A Portable Parallel Implementation of the U.S. Navy Layered Ocean Model

1995 ◽  
Author(s):  
A. J. Wallcraft ◽  
D. R. Moore
2019 ◽  
Vol 7 (6) ◽  
pp. 185
Author(s):  
Manuel Valera ◽  
Mary P. Thomas ◽  
Mariangel Garcia ◽  
Jose E. Castillo

The General Curvilinear Coastal Ocean Model (GCCOM) is a 3D curvilinear, structured-mesh, non-hydrostatic, large-eddy simulation model that is capable of running oceanic simulations. GCCOM is an inherently computationally expensive model: it uses an elliptic solver for the dynamic pressure; meter-scale simulations requiring memory footprints on the order of 10 12 cells and terabytes of output data. As a solution for parallel optimization, the Fortran-interfaced Portable–Extensible Toolkit for Scientific Computation (PETSc) library was chosen as a framework to help reduce the complexity of managing the 3D geometry, to improve parallel algorithm design, and to provide a parallelized linear system solver and preconditioner. GCCOM discretizations are based on an Arakawa-C staggered grid, and PETSc DMDA (Data Management for Distributed Arrays) objects were used to provide communication and domain ownership management of the resultant multi-dimensional arrays, while the fully curvilinear Laplacian system for pressure is solved by the PETSc linear solver routines. In this paper, the framework design and architecture are described in detail, and results are presented that demonstrate the multiscale capabilities of the model and the parallel framework to 240 cores over domains of order 10 7 total cells per variable, and the correctness and performance of the multiphysics aspects of the model for a baseline experiment stratified seamount.


2004 ◽  
Vol 38 (1) ◽  
pp. 61-79 ◽  
Author(s):  
Laurence C. Breaker ◽  
Desiraju B. Rao ◽  
John G.W. Kelley ◽  
Ilya Rivin

This paper discusses the needs to establish a capability to provide real-time regional ocean forecasts and the feasibility of producing them on an operational basis. Specifically, the development of a Regional Ocean Forecast System using the Princeton Ocean Model (POM) as a prototype and its application to the East Coast of the U.S. are presented. The ocean forecasts are produced using surface forcing from the Eta model, the operational mesoscale weather prediction model at the National Centers for Environmental Prediction (NCEP). At present, the ocean forecast model, called the East Coast-Regional Ocean Forecast System (EC-ROFS) includes assimilation of sea surface temperatures from in situ and satellite data and sea surface height anomalies from satellite altimeters. Examples of forecast products, their evaluation, problems that arose during the development of the system, and solutions to some of those problems are also discussed. Even though work is still in progress to improve the performance of EC-ROFS, it became clear that the forecast products which are generated can be used by marine forecasters if allowances for known model deficiencies are taken into account. The EC-ROFS became fully operational at NCEP in March 2002, and is the first forecast system of its type to become operational in the civil sector of the United States.


2007 ◽  
Vol 41 (2) ◽  
pp. 23-30 ◽  
Author(s):  
Peter C. Chu ◽  
G. R. Amezaga, Jr ◽  
Eric L. Gottshall ◽  
David S. Cwalina

The U.S. Navy is a major investor in ocean model development. The pay-off of such an investment is the value-added ocean nowcast/forecast systems on naval operations and warfare effectiveness. The purpose of this paper is to investigate the value added of the Navy's nowcast/forecast system to naval antisubmarine warfare (ASW) and anti-surface warfare (ASUW). The nowcast/forecast versus observational fields were used by the Weapon Acoustic Preset Program (WAPP) to determine the suggested presets for Mk 48 variant torpedo. The metric used to compare the two sets of outputs is the relative difference in acoustic coverage area generated by WAPP. Output presets are created for five different scenarios, two ASUW scenarios and three ASW scenarios in the South China Sea. The same metrics used in the nowcast/forecast case were used to generate and compare the acoustic coverage. Analysis of the output reveals that the ocean forecast system outperformed the nowcast system in most scenarios.


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