Regional Ocean Modeling System

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.

ROMS is used to model how a given region of the ocean responds to physical forcings such as heating or wind. It can also be used to model how a given ocean system responds to inputs like sediment, freshwater, ice, or nutrients, requiring coupled models nested within the ROMS framework.

Framework

ROMS is a 4D model, i.e. a 3-dimensional model that can be run to evaluate change over a given amount of time. It is gridded into vertical layers that make up the water column and horizontal cells that make up the coordinates of the 2D cartesian plane of the model region.

Kernel

Central to the ROMS model are four models that form what is called the dynamical center or "kernel" of the model:

  1. Nonlinear kernel (NLM)[1][2]
  2. Tangent linear kernel (TLM)
  3. Representer tangent linear kernel (RPM)
  4. Adjoint kernel (ADM)[3]

Vertical grid

The vertical grid is a hybrid stretched grid. It is hybrid in that its stretching intervals fall somewhere between the two extremes of 1) the evenly-spaced sigma grid used by the Princeton Ocean Model and 2) a true z-grid with a static depth interval . The vertical grid can be squeezed or stretched to increase or decrease the resolution for an area of interest, such as a thermocline or bottom boundary layer. Grid stretching in the vertical direction follows bottom topography, allowing for the idealized flow of water over features such as seamounts. [4]

Horizontal grid

The horizontal grid is a structured grid, meaning that it has a rectangular 4-sided grid cell structure. The horizontal grid is also an orthoganal curvilinear grid, meaning that it maximizes ocean grid cells of interest and minimizes extra land grid cells. The horizontal grid is also a staggered grid or Arakawa-C grid, where the velocities in the north-south and east-west directions are calculated at the edges of each grid cell, while the values for scalar variables such as density are calculated at the center of each grid cell, known as "rho-points."

Physics

In both the vertical and horizontal directions, the default equations use centered, second-order finite difference schemes. Higher order schemes are available if desired, for example using parabolic spline reconstruction.[2]

In general, the physical schemes used by ROMS are based on three governing equations:

  1. Continuity
  2. Conservation of momentum (Navier-Stokes)
  3. Transport equations of tracer variables (such as salinity and temperature)

Equations are coupled to solve for five unknowns at each location in the model grid using numerical solutions:

  • East-west velocity (u)
  • North-south velocity (v)
  • Vertical velocity (w)
  • Salinity
  • Temperature

Source code

ROMS uses an open-access source code that can be downloaded by filling out an online request form. It runs on C-processing and was developed for shared computing uses. To download the source code a user must create an account and file a request with the developers on the ROMS website.

Input and output

Input

Boundaries such as coastlines can be specified for a given region using land- and sea-masking. The top vertical boundary, the air-sea interface, uses an interaction scheme developed by Fairall et al. (1996).[5] The bottom vertical boundary, the sediment-water interface, uses a bottom stress or bottom-boundary-layer scheme developed by Styles and Glenn (2000).[6]

Inputs that are needed for an implementer to run ROMS for a specific ocean region include:

  • Bathymetry and coastline
  • Freshwater input
  • Wind
  • Tides
  • Open boundary forcings (idealized, such as a reanalysis product, or specific data)
  • Heat flux
  • Physical mixing (see above)

The programming framework of ROMS is split into three parts: Initialize, Run, and Finalize, which is standard for the Earth System Modeling Framework (ESMF). "Run" is the largest of these three parts, where the user chooses which options they want to use and assimilates data if desired.[7] The model run must be initialized or compiled before it is run.

Output

The output format of model run files is netCDF. Model output is often visualized using independent secondary programming software such as MATLAB or Python, or visualization software such as Panoply.

User options

The general approach of ROMS gives model implementers a high level of freedom and responsibility. One approach cannot meet the needs of all the diverse applications the model is currently used for. Therefore, it is up to each model implementer (either an individual or a research group) to choose how they want to use each of the available options. Options include choices such as:

  • Mixing formulations in the horizontal and vertical directions
  • Vertical grid stretching
  • Processing mode (serial, parallel with MPI, or parallel with OpenMP)
  • Debugging turned on or off [8]

When using ROMS, if an implementer runs into a problem or bug, they can report it to the ROMS forum.

Applications
A daily, global Sea Surface Temperature (SST) data set from December 2013 produced at 1-km resolution (also known as ultra-high resolution) by the JPL ROMS group.

The versatility of ROMS has been proven in its diverse applications to different systems and regions. It is best applied to mesoscale systems,[9] or those systems that can be mapped at high resolution, such as 1-km to 100-km grid spacing.

Coupled model applications

Biogeochemical, bio-optical, sea ice, sediment, and other models can be embedded within the ROMS framework to study specific processes. These are usually developed for specific regions of the world's oceans but can be applied elsewhere. For example, the sea ice application of ROMS was originally developed for the Barents Sea Region.[10]

ROMS modeling efforts are increasingly being coupled with observational platforms, such as buoys, satellites, and ship-mounted underway sampling systems, to provide more accurate forecasting of ocean conditions.

