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Fish Modeling and Deep Learning for the Lakshadweep Islands

Gupta, A., P.J. Haley, D.N. Subramani, and P.F.J. Lermusiaux, 2019. Fish Modeling and Deep Learning for the Lakshadweep Islands. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, in press

Of the several ocean-related activities, fisheries is a major industry in the coastal states of India,employing millions of people and contributing to 1.1% of GDP and 5.3% of agricultural GDP. Globally, the Indian fishing industry is the third largest in the world. The total marine fish production is around 3 billion metric tons. Indian waters contain about 2,500 species of finfishes and shellfishes. Among these, there are about 65 commercially important species or groups. In 2004, 52% of these commercially important groups were pelagic and midwater species. In 2006, over 600,000 metric tons of fish were exported, to some 90 countries, earning over $1.8 billion. Increased demand for fish, coupled with unsustainable fishing practices lead to over-exploitation and fast depletion of fish stocks. Coastal fisheries and aquaculture stocks often thrive on very specific water conditions. Building capabilities for coastal ecosystem forecasting will help ensuring and managing the survival and reproduction of healthy stock. Without sustainable fisheries management and conservation practices in place, the bounty of the ocean will not last much longer.

We first compile a comprehensive literature survey to review the status of fish modeling in the coastal oceans. Then, focusing on the Lakshadweep islands in India, where the main fishery is tuna, we complete a series of data-driven ocean-ecosystem simulations and analyses, using fish catch data and our modeling capabilities. We utilize the new capabilities of our MSEAS primitive equation ocean-ecosystem modeling system to capture the complex oceanic phenomenon in the region of interest, and a tuna fish model based on SEAPODYM. We also complete sensitivity analysis based on a Finite-Volume Framework. Our modeling software can provide coastal ecosystem predictions for fisheries management, allowing sustainable management of fish stocks as well as identification of probable fish location. Such modeling efforts could help improve practices from a standpoint of sustainability and efficiency.


Flowmaps and Coherent Sets for Characterizing Residence Times and Connectivity in Lagoons and Coral Reefs: The Case of the Red Sea

Doshi, M.M., C.S. Kulkarni, W.H. Ali, A. Gupta, P.F.J. Lermusiaux, P. Zhan, I. Hoteit, and O.M. Knio, 2019. Flowmaps and Coherent Sets for Characterizing Residence Times and Connectivity in Lagoons and Coral Reefs: The Case of the Red Sea. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, in press.

The objectives of the present paper are to: (i) Utilize our new Lagrangian transport theory and methods to forecast, characterize and quantify ocean processes involved in the three-dimensional transports and transformation of water masses, residence times, and connectivity dynamics in the Red Sea; (ii) Apply and expand our multi-resolution submesoscale-to-regional-scale ocean modeling, 2-way nesting, and uncertainty predictions, for real-time forecasting and process studies in the region; (iii) Help design field experiments and predict sampling strategies that maximize information on residence times, 4D pathways and dynamics in the region.


SeaVizKit: Interactive Maps for Ocean Visualization

Ali, W.H., M. Merhi, A. Gupta, C.S. Kulkarni, C. Foucart, D.N. Subramani, and P.F.J. Lermusiaux, 2019. SeaVizKit: Interactive Maps for Ocean Visualization. In: OCEANS '19 MTS/IEEE Seattle, 27-31 October 2019, in press.

With the increasing availability of high-resolution comprehensive spatiotemporal ocean models and observation systems, ocean data visualization has become ubiquitous. This is due to the major impact of ocean products on disaster management, shipping, fisheries, coastal operations and scientific studies. Yet, there are several challenges for effective communication of data through visualization techniques. Specifically, ocean data is multivariate (e.g. temperature, salinity, velocity, etc.), and is available for multiple depths and multiple time instants which leads to large, multi-dimensional datasets. Thus, it is necessary to have an interactive multiscale visualization tool that can assist scientists, policy makers, and the public in getting insights from big data produced by ocean predictions and observations.

In this work, we present a 3D (spatial) + 1 (temporal) multivariate visualization tool that produces interactive, dynamic, fast and portable ocean maps. The tool is based on Leaflet and D3.js JavaScript libraries, and is built for the multidisciplinary simulation, estimation, and assimilation systems (MSEAS) ocean products, along with it has been used for multiple real-time sea exercises.


Advection without Compounding Errors through Flow Map Composition

Kulkarni, C.S. and P.F.J. Lermusiaux, 2019. Advection without Compounding Errors through Flow Map Composition. Journal of Computational Physics, sub-judice.

We propose a novel numerical methodology to compute the advective transport and diffusion-reaction of tracer quantities. The tracer advection occurs through flow map composition and is super-accurate, yielding numerical solutions almost devoid of compounding numerical errors, while allowing for direct parallelization in the temporal direction. It is computed by implicitly solving the characteristic evolution through a modified transport partial differential equation and domain decomposition in the temporal direction, followed by composition with the known initial condition. This advection scheme allows a rigorous computation of the spatial and temporal error bounds, yields an accuracy comparable to that of Lagrangian methods, and maintains the advantages of Eulerian schemes. We further show that there exists an optimal value of the composition timestep that yields the minimum total numerical error in the computations, and derive the expression for this value. We develop schemes for the addition of tracer diffusion, reaction, and source terms, and for the implementation of boundary conditions. Finally, the methodology is applied in three flow examples, namely an analytical reversible swirl flow, an idealized flow exiting a strait undergoing sudden expansion, and a realistic ocean flow in the Bismarck sea. New benchmark problems for advection-diffusion-reaction schemes are developed and used to compare and contrast results with those of classic schemes. The results highlight the theoretical properties of the methodology as well as its efficiency, super-accuracy with minimal numerical errors, and applicability in realistic simulations.

Intelligent Systems for Geosciences: An Essential Research Agenda

Gil, Y., S.A. Pierce, H. Babaie, A. Banerjee, K. Borne, G. Bust, M. Cheatham, I. Ebert-Uphoff, C. Gomes, M. Hill, J. Horel, L. Hsu, J. Kinter, C. Knoblock, D. Krum, V. Kumar, P.F.J. Lermusiaux, Y. Liu, C. North, V. Pankratius, S. Peters, B. Plale, A. Pope, S. Ravela, J. Restrepo, A. Ridley, H. Samet, and S. Shekhar, 2019. Intelligent Systems for Geosciences: An Essential Research Agenda. Communications of the ACM, 62(1), 76–84. doi:10.1145/3192335

Many aspects of geosciences pose novel problems for intelligent systems research. Geoscience data is challenging because it tends to be uncertain, intermittent, sparse, multiresolution, and multiscale. Geosciences processes and objects often have amorphous spatiotemporal boundaries. The lack of ground truth makes model evaluation, testing, and comparison difficult. Overcoming these challenges requires breakthroughs that would significantly transform intelligent systems, while greatly benefitting the geosciences in turn. Although there have been significant and beneficial interactions between the intelligent systems and geosciences communities, the potential for synergistic research in intelligent systems for geosciences is largely untapped. A recently launched Research Coordination Network on Intelligent Systems for Geosciences followed a workshop at the National Science Foundation on this topic. This expanding network builds on the momentum of the NSF EarthCube initiative for geosciences, and is driven by practical problems in Earth, ocean, atmospheric, polar, and geospace sciences. Based on discussions and activities within this network, this article presents a research agenda for intelligent systems inspired by geosciences challenges.


Distributed Implementation and Verification of Hybridizable Discontinuous Galerkin Methods for Nonhydrostatic Ocean Processes

Foucart, C., C. Mirabito, P.J. Haley, Jr., and P.F.J. Lermusiaux, 2018. Distributed Implementation and Verification of Hybridizable Discontinuous Galerkin Methods for Nonhydrostatic Ocean Processes. In: Oceans '18 MTS/IEEE Charleston, 22-25 October 2018. doi:10.1109/oceans.2018.8604679

Nonhydrostatic, multiscale processes are an important part of our understanding of ocean dynamics. However, resolving these dynamics with traditional computational techniques can often be prohibitively expensive. We apply the hybridizable discontinuous Galerkin (HDG) finite element methodology to perform computationally efficient, high-order, nonhydrostatic ocean modeling by solving the Navier-Stokes equations with the Boussinesq approximation. In this work, we introduce a distributed implementation of our HDG projection method algorithm. We provide numerical experiments to verify our methodology using the method of manufactured solutions and provide preliminary benchmarking for our distributed implementation that highlight the advantages of the HDG methodology in the context of distributed computing. Lastly, we present simulations in which we capture nonhydrostatic internal waves that form as a result of tidal interactions with ocean topography. First, we consider the case of tidally-driven oscillatory flow over an abrupt, shallow seamount, and next, the case of strongly-stratified, oscillatory flow over a tall seamount. We analyze and compare our simulations to other results in literature.


