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Currently, the most popular class of methods for solving partial
differential equations on the sphere is the spectral transform
method (STM), which expresses the variables of interest as
series expansions in terms of the so-called spherical harmonic
basis functions.
The spherical harmonics gives spectral convergence for smooth flows,
are extremely stable, and represent functions isotropically.
The drawbacks of the STM, however, are the computational complexity
and communication overheads.
The STM requires O(N^3) operations, where N is the number of
latitude points. This is more than any other calculation in weather
modeling by a factor of N. And on distributed memory computer
architectures, the global nature of the STM imposes overhead in
the form of communication between processors which is
significant as N is increased. These two problems have led to a
search for a more efficient replacement for the STM, which
doesn't sacrifice too much in the way of accuracy and stability.
We study the possibility of
replacing the popular spectral transform method with the double Fourier method.
The method resides in spectral space, and transforms
to grid space only for nonlinear terms.
This approach minimizes the number of transposes required and thus minimizes
the required inter-processor communication.
Compared to the standard spectral transform method,
the double Fourier method requires an equally
spaced latitude grid instead of a Gauss distribution and utilizes
FFTs in the latitude direction rather than the more expensive associated
Legendre transforms.
A desirable aspect of the double Fourier approach is that its accuracy and
stability are identical to the spectral transform method on an equispaced
grid within machine precision.
When an Eulerian time integration method is used,
numerical stability is maintained by projecting data onto the spherical
harmonics.
Thus, the Eulerian approach offers little saving over the standard
spectral transform method.
(Currently, the most efficient spectral transform method requires 9
Legendre transforms per time step; the filter approach reduces this to 6.)
However, we believe that when combined with a semi-Lagrangian advection
scheme, it may be possible for the method to maintain stability without
using a projection (thus, requiring none or very few Legendre transforms).
This is because the nonlinearity in the SWEs arise mostly from the
advection terms.
which do not appear explicitly in the Lagrangian formulation of the equations.
Thus, the semi-Lagrangian double Fourier method, with a computational
complexity of O(N^2 log N), may be significantly more
efficient than the spectral transform method.
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