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Fibonacci grids: A novel approach to global modelling
Author(s) -
Swinbank Richard,
James Purser R.
Publication year - 2006
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1256/qj.05.227
Subject(s) - grid , computer science , computational science , isotropy , massively parallel , gravitational singularity , mathematics , algorithm , theoretical computer science , parallel computing , geometry , mathematical analysis , physics , quantum mechanics
Recent years have seen a resurgence of interest in a variety of non‐standard computational grids for global numerical prediction. The motivation has been to reduce problems associated with the converging meridians and the polar singularities of conventional regular latitude–longitude grids. A further impetus has come from the adoption of massively parallel computers, for which it is necessary to distribute work equitably across the processors; this is more practicable for some non‐standard grids. Desirable attributes of a grid for high‐order spatial finite differencing are: (i) geometrical regularity; (ii) a homogeneous and approximately isotropic spatial resolution; (iii) a low proportion of the grid points where the numerical procedures require special customization (such as near coordinate singularities or grid edges); (iv) ease of parallelization. One family of grid arrangements which, to our knowledge, has never before been applied to numerical weather prediction, but which appears to offer several technical advantages, are what we shall refer to as ‘Fibonacci grids’. These grids possess virtually uniform and isotropic resolution, with an equal area for each grid point. There are only two compact singular regions on a sphere that require customized numerics. We demonstrate the practicality of this type of grid in shallow‐water simulations, and discuss the prospects for efficiently using these frameworks in three‐dimensional weather prediction or climate models. © Crown copyright, 2006. Royal Meteorological Society

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