A parallel domain decomposition algorithm for coastal ocean circulation models based on integer linear programming

This paper presents a new parallel domain decomposition algorithm based on integer linear programming (ILP), a mathematical optimization method. To minimize the computation time of coastal ocean circulation models, the ILP decomposition algorithm divides the global domain in local domains with balanced work load according to the number of processors and avoids computations over as many as land grid cells as possible. In addition, it maintains the use of logically rectangular local domains and achieves the exact same results as traditional domain decomposition algorithms (such as Cartesian decomposition). However, the ILP decomposition algorithm may not converge to an exact solution for relatively large domains. To overcome this problem, we developed two ILP decomposition formulations. The first one (complete formulation) has no additional restriction, although it is impractical for large global domains. The second one (feasible) imposes local domains with the same dimensions and looks for the feasibility of such decomposition, which allows much larger global domains. Parallel performance of both ILP formulations is compared to a base Cartesian decomposition by simulating two cases with the newly created parallel version of the Stevens Institute of Technology’s Estuarine and Coastal Ocean Model (sECOM). Simulations with the ILP formulations run always faster than the ones with the base decomposition, and the complete formulation is better than the feasible one when it is applicable. In addition, parallel efficiency with the ILP decomposition may be greater than one.     

On open boundary conditions for three dimensional primitive equation ocean circulation models

Abstract

An open boundary condition is constructed for three dimensional primitive equation ocean circulation models. The boundary condition utilises dominant balances in the governing equations to assist calculations of variables at the boundary. The boundary condition can be used in two forms. Firstly as a passive one in which there is no forcing at the boundary and phenomena generated within the domain of interest can propagate outwards without distorting the interior. Secondly as an active condition where a model is forced by the boundary condition. Three simple idealised tests are performed to verify the open boundary condition, (1) a passive condition to test the outflow of free Kelvin waves, (2) an active condition during the spin up phase of an ocean, (3) finally an example of the use of the condition in a tropical ocean.     

Interpretations and observations of ocean wave spectra

The paper starts with a discussion of the linear stochastic theory of ocean waves and its various nonlinear extensions. The directional spectrum, with its unique dispersion relation connecting frequency (ω) and wavenumber (k), is no longer valid for nonlinear waves, and examples of $\left( \mathbf{k},\omega\right) The paper starts with a discussion of the linear stochastic theory of ocean waves and its various nonlinear extensions. The directional spectrum, with its unique dispersion relation connecting frequency (ω) and wavenumber (k), is no longer valid for nonlinear waves, and examples of ( k,w)\left( \mathbf{k},\omega\right) -spectra based on analytical expressions and computer simulations of nonlinear waves are presented. Simulations of the dynamic nonlinear evolution of unidirectional free waves using the nonlinear Schr?dinger equation and its generalizations show that components above the spectral peak have larger phase and group velocities than anticipated by linear theory. Moreover, the spectrum does not maintain a thin well-defined dispersion surface, but rather develops into a continuous distribution in ( k,w)\left( \mathbf{k,}\omega\right) -space. The majority of existing measurement systems rely on linear theory for the interpretation of their data, and no measurement systems are currently able to measure the full spectrum in the open ocean with high accuracy. Nevertheless, there exist a few low-resolution systems where data may be interpreted within a minimal assumption of a non-restricted ( k,w)\left( \mathbf{k,}\omega\right) -spectrum. The theory is reviewed, and analyses based on conventional spectral analysis as well as a directional wavelet analysis are carried out on data from a compact laser array at the Ekofisk field in the North Sea. The investigation confirms the strong impact of the second order spectrum below the spectral peak, but is non-conclusive about the off-set in the support of the first order spectrum seen in the dynamical simulations.     