Scalable Coupled Ocean and Water Turbine Modeling for Assessing Ocean Energy Extraction

Deluca, S., B. Rocchio, C. Foucart, C. Mirabito, S. Zanforlin, P.J. Haley, and P.F.J. Lermusiaux, 2018. Scalable Coupled Ocean and Water Turbine Modeling for Assessing Ocean Energy Extraction. In: Oceans '18 MTS/IEEE Charleston, 22-25 October 2018. doi:10.1109/oceans.2018.8604646

The interest in hydrokinetic conversion systems has significantly grown over the last decade with a special focus on cross-flow systems, generally known as Vertical Axis Water Turbines (VAWTs). However, analyzing of regions of interest for tidal energy extraction and outlining optimal rotor geometry is currently very computationally expensive via conventional 3D Computational Fluid Dynamics (CFD) methods. In this work, a VAWT load prediction routine developed at University of Pisa based upon the Blade Element-Momentum (BEM) theory is presented and validated against high-resolution 2D CFD simulations. Our model is able to work in two configurations, i.e. Double-Multiple Streamtube (DMST) mode, using 1D flow simplifications for quick analyses, and Hybrid mode, coupled to a CFD software for more accurate results. As a practical application, our routine is employed for a site assessment analysis of the Cape Cod area to quickly highlight oceanic regions with high hydrokinetic potential, where further higher-order and more computationally expensive CFD analyses can be performed. Ocean data are obtained from data-assimilative ocean simulations predicted by the 4D regional ocean modeling system of the Multidisciplinary Simulation, Estimation, and Assimilation Systems (MSEAS) group of the Massachusetts Institute of Technology.


Clustering of Massive Ensemble of Vehicle Trajectories in Strong, Dynamic and Uncertain Ocean Flows

Dutt, A., D.N. Subramani, C.S. Kulkarni, and P.F.J. Lermusiaux, 2018. Clustering of Massive Ensemble of Vehicle Trajectories in Strong, Dynamic and Uncertain Ocean Flows. In: Oceans '18 MTS/IEEE Charleston, 22-25 October 2018. doi:10.1109/oceans.2018.8604634

Recent advances in probabilistic forecasting of regional ocean dynamics, and stochastic optimal path planning with massive ensembles motivate principled analysis of their large datasets. Specifically, stochastic time-optimal path planning in strong, dynamic and uncertain ocean flows produces a massive dataset of the stochastic distribution of exact timeoptimal trajectories. To synthesize such big data and draw insights, we apply machine learning and data mining algorithms. Particularly, clustering of the time-optimal trajectories is important to describe their PDFs, identify representative paths, and compute and optimize risk of following these paths. In the present paper, we explore the use of hierarchical clustering algorithms along with a dissimilarity matrix computed from the pairwise discrete Frechet distance between all the optimal trajectories. We apply the algorithms to two datasets of massive ensembles of vehicle trajectories in a stochastic flow past a circular island and stochastic wind driven double gyre flow. These paths are computed by solving our dynamically orthogonal level set equations. Hierarchical clustering is applied to the two datasets, and results are qualitatively and quantitatively analyzed.


Real-Time Sediment Plume Modeling in the Southern California Bight

Kulkarni, C.S., P.J. Haley, Jr., P.F.J. Lermusiaux, A. Dutt, A. Gupta, C. Mirabito, D.N. Subramani, S. Jana, W.H. Ali, T. Peacock, C.M. Royo, A. Rzeznik, and R. Supekar, 2018. Real-Time Sediment Plume Modeling in the Southern California Bight. In: Oceans '18 MTS/IEEE Charleston, 22-25 October 2018. doi:10.1109/oceans.2018.8653642

With advances in engineering and technology, mining the deep sea for untapped rare metal resources from the bottom of the ocean has recently become economically viable. However, extracting these metal ores from the seabed creates plumes of fine particles that are deposited at various depths within the ocean, and these may be extremely harmful to the marine ecosystems and its components. Thus, for sustainable management, it is of utmost importance to carefully monitor and predict the impact of such harmful activities including plume dispersion on the marine environment. To forecast the plume dispersion in real-time, data-driven ocean modeling has to be coupled with accurate, efficient, and rigorous sediment plume transport computations. The goal of the present paper is to demonstrate the real-time applications of our coupled 3D-and-time data-driven ocean modeling and plume transport forecasting system. Here, the region of focus is the southern California bight, where the PLUMEX 2018 deep sea mining real-time sea experiment was recently conducted (23 Feb – 5 Mar, 2018). Specifically, we demonstrate the improved capabilities of the multiscale MSEAS primitive equation ocean modeling system to capture the complex oceanic phenomenon in the region of interest, the application of the novel method of composition to efficiently and accurately compute the transport of sediment plumes in 3D+1 domains, and the portability of our software and prediction system to different operational regions and its potential in estimating the environmental impacts of deep sea mining activities, ultimately aiding sustainable management and science-based regulations.

Sensitivity of the Bay of Bengal upper ocean to different winds and river input conditions

Jana, S., A. Gangopadhyay, P.F.J. Lermusiaux, A. Chakraborty, S. Sil, and P.J. Haley Jr., 2018. Sensitivity of the Bay of Bengal Upper Ocean to Different Winds and River Input Conditions. Journal of Marine Systems, 187, 206–222. doi:10.1016/j.jmarsys.2018.08.001

The sensitivity of the Bay of Bengal (BoB) upper ocean circulation and thermohaline structure to varying wind strengths and river salinity conditions is investigated using a set of long-term mesoscale simulations. The Regional Ocean Modeling System (ROMS) simulations differ in their forcing fields for winds (strong vs. weak) and in their representations of river input salinity conditions (seasonally varying estuarine salinity vs. zero salinity). The sensitivities are analyzed in terms of the responses of the surface circulation, thermohaline structure, freshwater plume dispersion, and the coastal upwelling along the western boundary. All the simulations reproduce the main broad-scale features of the Bay, while their magnitudes and variabilities depend on the forcing conditions. The impact of stronger wind is felt at greater depths for temperature than for salinity throughout the domain; however, the impact is realized with vertical distributions that are different in the northern than in the southern Bay.

As expected, the stronger wind-induced enhanced mixing lowers (enhances) the upper ocean temperature (salinity) by 0.2C (0.3 psu), and weakens the near-surface stratification. Moreover, stronger wind enhances eddy activity, strengthens the springtime Western Boundary Current (WBC) and enhances coastal upwelling during spring and summer along the east coast of India. The fresher river input reduces the surface salinity and hence enhances the spreading and intensity of the freshwater plume, stratification, and barrier layer thickness. The lower salinity simulation leads to an eddy-dominant springtime WBC, and enhances the freshness, strength, and southward extent of the autumn East India Coastal Current (EICC). The stronger wind simulations appear to prevent the spreading of the freshwater plume during the summer monsoon due to enhanced mixing. Fresher river input reduces the overall surface salinity by ~0.4 psu; however, it significantly underestimates the salinity near the river mouths, whereas the estuarine salinity river input simulations are closer to reality. These results highlight the importance of river input salinity and realistic strong winds in reducing model biases of high-resolution simulations for the Bay of Bengal.


Iterated Pressure-Correction Projection Methods for the Unsteady Incompressible Navier-Stokes Equations

Aoussou, J., J. Lin, and P.F.J. Lermusiaux, 2018. Iterated Pressure-Correction Projection Methods for the Unsteady Incompressible Navier-Stokes Equations. Journal of Computational Physics, 373, 940–974. doi:10.1016/j.jcp.2018.06.062

Iterated pressure-correction projection schemes for the unsteady incompressible Navier-Stokes equations are developed, analyzed and exemplified, in relation to preconditioned iterative methods and the pressure-Schur complement equation. Typical pressure-correction schemes perform only one iteration per stage or time step, and suffer from splitting errors that result in spurious numerical boundary layers and a limited order of convergence in time. We show that performing iterations not only reduces the effects of the splitting errors, but can also be more efficient computationally than merely reducing the time step. We devise stopping criteria to recover the desired order of temporal convergence, and to drive the splitting error below the time-integration error. We also develop and implement the iterated pressure corrections with both multi-step and multi-stage time integration schemes. Finally, to reduce further the computational cost of the iterated approach, we combine it with an Aitken acceleration scheme. Our theoretical results are validated and illustrated by numerical test cases for the Stokes and Navier-Stokes equations, using implicit-explicit (IMEX) backwards differences and Runge-Kutta time-integration solvers. The test cases comprise a now classical manufactured solution in the projection method community and a modified version of a more recently proposed manufactured solution. The different error types, stopping criterion, recovered orders of convergence, and acceleration rates are illustrated, as well as the effects of the rotational corrections and time-integration schemes. It is found that iterated pressure-correction schemes can retrieve the accuracy and temporal convergence order of fully-coupled schemes and are computationally more efficient than classic pressure-correction schemes.

