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The Princeton Ocean Model (POM) is a community general numerical model for ocean circulation that can be used to simulate and predict oceanic currents, temperatures, salinities and other water properties. POM-WEB [1] and POMusers.org [2]
The model code [3] was originally developed at Princeton University (G. Mellor and Alan Blumberg) in collaboration with Dynalysis of Princeton (H. James Herring, Richard C. Patchen). The model incorporates the Mellor–Yamada turbulence scheme developed in the early 1970s by George Mellor and Ted Yamada; this turbulence sub-model is widely used by oceanic and atmospheric models. At the time, early computer ocean models such as the Bryan–Cox model (developed in the late 1960s at the Geophysical Fluid Dynamics Laboratory, GFDL, and later became the Modular Ocean Model, MOM)), were aimed mostly at coarse-resolution simulations of the large-scale ocean circulation, so there was a need for a numerical model that can handle high-resolution coastal ocean processes. The Blumberg–Mellor [4] model (which later became POM) thus included new features such as free surface to handle tides, sigma vertical coordinates (i.e., terrain-following) to handle complex topographies and shallow regions, a curvilinear grid to better handle coastlines, and a turbulence scheme to handle vertical mixing. At the early 1980s the model was used primarily to simulate estuaries such as the Hudson–Raritan Estuary (by Leo Oey) and the Delaware Bay (Boris Galperin), but also first attempts to use a sigma coordinate model for basin-scale problems have started with the coarse resolution model of the Gulf of Mexico (Blumberg and Mellor) and models of the Arctic Ocean (with the inclusion of ice-ocean coupling by Lakshmi Kantha and Sirpa Hakkinen).
In the early 1990s when the web and browsers started to be developed, POM became one of the first ocean model codes that were provided free of charge to users through the web. [5] The establishment of the POM users group and its web support (by Tal Ezer) resulted in a continuous increase in the number of POM users which grew from about a dozen U.S. users in the 1980s to over 1000 users in 2000 and over 4000 users by 2009; there are users from over 70 different countries. In the 1990s the usage of POM expands to simulations of the Mediterranean Sea (Zavatarelli [6] ) and the first simulations with a sigma coordinate model of the entire Atlantic Ocean [7] for climate research (Ezer). The development of the Mellor–Ezer optimal interpolation data assimilation scheme [8] that projects surface satellite data into deep layers allows the construction of the first ocean forecast systems for the Gulf Stream [9] and the U.S. east coast running operationally at the NOAA's National Weather Service (Frank Aikman and others [10] ). Operational forecast system for other regions such as the Great Lakes, the Gulf of Mexico (Oey), the Gulf of Maine (Huijie Xue) and the Hudson River (Blumberg) followed. For more information on applications of the model, see the searchable database of over 1800 POM-related publications. [11]
In the late 1990s and the 2000s many other terrain-following community ocean models have been developed; some of their features can be traced back to features included in the original POM, other features are additional numerical and parameterization improvements. Several ocean models are direct descendants of POM such as the commercial version of POM known as the estuarine and coastal ocean model (ECOM), the navy coastal ocean model (NCOM) and the finite-volume coastal ocean model (FVCOM). Recent developments in POM include a generalized coordinate system that combines sigma and z-level grids (Mellor and Ezer), inundation features that allow simulations of wetting and drying (e.g., flood of land area) (Oey), and coupling ocean currents with surface waves (Mellor). Efforts to improve turbulent mixing also continue (Galperin, Kantha, Mellor and others).
POM users' meetings were held every few years, and in recent years the meetings were extended to include other models and renamed the International Workshop on Modeling the Ocean (IWMO). Meeting Pages: [12] List of meetings:
Reviewed papers from the IWMO meetings are published by Ocean Dynamics [13] in special issues (IWMO-2009 Part-I, [14] IWMO-2009 Part-II, [15] IWMO-2010, [16] IWMO-2011, [17] IWMO-2012, [18] IWMO-2013, [19] IWMO-2014 [20] ).
The Geophysical Fluid Dynamics Laboratory (GFDL) is a laboratory in the National Oceanic and Atmospheric Administration (NOAA) Office of Oceanic and Atmospheric Research (OAR). The current director is Venkatachalam Ramaswamy. It is one of seven Research Laboratories within NOAA's OAR.
A parent to the Florida Current, the Loop Current is a warm ocean current that flows northward between Cuba and the Yucatán Peninsula, moves north into the Gulf of Mexico, loops east and south before exiting to the east through the Florida Straits and joining the Gulf Stream. The Loop Current is an extension of the western boundary current of the North Atlantic subtropical gyre. Serving as the dominant circulation feature in the Eastern Gulf of Mexico, the Loop Currents transports between 23 and 27 sverdrups and reaches maximum flow speeds of from 1.5 to 1.8 meters/second.
In atmospheric science, an atmospheric model is a mathematical model constructed around the full set of primitive, dynamical equations which govern atmospheric motions. It can supplement these equations with parameterizations for turbulent diffusion, radiation, moist processes, heat exchange, soil, vegetation, surface water, the kinematic effects of terrain, and convection. Most atmospheric models are numerical, i.e. they discretize equations of motion. They can predict microscale phenomena such as tornadoes and boundary layer eddies, sub-microscale turbulent flow over buildings, as well as synoptic and global flows. The horizontal domain of a model is either global, covering the entire Earth, or regional (limited-area), covering only part of the Earth. The different types of models run are thermotropic, barotropic, hydrostatic, and nonhydrostatic. Some of the model types make assumptions about the atmosphere which lengthens the time steps used and increases computational speed.
