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Internal wave energy flux from density perturbations in nonlinear stratifications

Published online by Cambridge University Press:  12 October 2018

Frank M. Lee
Affiliation:
Institute for Fusion Studies and Department of Physics, University of Texas at Austin, Austin, TX 78712, USA
Michael R. Allshouse*
Affiliation:
Center for Nonlinear Dynamics and Department of Physics, University of Texas at Austin, Austin, TX 78712, USA Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA
Harry L. Swinney
Affiliation:
Center for Nonlinear Dynamics and Department of Physics, University of Texas at Austin, Austin, TX 78712, USA
Philip J. Morrison
Affiliation:
Institute for Fusion Studies and Department of Physics, University of Texas at Austin, Austin, TX 78712, USA
*
†Email address for correspondence: m.allshouse@northeastern.edu

Abstract

Internal gravity wave energy contributes significantly to the energy budget of the oceans, affecting mixing and the thermohaline circulation. Hence it is important to determine the internal wave energy flux $\boldsymbol{J}=p\,\boldsymbol{v}$, where $p$ is the pressure perturbation field and $\boldsymbol{v}$ is the velocity perturbation field. However, the pressure perturbation field is not directly accessible in laboratory or field observations. Previously, a Green’s function based method was developed to calculate the instantaneous energy flux field from a measured density perturbation field $\unicode[STIX]{x1D70C}(x,z,t)$, given a constant buoyancy frequency $N$. Here we present methods for computing the instantaneous energy flux $\boldsymbol{J}(x,z,t)$ for an internal wave field with vertically varying background $N(z)$, as in the oceans where $N(z)$ typically decreases by two orders of magnitude from the pycnocline to the deep ocean. Analytic methods are presented for computing $\boldsymbol{J}(x,z,t)$ from a density perturbation field for $N(z)$ varying linearly with $z$ and for $N^{2}(z)$ varying as $\tanh (z)$. To generalize this approach to arbitrary $N(z)$, we present a computational method for obtaining $\boldsymbol{J}(x,z,t)$. The results for $\boldsymbol{J}(x,z,t)$ for the different cases agree well with results from direct numerical simulations of the Navier–Stokes equations. Our computational method can be applied to any density perturbation data using the MATLAB graphical user interface ‘EnergyFlux’.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© 2018 Cambridge University Press
Figure 0

Figure 1. Two buoyancy frequency profiles computed from the World Ocean Circulation Experiment data sets by the method of King et al. (2012). (a) A measured buoyancy frequency squared profile (black dots) fit to a tanh profile (red). (b) A measured buoyancy frequency profile (black dots) fit to a linear profile (red). The insets show regions $1000~\text{km}\times 1000~\text{km}$ that contain the locations (red dots) where the measurements were made. The mean buoyancy frequency (squared for (a)) of bins of stratification measurements is plotted as a function of depth (black dots) with error bars representing two standard deviations from the mean.

Figure 1

Figure 2. (a) The $N$ profile of a broad transition tanh $N^{2}$ (dotted red curve) and a narrow transition tanh $N^{2}$ profile (solid blue curve). The dashed black line is a linear $N$ profile. (b) The simulation domain and density perturbation field $\unicode[STIX]{x1D70C}$ for the narrow transition tanh $N^{2}$ internal wave field. Rayleigh damping is applied in the outer grey region of the field. The dark grey region indicates the location of the internal wave body forcing. The black dashed line bounds the subdomain used for analysis.

Figure 2

Figure 3. The beam-normalized per cent difference between the density-perturbation-based method and a direct numerical simulation for the velocity components (a) $w$ and (b) $u$ of an internal wave beam incident diagonally from the upper left. The insets show the per cent difference across the beam for three transects in the simulation domain: the incoming beam (solid black), the transmitted beam (dashed green) and the second harmonic beam (dotted orange). In the simulation domain the locations of the transects are shown in their respective line styles.

Figure 3

Figure 4. The pressure perturbation field from (a) the direct numerical simulation and (b) the Green’s function calculation from the density perturbation. (c) The beam-normalized per cent difference between the pressure fields from the two methods.

Figure 4

Figure 5. The energy flux magnitude $|\boldsymbol{J}|$ computed in direct numerical simulations for the (a) narrow ($\unicode[STIX]{x1D6FC}=4$) and (d) broad transition ($\unicode[STIX]{x1D6FC}=0.1$) tanh $N^{2}$ profile. The beam-normalized per cent difference between the $x$-component of the energy flux $J_{x}$ from the simulations and from the Green’s function method is shown in (b) and (e), respectively, for the narrow and broad transition regions, and corresponding results for the $z$-component of the energy flux $J_{z}$ are in (c) and (f). For each case an inset shows the difference between the simulations and Green’s function methods is less than 5 % for most of the domain; the insets in each panel show the difference along two or three beam transects. The locations for these transects in the simulation domain are shown in their respective line styles.

Figure 5

Figure 6. (a) The energy flux magnitude from the numerical simulation for the linear $N$ profile. The beam-normalized per cent difference between simulation and the Green’s function method for the (b) $J_{x}$ and (c) $J_{z}$ components of the energy flux; the difference is less than 5 % for most of the beam, as illustrated by insets showing the difference for two beam transects. The locations for these transects in the simulation domain are shown in their respective line styles.

Figure 6

Figure 7. (a) The per cent difference between the finite difference (FD) and simulated pressure perturbation fields for the narrow tanh $N^{2}$ profile, which is essentially a two-layer system. (b) The per cent difference between the finite difference and the Green’s function based pressure perturbation fields for the narrow transition tanh $N^{2}$ profile. (c) Pressure perturbation profiles corresponding to the dashed black line in (b) from the narrow tanh $N^{2}$ simulation (black), Green’s function method (red) and finite difference method (blue) at $z=0.605$  m.

Figure 7

Figure 8. (a) Density profile from the ocean $\unicode[STIX]{x1D70C}_{0,obs}$ (red) and the scaled version used for simulation $\unicode[STIX]{x1D70C}_{0,sim}$ (blue). (b) The simulated absolute energy flux field. (c) The beam-normalized per cent difference between the simulated and finite difference energy flux fields.

Figure 8

Figure 9. Maximum per cent absolute difference between the energy flux from direct numerical simulations and the energy flux computed by our method as a function of the velocity amplitude and the maximum $\text{d}N/\text{d}z$. The diagonal lines have slope $-1$, as predicted by the scaling arguments for nonlinear terms neglected in our method, as described in § 5.2. The grey solid line corresponds to a 1 % error, the dashed grey line to a 5 % error and the dotted grey line to a 10 % error. (a) Domain of the sweep in simulation parameters, where white dots represent each simulation and symbols represent the approximate parameters for the following experiments: Mathur & Peacock (2009) (grey circles), Paoletti & Swinney (2012) (grey star) and Ghaemsaidi et al. (2016) (grey square). (b) A larger parameter domain that includes the internal wave beam parameters for ocean observations by Martin et al. (2006) (triangle) and Gerkema et al. (2004) (inverted triangle).

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