Environmental Ocean and Plume Modeling for Deep Sea Mining in the Bismarck Sea.

Coulin, J., P. J. Haley, Jr., S. Jana, C.S. Kulkarni, P. F. J. Lermusiaux, T. Peacock, 2017. Environmental Ocean and Plume Modeling for Deep Sea Mining in the Bismarck Sea. In: Oceans '17 MTS/IEEE Anchorage, 1-10, 18-21 September 2017.

A pressing environmental question facing the ocean is the potential impact of possible deep-sea mining activities. This work presents our initial results in developing an ocean and plume modeling system for the Bismark Sea where deep sea mining operations will probably take place. We employ the MSEAS modeling system to both simulate the ocean and to downscale initial conditions from a global system (HYCOM) and tidal forcing from the global TPXO-8 Atlas. We found that at least 1.5 km resolution was needed to adequately resolve the multiscale flow fields. In St. Georges channel, the interaction between the tides, background currents, and underlying density fields increased the subtidal flows. Comparing to historical transport estimates, we showed that tidal forcing is needed to maintain the correct subtidal transport through that Channel. Comparisons with past simulations and measured currents all showed good agreement between the MSEAS hindcasts. Quantitative comparisons made between our hindcasts and independent synoptic ARGO profiles showed that the hindcasts beat persistence by 33% to 50%. These comparisons demonstrated that the MSEAS current estimates were useful for assessing plume advection. Our Lagrangian transport and coherence analyses indicate that the specific location and time of the releases can have a big impact on their dispersal. Our results suggest that ocean mining plumes can be best mitigated by managing releases in accord with such ocean modeling and Lagrangian transport forecasts. Real-time integrated mining-modeling-sampling is likely to provide the most effective mitigation strategies.

From weather to ocean predictions: an historical viewpoint

Pinardi, N., L. Cavaleri, P. De Mey, C. Fratianni, I. Huthnance, P.F.J. Lermusiaux, A. Navarra, R. Preller, and S. Tibalidi, 2017. From Weather to Ocean Predictions: an Historical Viewpoint. The Sea. Volume 17, The Science of Ocean Prediction, Part 1, Special Issue, J. Marine Res. 75(3). pp. 103-159. https://doi.org/10.1357/002224017821836789

This paper reviews the historical development of concepts and practices in the science of ocean predictions. It begins with meteorology which conducted the first forecasting experiment in 1950, followed by the wind waves and continuing with tidal and storm surge predictions to arrive at the first successful ocean mesoscale forecast in 1983. The work of Professor A.R.Robinson of Harvard University who produced the first mesoscale ocean predictions for the deep ocean regions is documented for the first time. The scientific and technological developments that made accurate ocean predictions possible are connected with the gradual understanding of the importance of the oceanic mesoscales and their inclusion in the numerical models. Ocean forecasting developed first at the regional level, due to the relatively low computational requirements, but by the end of the nineties it was possible to produce global ocean uncoupled forecasts and coupled ocean-atmosphere seasonal forecasts.


Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea

Lermusiaux, P.F.J., P.J. Haley Jr., S. Jana, A. Gupta, C.S. Kulkarni, C. Mirabito, W.H. Ali, D.N. Subramani, A. Dutt, J. Lin, A. Y. Shcherbina, C. M. Lee, and A. Gangopadhyay, 2017. Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea. Oceanography 30(2):172–185, https://doi.org/10.5670/oceanog.2017.242.

Where, when, and what to sample, and how to optimally reach the sampling locations, are critical questions to be answered by Autonomous and Lagrangian Platforms and Sensors. For a reproducible scientific sampling approach, answers should be quantitative and provided using fundamental principles. Concepts and recent progress towards this principled approach are first overviewed, focusing on reachability, path planning, and adaptive sampling. Results of a real-time forecasting and planning experiment completed during February-April 2017 for the Northern Arabian Sea Circulation – Autonomous Research program are then presented. The predictive skill, layered fields, and uncertainty estimates obtained using our MIT MSEAS multi-resolution ensemble ocean modeling system are first studied. With such inputs, deterministic and probabilistic three-dimensional reachability forecasts issued daily for gliders and floats are then showcased and validated. Our Bayesian adaptive sampling framework is finally shown to forecast in real-time the observations that are most informative for estimating classic ocean fields but also secondary-variables such as Lagrangian Coherent Structures.

Pursuit-Evasion Games in Dynamic Flow Fields via Reachability Set Analysis

Sun, W., P. Tsiotras, T. Lolla, D. N. Subramani and P. F. J. Lermusiaux, 2017. Pursuit-evasion games in dynamic flow fields via reachability set analysis American Control Conference (ACC), Seattle, WA, 2017, pp. 4595-4600. doi: 10.23919/ACC.2017.7963664

In this paper, we adopt a reachability-based approach to deal with the pursuit-evasion differential game between two players in the presence of dynamic environmental disturbances (e.g., winds, sea currents). We give conditions for the game to be terminated in terms of reachable set inclusions. Level set equations are defined and solved to generate the reachable sets of the pursuer and the evader. The corresponding time-optimal trajectories and optimal strategies can be retrieved immediately afterwards. We validate our method by applying it to a pursuit-evasion game in a simple flow field, for which an analytical solution is available.We then implement the proposed scheme to a problem with a more realistic flow field.

Multiple-Pursuer-One-Evader Pursuit Evasion Game in Dynamic Flow Fields

Sun, W., P. Tsiotras, T. Lolla, D. N. Subramani, and P. F. J. Lermusiaux, 2017. Multiple-Pursuer-One-Evader Pursuit Evasion Game in Dynamic Flow Fields. Journal of Guidance, Control and Dynamics, 40 (7), 1627-1637. DOI: 10.2514/1.G002125

In this paper a reachability-based approach is adopted to deal with the pursuit-evasion di erential game between one evader and multiple pursuers in the presence of dynamic environmental disturbances (e.g., winds, sea currents). Conditions for the game to be terminated are given in terms of reachable set inclusions. Level set equations are defi ned and solved to generate the forward reachable sets of the pursuers and the evader. The time-optimal trajectories and the corresponding optimal strategies are sub- sequently retrieved from these level sets. The pursuers are divided into active pursuers, guards, and redundant pursuers according to their respec- tive roles in the pursuit-evasion game. The proposed scheme is implemented on problems with both simple and realistic time-dependent flow fi elds, with and without obstacles.

Hybridizable Discontinuous Galerkin Projection Methods for Navier-Stokes and Boussinesq Equations

Ueckermann, M.P. and P.F.J. Lermusiaux, 2016. Hybridizable Discontinuous Galerkin Projection Methods for Navier-Stokes and Boussinesq Equations. Journal of Computational Physics, 306, 390–421. http://dx.doi.org/10.1016/j.jcp.2015.11.028

Schemes for the incompressible Navier-Stokes and Boussinesq equations are formulated and derived combining the novel Hybridizable Discontinuous Galerkin (HDG) method, a projection method, and Implicit-Explicit Runge-Kutta (IMEX-RK) time-integration schemes. We employ an incremental pressure correction and develop the corresponding HDG finite element discretization including consistent edge-space fluxes for the velocity predictor and pressure correction. We then derive the proper forms of the element-local and HDG edge-space final corrections for both velocity and pressure, including the HDG rotational correction. We also find and explain a consistency relation between the HDG stability parameters of the pressure correction and velocity predictor. We discuss and illustrate the effects of the time-splitting error. We then detail how to incorporate the HDG projection method time-split within standard IMEX-RK time-stepping schemes. Our high-order HDG projection schemes are implemented for arbitrary, mixed–element unstructured grids, with both straight-sided and curved meshes. In particular, we provide a quadrature-free integration method for a nodal basis that is consistent with the HDG method. To prevent numerical oscillations, we develop a selective nodal limiting approach. Its applications show that it can stabilize high-order schemes while retaining high-order accuracy in regions where the solution is sufficiently smooth. We perform spatial and temporal convergence studies to evaluate the properties of our integration and selective limiting schemes and to verify that our solvers are properly formulated and implemented. To complete these studies and to illustrate a range of properties for our new schemes, we employ an unsteady tracer advection benchmark, a manufactured solution for the steady diffusion and Stokes equations, and a standard lock-exchange Boussinesq problem.

