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The long-period tides are a tool for understanding oceanic motions at low frequencies and large scales. Here we review observations and theory of the fortnightly, monthly and pole tide constitutents. Observations have been plagued by low signal-to-noise ratios and theory by the complex lateral geometry and great sensitivity to bottom slopes. A new spectral element model is used to compute the oceanic response to tidal forcing at 2-week and monthly periods. The general response is that of a heavily damped (Q ≈ 5) system with both the energy input from the moon and the dissipation strongly localized in space. The high dissipation result is probably generally applicable to all low frequency barotropic oceanic motions. Over much of the ocean, the response has both the character of a large-scale and a superposed Rossby wave-like character, thus vindicating two apparently conflicting earlier interpretations. To the extent that free waves are excited they are consistent with their being dominated by Rossby and topographic Rossby wave components, although gravity modes are also necessarily excited to some degree. In general, a modal representation is not very helpful. The most active regions are the Southern Ocean and the western and northern North Atlantic. These results are stable to changes in geometry, topography, and tide period. On a global average basis, the dynamical response of Mm is closer to equilibrium than is Mf. 相似文献
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Alen Alexanderian Justin Winokur Ihab Sraj Ashwanth Srinivasan Mohamed Iskandarani William C. Thacker Omar M. Knio 《Computational Geosciences》2012,16(3):757-778
Polynomial chaos (PC) expansions are used to propagate parametric uncertainties in ocean global circulation model. The computations
focus on short-time, high-resolution simulations of the Gulf of Mexico, using the hybrid coordinate ocean model, with wind
stresses corresponding to hurricane Ivan. A sparse quadrature approach is used to determine the PC coefficients which provides
a detailed representation of the stochastic model response. The quality of the PC representation is first examined through
a systematic refinement of the number of resolution levels. The PC representation of the stochastic model response is then
utilized to compute distributions of quantities of interest (QoIs) and to analyze the local and global sensitivity of these
QoIs to uncertain parameters. Conclusions are finally drawn regarding limitations of local perturbations and variance-based
assessment and concerning potential application of the present methodology to inverse problems and to uncertainty management. 相似文献
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A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database 总被引：1，自引：0，他引：1
Justin Winokur Patrick Conrad Ihab Sraj Omar Knio Ashwanth Srinivasan W. Carlisle Thacker Youssef Marzouk Mohamed Iskandarani 《Computational Geosciences》2013,17(6):899-911
This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting. 相似文献
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Guotu Li Mohamed Iskandarani Matthieu Le Hénaff Justin Winokur Olivier P. Le Maître Omar M. Knio 《Computational Geosciences》2016,20(5):1133-1153
This study aims at analyzing the combined impact of uncertainties in initial conditions and wind forcing fields in ocean general circulation models (OGCM) using polynomial chaos (PC) expansions. Empirical orthogonal functions (EOF) are used to formulate both spatial perturbations to initial conditions and space-time wind forcing perturbations, namely in the form of a superposition of modal components with uniformly distributed random amplitudes. The forward deterministic HYbrid Coordinate Ocean Model (HYCOM) is used to propagate input uncertainties in the Gulf of Mexico (GoM) in spring 2010, during the Deepwater Horizon oil spill, and to generate the ensemble of model realizations based on which PC surrogate models are constructed for both localized and field quantities of interest (QoIs), focusing specifically on sea surface height (SSH) and mixed layer depth (MLD). These PC surrogate models are constructed using basis pursuit denoising methodology, and their performance is assessed through various statistical measures. A global sensitivity analysis is then performed to quantify the impact of individual modes as well as their interactions. It shows that the local SSH at the edge of the GoM main current—the Loop Current—is mostly sensitive to perturbations of the initial conditions affecting the current front, whereas the local MLD in the area of the Deepwater Horizon oil spill is more sensitive to wind forcing perturbations. At the basin scale, the SSH in the deep GoM is mostly sensitive to initial condition perturbations, while over the shelf it is sensitive to wind forcing perturbations. On the other hand, the basin MLD is almost exclusively sensitive to wind perturbations. For both quantities, the two sources of uncertainty have limited interactions. Finally, the computations indicate that whereas local quantities can exhibit complex behavior that necessitates a large number of realizations, the modal analysis of field sensitivities can be suitably achieved with a moderate size ensemble. 相似文献
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Multiscale modeling of coastal, shelf, and global ocean dynamics 总被引：1，自引：1，他引：0
Pierre F. J. Lermusiaux Jens Schröter Sergey Danilov Mohamed Iskandarani Nadia Pinardi Joannes J. Westerink 《Ocean Dynamics》2013,63(11-12):1341-1344
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We present the derivation of the discrete Euler–Lagrange equations for an inverse spectral element ocean model based on the shallow water equations. We show that the discrete Euler–Lagrange equations can be obtained from the continuous Euler–Lagrange equations by using a correct combination of the weak and the strong forms of derivatives in the Galerkin integrals, and by changing the order with which elemental assembly and mass averaging are applied in the forward and in the adjoint systems. Our derivation can be extended to obtain an adjoint for any Galerkin finite element and spectral element system.We begin the derivations using a linear wave equation in one dimension. We then apply our technique to a two-dimensional shallow water ocean model and test it on a classic double-gyre problem. The spectral element forward and adjoint ocean models can be used in a variety of inverse applications, ranging from traditional data assimilation and parameter estimation, to the less traditional model sensitivity and stability analyses, and ensemble prediction. Here the Euler–Lagrange equations are solved by an indirect representer algorithm. 相似文献
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