Study on linear and nonlinear bottom friction parameterizations for regional tidal models using data assimilation

Data assimilation technique (adjoint method) is applied to study the similarities and the differences between the Ekman (linear) and the Quadratic (nonlinear) bottom friction parameterizations for a two-dimensional tidal model. Two methods are used to treat the bottom friction coefficient (BFC). The first method assumes that the BFC is a constant in the entire computation domain, while the second applies the spatially varying BFCs. The adjoint expressions for the linear and the nonlinear parameterizations and the optimization formulae for the two BFC methods are derived based on the typical Largrangian multiplier method. By assimilating the model-generated ‘observations’, identical twin experiments are performed to test and validate the inversion ability of the presented methodology. Four experiments, which employ the linear parameterization, the nonlinear parameterizations, the constant BFC and the spatially varying BFC, are carried out to simulate the M₂ tide in the Bohai Sea and the Yellow Sea by assimilating the TOPEX/Poseidon altimetry and tidal gauge data. After the assimilation, the misfit between model-produced and observed data is significantly decreased in the four experiments. The simulation results indicate that the nonlinear Quadratic parameterization is more accurate than the linear Ekman parameterization if the traditional constant BFC is used. However, when the spatially varying BFCs are used, the differences between the Ekman and the Quadratic approaches diminished, the reason of which is analyzed from the viewpoint of dissipation rate caused by bottom friction. Generally speaking, linear bottom friction parameterizations are often used in global tidal models. This study indicates that they are also applicable in regional ocean tidal models with the combination of spatially varying parameters and the adjoint method.     

Momentum transfer at the ocean–atmosphere interface: the wave basis for the inertial coupling approach

 The inertial coupling approach for the momentum transfer at the ocean–atmosphere interface, which is based on the assumption of a similarity hypothesis in which the ratio between the water and air reference velocities is equal to the square root of the ratio between the air and water densities, is reviewed using a wave model. In this model, the air and water reference velocities are identified, respectively, with the spectrally weighted phase velocity of the gravity waves and the Stokes velocity at the water roughness length, which are evaluated in terms of the dimensionless frequency limits in Toba's equilibrium spectrum. It is shown that the similarity hypothesis is approximately satisfied by the wave model over the range of wave ages encountered in typical sea states, and that the predicted values of the dimensionless surface drift velocity, the dimensionless water reference velocity, and the Charnock constant are in reasonable agreement with observational evidence. The application of the bulk relationship for the surface shear stress, derived from the inertial coupling hypothesis in general circulation modeling, is also discussed. Received: 6 January 2001 / Accepted: 28 June 2001     

Multi-scale modeling of Puget Sound using an unstructured-grid coastal ocean model: from tide flats to estuaries and coastal waters

Water circulation in Puget Sound, a large complex estuary system in the Pacific Northwest coastal ocean of the United States, is governed by multiple spatially and temporally varying forcings from tides, atmosphere (wind, heating/cooling, precipitation/evaporation, pressure), and river inflows. In addition, the hydrodynamic response is affected strongly by geomorphic features, such as fjord-like bathymetry and complex shoreline features, resulting in many distinguishing characteristics in its main and sub-basins. To better understand the details of circulation features in Puget Sound and to assist with proposed nearshore restoration actions for improving water quality and the ecological health of Puget Sound, a high-resolution (around 50 m in estuaries and tide flats) hydrodynamic model for the entire Puget Sound was needed. Here, a three-dimensional circulation model of Puget Sound using an unstructured-grid finite volume coastal ocean model is presented. The model was constructed with sufficient resolution in the nearshore region to address the complex coastline, multi-tidal channels, and tide flats. Model open boundaries were extended to the entrance of the Strait of Juan de Fuca and the northern end of the Strait of Georgia to account for the influences of ocean water intrusion from the Strait of Juan de Fuca and the Fraser River plume from the Strait of Georgia, respectively. Comparisons of model results, observed data, and associated error statistics for tidal elevation, velocity, temperature, and salinity indicate that the model is capable of simulating the general circulation patterns on the scale of a large estuarine system as well as detailed hydrodynamics in the nearshore tide flats. Tidal characteristics, temperature/salinity stratification, mean circulation, and river plumes in estuaries with tide flats are discussed.     

