A two-dimensional toy model for geophysical turbulence

Lindborg, Erik; Mohanan, Ashwin Vishnu

doi:10.1063/1.4985990

Cited by 16 publications

(13 citation statements)

References 47 publications

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“…The reduced model (2.6) obtained by truncating the primitive equations was not seen to develop shock-like discontinuities in the wave field, typical of shallow water models, in any of the of the simulations we examined. We have not succeeded in developing a mathematical proof to demonstrate that the gradients of the wave field would remain bounded uniformly in time, and our arguments below for the absence of shocks closely follow the discussion in Lindborg & Mohanan (2017).…”

Section: Appendix a Absence Of Shocksmentioning

confidence: 87%

Geophysical turbulence dominated by inertia–gravity waves

Thomas

Yamada

2019

J. Fluid Mech.

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Recent evidence from both oceanic observations and global-scale ocean model simulations indicate the existence of regions where low-mode internal tidal energy dominates over that of the geostrophic balanced flow. Inspired by these findings, we examine the effect of the first vertical mode inertia–gravity waves on the dynamics of balanced flow using an idealized model obtained by truncating the hydrostatic Boussinesq equations on to the barotropic and the first baroclinic mode. On investigating the wave–balance turbulence phenomenology using freely evolving numerical simulations, we find that the waves continuously transfer energy to the balanced flow in regimes where the balanced-to-wave energy ratio is small, thereby generating small-scale features in the balanced fields. We examine the detailed energy transfer pathways in wave-dominated flows and thereby develop a generalized small Rossby number geophysical turbulence phenomenology, with the two-mode (barotropic and one baroclinic mode) quasi-geostrophic turbulence phenomenology being a subset of it. The present work therefore shows that inertia–gravity waves would form an integral part of the geophysical turbulence phenomenology in regions where balanced flow is weaker than gravity waves.

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Section: Appendix a Absence Of Shocksmentioning

confidence: 87%

Geophysical turbulence dominated by inertia–gravity waves

Thomas

Yamada

2019

J. Fluid Mech.

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“…It is much less a problem with Python where one can easily decipher this information from object attributes or using IPython's dynamic object information feature. 9 Now, fluidsim goes one step further and one can effortlessly print the sim.info_ solver object in the Python/IPython console, to get this information. A truncated example of the output is shown below.…”

Section: The Simulation Objectmentioning

confidence: 99%

“…Its simplicity of use and its plotting capacities make it particularly adapted for teaching. fluidsim is used at LEGI and at KTH for studies on geophysical turbulence (see for example [9]). Since it is easy to modify any characteristics of the existing solvers or to build new solvers, fluidsim is a good tool to carry out other types of simulations for academic studies.…”

Section: Licence: Cecill Date Published: 2015mentioning

confidence: 99%

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FluidSim: Modular, Object-Oriented Python Package for High-Performance CFD Simulations

Mohanan¹,

Bonamy²,

Linares³

et al. 2019

JORS

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The Python package fluidsim is introduced in this article as an extensible framework for Computational Fluid Mechanics (CFD) solvers. It is developed as a part of FluidDyn project [2], an effort to promote opensource and open-science collaboration within fluid mechanics community and intended for both educational as well as research purposes. Solvers in fluidsim are scalable, High-Performance Computing (HPC) codes which are powered under the hood by the rich, scientific Python ecosystem and the Application Programming Interfaces (API) provided by fluiddyn and fluidfft packages [11]. The present article describes the design aspects of fluidsim, which includes use of Python as the main language; focus on the ease of use, reuse and maintenance of the code without compromising performance. The implementation details including optimization methods, modular organization of features and object-oriented approach of using classes to implement solvers are also briefly explained. Currently, fluidsim includes solvers for a variety of physical problems using different numerical methods (including finite-difference methods). However, this metapaper shall dwell only on the implementation and performance of its pseudo-spectral solvers, in particular the two-and three-dimensional Navier-Stokes solvers. We investigate the performance and scalability of fluidsim in a state of the art HPC cluster. Three similar pseudo-spectral CFD codes based on Python (Dedalus, SpectralDNS) and Fortran (NS3D) are presented and qualitatively and quantitatively compared to fluidsim. The source code is hosted at Bitbucket as a Mercurial repository bitbucket.org/fluiddyn/fluidsim and the documentation generated using Sphinx can be read online at fluidsim.readthedocs.io.

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“…See the report by Internet Association titled "Refreshing Our Understanding of the Internet Economy". 2 http://www.cecill.info/licences.en.html 3. We use FluidDyn (with capital letters) to name the project and fluiddyn for the base package 4.…”

mentioning

confidence: 99%

FluidDyn: A Python Open-Source Framework for Research and Teaching in Fluid Dynamics by Simulations, Experiments and Data Processing

Augier¹,

Mohanan²,

Bonamy

2019

JORS

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FluidDyn is a project to foster open-science and open-source in the fluid dynamics community. It is thought of as a research project to channel open-source dynamics, methods and tools to do science. We propose a set of Python packages forming a framework to study fluid dynamics with different methods, in particular laboratory experiments (package fluidlab), simulations (packages fluidfft, fluidsim and fluidfoam) and data processing (package fluidimage). In the present article, we give an overview of the specialized packages of the project and then focus on the base package called fluiddyn, which contains common code used in the specialized packages. Packages fluidfft and fluidsim are described with greater detail in two companion papers [4, 5]. With the project FluidDyn, we demonstrate that specialized scientific code can be written with methods and good practices of the open-source community. The Mercurial repositories are available in Bitbucket (https://bitbucket.org/fluiddyn/). All codes are documented using Sphinx and Read the Docs, and tested with continuous integration run on Bitbucket Pipelines and Travis. To improve the reuse potential, the codes are as modular as possible, leveraging the simple object-oriented programming model of Python. All codes are also written to be highly efficient, using C++, Cython and Pythran to speedup the performance of critical functions.

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A two-dimensional toy model for geophysical turbulence

Abstract: A two-dimensional toy model for geophysical turbulence.

Cited by 16 publications

References 47 publications

Geophysical turbulence dominated by inertia–gravity waves

Geophysical turbulence dominated by inertia–gravity waves

FluidSim: Modular, Object-Oriented Python Package for High-Performance CFD Simulations

FluidDyn: A Python Open-Source Framework for Research and Teaching in Fluid Dynamics by Simulations, Experiments and Data Processing

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