The Lorenz system is a system of ordinary differential equations first studied by mathematician and meteorologist Edward Lorenz. It is notable for having chaotic solutions for certain parameter values and initial conditions. In particular, the Lorenz attractor is a set of chaotic solutions of the Lorenz system. The term "butterfly effect" in popular media may stem from the real-world implications of the Lorenz attractor, namely that several different initial chaotic conditions evolve in phase space in a way that never repeats, so all chaos is unpredictable. This underscores that chaotic systems can be completely deterministic and yet still be inherently unpredictable over long periods of time. Because chaos continually increases in systems, it is impossible to predict the future of systems well. For instance, even the small flap of a butterfly's wings could set the world on a vastly different trajectory, such as by causing a hurricane. The shape of the Lorenz attractor itself, when plotted in phase space, may also be seen to resemble a butterfly.
The material point method (MPM) is a numerical technique used to simulate the behavior of solids, liquids, gases, and any other continuum material. Especially, it is a robust spatial discretization method for simulating multi-phase (solid-fluid-gas) interactions. In the MPM, a continuum body is described by a number of small Lagrangian elements referred to as 'material points'. These material points are surrounded by a background mesh/grid that is used to calculate terms such as the deformation gradient. Unlike other mesh-based methods like the finite element method, finite volume method or finite difference method, the MPM is not a mesh based method and is instead categorized as a meshless/meshfree or continuum-based particle method, examples of which are smoothed particle hydrodynamics and peridynamics. Despite the presence of a background mesh, the MPM does not encounter the drawbacks of mesh-based methods which makes it a promising and powerful tool in computational mechanics.
In fluid dynamics, wind wave modeling describes the effort to depict the sea state and predict the evolution of the energy of wind waves using numerical techniques. These simulations consider atmospheric wind forcing, nonlinear wave interactions, and frictional dissipation, and they output statistics describing wave heights, periods, and propagation directions for regional seas or global oceans. Such wave hindcasts and wave forecasts are extremely important for commercial interests on the high seas. For example, the shipping industry requires guidance for operational planning and tactical seakeeping purposes.
The moving particle semi-implicit (MPS) method is a computational method for the simulation of incompressible free surface flows. It is a macroscopic, deterministic particle method developed by Koshizuka and Oka (1996).
The sigma coordinate system is a common coordinate system used in computational models for oceanography, meteorology and other fields where fluid dynamics are relevant. This coordinate system receives its name from the independent variable used to represent a scaled pressure level.
Gerris is computer software in the field of computational fluid dynamics (CFD). Gerris was released as free and open-source software, subject to the requirements of the GNU General Public License (GPL), version 2 or any later.
Regional Ocean Modeling System (ROMS) is a free-surface, terrain-following, primitive equations ocean model widely used by the scientific community for a diverse range of applications. The model is developed and supported by researchers at the Rutgers University, University of California Los Angeles and contributors worldwide.
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The ADCIRC model is a high-performance, cross-platform numerical ocean circulation model popular in simulating storm surge, tides, and coastal circulation problems. Originally developed by Drs. Rick Luettich and Joannes Westerink, the model is developed and maintained by a combination of academic, governmental, and corporate partners, including the University of North Carolina at Chapel Hill, the University of Notre Dame, and the US Army Corps of Engineers. The ADCIRC system includes an independent multi-algorithmic wind forecast model and also has advanced coupling capabilities, allowing it to integrate effects from sediment transport, ice, waves, surface runoff, and baroclinicity.
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The Kuroshio Current is a northward flowing Western Boundary Current (WBC) in the Pacific Ocean. It is a bifurcation arm of the North Equatorial Current and consists of northwestern Pacific Ocean water. The other arm is the southward flowing Mindanao Current. The Kuroshio Current flows along the eastern Philippine coast, up to 13.7 Sv... of it leaking into the Luzon Strait - the gap between the Philippines and Taiwan - before continuing along the Japanese coast. Some of the leaked water manages to intrude into the South China Sea (SCS). This affects the heat and salt budgets and circulation and eddy generation mechanisms in the SCS. There are various theories about possible intrusion paths and what mechanisms initiate them.
Lagrangian ocean analysis is a way of analysing ocean dynamics by computing the trajectories of virtual fluid particles, following the Lagrangian perspective of fluid flow, from a specified velocity field. Often, the Eulerian velocity field used as an input for Lagrangian ocean analysis has been computed using an ocean general circulation model (OGCM). Lagrangian techniques can be employed on a range of scales, from modelling the dispersal of biological matter within the Great Barrier Reef to global scales. Lagrangian ocean analysis has numerous applications, from modelling the diffusion of tracers, through the dispersal of aircraft debris and plastics, to determining the biological connectivity of ocean regions.
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OceanParcels, “Probably A Really Computationally Efficient Lagrangian Simulator”, is a set of python classes and methods that is used to track particles like water, plankton and plastics. It uses the output of ocean general circulation model (OGCMs). OceanParcels main goal is to process the increasingly large amounts of data that is governed by OGCM's. The flow dynamics are simulated using Lagrangian modelling and the geophysical fluid dynamics are simulated with Eulerian modelling or provided through experimental data. OceanParcels is dependent on two principles, namely the ability to read external data sets from different formats and customizable kernels to define particle dynamics.
Ronald J. Stouffer is a meteorologist and adjunct professor at the University of Arizona, formerly Senior Research Climatologist and head of the Climate and Ecosystems Group at the Geophysical Fluid Dynamics Laboratory (GFDL), part of NOAA. He has also served on the faculty of Princeton University.
