Weller, H.
ORCID: https://orcid.org/0000-0003-4553-7082, Weller, H. G.
ORCID: https://orcid.org/0000-0003-4553-7082 and Fournier, A.
(2009)
Voronoi, Delaunay, and Block-Structured Mesh Refinement for Solution of the Shallow-Water Equations on the Sphere.
Monthly Weather Review, 137 (12).
pp. 4208-4224.
ISSN 0027-0644
doi: 10.1175/2009MWR2917.1
Abstract/Summary
Alternative meshes of the sphere and adaptive mesh refinement could be immensely beneficial for weather and climate forecasts, but it is not clear how mesh refinement should be achieved. A finite-volume model that solves the shallow-water equations on any mesh of the surface of the sphere is presented. The accuracy and cost effectiveness of four quasi-uniform meshes of the sphere are compared: a cubed sphere, reduced latitude–longitude, hexagonal–icosahedral, and triangular–icosahedral. On some standard shallow-water tests, the hexagonal–icosahedral mesh performs best and the reduced latitude–longitude mesh performs well only when the flow is aligned with the mesh. The inclusion of a refined mesh over a disc-shaped region is achieved using either gradual Delaunay, gradual Voronoi, or abrupt 2:1 block-structured refinement. These refined regions can actually degrade global accuracy, presumably because of changes in wave dispersion where the mesh is highly nonuniform. However, using gradual refinement to resolve a mountain in an otherwise coarse mesh can improve accuracy for the same cost. The model prognostic variables are height and momentum collocated at cell centers, and (to remove grid-scale oscillations of the A grid) the mass flux between cells is advanced from the old momentum using the momentum equation. Quadratic and upwind biased cubic differencing methods are used as explicit corrections to a fast implicit solution that uses linear differencing.
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| Item Type | Article |
| URI | https://reading-clone.eprints-hosting.org/id/eprint/1956 |
| Identification Number/DOI | 10.1175/2009MWR2917.1 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology |
| Publisher | American Meteorological Society |
| Download/View statistics | View download statistics for this item |
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