Local time-stepping for the shallow water equations using CFL optimized forward-backward Runge-Kutta schemes

The Courant–Friedrichs–Lewy (CFL) condition is a well known, necessary condition for the stability of explicit time-stepping schemes that effectively places a limit on the size of the largest admittable time-step for a given problem. We formulate and present a new local time-stepping (LTS) scheme optimized, in the CFL sense, for the shallow water equations (SWEs). This new scheme, called FB-LTS, is based on the CFL optimized forward-backward Runge-Kutta schemes from Lilly et al. [16] . We show that FB-LTS maintains exact conservation of mass and absolute vorticity when applied to the TRiSK spatial discretization [21] , and provide numerical experiments showing that it retains the temporal order of the scheme on which it is based (second order). We implement FB-LTS, along with a certain operator splitting, in MPAS-Ocean to test computational performance. This scheme, SplitFB-LTS, is up to 10 times faster than the classical four-stage, fourth-order Runge-Kutta method (RK4), and 2.3 times faster than an existing strong stability preserving Runge-Kutta based LTS scheme with the same operator splitting (SplitLTS3). Despite this significant increase in efficiency, the solutions produced by SplitFB-LTS are qualitatively equivalent to those produced by both RK4 and SplitLTS3. • FB-LTS is a new local time-stepping scheme optimized for the shallow water equations. • FB-LTS takes time-steps up to 2.3 times larger than a comparable LTS scheme. • FB-LTS is 10 times faster than the MPAS-O default in a real-world test case. • FB-LTS produces solutions qualitatively equivalent to existing methods.

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Publication Details

Journal
Journal of Computational Physics
Published
2024-10-18
DOI
https://doi.org/10.1016/j.jcp.2024.113511
Citations
3
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
2.20

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article

Local time-stepping for the shallow water equations using CFL optimized forward-backward Runge-Kutta schemes

Jeremy R. Lilly, Darren Engwirda, Giacomo Capodaglio, Robert L. Higdon et al.
3 citations
Journal of Computational Physics
Numerical methods for differential equations
2.20
article

Local time-stepping for the shallow water equations using CFL optimized forward-backward Runge-Kutta schemes

Jeremy R. Lilly, Darren Engwirda, Giacomo Capodaglio, Robert L. Higdon, Mark Petersen
article en
3 citations

Abstract

The Courant–Friedrichs–Lewy (CFL) condition is a well known, necessary condition for the stability of explicit time-stepping schemes that effectively places a limit on the size of the largest admittable time-step for a given problem. We formulate and present a new local time-stepping (LTS) scheme optimized, in the CFL sense, for the shallow water equations (SWEs). This new scheme, called FB-LTS, is based on the CFL optimized forward-backward Runge-Kutta schemes from Lilly et al. [16] . We show that FB-LTS maintains exact conservation of mass and absolute vorticity when applied to the TRiSK spatial discretization [21] , and provide numerical experiments showing that it retains the temporal order of the scheme on which it is based (second order). We implement FB-LTS, along with a certain operator splitting, in MPAS-Ocean to test computational performance. This scheme, SplitFB-LTS, is up to 10 times faster than the classical four-stage, fourth-order Runge-Kutta method (RK4), and 2.3 times faster than an existing strong stability preserving Runge-Kutta based LTS scheme with the same operator splitting (SplitLTS3). Despite this significant increase in efficiency, the solutions produced by SplitFB-LTS are qualitatively equivalent to those produced by both RK4 and SplitLTS3. • FB-LTS is a new local time-stepping scheme optimized for the shallow water equations. • FB-LTS takes time-steps up to 2.3 times larger than a comparable LTS scheme. • FB-LTS is 10 times faster than the MPAS-O default in a real-world test case. • FB-LTS produces solutions qualitatively equivalent to existing methods.

Journal of Computational PhysicsVol. 520
Oregon State University (US), Los Alamos National Laboratory (US)
National Science Foundation, U.S. Department of Energy, Office of Science, Biological and Environmental Research, Los Alamos National Laboratory
Clean water and sanitation
Openalex Percentile: Top 12%
Numerical methods for differential equations
2.20
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