Difference between revisions of "Convergence study with SELFE"
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If you are doing a convergence study, you need to keep the CFL number fixed while reducing the time step (which means you have to reduce the grid spacing). | If you are doing a convergence study, you need to keep the CFL number fixed while reducing the time step (which means you have to reduce the grid spacing). | ||
| − | For a given grid, the errors changes with dt in a nonlinear manner [[File:SELFE-sensitivity-timestep-Aug2012.png]] | + | For a given grid, the errors changes with dt in a nonlinear manner <br /> |
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| + | [[File:SELFE-sensitivity-timestep-Aug2012.png]] | ||
Revision as of 09:39, 29 August 2012
As indicated in the SELFE main page, SELFE is an implicit model. This means that large time step is not only allowed but also encouraged! In fact the numerical diffusion in SELFE will increase when the CFL number is below ~0.4, which may lead to undesirable results. So estimate the CFL number in your application and start from a large time step (e.g., a 5 min step for barotropic applications; for baroclinic applications, the time step is constrained by the internal Courant number and so may need to be slightly smaller).
If you are doing a convergence study, you need to keep the CFL number fixed while reducing the time step (which means you have to reduce the grid spacing).
For a given grid, the errors changes with dt in a nonlinear manner
