POM (Princeton Ocean Model)

A simple-to-run yet powerful ocean modeling code to simulate a wide-range of problems, from small-scale coastal processes to global ocean climate change. POM is a sigma coordinate (terrain-following), free surface ocean model with embedded turbulence and wave sub-models, and wet-dry capability.

ocean modelingcoastal processessigma coordinatefree surfaceturbulencewave
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contributed at 2019-10-16

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Princeton University
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Application-focused categoriesNatural-perspectiveOcean regions

Model Description

English {{currentDetailLanguage}} English

Quoted from: http://www.ccpo.odu.edu/POMWEB/index.html and http://mafija.fmf.uni-lj.si/seminar/files/2006_2007/semeng.pdf 

The Princeton Ocean Model[8] (POM) is a community general circulation numerical ocean model, that can be used to simulate and predict oceanic currents, temperatures, salinity and other water properties. The model code was originally developed in late 1970’s at Princeton University[4] and Analysis of Princeton[7] by Alan Blumberg and George Mellor with later contributions from other people. The model incorporates the Mellor-Yamada turbulence scheme developed in the early 1970’s by George Mellor and Ted Yamada; this turbulence sub–model is widely used by oceanic and atmospheric models. In the past, early computer ocean models such as the Bryan-Cox model (developed in the late 1960’s at the Geophysical Fluid Dynamics Laboratory, GFDL, later became the Modular Ocean Model1 , MOM)), which aimed mostly at coarse–resolution simulations of the large–scale ocean circulation, so there was still a need for a numerical model, that can handle high–resolution calculation of coastal ocean. The BlumbergMellor[8] model, which later became known as 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 1980’s, 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 which were simulated 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). The principal attributes of the POM model are as follows: • It contains an embedded second moment turbulence closure sub-model to provide vertical mixing coefficients. • It is a sigma coordinate model in that the vertical coordinate is scaled on the water column depth. • The horizontal curvilinear orthogonal coordinates and an Arakava C differencing scheme. • The horizontal time differencing is explicit whereas the vertical differencing is implicit. This later eliminates time constraints for the vertical coordinate and permits the use of fine vertical resolution in the surface and bottom boundary layers. • The model is able to use free surface and a split time step. The external model portion of the model is two–dimensional and uses a short time step based on the CFL2 condition and the external wave speed. The internal mode is three–dimensional and uses a long time step based on the CFL condition and the internal wave speed.• Complete thermodynamics have been implemented. The turbulence closure sub-model is one that was introduced my George Mellor, 1973 and was significantly advanced in collaboration with Tetsuji Yamada (Mellor and Yamada, 1974; Mellor and Yamada, 1982). It is often cited in the literature as the Mellor and Yamada turbulence closure model. There are other versions of model in existence such as a non-Boussinesq3 version and a more general vertical coordinate version of which the sigma coordinate is a special case.

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How to Cite

George Mellor, Alan Blumberg (2019). POM (Princeton Ocean Model), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/4a741123-ef39-4149-87b9-225e7ff9d4a7
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Last modifier : 
zhangshuo
Last modify time : 
2021-01-11
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Contributor(s)

Initial contribute: 2019-10-16

Authorship

Affiliation:  
Princeton University
Homepage:  
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Affiliation:  
Princeton University
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History

Last modifier : 
zhangshuo
Last modify time : 
2021-01-11
Modify times : 
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