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Title: A Parallel Ocean Model With Adaptive Mesh Refinement Capability For Global Ocean Prediction

Abstract

An ocean model with adaptive mesh refinement (AMR) capability is presented for simulating ocean circulation on decade time scales. The model closely resembles the LLNL ocean general circulation model with some components incorporated from other well known ocean models when appropriate. Spatial components are discretized using finite differences on a staggered grid where tracer and pressure variables are defined at cell centers and velocities at cell vertices (B-grid). Horizontal motion is modeled explicitly with leapfrog and Euler forward-backward time integration, and vertical motion is modeled semi-implicitly. New AMR strategies are presented for horizontal refinement on a B-grid, leapfrog time integration, and time integration of coupled systems with unequal time steps. These AMR capabilities are added to the LLNL software package SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) and validated with standard benchmark tests. The ocean model is built on top of the amended SAMRAI library. The resulting model has the capability to dynamically increase resolution in localized areas of the domain. Limited basin tests are conducted using various refinement criteria and produce convergence trends in the model solution as refinement is increased. Carbon sequestration simulations are performed on decade time scales in domains the size of the North Atlantic andmore » the global ocean. A suggestion is given for refinement criteria in such simulations. AMR predicts maximum pH changes and increases in CO 2 concentration near the injection sites that are virtually unattainable with a uniform high resolution due to extremely long run times. Fine scale details near the injection sites are achieved by AMR with shorter run times than the finest uniform resolution tested despite the need for enhanced parallel performance. The North Atlantic simulations show a reduction in passive tracer errors when AMR is applied instead of a uniform coarse resolution. No dramatic or persistent signs of error growth in the passive tracer outgassing or the ocean circulation are observed to result from AMR.« less

Authors:
 [1]
  1. Univ. of California, Davis, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
883585
Report Number(s):
UCRL-TH-215803
TRN: US200615%%154
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Thesis/Dissertation
Country of Publication:
United States
Language:
English
Subject:
16 TIDAL AND WAVE POWER; 58 GEOSCIENCES; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; BENCHMARKS; CARBON SEQUESTRATION; CONVERGENCE; DEGASSING; FORECASTING; GENERAL CIRCULATION MODELS; LAWRENCE LIVERMORE NATIONAL LABORATORY; PERFORMANCE; RESOLUTION

Citation Formats

Herrnstein, Aaron R. A Parallel Ocean Model With Adaptive Mesh Refinement Capability For Global Ocean Prediction. United States: N. p., 2005. Web. doi:10.2172/883585.
Herrnstein, Aaron R. A Parallel Ocean Model With Adaptive Mesh Refinement Capability For Global Ocean Prediction. United States. doi:10.2172/883585.
Herrnstein, Aaron R. Thu . "A Parallel Ocean Model With Adaptive Mesh Refinement Capability For Global Ocean Prediction". United States. doi:10.2172/883585. https://www.osti.gov/servlets/purl/883585.
@article{osti_883585,
title = {A Parallel Ocean Model With Adaptive Mesh Refinement Capability For Global Ocean Prediction},
author = {Herrnstein, Aaron R.},
abstractNote = {An ocean model with adaptive mesh refinement (AMR) capability is presented for simulating ocean circulation on decade time scales. The model closely resembles the LLNL ocean general circulation model with some components incorporated from other well known ocean models when appropriate. Spatial components are discretized using finite differences on a staggered grid where tracer and pressure variables are defined at cell centers and velocities at cell vertices (B-grid). Horizontal motion is modeled explicitly with leapfrog and Euler forward-backward time integration, and vertical motion is modeled semi-implicitly. New AMR strategies are presented for horizontal refinement on a B-grid, leapfrog time integration, and time integration of coupled systems with unequal time steps. These AMR capabilities are added to the LLNL software package SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) and validated with standard benchmark tests. The ocean model is built on top of the amended SAMRAI library. The resulting model has the capability to dynamically increase resolution in localized areas of the domain. Limited basin tests are conducted using various refinement criteria and produce convergence trends in the model solution as refinement is increased. Carbon sequestration simulations are performed on decade time scales in domains the size of the North Atlantic and the global ocean. A suggestion is given for refinement criteria in such simulations. AMR predicts maximum pH changes and increases in CO2 concentration near the injection sites that are virtually unattainable with a uniform high resolution due to extremely long run times. Fine scale details near the injection sites are achieved by AMR with shorter run times than the finest uniform resolution tested despite the need for enhanced parallel performance. The North Atlantic simulations show a reduction in passive tracer errors when AMR is applied instead of a uniform coarse resolution. No dramatic or persistent signs of error growth in the passive tracer outgassing or the ocean circulation are observed to result from AMR.},
doi = {10.2172/883585},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2005},
month = {12}
}

Thesis/Dissertation:
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