Langmuir turbulence in horizontal salinity gradient

Fan, Yalin; Jarosz, Ewa; Yu, Zhitao; Rogers, W. Erick; Jensen, Tommy G.; Liang, Jun‐Hong

doi:10.1016/j.ocemod.2018.07.010

Cited by 23 publications

(15 citation statements)

References 31 publications

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“…The model has been extensively applied to study the ocean surface boundary layer turbulence driven by a variety of surface and lateral boundary conditions (e.g., Hamlington et al, 2014;Harcourt, 2015;Liu et al, 2018;McWilliams et al, 2012McWilliams et al, , 2014Sullivan et al, 2012;Van Roekel et al, 2012) and produces results that agree with in situ observation (e.g., Fan et al, 2018;Liang et al, 2017). It has also been applied to study neutrally (e.g., Smith et al, 2016) and positively buoyant tracers (e.g., Brunner et al, 2015;Liang et al, 2018).…”

Section: Les Modelmentioning

confidence: 99%

Modeling Sediment Flocculation in Langmuir Turbulence

Liu

Liang

et al. 2019

JGR Oceans

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Cohesive sediments exist as flocs of different sizes, which are built and destroyed through flocculation processes including both aggregation and breakup. This study investigates sediment flocculation processes in wave-driven Langmuir turbulence that is commonly observed in coastal ocean through embedding a size-resolving flocculation model into a turbulence-resolving hydrodynamic model. The specific research questions are how Langmuir turbulence affects flocculation processes and how flocculation processes impact the spatial and size distributions of suspended cohesive sediment. The results show that Langmuir turbulence suspends flocs in the water column and organizes flocs of different sizes. By modulating the encounter of flocs and redistributing flocs in the turbulence field, Langmuir turbulence enhances the aggregation and breakup rates of flocs that are located in similar regions with high turbulent dissipation rates and suppresses those of others. As an outcome of modulated flocculation processes, floc size distribution changes with depth and floc mass concentration profiles change with floc size. The addition of wave breaking increases the shear rate near the surface and reduces the median floc size and averaged settling velocity, leading to increase in total floc mass concentration in the whole water column. Wave breaking also increases cross-shelf sediment transport by more than 15% under the simulated conditions, which is comparable to that due to Langmuir turbulence compared to shear turbulence. Both floc size distribution and floc concentration vary with wind and wave conditions. Key Points:• A size-resolving floc model embedded in a large eddy simulation model is used to study flocculation in shallow-water Langmuir turbulence • Flocculation processes modify vertical mean concentration profiles for flocs of a certain size • Langmuir turbulence modulates aggregation and breakup rates Supporting Information:• Supporting Information S1

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Section: Les Modelmentioning

confidence: 99%

Modeling Sediment Flocculation in Langmuir Turbulence

Liu

Liang

et al. 2019

JGR Oceans

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“…(19) and (21). Similar approach has been suggested in, e.g., Grooms and Julien (2018) for multiscale modeling, as well as applied in LES studies of the frontal regions (e.g., Bachman and Taylor, 2016;Fan et al, 2018). The tricky part is estimating the horizontal gradient of large-scale quantities, which strongly depends on the horizontal resolution of the GCMs.…”

Section: Remaining Issuesmentioning

confidence: 89%

“…It can potentially also be used to guide a systematic exploration of the parameter space using LES. However, such approach ignores the interactions between the OSBL turbulence and larger-scale processes, such as submesoscale fronts and eddies, which have been shown to be important (e.g., Hamlington et al, 2014;Bachman and Taylor, 2016;Fan et al, 2018;Verma et al, 2019;Sullivan and McWilliams, 2019).…”

Section: Towards a Better Osbl Parameterizationmentioning

confidence: 99%

“…Alternatively, the impact of large-scale processes on the small-scale OSBL turbulence can be studied by applying an externally determined large-scale lateral buoyancy gradient in a much smaller LES domain (e.g., Bachman and Taylor, 2016;Fan et al, 2018), though at the expense of missing the feedback to the large-scales. In this sense, a superparameterized GCM may provide an intermediate approach to systematically examine the impact of large-scale processes (resolved in the GCM) on the smallscale OSBL turbulence (in LES) and vice versa, with a loose but controllable coupling between the two.…”

