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March 28, 2026Journal of Fluid Mechanics0 citationsOpen Access

Distinguished regimes of 2-D internal gravity wave turbulence

VLVincent LabarreCentre National de la Recherche ScientifiqueMSMichal ShavitCourant Institute of Mathematical Sciences

Key Points

  • This research aims to identify different turbulence regimes in two-dimensional stratified fluids and confirm the wave turbulence theory for internal gravity waves.
  • Applied weak wave turbulence theory to categorize turbulence regimes.
  • Conducted direct numerical simulation of 2-D Boussinesq equations with shear modes excluded.
  • Analyzed spectral distributions across different regimes.
  • Distinguished three turbulence regimes: discrete wave turbulence, weak wave turbulence, and strong nonlinear interaction.
  • Observed a spectrum in the weak wave turbulence regime that aligns with predictions from kinetic theory.
  • Confirmed the wave turbulence theory for internal gravity waves through DNS for the first time.
  • Noted formation of layers and spectral peaks at low discrete frequencies in weak and strong interaction regimes.

Abstract

Using weak wave turbulence theory analysis, we distinguish three main regimes for two-dimensional (2-D) stratified fluids in the dimensionless parameter space defined by the Froude number and the Reynolds number: discrete wave turbulence, weak wave turbulence and strong nonlinear interaction. These regimes are investigated using direct numerical simulation (DNS) of the 2-D Boussinesq equations with shear modes removed. In the weak wave turbulence regime, excluding slow frequencies, we observe a spectrum that aligns with recent predictions from kinetic theory. This finding represents the first DNS-based confirmation of wave turbulence theory for internal gravity waves. At strong stratification, in both the weak and strong interaction regimes, we observe the formation of layers accompanied by spectral peaks at low discrete frequencies. We attribute this layering to an inverse kinetic-energy transfer in combination with discrete wave–wave interactions at large scales. This analysis allows us to predict the layer thickness and typical flow velocity in terms of the control parameters.

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Cite This Study

Labarre et al. (2026) studied this question.

synapsesocial.com/papers/69c7725e8bbfbc51511e2bcahttps://doi.org/10.1017/jfm.2026.11329
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