On the form of the momentum equation for shallow water models based on the generalized wave continuity equation

Nearly all generalized wave continuity (GWC)-based models utilize the velocity-based, non-conservative form of the momentum equation to obtain the depth-averaged changes in velocity. It has been hypothesized that a flux-based, conservative form of the momentum equation may improve accuracy and stability. Herein, we study the impact of the choice of dependent variable and form of the momentum equation in a GWC-based finite element shallow water model. The impact of this change on mass balance, stability, and accuracy (spatial and temporal) is rigorously assessed, first for 1D barotropic flows and then for 2D barotropic flows in a variety of basins. Both 1D and 2D results indicate that the conservative form improves mass balance on both global and local scales, with the most significant gains found in local mass balance in areas with steep bathymetry gradients. This is also the region where the conservative form shows an increase in local spatial accuracy. Taylor series analysis and numerical simulations indicate a strong correlation between local spatial truncation errors and local mass balance errors. Stability, temporal accuracy and global spatial accuracy do not show statistically significant changes between the two algorithms in both 1D and 2D studies.     

Soil moisture variability and scale-dependency of nonlinear parameterizations in coupled land–atmosphere models

Many of the relationships used in coupled land–atmosphere models to describe interactions between the land surface and the atmosphere have been empirically parameterized and thus are inherently dependent on the observational scale for which they were derived and tested. However, they are often applied at scales quite different than the ones they were intended for due to practical necessity. In this paper, a study is presented on the scale-dependency of parameterizations which are nonlinear functions of variables exhibiting considerable spatial variability across a wide range of scales. For illustration purposes, we focus on parameterizations which are explicit nonlinear functions of soil moisture. We use data from the 1997 Southern Great Plains Hydrology Experiment (SGP97) to quantify the spatial variability of soil moisture as a function of scale. By assuming that a parameterization keeps its general form the same over a range of scales, we quantify how the values of its parameters should change with scale in order to preserve the spatially averaged predicted fluxes at any scale of interest. The findings of this study illustrate that if modifications are not made to nonlinear parameterizations to account for the mismatch of scales between optimization and application, then significant systematic biases may result in model-predicted water and energy fluxes.     

Scientific management of Mediterranean coastal zone: a hybrid ocean forecasting system for oil spill and search and rescue operations

The oil spill from Prestige tanker showed the importance of scientifically based protocols to minimize the impacts on the environment. In this work, we describe a new forecasting system to predict oil spill trajectories and their potential impacts on the coastal zone. The system is formed of three main interconnected modules that address different capabilities: (1) an operational circulation sub-system that includes nested models at different scales, data collection with near-real time assimilation, new tools for initialization or assimilation based on genetic algorithms and feature-oriented strategic sampling; (2) an oil spill coastal sub-system that allows simulation of the trajectories and fate of spilled oil together with evaluation of coastal zone vulnerability using environmental sensitivity indexes; (3) a risk management sub-system for decision support based on GIS technology. The system is applied to the Mediterranean Sea where surface currents are highly variable in space and time, and interactions between local, sub-basin and basin scale increase the non-linear interactions effects which need to be adequately resolved at each one of the intervening scales. Besides the Mediterranean Sea is a complex reduced scale ocean representing a real scientific and technological challenge for operational oceanography and particularly for oil spill response and search and rescue operations.     

A new methodology for the extension of the impact of data assimilation on ocean wave prediction

It is a common fact that the majority of today's wave assimilation platforms have a limited, in time, ability of affecting the final wave prediction, especially that of long-period forecasting systems. This is mainly due to the fact that after “closing” the assimilation window, i.e., the time that the available observations are assimilated into the wave model, the latter continues to run without any external information. Therefore, if a systematic divergence from the observations occurs, only a limited portion of the forecasting period will be improved. A way of dealing with this drawback is proposed in this study: A combination of two different statistical tools—Kolmogorov–Zurbenko and Kalman filters—is employed so as to eliminate any systematic error of (a first run of) the wave model results. Then, the obtained forecasts are used as artificial observations that can be assimilated to a follow-up model simulation inside the forecasting period. The method was successfully applied to an open sea area (Pacific Ocean) for significant wave height forecasts using the wave model WAM and six different buoys as observational stations. The results were encouraging and led to the extension of the assimilation impact to the entire forecasting period as well as to a significant reduction of the forecast bias.