Optimizing Velocities and Transports for Complex Coastal Regions and Archipelagos

Haley, P.J., Jr., A. Agarwal, P.F.J. Lermusiaux, 2015. Optimizing Velocities and Transports for Complex Coastal Regions and Archipelagos. Ocean Modeling, 89, 1-28. doi:10.1016/j.ocemod.2015.02.005

We derive and apply a methodology for the initialization of velocity and transport fields in complex multiply-connected regions with multiscale dynamics. The result is initial fields that are consistent with observations, complex geometry and dynamics, and that can simulate the evolution of ocean processes without large spurious initial transients. A class of constrained weighted least squares optimizations is defined to best fit first-guess velocities while satisfying the complex bathymetry, coastline and divergence strong constraints. A weak constraint towards the minimum inter-island transports that are in accord with the first-guess velocities provides important velocity corrections in complex archipelagos. In the optimization weights, the minimum distance and vertical area between pairs of coasts are computed using a Fast Marching Method. Additional information on velocity and transports are included as strong or weak constraints. We apply our methodology around the Hawaiian islands of Kauai/Niihau, in the Taiwan/Kuroshio region and in the Philippines Archipelago. Comparisons with other common initialization strategies, among hindcasts from these initial conditions (ICs), and with independent in situ observations show that our optimization corrects transports, satisfies boundary conditions and redirects currents. Differences between the hindcasts from these different ICs are found to grow for at least 2-3 weeks. When compared to independent in situ observations, simulations from our optimized ICs are shown to have the smallest errors.


Issues and Progress in the Prediction of Ocean Submesoscale Features and Internal Waves

Duda T.F., W.G. Zhang, K.R. Helfrich, A.E. Newhall, Y.-T. Lin, J.F. Lynch, P.F.J. Lermusiaux, P.J. Haley Jr., J. Wilkin, 2014. Issues and Progress in the Prediction of Ocean Submesoscale Features and Internal Waves. OCEANS'14 MTS/IEEE.

Data-constrained dynamical ocean modeling for the purpose of detailed forecasting and prediction continues to evolve and improve in quality. Modeling methods and computational capabilities have each improved. The result is that mesoscale phenomena can be modeled with skill, given sufficient data. However, many submesoscale features are less well modeled and remain largely unpredicted from a deterministic event standpoint, and possibly also from a statistical property standpoint. A multi-institution project is underway with goals of uncovering more of the details of a few submesoscale processes, working toward better predictions of their occurrence and their variability. A further component of our project is application of the new ocean models to ocean acoustic modeling and prediction. This paper focuses on one portion of the ongoing work: Efforts to link nonhydrostatic-physics models of continental-shelf nonlinear internal wave evolution to data-driven regional models. Ocean front-related effects are also touched on.


A Relocatable Ocean Model in support of environmental emergencies – The Costa Concordia emergency case

De Dominicis M., S. Falchetti, F. Trotta, N. Pinardi, L. Giacomelli, E. Napolitano, L. Fazioli, R. Sorgente, P.J. Haley Jr., P.F.J. Lermusiaux, F. Martins and M. Cocco, 2014. A Relocatable Ocean Model in support of environmental emergencies - The Costa Concordia emergency case. Ocean Dynamics, 64, 5:667–688. DOI 10.1007/s10236-014-0705-x

During the Costa Concordia emergency case, regional, subregional, and relocatable ocean models have been used together with the oil spill model, MEDSLIKII, to provide ocean currents forecasts, possible oil spill scenarios, and drifters trajectories simulations. The models results together with the evaluation of their performances are presented in this paper. In particular, we focused this work on the implementation of the Interactive RElocatable Nested Ocean Model (IRENOM), based on the Harvard Ocean Prediction System (HOPS), for the Costa Concordia emergency and on its validation using drifters released in the area of the accident. It is shown that thanks to the capability of improving easily and quickly its configuration, the IRENOM results are of greater accuracy than the results achieved using regional or subregional model products. The model topography, the initialization procedures, and the horizontal resolution are the key model settings to be configured. Furthermore, the IRENOM currents and the MEDSLIK-II simulated trajectories showed to be sensitive to the spatial resolution of the meteorological fields used, providing higher prediction skills with higher resolution wind forcing.

Multiscale Modeling of Coastal, Shelf and Global Ocean Dynamics

Lermusiaux, P.F.J., J. Schröter, S. Danilov, M. Iskandarani, N. Pinardi and J.J. Westerink, 2013. Multiscale Modeling of Coastal, Shelf and Global Ocean Dynamics, Ocean Dynamics. 63:1341–1344. DOI: 10.1007/s10236-013-0655-8

In contemporary ocean science, modeling systems that integrate understanding of complex multiscale phenomena and utilize efficient numerics are paramount. Many of today’s fundamental ocean science questions involve multiple scales and multiple dynamics. A new generation of modeling systems would allow to study such questions quantitatively, by being less restrictive dynamically and more efficient numerically than more traditional systems. Such multiscale ocean modeling is the theme of this topical issue. Two large international workshops were organized on this theme, one in Cambridge, USA (IMUM2010), and one in Bremerhaven, Germany (IMUM2011). Contributions from the scientific community were encouraged on all aspects of multiscale ocean modeling, from ocean science and dynamics to the development of new computational methods and systems. Building on previous meetings (e.g. Deleersnijder and Lermusiaux, 2008; Deleersnijder et al., 2010), the workshop discussions and the final contributions to the topical issue are summarized next. The scientific application domains discussed and presented ranged from estuaries to the global ocean, including coastal regions and shelf seas. Multi-resolution modeling of physical, biological, chemical, and sea ice processes as well as air-sea interactions were described. The multiscale dynamics considered involved hydrostatic, non-hydrostatic, turbulent and sea surface processes. Computational results and discussions emphasized multi-resolution simulations using unstructured and structured meshes, aiming to widen the range of resolved scales in space and time. They included finite volume and finite element spatial-discretizations, high-order schemes, preconditioners, solver issues, grid generation, adaptive modeling, data assimilation, coupling with atmospheric or biogeochemical models, and distributed computing. The advantages of using unstructured meshes and related approaches, in particular multi-grid embedding, nesting systems, wavelets and other multi-scale decompositions were discussed. Techniques for the study of multi-resolution results, visualization, optimization, model evaluations, and uncertainty quantification were also examined.

Many Task Computing for Real-Time Uncertainty Prediction and Data Assimilation in the Ocean

Evangelinos, C., P.F.J. Lermusiaux, J. Xu, P.J. Haley, and C.N. Hill, 2011. Many Task Computing for Real-Time Uncertainty Prediction and Data Assimilation in the Ocean. IEEE Transactions on Parallel and Distributed Systems, Special Issue on Many-Task Computing, I. Foster, I. Raicu and Y. Zhao (Guest Eds.), 22, doi: 10.1109/TPDS.2011.64.

Uncertainty prediction for ocean and climate predictions is essential for multiple applications today. Many-Task Computing can play a significant role in making such predictions feasible. In this manuscript, we focus on ocean uncertainty prediction using the Error Subspace Statistical Estimation (ESSE) approach. In ESSE, uncertainties are represented by an error subspace of variable size. To predict these uncertainties, we perturb an initial state based on the initial error subspace and integrate the corresponding ensemble of initial conditions forward in time, including stochastic forcing during each simulation. The dominant error covariance (generated via SVD of the ensemble) is used for data assimilation. The resulting ocean fields are used as inputs for predictions of underwater sound propagation. ESSE is a classic case of Many Task Computing: It uses dynamic heterogeneous workflows and ESSE ensembles are data intensive applications. We first study the execution characteristics of a distributed ESSE workflow on a medium size dedicated cluster, examine in more detail the I/O patterns exhibited and throughputs achieved by its components as well as the overall ensemble performance seen in practice. We then study the performance/usability challenges of employing Amazon EC2 and the Teragrid to augment our ESSE ensembles and provide better solutions faster.

Statistical Field Estimation for Complex Coastal Regions and Archipelagos

Agarwal, A. and P.F.J. Lermusiaux, 2011. Statistical Field Estimation for Complex Coastal Regions and Archipelagos. Ocean Modeling, 40(2), 164-189, doi: 10.1016/j.ocemod.2011.08.001.

A fundamental requirement in realistic ocean simulations and dynamical studies is the optimal estimation of gridded fields from the spatially irregular and multivariate data sets that are collected by varied platforms. In this work, we derive and utilize new schemes for the mapping and dynamical inference of ocean fields in complex multiply-connected domains and study the computational properties of these schemes. Specifically, we extend a Bayesian-based multiscale Objective Analysis (OA) approach to complex coastal regions and archipelagos. Such OAs commonly require an estimate of the distances between data and model points, without going across complex landforms. New OA schemes that estimate the length of shortest sea paths using the Level Set Method (LSM) and Fast Marching Method (FMM) are thus derived, implemented and utilized in idealized and realistic ocean cases. An FMM-based methodology for the estimation of total velocity under geostrophic balance in complex domains is also presented. Comparisons with other OA approaches are provided, including those using stochastically forced partial differential equations (SPDEs). We find that the FMM-based OA scheme is the most efficient and accurate. The FMM-based field maps do not require postprocessing (smoothing). Mathematical and computational properties of our new OA schemes are studied in detail, using fundamental theorems and illustrations. We find that higher-order FMM’s schemes improve accuracy and that a multi-order scheme is efficient. We also provide solutions that ensure the use of positive-definite covariances, even in complex multiply-connected domains.

