Weighted-norm preconditioners for a multilayer tide model
File(s)
Author(s)
Cotter, Colin J
Kirby, Robert C
Morris, Hunter
Type
Journal Article
Abstract
We derive a linearized rotating shallow water system modeling tides, which can be discretized by mixed finite elements. Unlike previous models, this model allows for multiple layers stratified by density. Like the single-layer case [R. C. Kirby and T. Kernell, Comput. Math. Appl., 82 (2021), pp. 212–227], a weighted-norm preconditioner gives a (nearly) parameter-robust method for solving the resulting linear system at each time step, but the all-to-all coupling between the layers in the model poses a significant challenge to efficiency. Neglecting the inter-layer coupling gives a preconditioner that degrades rapidly as the number of layers increases. By a careful analysis of the matrix that couples the layers, we derive a robust method that requires solving a reformulated system that only involves coupling between adjacent layers. Numerical results obtained using Firedrake [F. Rathgeber et al., ACM Trans. Math. Software, 43 (2016), 24] confirm the theory.
Date Issued
2023-08
Date Acceptance
2023-03-13
Citation
SIAM Journal on Scientific Computing, 2023, 45 (4), pp.A1789-A1811
ISSN
1064-8275
Publisher
Society for Industrial and Applied Mathematics
Start Page
A1789
End Page
A1811
Journal / Book Title
SIAM Journal on Scientific Computing
Volume
45
Issue
4
Copyright Statement
© 2023 Society for Industrial and Applied Mathematics. Cotter, C. J., Kirby, R. C., & Morris, H. (2023). Weighted-norm preconditioners for a multilayer tide model. SIAM Journal on Scientific Computing, 45(4), A1789-A1811.
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:001037760900009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Subjects
block preconditioner
finite element method
GENERATION
H(DIV)
Key words
Mathematics
Mathematics, Applied
MIXED FINITE-ELEMENTS
NUMERICALLY INDUCED OSCILLATIONS
Physical Sciences
Science & Technology
SHALLOW-WATER MODELS
tide models
Publication Status
Published
Date Publish Online
2023-07-19