The development of grids smoothly covering the sphere has had a long history in computational meteorology that has led to two distinct approaches: (i) the stereographic approach in which the sphere is covered by two overlapping patches obtained by stereographic projection about the North and South poles ; and (ii) the cubed-sphere approach in which the sphere is covered by the 6 patches obtained by a projection of the faces of a circumscribed cube . A discussion of the advantages of each of these methods and a comparison of their performance in a standard fluid testbed are given in . In numerical relativity, the stereographic method has been reinvented in the context of the characteristic evolution problem ; and the cubed-sphere method has been reinvented in building an apparent horizon finder . The cubed sphere module, including the interpatch transformations, has been integrated into the Cactus toolkit and later applied to black hole excision . Perhaps the most ingenious treatment of the sphere, based upon a toroidal map, was devised by the Canberra group in building their characteristic code . These methods are described below.
Motivated by problems in meteorology, G. L. Browning, J. J. Hack and P. N. Swartztrauber  developed the first finite difference scheme based upon a composite mesh with two overlapping stereographic coordinate patches, each having a circular boundary centered about the North or South poles. Values for quantities required at ghost points beyond the boundary of one of the patches were interpolated from values in the other patch. Because a circular boundary does not fit regularly on a stereographic grid, dissipation was found necessary to remove the short wavelength error resulting from the inter-patch interpolations. They used the shallow water equations as a testbed to compare their approach to existing spectral approaches in terms of computer time, execution rate and accuracy. Such comparisons of different numerical methods can be difficult. Both the finite difference and spectral approaches gave good results and were competitive in terms of overall operation count and memory requirements For the particular initial data sets tested, the spectral approach had an advantage but not enough to give clear indication of the suitability of one method over another. The spectral method with M modes requires operations per time step compared with for a finite difference method on a grid. However, assuming that the solution is smooth, the accuracy of the spectral method is compared to, say, for a sixth order finite difference method. Hence, for comparable accuracy, which implies that the operation count for the spectral and finite difference methods are and , respectively. Thus for sufficiently high accuracy, i.e. large , the spectral method requires fewer operations. The issue of spectral vs finite difference methods thus depends on the nature of the smoothness of the physical problem being addressed and the accuracy desired.
The Pitt null code was first developed using two stereographic patches with square boundaries, each overlapping the equator. This has recently been modified based upon the approach advocated in , which retains the original stereographic coordinates but shrinks the overlap region by masking a circular boundary near the equator. The original square boundaries aligned with the grid and did not require numerical dissipation. However, the corners of the square boundary, besides being a significant waste of economy, were a prime source of inaccuracy. The resolution at the corners is only 1/9th that at the poles due to the stretching of the stereographic map. Near the equator, the resolution is approximately 1/2 that at the poles. The use of a circular boundary requires an angular version of numerical dissipation to control the resulting high frequency error (see Section 4.2.1).
A crucial ingredient of the PITT code is the -module  which incorporates a computational version of the Newman–Penrose eth-formalism . The underlying method can be applied to any smooth coordinatization of the sphere based upon several patches. The unit sphere metric , defined by these coordinates, is decomposed in each patch in terms of a complex basis vector ,
C. Ronchi, R. Iacono and P. S. Paolucci , developed the “cubed-sphere” approach as a new gridding method for solving global meteorological problems. The method decomposes the sphere into the 6 identical regions obtained by projection of a cube circumscribed on its surface. This gives a variation of the composite mesh method in which the 6 domains butt up against each other along shared grid boundaries. As a result only 1-dimensional intergrid interpolations are necessary (as opposed to the 2-dimensional interpolations of the stereographic grid), which results in enhanced accuracy. The symmetry of the scheme, in which the six patches have the same geometric structure and grid, also allows efficient use of parallel computer architectures. Their tests of the cubed sphere method based upon the simulation of shallow water waves in spherical geometry show that the numerical solutions are as accurate as those with spectral methods, with substantial saving in execution time. Recently, the cubed-sphere method has also been developed for application to characteristic evolution in numerical relativity [201, 111]. The eth-calculus is used to treat tensor fields on the sphere in the same way as in the stereographic method except the interpatch transformations now involve 6, rather than 2, sets of basis vectors.
The Canberra group treats fields on the sphere by taking advantage of the existence of a smooth map from the torus to the sphere . The pullback of this map allows functions on the sphere to be expressed in terms of toroidal coordinates. The intrinsic topology of these toroidal coordinates allow them to take advantage of of fast-Fourier transforms to implement a highly efficient pseudo-spectral treatment. This ingenious method has apparently not yet been adopted in other fields.
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