Space-time transformation in flux-form semi-Lagrangian schemes
Chu, Peter C.
MetadataShow full item record
With a finite volume approach, a flux-form semi-Lagrangian (TFSL) scheme with space-time transformation was developed to provide stable and accurate algorithm in solving the advection-diffusion equation. Different from the existing fluxform semi-Lagrangian schemes, the temporal integration of the flux from the present to the next time step is transformed into a spatial integration of the flux at the side of a grid cell (space) for the present time step using the characteristic-line concept. The TFSL scheme not only keeps the good features of the semi-Lagrangian schemes (no Courant number limitation), but also has higher accuracy (of a second order in both time and space). The capability of the TFSL scheme is demonstrated by the simulation of the equatorial Rossby-soliton propagation. Computational stability and high accuracy makes this scheme useful in ocean modeling, computational fluid dynamics, and numerical weather prediction.
Terrestrial, Atmospheric, and Oceanic Sciences
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Showing items related by title, author, creator and subject.
Fan, Chenwu; Chu, Peter C. (2001-07);How to reduce the computational error is a key issue in numerical modeling and simulation. The higher the order of the difference scheme, the less the truncation error and the more complicated the computation. For compromise, ...
Hydrostatic correction for reducing horizontal pressure gradient errors in sigma coordinate models Fan, C.W.; Chu, Peter C. (2003);How to reduce the horizontal pressure gradient error is a key issue in terrain-following coastal models. The horizontal pressure gradient splits into two parts, and incomplete cancellation of the truncation errors of ...
Chu, Peter C.; Fan, Chenwu (2003);How to reduce the horizontal pressure gradient error is a key issue in terrain-following coastal models. The horizontal pressure gradient splits into two parts, and incomplete cancellation of the truncation errors of those ...