Automated Sensor Networks to Advance Ocean Science

Schofield, O., S. Glenn, J. Orcutt, M. Arrott, M. Meisinger, A. Gangopadhyay, W. Brown, R. Signell, M. Moline, Y. Chao, S. Chien, D. Thompson, A. Balasuriya, P.F.J. Lermusiaux and M. Oliver, 2010. Automated Sensor Networks to Advance Ocean Science. EOS, Vol. 91, No. 39, 28 September 2010.

Oceanography is evolving from a ship-based expeditionary science to a distributed, observatory- based approach in which scientists continuously interact with instruments in the field. These new capabilities will facilitate the collection of long- term time series while also providing an interactive capability to conduct experiments using data streaming in real time. The U.S. National Science Foundation has funded the Ocean Observatories Initiative (OOI), which over the next 5 years will deploy infrastructure to expand scientists’ ability to remotely study the ocean. The OOI is deploying infrastructure that spans global, regional, and coastal scales. A global component will address planetary- scale problems using a new network of moored buoys linked to shore via satellite telecommunications. A regional cabled observatory will “wire” a single region in the northeastern Pacific Ocean with a high-speed optical and power grid. The coastal component will expand existing coastal observing assets to study the importance of high-frequency forcing on the coastal environment. These components will be linked by a robust cyberinfrastructure (CI) that will integrate marine observatories into a coherent system of systems. This CI infrastructure will also provide a Web- based social network enabled by real- time visualization and access to numerical model information, to provide the foundation for adaptive sampling science. Thus, oceanographers will have access to automated machine-to-machine sensor networks that can be scalable to increase in size and incorporate new technology for decades to come. A case study of this CI in action shows how a community of ocean scientists and engineers located throughout the United States at 12 different institutions used the automated ocean observatory to address daily adaptive science priorities in real time.

High Order Schemes for 2D Unsteady Biogeochemical Ocean Models

Ueckermann, M.P. and P.F.J. Lermusiaux, 2010. High Order Schemes for 2D Unsteady Biogeochemical Ocean Models. Ocean Dynamics, 60, 1415-1445, doi:10.1007/s10236-010-0351-x

Accurate numerical modeling of biogeochemical ocean dynamics is essential for numerous applications, including coastal ecosystem science, environmental management and energy, and climate dynamics. Evaluating computational requirements for such often highly nonlinear and multiscale dynamics is critical. To do so, we complete comprehensive numerical analyses, comparing low- to high-order discretization schemes, both in time and space, employing standard and hybrid discontinuous Galerkin finite element methods, on both straight and new curved elements. Our analyses and syntheses focus on nutrient-phytoplankton-zooplankton dynamics under advection and diffusion within an ocean strait or sill, in an idealized 2D geometry. For the dynamics, we investigate three biological regimes, one with single stable points at all depths and two with stable limit cycles. We also examine interactions that are dominated by the biology, by the advection, or that are balanced. For these regimes and interactions, we study the sensitivity to multiple numerical parameters including quadrature-free and quadrature-based discretizations of the source terms, order of the spatial discretizations of advection and diffusion operators, order of the temporal discretization in explicit schemes, and resolution of the spatial mesh, with and without curved elements. A first finding is that both quadrature-based and quadrature-free discretizations give accurate results in well-resolved regions, but the quadrature-based scheme has smaller errors in underresolved regions. We show that low-order temporal discretizations allow rapidly growing numerical errors in biological fields. We find that if a spatial discretization (mesh resolution and polynomial degree) does not resolve the solution, oscillations due to discontinuities in tracer fields can be locally significant for both lowand high-order discretizations. When the solution is sufficiently resolved, higher-order schemes on coarser grids perform better (higher accuracy, less dissipative) for the same cost than lower-order scheme on finer grids. This result applies to both passive and reactive tracers and is confirmed by quantitative analyses of truncation errors and smoothness of solution fields. To reduce oscillations in un-resolved regions, we develop a numerical filter that is active only when and where the solution is not smooth locally. Finally, we consider idealized simulations of biological patchiness. Results reveal that higher-order numerical schemes can maintain patches for long-term integrations while lowerorder schemes are much too dissipative and cannot, even at very high resolutions. Implications for the use of simulations to better understand biological blooms, patchiness, and other nonlinear reactive dynamics in coastal regions with complex bathymetric features are considerable.

Multiscale two-way embedding schemes for free-surface primitive-equations in the Multidisciplinary Simulation, Estimation and Assimilation System

Haley, P.J., Jr. and P.F.J. Lermusiaux, 2010. Multiscale two-way embedding schemes for free-surface primitive-equations in the Multidisciplinary Simulation, Estimation and Assimilation System. Ocean Dynamics, 60, 1497-1537. doi:10.1007/s10236-010-0349-4.

We derive conservative time-dependent structured discretizations and two-way embedded (nested) schemes for multiscale ocean dynamics governed by primitive equations (PEs) with a nonlinear free surface. Our multiscale goal is to resolve tidalto- mesoscale processes and interactions over large multiresolution telescoping domains with complex geometries including shallow seas with strong tides, steep shelfbreaks, and deep ocean interactions. We first provide an implicit time-stepping algorithm for the nonlinear free-surface PEs and then derive a consistent time-dependent spatial discretization with a generalized vertical grid. This leads to a novel timedependent finite volume formulation for structured grids on spherical or Cartesian coordinates, second order in time and space, which preserves mass and tracers in the presence of a time-varying free surface. We then introduce the concept of two-way nesting, implicit in space and time, which exchanges all of the updated fields values across grids, as soon as they become available. A class of such powerful nesting schemes applicable to telescoping grids of PE models with a nonlinear free surface is derived. The schemes mainly differ in the fine-to-coarse scale transfers and in the interpolations and numerical filtering, specifically for the barotropic velocity and surface pressure components of the two-way exchanges. Our scheme comparisons show that for nesting with free surfaces, the most accurate scheme has the strongest implicit couplings among grids. We complete a theoretical truncation error analysis to confirm and mathematically explain findings. Results of our discretizations and two-way nesting are presented in realistic multiscale simulations with data assimilation for the middle Atlantic Bight shelfbreak region off the east coast of the USA, the Philippine archipelago, and the Taiwan-Kuroshio region. Multiscale modeling with two-way nesting enables an easy use of different sub-gridscale parameterizations in each nested domain. The new developments drastically enhance the predictive capability and robustness of our predictions, both qualitatively and quantitatively. Without them, our multiscale multiprocess simulations either were not possible or did not match ocean data.

Multi-scale modelling of coastal, shelf and global ocean dynamics

Deleersnijder, E., V. Legat and P.F.J. Lermusiaux, 2010. Multi-scale modelling of coastal, shelf and global ocean dynamics. Ocean Dynamics. 60, 1357-1359. doi:10.1007/s10236-010-0363-6.

