Articles | Volume 11, issue 4
https://doi.org/10.5194/gmd-11-1497-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-1497-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Implicit–explicit (IMEX) Runge–Kutta methods for non-hydrostatic atmospheric models
David J. Gardner
CORRESPONDING AUTHOR
Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94550, USA
Jorge E. Guerra
Department of Land, Air and Water Resources, University of California, Davis, One Shields Ave., Davis, CA 95616, USA
François P. Hamon
Center for Computational Sciences and Engineering, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd., Berkeley, CA 94720
Daniel R. Reynolds
Department of Mathematics, Southern Methodist University, P.O. Box 750156, Dallas, TX 75257, USA
Paul A. Ullrich
Department of Land, Air and Water Resources, University of California, Davis, One Shields Ave., Davis, CA 95616, USA
Carol S. Woodward
Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA 94550, USA
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- High order semi-implicit weighted compact nonlinear scheme for viscous Burgers’ equations Y. Jiang et al. 10.1016/j.matcom.2021.06.006
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- An energetically balanced, quasi-Newton integrator for non-hydrostatic vertical atmospheric dynamics D. Lee 10.1016/j.jcp.2020.109988
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- An implicit–explicit time discretization scheme for second-order semilinear wave equations with application to dynamic boundary conditions M. Hochbruck & J. Leibold 10.1007/s00211-021-01184-w
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- Taste sensation evaluation for an electronic tongue based on an optimized computational model of taste pathways W. Zheng et al. 10.1088/1361-6501/ac9497
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Latest update: 20 Nov 2024
Short summary
As the computational power of supercomputing systems increases, and models for simulating the fluid flow of the Earth's atmosphere operate at higher resolutions, new approaches for advancing these models in time will be necessary. In order to produce the best possible result in the least amount of time, we evaluate a number of splittings, methods, and solvers on two test cases. Based on these results, we identify the most accurate and efficient approaches for consideration in production models.
As the computational power of supercomputing systems increases, and models for simulating the...