Numerical simulations of internal wave generation by convection in water

Daniel Lecoanet, Michael Le Bars, Keaton J. Burns, Geoffrey M. Vasil, Benjamin P. Brown, Eliot Quataert, Jeffrey S. Oishi

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

Water's density maximum at 4°C makes it well suited to study internal gravity wave excitation by convection: an increasing temperature profile is unstable to convection below 4°C, but stably stratified above 4°C. We present numerical simulations of a waterlike fluid near its density maximum in a two-dimensional domain. We successfully model the damping of waves in the simulations using linear theory, provided we do not take the weak damping limit typically used in the literature. To isolate the physical mechanism exciting internal waves, we use the spectral code dedalus to run several simplified model simulations of our more detailed simulation. We use data from the full simulation as source terms in two simplified models of internal-wave excitation by convection: bulk excitation by convective Reynolds stresses, and interface forcing via the mechanical oscillator effect. We find excellent agreement between the waves generated in the full simulation and the simplified simulation implementing the bulk excitation mechanism. The interface forcing simulations overexcite high-frequency waves because they assume the excitation is by the "impulsive" penetration of plumes, which spreads energy to high frequencies. However, we find that the real excitation is instead by the "sweeping" motion of plumes parallel to the interface. Our results imply that the bulk excitation mechanism is a very accurate heuristic for internal-wave generation by convection.

Original languageEnglish (US)
Article number063016
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume91
Issue number6
DOIs
StatePublished - Jun 30 2015
Externally publishedYes

Funding

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Statistics and Probability

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