Methods for widening the range of resolved scales (i.e. performing multi-scale simulations) in ocean sciences and engineering are developing rapidly, now allowing multiscale ocean dynamics studies. Having recourse to grid nesting has been and still is a popular method for increasing marine models’ resolution when and where needed and for easily allowing the use of different dynamics at different resolution. However, this is not the only way to achieve this goal. Various techniques for modifying locally the grid resolution or dealing with complex-geometry domains are available. For instance, composite, structured grids and unstructured meshes offer an almost infinite geometrical flexibility. This special issue focuses on multi-scale modelling of coastal, shelf and global ocean dynamics, including the development of new methodologies and schemes and their applications to ocean process studies. Several articles focus on numerical aspects of unstructured mesh space discretisation. Danilov (2010) shows that the noise developing on triangular meshes on which the location of the variables is inspired by Arakawa’s C-grid is the largest for regimes close to geostrophic balance. The noise can be reduced by specific operators but cannot be entirely suppressed, “making the triangular C-grid a suboptimal choice for large-scale ocean modelling”. Then, the companion articles of Blaise et al. (2010) and Comblen et al. (2010) describe the space and time discretisation of a three-dimensional, baroclinic, finite element model based on the discontinuous Galerkin (DG) technique. This is a significant step forward in the field of finite element ocean modelling, though this model cannot yet be regarded as suitable for tackling realistic applications. Ueckermann and Lermusiaux (2010) also consider DG finite element techniques, focusing on biological-physical dynamics in regions with complex bathymetric features. They compare low- to high-order discretisations, both in time and space, for regimes in which biology dominates, advection dominates or terms are balanced. They find that higher-order schemes on relatively coarse grids generally perform better than low-order schemes on fine grids. Kleptsova et al. (2010) assess various advection schemes for z-coordinate, threedimensional models in which flooding and drying is taken into account. In this study, the ability to conserve momentum is regarded as the main criterion for selecting a suitable method. On the other hand, Massmann (2010) assesses automatic differentiation for obtaining the adjoint of an unstructured mesh, tidal model of the European continental shelf. Two articles deal with grid nesting. Nash and Hartnett (2010) introduce a flooding and drying method that can be used in structured, nested grid systems. This can be regarded as an alternative to flooding and drying techniques that are being developed for unstructured mesh models (e.g. Karna et al. 2010). Then, Haley and Lermusiaux (2010) derive conservative time-dependent structured finite volume discretisations and implicit two-way embedded schemes for primitive equations with the intent to resolve tidal-to-mesoscale processes over large multi-resolution telescoping domains with complex geometries including shallow seas with strong tides, steep shelf breaks and deep ocean interactions. The authors present realistic simulations with data assimilation in three regions with diverse dynamics and show that their developments enhance the predictive capability, leading to better match with ocean data. Various multi-scale, realistic simulations are presented. Using a finite element ice model and a slab ocean as in Lietaer et al. (2008), Terwisscha van Scheltinga et al. (2010) model the Canadian Arctic Archipelago, focusing on the pathways for freshwater and sea-ice transport from the Arctic Ocean to the Labrador Sea and the Atlantic Ocean. The unstructured mesh can represent the complex geometry and narrow straits at high resolution and allows improving transports of water masses and sea ice. Walters et al. (2010) have recourse to an unstructured mesh model to study tides and current in Greater Cook Strait (New Zealand). They identify the mechanisms causing residual currents. By means of the unstructured mesh Finite Volume Coastal Ocean Model (FVCOM), Wang et al. (2010) study the hydrodynamics of the Bohai Sea. Xu et al. (2010) simulate coastal and urban inundation due to storm surges along US East and Gulf Coasts. A sensitivity analysis reveals the importance of precise topographic data and the need for a bottom drag coefficient accounting for the presence of mangroves. Finally, Yang and Khangaonkar (2010) resort to FVCOM to simulate the three-dimensional circulation of Puget Sound, a large complex estuary system in the Pacific Northwest coastal ocean, including variable forcing from tides, the atmosphere and river inflows. Comparisons of model estimates with measurements for tidal elevation, velocity, temperature and salinity are deemed to be promising, from larger-scale circulation features to nearshore tide flats. This special issue suggests that numerical techniques for multi-scale space discretisation are progressively becoming mature. One direction for future progress lies in the improvement of time discretisation methods for the new generation models, so that they can successfully compete with finite difference, structured mesh models based on (almost) constant resolution grids that have been developed and used over the past 40 years (e.g. Griffies et al. 2009).

Many Task Computing for Multidisciplinary Ocean Sciences: Real-Time Uncertainty Prediction and Data Assimilation

Evangelinos, C., P.F.J. Lermusiaux, J. Xu, P.J. Haley, and C.N. Hill, 2009. Many Task Computing for Multidisciplinary Ocean Sciences: Real-Time Uncertainty Prediction and Data Assimilation. Conference on High Performance Networking and Computing, Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers (Portland, OR, 16 November 2009), 10pp. doi.acm.org/10.1145/1646468.1646482.

Error Subspace Statistical Estimation (ESSE), an uncertainty prediction and data assimilation methodology employed for real-time ocean forecasts, is based on a characterization and prediction of the largest uncertainties. This is carried out by evolving an error subspace of variable size. We use an ensemble of stochastic model simulations, initialized based on an estimate of the dominant initial uncertainties, to predict the error subspace of the model fields. The dominant error covariance (generated via an SVD of the ensemble-generated error covariance matrix) is used for data assimilation. The resulting ocean fields are provided as the input to acoustic modeling, allowing for the prediction and study of the spatiotemporal variations in acoustic propagation and their uncertainties. The ESSE procedure is a classic case of Many Task Computing: These codes are managed based on dynamic workflows for the: (i) perturbation of the initial mean state, (ii) subsequent ensemble of stochastic PE model runs, (iii) continuous generation of the covariance matrix, (iv) successive computations of the SVD of the ensemble spread until a convergence criterion is satisfied, and (v) data assimilation. Its ensemble nature makes it a many task data intensive application and its dynamic workflow gives it heterogeneity. Subsequent acoustics propagation modeling involves a very large ensemble of short-in-duration acoustics runs.

Towards Dynamic Data Driven Systems for Rapid Adaptive Interdisciplinary Ocean Forecasting

Patrikalakis, N.M., P.F.J. Lermusiaux, C. Evangelinos, J.J. McCarthy, A.R. Robinson, H. Schmidt, P.J. Haley, S. Lalis, R. Tian, W.G. Leslie, and W. Cho, 2009. Towards Dynamic Data Driven Systems for Rapid Adaptive Interdisciplinary Ocean Forecasting Invited paper in "Dynamic Data-Driven Application Systems''. F. Darema, Editor. Springer, 2009. In press.

The state of the ocean evolves and its dynamics involves transitions occurring at multiple scales. For efficient and rapid interdisciplinary forecasting, ocean observing and prediction systems must have the same behavior and adapt to the everchanging dynamics. The work discussed here aims to set the basis of a distributed system for real-time interdisciplinary ocean field and uncertainty forecasting with adaptive modeling and adaptive sampling. The scientific goal is to couple physical and biological oceanography with ocean acoustics. The technical goal is to build a dynamic system based on advanced infrastructures, distributed / grid computing and efficient information retrieval and visualization interfaces. Importantly, the system combines a suite of modern legacy physical models, acoustic models and ocean current monitoring data assimilation schemes with new adaptive modeling and adaptive sampling methods. The legacy systems are encapsulated at the binary level using software component methodologies. Measurement models are utilized to link the observed data to the dynamical model variables and structures. With adaptive sampling, the data acquisition is dynamic and aims to minimize the predicted uncertainties, maximize the sampling of key dynamics and maintain overall coverage. With adaptive modeling, model improvements are dynamic and aim to select the best model structures and parameters among different physical or biogeochemical parameterizations. The dynamic coupling of models and measurements discussed here represents a Dynamic Data-Driven Application System (DDDAS). Technical and scientific progress is highlighted based on examples in Massachusetts Bay, and Monterey Bay and the California Current System. Keywords: Oceanography, interdisciplinary, adaptive, sampling,

Multi-Scale Modelling: Nested Grid and Unstructured Mesh Approaches, Editorial

Deleersnijder, E. and P.F.J. Lermusiaux, (Guest Eds.), 2008. Multi-Scale Modelling: Nested Grid and Unstructured Mesh Approaches, Editorial. Ocean Dynamics, 58, 335-336, Springer. doi: 10.1007/s10236-008-0170-5.

