Simulations of strongly stratified turbulence often exhibit coherent large-scale structures called vertically sheared horizontal flows (VSHFs). VSHFs emerge in both two-dimensional (2D) and three-dimensional (3D) stratified turbulence with similar vertical structure. The mechanism responsible for VSHF formation is not fully understood. In this work, the formation and equilibration of VSHFs in a 2D Boussinesq model of stratified turbulence is studied using statistical state dynamics (SSD). In SSD, equations of motion are expressed directly in the statistical variables of the turbulent state. Restriction to 2D turbulence facilitates application of an analytically and computationally attractive implementation of SSD referred to as S3T, in which the SSD is expressed by coupling the equation for the horizontal mean structure with the equation for the ensemble mean perturbation covariance. This second-order SSD produces accurate statistics, through second order, when compared with fully nonlinear simulations. In particular, S3T captures the spontaneous emergence of the VSHF and associated density layers seen in simulations of turbulence maintained by homogeneous large-scale stochastic excitation. An advantage of the S3T system is that the VSHF formation mechanism, which is wave-mean flow interaction between the emergent VSHF and the stochastically excited large-scale gravity waves, is analytically understood in the S3T system. Comparison with fully nonlinear simulations verifies that S3T solutions accurately predict the scale selection, dependence on stochastic excitation strength, and nonlinear equilibrium structure of the VSHF. These results constitute a theory for VSHF formation applicable to interpreting simulations and observations of geophysical examples of turbulent jets such as the ocean's equatorial deep jets.
机构:
Peking Univ, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
Johns Hopkins Univ, Dept Mech Engn, Baltimore, MD 21218 USAPeking Univ, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
Xiao, Z.
Wan, M.
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Johns Hopkins Univ, Dept Mech Engn, Baltimore, MD 21218 USAPeking Univ, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
Wan, M.
Chen, S.
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Peking Univ, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
Johns Hopkins Univ, Dept Mech Engn, Baltimore, MD 21218 USA
Johns Hopkins Univ, Dept Appl Math & Stat, Baltimore, MD 21218 USA
Los Alamos Natl Lab, Ctr Nonlinear Studies, Los Alamos, NM 87545 USA
Los Alamos Natl Lab, Div Theoret, Los Alamos, NM 87545 USAPeking Univ, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
Chen, S.
Eyink, G. L.
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Johns Hopkins Univ, Dept Mech Engn, Baltimore, MD 21218 USA
Johns Hopkins Univ, Dept Appl Math & Stat, Baltimore, MD 21218 USA
Los Alamos Natl Lab, Ctr Nonlinear Studies, Los Alamos, NM 87545 USA
Los Alamos Natl Lab, Div Theoret, Los Alamos, NM 87545 USAPeking Univ, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
机构:
KTH Royal Inst Technol, Nordita, Roslagstullsbacken 23, S-10691 Stockholm, Sweden
Stockholm Univ, Roslagstullsbacken 23, S-10691 Stockholm, SwedenKTH Royal Inst Technol, Nordita, Roslagstullsbacken 23, S-10691 Stockholm, Sweden
Mitra, Dhrubaditya
Perlekar, Prasad
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Tata Inst Fundamental Res, Ctr Interdisciplinary Sci, Hyderabad 500107, Andhra Pradesh, IndiaKTH Royal Inst Technol, Nordita, Roslagstullsbacken 23, S-10691 Stockholm, Sweden