Section: Towards a Better Osbl Parameterizationmentioning

confidence: 99%

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Towards Multiscale Modeling of Ocean Surface Turbulent Mixing Using Coupled MPAS-Ocean v6.3 and PALM v5.0

Li¹,

Roekel²

2020

Preprint

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Abstract. A multiscale modeling approach for studying the ocean surface turbulent mixing is explored by coupling an ocean general circulation model (GCM) MPAS-Ocean with the PArallel Large eddy simulation Model (PALM). The coupling approach is similar to the superparameterization approach that has been used mostly to represent the effects of deep convection in atmospheric GCMs. However, since the emphasis here is on the small-scale turbulent mixing processes and their interactions with the larger-scale processes, a high-fidelity, three-dimensional large eddy simulation (LES) model is used, in contrary to a simplified process-resolving model with reduced physics or reduced dimension commonly used in the superparameterization literature. To reduce the computational cost, a customized version of PALM is ported on the general-purpose graphics processing unit (GPU) with OpenACC, achieving 10–16 times overall speedup as compared to running on a single CPU. Even with the GPU-acceleration technique, superparameterization of the ocean surface turbulent mixing using high-fidelity and three-dimensional LES over the global ocean in GCMs is still computationally intensive and infeasible for long simulations. However, running PALM regionally on selected MPAS-Ocean grid cells is shown to be a promising approach moving forward. The flexible coupling between MPAS-Ocean and PALM outlined here allows further exploration of the interactions between ocean surface turbulent mixing and larger-scale processes, and development of better ocean surface turbulent mixing parameterizations in GCMs.

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“…Vertical mixing not only mediates the exchange of momentum, heat, and trace materials between the ocean interior and the atmosphere, but also modulates horizontal transport and dispersion by controlling the vertical profiles of horizontal currents, material concentrations, and temperature in the OSBL (e.g., D'Asaro et al, 2014; Liang et al, 2018). A number of studies (e.g., Fan et al, 2018; Kukulka et al, 2013; Rabe et al, 2015) demonstrate that simulated mixed layer temperature, mixing layer depth, and turbulence kinetic energy are consistent with the observations only when Langmuir circulation is included in the model. These findings are generic to all ocean regions and suggest that wind speed alone is not sufficient to quantify mixing in the upper ocean.…”

Section: Introductionmentioning

confidence: 99%

Surface Gravity Waves and Their Role in Ocean‐Atmosphere Coupling in the Gulf of Mexico

et al. 2020

Self Cite

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This study provides an overview of the surface gravity wave dynamics in the Gulf of Mexico (GoM) using numerical simulations. The focus is on the effects of ocean currents on waves, and the geographic distribution of wave statistics and parameters related to the role of waves on both sides of the ocean‐atmosphere interface. Simulations are performed using the Simulating WAves Nearshore (SWAN) model with and without coupling with the Regional Ocean Modeling System (ROMS) model within the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) framework. In the GoM, currents alter the climatological significant wave heights by up to 0.18 m (±15%), reducing wave heights in the southwestern GoM and generally increasing wave heights in other regions. In two instantaneous snapshots representing the Loop Current variability in terms of its northward extension into the GoM, significant wave heights are modulated by as much as 0.30 m (±35%) by the currents. Probability density of wave height modulation covers a wider range of values and is skewed toward positive values over the eastern flank of the Loop Current. In winter, spring, and fall, swell fraction of wave energy increases from east to west in the GoM and reaches as high as 0.8 in the southwestern GoM, off the coast of Mexico. The dominance of swell in this region combined with weak wind results in a higher prevalence of the wave‐driven wind regime throughout the year. The interannual variability of significant wave height and swell fraction shows signals of major storms in the GoM.

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Langmuir turbulence in horizontal salinity gradient

Cited by 23 publications

References 31 publications

Modeling Sediment Flocculation in Langmuir Turbulence

Modeling Sediment Flocculation in Langmuir Turbulence

Towards Multiscale Modeling of Ocean Surface Turbulent Mixing Using Coupled MPAS-Ocean v6.3 and PALM v5.0

Surface Gravity Waves and Their Role in Ocean‐Atmosphere Coupling in the Gulf of Mexico

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