficult to observe oceanic convection features in the Greenland Sea with ERS-2 or RADARSAT-1 SAR, since their signatures resulting from pure wave-current interaction will be too weak to become visible in the noisy SAR images in most cases. This situation will improve with the availability of future high-resolution SARs such as RADARSAT-2 SAR in fine resolution mode (2004) and TerraSAR-X (2005), which will offer significantly reduced speckle noise fluctuations at comparable spatial resolutions and thus a much better visibility of small image intensity variations on spatial scales on the order of a few hundred meters.

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Section: Interpretation Of Radar Signatures Of Oceanic and Atmospherimentioning

confidence: 99%

On the remote sensing of oceanic and atmospheric convection in the Greenland Sea by synthetic aperture radar

Romeiser¹,

Ufermann

Androssov³

et al. 2004

J. Geophys. Res.

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“…Recent works of Li and Zhan [11] and Shi et al [12] on improved Boussinesq models in boundary-fitted coordinates are notable exceptions to non-dispersive wave models. Romanenkov et al [13] investigated the advantages and disadvantages of different velocity variables and grids in viscous shallow-water equations, and, quite recently, Sankaranarayanan and Spaulding [14] studied the effects of grid non-orthogonality on the numerical results obtained from the shallow water equations in boundary-fitted coordinate systems.…”

Section: Introductionmentioning

confidence: 99%

Fully dispersive nonlinear water wave model in curvilinear coordinates

Beji¹,

Nadaoka²

2004

Journal of Computational Physics

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“…Li and Zhan's [10] work on an improved Boussinesq model in boundary-ÿtted co-ordinates may be considered as a notable exception to non-dispersive wave models. Romanenkov et al [11] investigated the e ects of using di erent velocity variables in viscous shallow-water equations, and, quite recently, Sankaranarayanan and Spaulding [12] studied the e ects of grid non-orthogonality on the solution of shallow water equations in boundary-ÿtted co-ordinate systems.…”

Section: Introductionmentioning

confidence: 99%

Boundary‐fitted non‐linear dispersive wave model for regions of arbitrary geometry

Beji

Barlas

2004

Numerical Methods in Fluids

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SUMMARYA vertically integrated non-linear dispersive wave model is expressed in non-orthogonal curvilinear coordinate system for simulating shallow or deep water wave motions in regions of arbitrary geometry. Both dependent and independent variables are transformed so that an irregular physical domain is converted into a rectangular computational domain with contravariant velocities. Thus, the wall condition for enclosures surrounding a typical physical domain, such as a channel, port or harbor, is satisÿed accurately and easily. The numerical scheme is based on staggered grid ÿnite-di erence approximations, which result in implicit formulations for the momentum equations and semi-explicit formulation for the continuity equation. Test cases of linear wave propagation in converging, diverging and circular channels are performed to check the reliability of model simulations against the analytical solutions. Cnoidal waves of di erent steepness values in a circular channel are also considered as examples to non-linear wave propagation within curved walls. In closing, remarks concerning versatility and practical uses of the numerical model are made.

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Comparison of forms of the viscous shallow-water equations in the boundary-fitted coordinates

Cited by 6 publications

References 23 publications

On the remote sensing of oceanic and atmospheric convection in the Greenland Sea by synthetic aperture radar

On the remote sensing of oceanic and atmospheric convection in the Greenland Sea by synthetic aperture radar

Fully dispersive nonlinear water wave model in curvilinear coordinates

Boundary‐fitted non‐linear dispersive wave model for regions of arbitrary geometry

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