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Analyzing the Adaptive Mesh Refinement (AMR) Characteristics of a High-Order 2D Cubed-Sphere Shallow-Water Model

Journal Article · · Monthly Weather Review
 [1];  [1];  [2];  [2];  [2];  [3]
  1. Univ. of Michigan, Ann Arbor, MI (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Univ. of California, Davis, CA (United States)
+ Show Author Affiliations
Adaptive mesh refinement (AMR) is a technique that has been featured only sporadically in atmospheric science literature. This study aims to demonstrate the utility of AMR for simulating atmospheric flows. Several test cases are implemented in a 2D shallow-water model on the sphere using the Chombo-AMR dynamical core. This high-order finite-volume model implements adaptive refinement in both space and time on a cubed-sphere grid using a mapped-multiblock mesh technique. The tests consist of the passive advection of a tracer around moving vortices, a steady-state geostrophic flow, an unsteady solid-body rotation, a gravity wave impinging on a mountain, and the interaction of binary vortices. Both static and dynamic refinements are analyzed to determine the strengths and weaknesses of AMR in both complex flows with small-scale features and large-scale smooth flows. The different test cases required different AMR criteria, such as vorticity or height-gradient based thresholds, in order to achieve the best accuracy for cost. The simulations show that the model can accurately resolve key local features without requiring global high-resolution grids. The adaptive grids are able to track features of interest reliably without inducing noise or visible distortions at the coarse–fine interfaces. Finally and furthermore, the AMR grids keep any degradations of the large-scale smooth flows to a minimum.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Grant/Contract Number:
AC02-05CH11231; SC0003990
OSTI ID:
1378731
Journal Information:
Monthly Weather Review, Journal Name: Monthly Weather Review Journal Issue: 12 Vol. 144; ISSN 0027-0644
Publisher:
American Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (3)

Automatic, unstructured mesh optimization for simulation and assessment of tide- and surge-driven hydrodynamics in a longitudinal estuary: St. Johns River journal April 2018
Sensitivity of Mountain Hydroclimate Simulations in Variable‐Resolution CESM to Microphysics and Horizontal Resolution journal June 2018
WAVETRISK-1.0: an adaptive wavelet hydrostatic dynamical core journal January 2019

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Related Subjects

54 ENVIRONMENTAL SCIENCES
58 GEOSCIENCES
adaptive models
multigrid models
shallow-water equations