In 1969, the Journal of Computational Physics published a seminal article by K. Bryan presenting the first ocean general circulation model. Since then, many numerical studies of the World Ocean, as well as regional or coastal flows, used models directly or indirectly inspired by the work of Bryan and his colleagues. A number of these models have evolved into highly modular and versatile computational systems, including multiple physical modules and options as well as varied biogeochemical, ecosystem and acoustics modeling capabilities. Several modeling systems are now well-documented tools, which are widely used in research institutions and various organizations around the world. The list of such modeling systems is large and too long to be summarized in this editorial. Over the last three decades, significant progress has been made in the parameterization of subgrid-scale processes, in data assimilation methodologies and in boundary condition schemes, as well as in the efficient implementation of algorithms on fast vector and subsequently parallel computers, allowing higher and higher resolution in space and time. However, many of today’s popular modeling systems can still be regarded as members of the first generation of ocean models: at their core, rather similar geophysical fluid dynamics equations are solved numerically using a conservative finite-difference method on a structured grid. Today, several aspects of structured-grid models could benefit from significant upgrades, learning from major advances in computational fluid dynamics. In particular, the use of a structured grid limits the flexibility in the spatial resolution and does not allow one to take full advantage of numerical algorithms such as finite volumes and finite elements, which can achieve their best performance when implemented on unstructured meshes. Even though many of today’s complex marine modeling and data assimilation systems have evolved significantly since Bryan’s prototype, it would be challenging to modify them step-by-step from a structured-grid approach to an unstructured-grid one. Therefore, novel marine model design research is underway, paving the way for the second generation of ocean modeling systems. It is difficult to predict today if this new generation of ocean models will achieve its chief objective: widening the range of resolved scales of motion with increased efficiencies and accuracies, possibly allowing multi-resolution, multi-scale, and multidynamics numerical simulations of marine flows, all occurring seamlessly within distributed computing environments. In fact, hybrid approaches merging the advantages of structured and unstructured-grid modeling may be the way forward. Whether or not unstructured mesh approaches will prevail is all the more difficult to predict now that structured mesh modelers have developed powerful solutions for increasing the resolution when and where needed. For instance, grid embedding is still a popular and useful method for enhancing model resolution. It can involve multiply nested domains and allows the relatively straightforward use of different dynamics or models in each domain. Research is also underway for developing multigrid, wavelet, and other multi-scale decompositions for the numerical solution of dynamical equations but also for the study of results, model evaluation or data assimilation. This special issue presents a number of examples of the abovementioned developments. Ringler et al. examine the potential of spherical centroidal Voronoi tessellations for performing multi-resolution simulations; they apply this method to the Greenland ice sheet and the North Atlantic Ocean. Lambrechts et al. present a triangular mesh generation system and its applications to the World Ocean and various shelf seas, including the Great Barrier Reef, Australia. Finite element models on unstructured grids are described and utilized in several manuscripts. Bellafiore et al. study the Adriatic Sea and the Lagoon of Venice, while Jones and Davies simulate tides and storm surges along the western coast of Britain. Danilov et al. assess two finite element discretizations, i.e., a continuous element and a non-conforming one, and compare the results of these discretizations with those of a finite-difference model. In Harig et al., the tsunami generated by the great Sumatra-Andaman earthquake of 26 December 2004 is simulated by means of a finite element model. Comparisons are carried out with various types of data as well as with the results of a structured mesh model using a nested structured-grid system. A nested-grid ocean circulation model is also employed by Yang and Sheng to carry out a process study on the Inner Scotian Shelf, Canada, focusing on the circulation induced by a tropical storm. Debreu and Blayo present a detailed review of two-way embedding algorithms for structured-grid models. Finally, Logutov develops a multi-scale assimilation scheme for tidal data within the framework of a multiply nested structured-grid barotropic tidal modeling approach. As illustrated by these manuscripts, the next generation of ocean modelers is motivated by a wide range of research opportunities over a rich spectrum of needs. Future progress will involve fundamental and applied numerical and computational research as well as new multi-scale geophysical fluid modeling. Domains of ongoing interest range from estuaries to the global ocean, including coastal regions and shelf seas. New multi-scale modeling of physical as well as biological, chemical or interdisciplinary processes will flourish in the coming decades. We are grateful to the authors for their contributions and to the chief-editor for his support in this endeavor. We are thankful to the reviewers for their time and help in assessing the manuscripts submitted to this special issue. Eric Deleersnijder is a Research associate with the Belgian National Fund for Scientific Research (FNRS); he is indebted to the Communaut Francaise de Belgique for its support through contract ARC 04/09-316. Pierre Lermusiaux is grateful to the Office of Naval Research for support under grant N00014-08-1-1097 to the Massachusetts Institute of Technology.

Inverse Barotropic Tidal Estimation for Regional Ocean Applications

Logutov, O.G. and Lermusiaux, P.F.J., 2008. Inverse Barotropic Tidal Estimation for Regional Ocean Applications. Ocean Modeling, 25, 17-34. doi: 10.1016/j.ocemod.2008.06.004.

Correct representation of tidal processes in regional ocean models is contingent on the accurate specification of open boundary conditions. This paper describes a new inverse scheme for the assimilation of observational data into a depth-integrated spectral shallow water tidal model and the numerical implementation of this scheme into a stand-alone computational system for regional tidal prediction. A novel aspect is a specific implementation of the inverse which does not require an adjoint model. An optimization is carried out in the open boundary condition space rather than in the observational space or model state space. Our approach reflects the specifics of regional tidal modeling applications in which open boundary conditions (OBCs) typically constitute a significant source of uncertainty. Regional tidal models rely predominantly on global tidal estimates for open boundary conditions. As the resolution of global tidal models is insufficient to fully resolve regional topographic and coastal features, the a priori OBC estimates potentially contain an error. It is, therefore, desirable to correct these OBCs by finding an inverse OBC estimate that is fitted to the regional observations, in accord with the regional dynamics and respective error estimates. The data assimilation strategy presented in this paper provides a consistent and practical estimation scheme for littoral ocean science and applications where tidal effects are significant. Illustrations of our methodological and computational results are presented in the area of Dabob Bay and Hood Canal, WA, which is a region connected to the open Pacific ocean through a series of inland waterways and complex shorelines and bathymetry.

Verification and Training of Real-Time Forecasting of Multi-Scale Ocean Dynamics for MREA

Leslie, W.G., A.R. Robinson, P.J. Haley, O. Logoutov, P. Moreno, P.F.J. Lermusiaux, E. Coehlo, 2008. Verification and Training of Real-Time Forecasting of Multi-Scale Ocean Dynamics for MREA. Journal of Marine Systems, 69, 3-16, doi: 10.1016/j.jmarsys.2007.02.001.

The Harvard Ocean Prediction System (HOPS) provides real-time and hindcast, multi-scale oceanic field estimates for Maritime Rapid Environmental Assessment (MREA). Results of aspects of the validation, calibration and verification of HOPS for MREA03 and MREA04 are presented, with implications for future MREA exercises. A new method of model training, via bias correction through the use of limited data, was applied to MREA03 and shown to produce significant forecast improvement while reducing computational requirements. Advances in, and the demand for, adaptive modeling, require that aspects of validation, calibration and verification be carried out in real-time in order to expand the usage and relevance of dynamical forecast-based MREA tactical decision aids

Web-Enabled Configuration and Control of Legacy Codes: An Application to Ocean Modeling

Evangelinos, C., P.F.J. Lermusiaux, S. Geiger, R.C. Chang, and N.M. Patrikalakis, 2006. Web-Enabled Configuration and Control of Legacy Codes: An Application to Ocean Modeling. Ocean Modeling, 13, 197-220.

For modern interdisciplinary ocean prediction and assimilation systems, a significant part of the complexity facing users is the very large number of possible setups and parameters, both at build-time and at run-time, especially for the core physical, biological and acoustical ocean predictive models. The configuration of these modeling systems for both local as well as remote execution can be a daunting and error-prone task in the absence of a graphical user interface (GUI) and of software that automatically controls the adequacy and compatibility of options and parameters. We propose to encapsulate the configurability and requirements of ocean prediction codes using an eXtensible Markup Language (XML) based description, thereby creating new computer-readable manuals for the executable binaries. These manuals allow us to generate a GUI, check for correctness of compilation and input parameters, and finally drive execution of the prediction system components, all in an automated and transparent manner. This web-enabled configuration and automated control software has been developed (it is currently in “beta” form) and exemplified for components of the interdisciplinary Harvard ocean prediction system (HOPS) and for the uncertainty prediction components of the error subspace statistical estimation (ESSE) system. Importantly, the approach is general and applies to other existing ocean modeling applications and to other “legacy” codes.

Dynamics and Lagrangian Coherent Structures in the Ocean and their Uncertainty

Lermusiaux, P.F.J. and F. Lekien, 2005. Dynamics and Lagrangian Coherent Structures in the Ocean and their Uncertainty. Extended Abstract in report of the "Dynamical System Methods in Fluid Dynamics" Oberwolfach Workshop. Jerrold E. Marsden and Jurgen Scheurle (Eds.), Mathematisches Forschungsinstitut Oberwolfach, July 31st - August 6th, 2005, Germany. 2pp.

The observation, computation and study of “Lagrangian Coherent Structures” (LCS) in turbulent geophysical flows have been active areas of research in fluid mechanics for the last 30 years. Growing evidence for the existence of LCSs in geophysical flows (e.g., eddies, oscillating jets, chaotic mixing) and other fluid flows (e.g., separation pro le at the surface of an airfoil, entrainment and detrainment by a vortex) generates an increasing interest for the extraction and understanding of these structures as well as their properties. In parallel, realistic ocean modeling with dense data assimilation has developed in the past decades and is now able to provide accurate nowcasts and predictions of ocean flow fields to study coherent structures. Robust numerical methods and sufficiently fast hardware are now available to compute real-time forecasts of oceanographic states and render associated coherent structures. It is therefore natural to expect the direct predictions of LCSs based on these advanced models. The impact of uncertainties on the coherent structures is becoming an increasingly important question for practical applications. The transfer of these uncertainties from the ocean state to the LCSs is an unexplored but intriguing scientific problem. These two questions are the motivation and focus of this presentation. Using the classic formalism of continuous-discrete estimation [1], the spatially discretized dynamics of the ocean state vector x and observations are described by (1a) dx =M(x; t) + d yok (1b) = H(xk; tk) + k where M and H are the model and measurement model operator, respectively. The stochastic forcings d and k are Wiener/Brownian motion processes,   N(0;Q(t)), and white Gaussian sequences, k  N(0;Rk), respectively. In other words, Efd(t)d T (t)g := Q(t) dt. The initial conditions are also uncertain and x(t0) is random with a prior PDF, p(x(t0)), i.e. x(t0) = bx0 + n(0) with n(0) random. Of course, vectors and operators in Eqs. (1a-b) are multivariate which impacts the PDFs: e.g. their moments are also multivariate. The estimation problem at time t consists of combining all available information on x(t), the dynamics and data (Eqs. 1a-b), their prior distributions and the initial conditions p(x(t0)). Defining the set of all observations prior to time t by yt

Rapid real-time interdisciplinary ocean forecasting using adaptive sampling and adaptive modeling and legacy codes: Component encapsulation using XML

Evangelinos C., R. Chang, P.F.J. Lermusiaux and N.M. Patrikalakis, 2003. Rapid real-time interdisciplinary ocean forecasting using adaptive sampling and adaptive modeling and legacy codes: Component encapsulation using XML. Lecture Notes in Computer Science, 2660, 375-384.

