Shear coincidence: implications of the statistics of ocean turbulence microphysics for global diapycnal mixing

2021 ◽  
Author(s):  
Ali Mashayek ◽  
Brendan Barry ◽  
Matthew Alford ◽  
Laura Cimoli ◽  
Colm-cille Caulfield
2019 ◽  
Vol 861 ◽  
Author(s):  
Hesam Salehipour ◽  
W. R. Peltier

Current global ocean models rely on ad hoc parameterizations of diapycnal mixing, in which the efficiency of mixing is globally assumed to be fixed at 20 %, despite increasing evidence that this assumption is questionable. As an ansatz for small-scale ocean turbulence, we may focus on stratified shear flows susceptible to either Kelvin–Helmholtz (KHI) or Holmboe wave (HWI) instability. Recently, an unprecedented volume of data has been generated through direct numerical simulation (DNS) of these flows. In this paper, we describe the application of deep learning methods to the discovery of a generic parameterization of diapycnal mixing using the available DNS dataset. We furthermore demonstrate that the proposed model is far more universal compared to recently published parameterizations. We show that a neural network appropriately trained on KHI- and HWI-induced turbulence is capable of predicting mixing efficiency associated with unseen regions of the parameter space well beyond the range of the training data. Strikingly, the high-level patterns learned based on the KHI and weakly stratified HWI are ‘transferable’ to predict HWI-induced mixing efficiency under much more strongly stratified conditions, suggesting that through the application of appropriate networks, significant universal abstractions of density-stratified turbulent mixing have been recognized.


2006 ◽  
Author(s):  
Michael Gregg ◽  
Jack Miller
Keyword(s):  

2021 ◽  
pp. 112891
Author(s):  
Congcong Hao ◽  
Wenjun Zhang ◽  
Bin Wu ◽  
Zhidong Zhang ◽  
Jian He ◽  
...  

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Zhao Jing ◽  
Lixin Wu ◽  
Xiaohui Ma ◽  
Ping Chang
Keyword(s):  

2015 ◽  
Vol 120 (7) ◽  
pp. 4729-4759 ◽  
Author(s):  
Di Yang ◽  
Bicheng Chen ◽  
Marcelo Chamecki ◽  
Charles Meneveau

2016 ◽  
Vol 46 (12) ◽  
pp. 3751-3775 ◽  
Author(s):  
Olivier Arzel ◽  
Alain Colin de Verdière

AbstractThe turbulent diapycnal mixing in the ocean is currently obtained from microstructure and finestructure measurements, dye experiments, and inverse models. This study presents a new method that infers the diapycnal mixing from low-resolution numerical calculations of the World Ocean whose temperatures and salinities are restored to the climatology. At the difference of robust general circulation ocean models, diapycnal diffusion is not prescribed but inferred. At steady state the buoyancy equation shows an equilibrium between the large-scale diapycnal advection and the restoring terms that take the place of the divergence of eddy buoyancy fluxes. The geography of the diapycnal flow reveals a strong regional variability of water mass transformations. Positive values of the diapycnal flow indicate an erosion of a deep-water mass and negative values indicate a creation. When the diapycnal flow is upward, a diffusion law can be fitted in the vertical and the diapycnal eddy diffusivity is obtained throughout the water column. The basin averages of diapycnal diffusivities are small in the first 1500 m [O(10−5) m2 s−1] and increase downward with bottom values of about 2.5 × 10−4 m2 s−1 in all ocean basins, with the exception of the Southern Ocean (50°–30°S), where they reach 12 × 10−4 m2 s−1. This study confirms the small diffusivity in the thermocline and the robustness of the higher canonical Munk’s value in the abyssal ocean. It indicates that the upward dianeutral transport in the Atlantic mostly takes place in the abyss and the upper ocean, supporting the quasi-adiabatic character of the middepth overturning.


2015 ◽  
Vol 775 ◽  
pp. 415-435 ◽  
Author(s):  
Andrea A. Cimatoribus ◽  
H. van Haren

We present a detailed analysis of temperature statistics in an oceanographic observational dataset. The data are collected using a moored array of thermistors,$100~\text{m}$tall and starting$5~\text{m}$above the bottom, deployed during four months above the slopes of a Seamount in the north-eastern Atlantic Ocean. Turbulence at this location is strongly affected by the semidiurnal tidal wave. Mean stratification is stable in the entire dataset. We compute structure functions, of order up to 10, of the distributions of temperature increments. Strong intermittency is observed, in particular, during the downslope phase of the tide, and farther from the solid bottom. In the lower half of the mooring during the upslope phase, the temperature statistics are consistent with those of a passive scalar. In the upper half of the mooring, the temperature statistics deviate from those of a passive scalar, and evidence of turbulent convective activity is found. The downslope phase is generally thought to be more shear-dominated, but our results suggest on the other hand that convective activity is present. High-order moments also show that the turbulence scaling behaviour breaks at a well-defined scale (of the order of the buoyancy length scale), which is however dependent on the flow state (tidal phase, height above the bottom). At larger scales, wave motions are dominant. We suggest that our results could provide an important reference for laboratory and numerical studies of mixing in geophysical flows.


2013 ◽  
Vol 43 (7) ◽  
pp. 1485-1511 ◽  
Author(s):  
Ivana Cerovečki ◽  
Lynne D. Talley ◽  
Matthew R. Mazloff ◽  
Guillaume Maze

Abstract Subantarctic Mode Water (SAMW) is examined using the data-assimilating, eddy-permitting Southern Ocean State Estimate, for 2005 and 2006. Surface formation due to air–sea buoyancy flux is estimated using Walin analysis, and diapycnal mixing is diagnosed as the difference between surface formation and transport across 30°S, accounting for volume change with time. Water in the density range 26.5 < σθ < 27.1 kg m−3 that includes SAMW is exported northward in all three ocean sectors, with a net transport of (18.2, 17.1) Sv (1 Sv ≡ 106 m3 s−1; for years 2005, 2006); air–sea buoyancy fluxes form (13.2, 6.8) Sv, diapycnal mixing removes (−14.5, −12.6) Sv, and there is a volume loss of (−19.3, −22.9) Sv mostly occurring in the strongest SAMW formation locations. The most vigorous SAMW formation is in the Indian Ocean by air–sea buoyancy flux (9.4, 10.9) Sv, where it is partially destroyed by diapycnal mixing (−6.6, −3.1) Sv. There is strong export to the Pacific, where SAMW is destroyed both by air–sea buoyancy flux (−1.1, −4.6) Sv and diapycnal mixing (−5.6, −8.4) Sv. In the South Atlantic, SAMW is formed by air–sea buoyancy flux (5.0, 0.5) Sv and is destroyed by diapycnal mixing (−2.3, −1.1) Sv. Peaks in air–sea flux formation occur at the Southeast Indian and Southeast Pacific SAMWs (SEISAMWs, SEPSAMWs) densities. Formation over the broad SAMW circumpolar outcrop windows is largely from denser water, driven by differential freshwater gain, augmented or decreased by heating or cooling. In the SEISAMW and SEPSAMW source regions, however, formation is from lighter water, driven by differential heat loss.


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