A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations
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During the next decade and beyond, climate system models will be challenged to resolve scales and processes that are far beyond their current scope. Each climate system component has its prototypical example of an unresolved process that may strongly influence the global climate system, ranging from eddy activity within ocean models, to ice streams within ice sheet models, to surface hydrological processes within land system models, to cloud processes within atmosphere models. These new demands will almost certainly result in the develop of multiresolution schemes that are able, at least regionally, to faithfully simulate these fine-scale processes. Spherical centroidal Voronoi tessellations (SCVTs) offer one potential path toward the development of a robust, multiresolution climate system model components. SCVTs allow for the generation of high-quality Voronoi diagrams and Delaunay triangulations through the use of an intuitive, user-defined density function. In each of the examples provided, this method results in high-quality meshes where the quality measures are guaranteed to improve as the number of nodes is increased. Real-world examples are developed for the Greenland ice sheet and the North Atlantic ocean. Idealized examples are developed for ocean–ice shelf interaction and for regional atmospheric modeling. In addition to defining, developing, and exhibiting SCVTs, we pair this mesh generation technique with a previously developed finite-volume method. Our numerical example is based on the nonlinear, shallow-water equations spanning the entire surface of the sphere. This example is used to elucidate both the po tential benefits of this multiresolution method and the challenges ahead.
KeywordsVoronoi diagram Delaunay triangulation Climate modeling Multiresolution
This work was supported by the DOE Office of Science Climate Change Prediction Program through DE-FG02-07ER64431, DE-FG02-07ER64432, and DOE 07SCPF152. The authors would like to thank Dr. Sebastien Legrand and two anonymous reviewers for their constructive comments.
- Comblen R, Legrand S, Deleersnijder E, Legat V (2008) A finite element method for solving the shallow water equations on the sphere. Ocean Model. doi:10.1016/j.ocemod.2008.05.004
- Gersho A, Gray R (1992) Vector quantization and signal compression. Kluwer, BostonGoogle Scholar
- International Panel on Climate Change (2007) Climate change 2007: the scientific basis. International Panel on Climate Change, ValenciaGoogle Scholar
- MacQueen J (1967) Some methods for classification and analysis of multivariate observations. In: Proc. fifth Berkeley symposium on mathematical statistics and probability, vol I. University of California, Berkeley, pp 281–297Google Scholar
- Nair R, Thomas S, Loft R (2005) A discontinuous Galerkin global shallow water model. Mon Weather Rev 133:867–888Google Scholar
- Okabe A, Boots B, Sugihara K, Chiu S (2000) Spatial tessellations: concepts and applications of Voronoi diagrams, 2nd edn. Wiley, ChichesterGoogle Scholar