We present the high level architecture of a real-time interdisciplinary ocean forecasting system that employs adaptive elements in both modeling and sampling. We also discuss an important issue that arises in creating an integrated, web-accessible framework for such a system out of existing stand-alone components: transparent support for handling legacy binaries. Such binaries, that are most common in scientific applications, expect a standard input stream, maybe some command line options, a set of input files and generate a set of output files as well as standard output and error streams. Legacy applications of this form are encapsulated using XML. We present a method that uses XML documents to describe the parameters for executing a binary.

Visualizing scalar volumetric data with uncertainty

Djurcilov, S., K. Kim, P.F.J. Lermusiaux and A. Pang, 2002. Visualizing scalar volumetric data with uncertainty. Computers and Graphics, 26 (2): 239-248.

Increasingly, more importance is placed on the uncertainty information of data being displayed. This paper focuses on techniques for visualizing 3D scalar data sets with corresponding uncertainty information at each point which is also representedas a scalar value. In Djurcilov (in: D. Ebert, J.M. Favre, R. Peikert (Eds.), Data Visualization 2001, Springer, Berlin, 2001), we presentedtwo general methods (inline DVR approach anda post-processing approach) for carrying out this task. The first methodinvolves incorporating the uncertainty information directly into the volume rendering equation. The second method involves post-processing information of volume rendered images to composite uncertainty information.

Predictive Skill, Predictive Capability and Predictability in Ocean Forecasting

Robinson, A.R., P.J. Haley, P.F.J. Lermusiaux and W.G. Leslie, 2002. Predictive Skill, Predictive Capability and Predictability in Ocean Forecasting. Proceedings of "The OCEANS 2002 MTS/IEEE" conference, Holland Publications, 787-794.

We discuss the concepts involved in the evaluation and quantitative verification of ocean forecasts and present two predictive skill experiments to develop and research these concepts, carried out in the North Atlantic and Mediterranean Sea in 2001 and 2002. Ocean forecasting involves complex ocean observing and prediction systems for ocean regions with multi-scale interdisciplinary dynamical processes and strong, intermittent events. Now that ocean forecasting is becoming more common, it is critically important to interpret and evaluate regional forecasts in order to establish their usefulness to the scientific and applied communities. The Assessment of Skill for Coastal Ocean Transients (ASCOT) project is a series of real-time Coastal Predictive Skill (CPSE) and Rapid Environmental Assessment (REA) experiments and simulations focused on quantitative skill evaluation, carried out by the Harvard Ocean Prediction System group in collaboration with the NATO SACLANT Undersea Research Centre. ASCOT-01 was carried out in Massachusetts Bay and the Gulf of Maine in June 2001. ASCOT-02 took place in May 2002 in the Corsican Channel near the island of Elba in the Mediterranean Sea. Results from the ASCOT exercises highlight the dual use of data for skill evaluation and assimilation, real-time adaptive sampling and skill optimization and present both real-time and a posteriori evaluations of predictive skill and predictive capability.

Volume rendering data with uncertainty information

Djurcilov, S., K. Kim, P.F.J. Lermusiaux and A. Pang, 2001. Volume rendering data with uncertainty information. In "Data visualization", Joint Eurographics - IEEE TCVG Symposium on Visualization, D. Ebert, J. M. Favre and R. Peikert (Eds.), Springer-Verlag. pp. 243-252, 355-356.

This paper explores two general methods for incorporating volumetric uncertainty information in direct volume rendering. The goal is to produce volume rendered images that depict regions of high (or low) uncertainty in the data. The first method involves incorporating the uncertainty information directly into the volume rendering equation. The second method involves post-processing information of volume rendered images to composite uncertainty information. We present some initial findings on what mappings provide qualitatively satisfactory results and what mappings do not. Results are considered satisfactory if the user can identify regions of high or low uncertainty in the rendered image. We also discuss the advantages and disadvantages of both approaches.

The development and demonstration of an advanced fisheries management information system

Robinson, A.R., B.J. Rothschild, W.G. Leslie, J.J. Bisagni, M.F. Borges, W.S. Brown, D. Cai, P. Fortier, A. Gangopadhyay, P.J. Haley, Jr., H.S. Kim, L. Lanerolle, P.F.J. Lermusiaux, C.J. Lozano, M.G. Miller, G. Strout and M.A. Sundermeyer, 2001. The development and demonstration of an advanced fisheries management information system. Proc. of the 17th Conference on Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology, Albuquerque, New Mexico. American Meteorological Society, 186-190.

Fishery management regulates size and species-specific fishing mortality to optimize biological production from the fish populations and economic production from the fishery. Fishery management is similar to management in industries and in natural resources where the goals of management are intended to optimize outputs relative to inputs. However, the management of fish populations is among the most difficult. The difficulties arise because (a) the dynamics of the natural production system are extremely complicated; involving an infinitude of variables and interacting natural systems and (b) the size-and species-specific fishing mortality (i.e. system control) is difficult to measure, calibrate, and deploy. Despite the difficulties, it is believed that significant advances can be made by employing a fishery management system that involves knowing the short-term (daily to weekly) variability in the structures of environmental and fish fields. We need new information systems that bring together existing critical technologies and thereby place fishery management in a total-systems feedback-control context. Such a system would monitor the state of the structure of all stocks simultaneously in near real-time, be adaptive to the evolving fishery and consider the effects of the environment and economics. To do this the system would need to (a) employ new in situ and remote sensors in innovative ways, (b) develop new data streams to support the development of new information, (c) employ modern modeling, information and knowledge-base technology to process the diverse information and (d) generate management advice and fishing strategies that would optimize the production of fish.

The Advanced Fisheries Management Information System (AFMIS), built through a collaboration of Harvard University and the Center for Marine Science and Technology at the University of Massachusetts at Dartmouth, is intended to apply state-of-the-art multidisciplinary and computational capabilities to operational fisheries management. The system development concept is aimed toward: 1) utilizing information on the “state” of ocean physics, biology, and chemistry; the assessment of spatially-resolved fish-stock population dynamics and the temporal-spatial deployment of fishing effort to be used in fishing and in the operational management of fish stocks; and, 2) forecasting and understanding physical and biological conditions leading to recruitment variability. Systems components are being developed in the context of using the Harvard Ocean Prediction System to support or otherwise interact with the: 1) synthesis and analysis of very large data sets; 2) building of a multidisciplinary multiscale model (coupled ocean physics/N-P-Z/fish dynamics/management models) appropriate for the northwest Atlantic shelf, particularly Georges Bank and Massachusetts Bay; 3) the application and development of data assimilation techniques; and, 4) with an emphasis on the incorporation of remotely sensed data into the data stream.

AFMIS is designed to model a large region of the northwest Atlantic (NWA) as the deep ocean influences the slope and shelves. Several smaller domains, including the Gulf of Maine (GOM) and Georges Bank (GB) are nested within this larger domain (Figure 1). This provides a capability to zoom into these domains with higher resolution while maintaining the essential physics which are coupled to the larger domain. AFMIS will be maintained by the assimilation of a variety of real time data. Specifically this includes sea surface temperature (SST), color (SSC), and height (SSH) obtained from several space-based remote sensors (AVHRR, SeaWiFS and Topex/Poseidon). The assimilation of the variety of real-time remotely sensed data supported by in situ data will allow nowcasting and forecasting over significant periods of time.

A real-time demonstration of concept (RTDOC) nowcasting and forecasting exercise to demonstrate important aspects of the AFMIS concept by producing real time coupled forecasts of physical fields, biological and chemical fields, and fish abundance fields took place in March-May 2000. The RTDOC was designed to verify the physics, to validate the biology and chemistry but only to demonstrate the concept of forecasting the fish fields, since the fish dynamical models are at a very early stage of development. In addition, it demonstrated the integrated system concept and the implication for future coupling of a management model. This note reports on the RTDOC.