Regional applications

There is an ever-growing number of applications of ROMS to particular regions of the world's oceans. These integrated ocean modeling systems use ROMS for the circulation component, and add other variables and processes of interest. A few examples are:

  • Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST)[11]
  • Experimental System for Predicting Shelf and Slope Optics (ESPRESSO)
  • New York Harbor Observing and Prediction System (NYHOPS)
  • Chesapeake Bay Estuarine Carbon & Biogeochemistry (ChesROMS ECB)[12]
  • Climatic indices in the Gulf of Alaska[13]
  • LiveOcean daily forecast model of the NE Pacific and Salish Sea
gollark: Once I made a Rust program!
gollark: I use other things too!
gollark: PARADOX!
gollark: So now we agree on you disagreeing with me.
gollark: <@!309787486278909952> I must also disagree with gollark.

See also

References
  1. Shchepetkin, Alexander F. (2003). "A method for computing horizontal pressure-gradient force in an oceanic model with a nonaligned vertical coordinate". Journal of Geophysical Research. 108 (C3). doi:10.1029/2001jc001047. ISSN 0148-0227.
  2. Shchepetkin, A.F.; McWilliams, J.C. (2005). The Regional Ocean Modeling System: A Split-Explicit, Free-Surface, Topography-Following-Coordinate Ocean Model, 2003. Los Angeles, California: University of California at Los Angeles: Institute of Geophysics and Planetary Physics.
  3. Moore, Andrew M.; Arango, Hernan G.; Di Lorenzo, Emanuele; Cornuelle, Bruce D.; Miller, Arthur J.; Neilson, Douglas J. (2004-01-01). "A comprehensive ocean prediction and analysis system based on the tangent linear and adjoint of a regional ocean model". Ocean Modelling. 7 (1–2): 227–258. doi:10.1016/j.ocemod.2003.11.001. ISSN 1463-5003.
  4. Song, Yuhe; Haidvogel, Dale (1994-11-01). "A Semi-implicit Ocean Circulation Model Using a Generalized Topography-Following Coordinate System". Journal of Computational Physics. 115 (1): 228–244. doi:10.1006/jcph.1994.1189. ISSN 0021-9991.
  5. Fairall, C. W.; Bradley, E. F.; Rogers, D. P.; Edson, J. B.; Young, G. S. (1996-02-15). "Bulk parameterization of air-sea fluxes for Tropical Ocean-Global Atmosphere Coupled-Ocean Atmosphere Response Experiment". Journal of Geophysical Research: Oceans. 101 (C2): 3747–3764. CiteSeerX 10.1.1.469.6689. doi:10.1029/95jc03205. ISSN 0148-0227.
  6. Styles, Richard; Glenn, Scott M. (2000-10-15). "Modeling stratified wave and current bottom boundary layers on the continental shelf" (PDF). Journal of Geophysical Research: Oceans. 105 (C10): 24119–24139. doi:10.1029/2000jc900115. ISSN 0148-0227.
  7. "ROMS > start". www.myroms.org. Retrieved 2019-02-08.
  8. Hedstrom, Katherine S. (2016). "Technical Manual for a Coupled Sea-Ice/Ocean Circulation Model (Version 5)" (PDF). OCS Study BOEM 2016-037. Cooperative Agreement No. M15AC00011.
  9. "Met Office: Mesoscale modelling". 2010-12-29. Retrieved 2018-04-26.
  10. Budgell, W. P. (2005-12-01). "Numerical simulation of ice-ocean variability in the Barents Sea region". Ocean Dynamics. 55 (3–4): 370–387. doi:10.1007/s10236-005-0008-3. ISSN 1616-7341.
  11. Warner, John C.; Armstrong, Brandy; He, Ruoying; Zambon, Joseph B. (2010-01-01). "Development of a Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) Modeling System" (PDF). Ocean Modelling. 35 (3): 230–244. doi:10.1016/j.ocemod.2010.07.010. hdl:1912/4099. ISSN 1463-5003.
  12. Feng, Yang; Friedrichs, Marjorie A. M.; Wilkin, John; Tian, Hanqin; Yang, Qichun; Hofmann, Eileen E.; Wiggert, Jerry D.; Hood, Raleigh R. (2015). "Chesapeake Bay nitrogen fluxes derived from a land-estuarine ocean biogeochemical modeling system: Model description, evaluation, and nitrogen budgets". Journal of Geophysical Research: Biogeosciences. 120 (8): 1666–1695. doi:10.1002/2015jg002931. PMC 5014239. PMID 27668137.
  13. Combes, Vincent; Di Lorenzo, Emanuele (2007-10-01). "Intrinsic and forced interannual variability of the Gulf of Alaska mesoscale circulation". Progress in Oceanography. 75 (2): 266–286. doi:10.1016/j.pocean.2007.08.011. hdl:1853/14532. ISSN 0079-6611.
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