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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Comparing Numerical Accuracy of Icosahedral A-Grid and C-Grid Schemes in Solving the Shallow-Water Model

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Autor(es):
Yu, Yonggang G. [1, 2] ; Wang, Ning [3, 2] ; Middlecoff, Jacques [3, 2] ; Peixoto, Pedro S. [4] ; Govett, Mark W. [2]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 - USA
[2] NOAA, Global Syst Lab, Earth Syst Res Labs, Boulder, CO 80305 - USA
[3] Colorado State Univ, Cooperat Inst Res Atmosphere, Ft Collins, CO 80523 - USA
[4] Univ Sao Paulo, Inst Math & Stat, Appl Math, Sao Paulo - Brazil
Número total de Afiliações: 4
Tipo de documento: Artigo Científico
Fonte: MONTHLY WEATHER REVIEW; v. 148, n. 10, p. 4009-4033, OCT 2020.
Citações Web of Science: 0
Resumo

A single software framework is introduced to evaluate numerical accuracy of the A-grid (NICAM) versus C-grid (MPAS) shallow-water model solvers on icosahedral grids. The C-grid staggering scheme excels in numerical noise control and total energy conservation, which results in exceptional stability for long time integration. Its weakness lies in the lack of model error reduction with increasing resolution in specific test cases (especially the root-mean-square error). The A-grid method conserves well potential enstrophy and shows a linear reduction of error with increasing resolution. The gridpoint noise manifests itself clearly on A-grid, but much less on C-grid. We show that the Coriolis force term on C-grid has a larger error than on A-grid. To treat the Coriolis term and kinetic energy gradient on an equal footing on C-grid, we propose combining these two quantities into a single tendency term and computing its value by a linear combination operation. This modification alone reduces numerical errors but still fails to converge the maximum error with resolution. The method of Peixoto can solve the maximum-error nonconvergence problem on C-grid but degrades the numerical stability. For the steady-state thin-layer test (0.01 m in depth), the A-grid method is less susceptible than C-grid methods, which are presumably disrupted by the Hollingsworth instability. The effect of horizontal diffusion on model accuracy and energy conservation is shown in detail. Programming experience shows that software implementation and optimization can strongly influence computational performance for models, although memory requirement and computational load of the two schemes are comparable. (AU)

Processo FAPESP: 16/18445-7 - Métodos numéricos para a nova geração de modelos de previsão de tempo e clima
Beneficiário:Pedro da Silva Peixoto
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores