Deficiencies in upper ocean vertical mixing parameterizations contribute to tropical upper ocean biases in global coupled general circulation models, affecting their simulated ocean heat uptake and ENSO variability. To better understand these deficiencies, we develop a suite of ocean model experiments including both idealized single column models and realistic global simulations. The vertical mixing parameterizations are first evaluated using large eddy simulations as a baseline to assess uncertainties and evaluate their implied turbulent mixing. Global models are then developed following NOAA/GFDL's 0.25° nominal horizontal grid spacing OM4 (uncoupled) configuration of the MOM6 ocean model, with various modifications that target biases in the original model. We test several enhancements to the existing mixing schemes and evaluate them against observational constraints from Tropical Atmosphere Ocean moorings and Argo floats. In particular, we find that we can improve the diurnal variability of mixing in OM4 via modifications to its surface boundary layer mixing scheme, and can improve the net mixing in the upper thermocline by reducing the background vertical viscosity, allowing for more realistic, less diffuse currents. The improved OM4 model better represents the mixing, leading to improved diurnal deep-cycle variability, a more realistic time-mean tropical thermocline structure, and a better Pacific Equatorial Undercurrent.
Sane, Aakash, Brandon G Reichl, Alistair Adcroft, and Laure Zanna, October 2023: Parameterizing vertical mixing coefficients in the ocean surface boundary layer using neural networks. Journal of Advances in Modeling Earth Systems, 15(10), DOI:10.1029/2023MS003890. Abstract
Vertical mixing parameterizations in ocean models are formulated on the basis of the physical principles that govern turbulent mixing. However, many parameterizations include ad hoc components that are not well constrained by theory or data. One such component is the eddy diffusivity model, where vertical turbulent fluxes of a quantity are parameterized from a variable eddy diffusion coefficient and the mean vertical gradient of the quantity. In this work, we improve a parameterization of vertical mixing in the ocean surface boundary layer by enhancing its eddy diffusivity model using data-driven methods, specifically neural networks. The neural networks are designed to take extrinsic and intrinsic forcing parameters as input to predict the eddy diffusivity profile and are trained using output data from a second moment closure turbulent mixing scheme. The modified vertical mixing scheme predicts the eddy diffusivity profile through online inference of neural networks and maintains the conservation principles of the standard ocean model equations, which is particularly important for its targeted use in climate simulations. We describe the development and stable implementation of neural networks in an ocean general circulation model and demonstrate that the enhanced scheme outperforms its predecessor by reducing biases in the mixed-layer depth and upper ocean stratification. Our results demonstrate the potential for data-driven physics-aware parameterizations to improve global climate models.
Zhou, Xiaohui, Brandon G Reichl, Leonel Romero, and L Deike, November 2023: A sea state dependent gas transfer velocity for CO2 unifying theory, model, and field Data. Earth and Space Science, 10(11), DOI:10.1029/2023EA003237. Abstract
Wave breaking induced bubbles contribute a significant part of air-sea gas fluxes. Recent modeling of the sea state dependent CO2 flux found that bubbles contribute up to ∼40% of the total CO2 air-sea fluxes (Reichl & Deike, 2020, https://doi.org/10.1029/2020gl087267). In this study, we implement the sea state dependent bubble gas transfer formulation of Deike and Melville (2018, https://doi.org/10.1029/2018gl078758) into a spectral wave model (WAVEWATCH III) incorporating the spectral modeling of the wave breaking distribution from Romero (2019, https://doi.org/10.1029/2019gl083408). We evaluate the accuracy of the sea state dependent gas transfer parameterization against available measurements of CO2 gas transfer velocity from 9 data sets (11 research cruises, see Yang et al. (2022, https://doi.org/10.3389/fmars.2022.826421)). The sea state dependent parameterization for CO2 gas transfer velocity is consistent with observations, while the traditional wind-only parameterization used in most global models slightly underestimates the observations of gas transfer velocity. We produce a climatology of the sea state dependent gas transfer velocity using reanalysis wind and wave data spanning 1980–2017. The climatology shows that the enhanced gas transfer velocity occurs frequently in regions with developed sea states (with strong wave breaking and high significant wave height). The present study provides a general sea state dependent parameterization for gas transfer, which can be implemented in global coupled models.
Bubbles bursting at the ocean surface are an important source of ocean-spray aerosol, with implications on radiative and cloud processes. Yet, very large uncertainties exist on the role of key physical controlling parameters, including wind speed, sea state and water temperature. We propose a mechanistic sea spray generation function that is based on the physics of bubble bursting. The number and mean droplet radius of jet and film drops is described by scaling laws derived from individual bubble bursting laboratory and numerical experiments, as a function of the bubble radius and the water physico-chemical properties (viscosity, density and surface tension, all functions of temperature), with drops radii at production from 0.1 to 500 µm. Next, we integrate over the bubble size distribution entrained by breaking waves. Finally, the sea spray generation function is obtained by considering the volume flux of entrained bubbles due to breaking waves in the field constrained by the third moment of the breaking distribution (akin to the whitecap coverage). This mechanistic approach naturally integrates the role of wind and waves via the breaking distribution and entrained air flux, and a sensitivity to temperature via individual bubble bursting mechanisms. The resulting sea spray generation function has not been tuned or adjusted to match any existing data sets, in terms of magnitude of sea salt emissions and recently observed temperature dependencies. The remarkable coherence between the model and observations of sea salt emissions therefore strongly supports the mechanistic approach and the resulting sea spray generation function.
Kim, Hyun-Sook, Jessica Meixner, Biju Thomas, Brandon G Reichl, Bin Liu, Avichal Mehra, and A Wallcraft, August 2022: Skill assessment of NCEP three-way coupled HWRF–HYCOM–WW3 modeling system: Hurricane Laura case study. Weather and Forecasting, 37(8), DOI:10.1175/WAF-D-21-0191.11309-1331. Abstract
In this research, we develop a three-way coupled prediction system to advance the realization of air–sea interaction processes. This study considers the sea-state-dependent momentum flux and nonlinear interactions between waves, winds, and ocean currents using the U.S. National Centers for Environmental Prediction’s operational Hurricane Weather Research and Forecasting (HWRF)-Hybrid Coordinate Ocean Model (HYCOM) coupled modeling system. Wave feedback is performed through the air–sea interaction module (ASIM) added to WAVEWATCH III (WW3), which employs the wave boundary layer to parameterize unresolved high-frequency tail spectra by using the mean flux profile constructed from the conservation of total momentum and wave energy. The atmospheric momentum flux is updated using the sea-state-dependent Charnock coefficient, wave-induced stress, and ocean surface currents before being passed to HYCOM. Wave coupling in HYCOM includes Coriolis–Stokes forcing to simulate wave–current interactions and to enhance mixing to account for Langmuir turbulence. The fully coupled system is tested for Hurricane Laura (2020). This paper examines the forecast skills of the individual component models by comparing simulations with observations. Without skill degradation of HYCOM and WW3, the three-way coupling method improves the track and intensity forecast skills by 5% each over those of HWRF-HYCOM coupling, and 27% and 17% over those of uncoupling, respectively. Importantly, this fully coupled system outperforms rapid intensification by reducing the intensification magnitude and matching the occurrence and duration. Overall, the forecast performance evaluated in the study establishes a baseline for the next-generation hurricane prediction system.
Turbulent mixing in the ocean surface boundary layer leads to the presence of a surface mixed layer. This mixed layer is important for many phenomena including large-scale ocean dynamics, ocean-atmosphere coupling, and biological and biogeochemical processes. Analysis of the ocean mixed layer requires one to estimate its vertical extent, for which there are various definitions. Correspondingly, there are uncertainties on how to best identify an ocean surface mixed layer for a given application. We propose defining the mixed layer depth (MLD) from energetic principles through the potential energy (PE). The PE based MLD is based on the concept of PE anomaly, which measures the stratification of a layer of seawater by estimating its energetic distance from a well-mixed state. We apply the PE anomaly to diagnose the MLD as the depth to which a given energy could homogenize a layer of seawater. We evaluate the MLD defined by common existing methods and demonstrate that they contain a wide range of PE anomalies for the same MLD, particularly evident for deep winter mixed layers. The MLD defined from the PE anomaly ensures a more consistent MLD identified for a large range of stratifications. Furthermore, the PE method relates to the turbulent kinetic energy budget of the ocean surface boundary layer, which is fundamental to upper ocean mixing processes and parameterizations. The resulting MLD is more representative of active boundary layer turbulence, and is more robust to small anomalies in seawater properties.
Zhou, Xiaohui, Tetsu Hara, Isaac Ginis, Eric D'Asaro, Je-Yuan Hsu, and Brandon G Reichl, July 2022: Drag coefficient and its sea state dependence under tropical cyclones. Journal of Physical Oceanography, 52(7), DOI:10.1175/JPO-D-21-0246.11447-1470. Abstract
The drag coefficient under tropical cyclones and its dependence on sea states are investigated by combining upper-ocean current observations [using electromagnetic autonomous profiling explorer (EM-APEX) floats deployed under five tropical cyclones] and a coupled ocean–wave (Modular Ocean Model 6–WAVEWATCH III) model. The estimated drag coefficient averaged over all storms is around 2–3 × 10−3 for wind speeds of 25–55 m s−1. While the drag coefficient weakly depends on wind speed in this wind speed range, it shows stronger dependence on sea states. In particular, it is significantly reduced when the misalignment angle between the dominant wave direction and the wind direction exceeds about 45°, a feature that is underestimated by current models of sea state–dependent drag coefficient. Since the misaligned swell is more common in the far front and in the left-front quadrant of the storm (in the Northern Hemisphere), the drag coefficient also tends to be lower in these areas and shows a distinct spatial distribution. Our results therefore support ongoing efforts to develop and implement sea state–dependent parameterizations of the drag coefficient in tropical cyclone conditions.
We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.
Reichl, Brandon G., and L Deike, May 2020: Contribution of Sea‐State Dependent Bubbles to Air‐Sea Carbon Dioxide Fluxes. Geophysical Research Letters, 47(9), DOI:10.1029/2020GL087267. Abstract
Breaking surface ocean waves produce bubbles that are important for air‐sea gas exchanges, particularly during high winds. In this study we estimate air‐sea CO2 fluxes globally using a new approach that considers the surface wave contribution to gas fluxes. We estimate that 40% of the net air‐sea CO2 flux is via bubbles, with annual, seasonal, and regional variability. When compared to traditional gas‐flux parameterization methods that consider the wind speed alone, we find high‐frequency (daily to weekly) differences in the predicted gas flux using the sea‐state dependent method at spatial scales related to atmospheric weather (10 to 100 km). Seasonal net differences in the air‐sea CO2 flux due to the sea‐state dependence can exceed 20%, with the largest values associated with North Atlantic and North Pacific winter storms. These results confirm that bubbles are important for global gas‐flux dynamics and that sea‐state dependent parameterizations may improve performance of global coupled models.
We document the configuration and emergent simulation features from the Geophysical Fluid Dynamics Laboratory (GFDL) OM4.0 ocean/sea‐ice model. OM4 serves as the ocean/sea‐ice component for the GFDL climate and Earth system models. It is also used for climate science research and is contributing to the Coupled Model Intercomparison Project version 6 Ocean Model Intercomparison Project (CMIP6/OMIP). The ocean component of OM4 uses version 6 of the Modular Ocean Model (MOM6) and the sea‐ice component uses version 2 of the Sea Ice Simulator (SIS2), which have identical horizontal grid layouts (Arakawa C‐grid). We follow the Coordinated Ocean‐sea ice Reference Experiments (CORE) protocol to assess simulation quality across a broad suite of climate relevant features. We present results from two versions differing by horizontal grid spacing and physical parameterizations: OM4p5 has nominal 0.5° spacing and includes mesoscale eddy parameterizations and OM4p25 has nominal 0.25° spacing with no mesoscale eddy parameterization.
MOM6 makes use of a vertical Lagrangian‐remap algorithm that enables general vertical coordinates. We show that use of a hybrid depth‐isopycnal coordinate reduces the mid‐depth ocean warming drift commonly found in pure z* vertical coordinate ocean models. To test the need for the mesoscale eddy parameterization used in OM4p5, we examine the results from a simulation that removes the eddy parameterization. The water mass structure and model drift are physically degraded relative to OM4p5, thus supporting the key role for a mesoscale closure at this resolution.
We describe GFDL's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the pre‐industrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasi‐periodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.
Six recent Langmuir turbulence parameterization schemes and five traditional schemes are implemented in a common single column modeling framework and consistently compared. These schemes are tested in scenarios versus matched large eddy simulations (LES), across the globe with realistic forcing (JRA55‐do, WAVEWATCH‐III simulated waves) and initial conditions (Argo), and under realistic conditions as observed at ocean moorings. Traditional non‐Langmuir schemes systematically under‐predict LES vertical mixing under weak convective forcing, while Langmuir schemes vary in accuracy. Under global, realistic forcing Langmuir schemes produce 6% (‐1% to 14% for 90% confidence) or 5.2 m (‐0.2 m to 17.4 m for 90% confidence) deeper monthly mean mixed layer depths (MLD) than their non‐Langmuir counterparts, with the greatest differences in extratropical regions, especially the Southern Ocean in austral summer. Discrepancies among Langmuir schemes are large (15% in MLD standard deviation over the mean): largest under wave‐driven turbulence with stabilizing buoyancy forcing, next largest under strongly wave‐driven conditions with weak buoyancy forcing, and agreeing during strong convective forcing. Non‐Langmuir schemes disagree with each other to a lesser extent, with a similar ordering. Langmuir discrepancies obscure a cross‐scheme estimate of the Langmuir effect magnitude under realistic forcing, highlighting limited understanding and numerical deficiencies. Maps of the regions and seasons where the greatest discrepancies occur are provided to guide further studies and observations.
Reichl, Brandon G., and Q Li, November 2019: A parameterization with a constrained potential energy conversion rate of vertical mixing due to Langmuir turbulence. Journal of Physical Oceanography, 49(11), DOI:10.1175/JPO-D-18-0258.1. Abstract
In this study we develop a new parameterization for turbulent mixing in the ocean surface boundary layer (OSBL), including the effect of Langmuir turbulence. This new parameterization builds on a recent study (Reichl and Hallberg, 2018, hereafter RH18), which predicts the available energy for turbulent mixing against stable stratification driven by shear and convective turbulence. To investigate the role of Langmuir turbulence in the framework of RH18, we utilize data from a suite of previously published Large Eddy Simulation (LES) experiments (Li and Fox-Kemper, 2017, hereafter LF17) with and without Langmuir turbulence under different idealized forcing conditions. We find that the parameterization of RH18 is able to reproduce the mixing simulated by the LES in the non-Langmuir cases, but not the Langmuir cases. We therefore investigate the enhancement of the integrated vertical buoyancy flux within the entrainment layer in the presence of Langmuir turbulence using the LES data. An additional factor is introduced in the RH18 framework to capture the enhanced mixing due to Langmuir turbulence. This additional factor depends on the surface-layer averaged Langmuir number with a reduction in the presence of destabilizing surface buoyancy fluxes. It is demonstrated that including this factor within the RH18 OSBL turbulent mixing parameterization framework captures the simulated effect of Langmuir turbulence in the LES, which can be used for simulating the effect of Langmuir turbulence in climate simulations. This new parameterization is compared to the KPP-based Langmuir entrainment parameterization introduced by LF17, and differences are explored in detail.
Wang, D, T Kukulka, Brandon G Reichl, Tetsu Hara, and Isaac Ginis, December 2019: Wind-Wave Misalignment Effects on Langmuir Turbulence in Tropical Cyclones Conditions. Journal of Physical Oceanography, 49(12), DOI:10.1175/JPO-D-19-0093.1. Abstract
This study utilizes a large eddy simulation (LES) approach to systematically assess the directional variability of wave-driven Langmuir turbulence (LT) in the ocean surface boundary layer (OSBL) under tropical cyclones (TCs). The Stokes drift vector, which drives LT through the Craik-Leibovich vortex force, is obtained through spectral wave simulations. LT’s direction is identified by horizontally elongated turbulent structures and objectively determined from horizontal autocorrelations of vertical velocities. In spite of TC’s complex forcing with great wind and wave misalignments, this study finds that LT is approximately aligned with the wind. This is because the Reynolds stress and the depth-averaged Lagrangian shear (Eulerian plus Stokes drift shear) that are key in determining the LT intensity (determined by normalized depthaveraged vertical velocity variances) and direction, are also approximately aligned with the wind relatively close to the surface. A scaling analysis of the momentum budget suggests that the Reynolds stress is approximately constant over a near surface layer with predominant production of LT, which is confirmed from the LES results. In this layer, Stokes drift shear, which dominates the Lagrangian shear, is aligned with the wind because of relatively short, wind-driven waves. On the contrary, Stokes drift exhibits considerable amount of misalignments with the wind. This wind-wave misalignment reduces LT intensity, consistent with a simple turbulent kinetic energy model. Our analysis shows that both the Reynolds stress and LT are aligned with the wind for different reasons: the former is dictated by the momentum budget, while the latter is controlled by wind-forced waves.
This paper presents a method to parameterize vertical turbulent mixing coefficients within the ocean surface boundary layer (OSBL) for climate applications. The new method is specifically constructed to satisfy two requirements. The first aspect is to explicitly consider the mechanical energy budget of the turbulence that drives mixing. This constraint ensures a realistic and robust simulation of the OSBL, which is critical for coupled climate simulations. The second aspect is that the model should be formulated so that it is not sensitive to the numerical limitations common to climate simulations, such as long time-steps and coarse vertical grids. This goal is achieved by combining an existing resolved shear-driven mixing parameterization (here Jackson et al., 2008) with a new method to avoid time step sensitivity. The new method is motivated by the Kraus-Turner-Niiler type bulk boundary layer parameterization, but relaxes the requirement for vertical homogeneity. The non-dimensional coefficients m* and n* from the Kraus-Turner-Niiler approach are parameterized for the new method based on results of simulations using a previously tested parameterization at high resolution. The resulting parameterization is evaluated by comparing simulations with the new parameterization to simulations with the parameterization over a wide range of combinations of surface wind stress, surface buoyancy flux, and latitudes. The new method for vertical turbulent OSBL mixing is therefore proposed as a computationally efficient, implicitly energetically constrained option appropriate for ocean climate modeling applications.
Van Roekel, L, Alistair Adcroft, Gokhan Danabasoglu, Stephen M Griffies, B Kauffman, William G Large, Michael Levy, and Brandon G Reichl, et al., November 2018: The KPP boundary layer scheme for the ocean: revisiting its formulation and benchmarking one‐dimensional simulations relative to LES. Journal of Advances in Modeling Earth Systems, 10(11), DOI:10.1029/2018MS001336. Abstract
We evaluate the Community ocean Vertical Mixing (CVMix) project version of the K‐profile parameterization (KPP) for modeling upper ocean turbulent mixing. For this purpose, one‐dimensional KPP simulations are compared across a suite of oceanographically relevant regimes against horizontally averaged large eddy simulations (LES). We find the standard configuration of KPP consistent with LES across many forcing regimes, supporting its physical basis. Our evaluation also motivates recommendations for KPP “best practices” within ocean circulation models, and identifies areas where further research is warranted.
The original treatment of KPP recommends the matching of interior diffusivities and their gradients to the KPP predicted values computed in the ocean surface boundary layer (OSBL). However, we find that difficulties in representing derivatives of rapidly changing diffusivities near the base of the OSBL can lead to loss of simulation fidelity. To mitigate this difficulty, we propose and evaluate two computationally simpler approaches: (1) match to the internal predicted diffusivity alone, (2) set the KPP diffusivity to zero at the OSBL base.
We find the KPP entrainment buoyancy flux to be sensitive to vertical grid resolution and details of how to diagnose the KPP boundary layer depth. We modify the KPP turbulent shear velocity parameterization to reduce resolution dependence. Additionally, an examination of LES vertical turbulent scalar flux budgets shows that the KPP parameterized non‐local tracer flux is incomplete due to the assumption that it solely redistributes the surface tracer flux. This result motivates further studies of the non‐local flux parameterization.
Wang, D, T Kukulka, Brandon G Reichl, Tetsu Hara, and Isaac Ginis, et al., September 2018: Interaction of Langmuir Turbulence and Inertial Currents in the Ocean Surface Boundary Layer under Tropical Cyclones. Journal of Physical Oceanography, 48(9), DOI:10.1175/JPO-D-17-0258.1. Abstract
Based on a large-eddy simulation approach, this study investigates the response of the ocean surface boundary layer (OSBL) and Langmuir turbulence (LT) to extreme wind and complex wave forcing under tropical cyclones (TCs). The Stokes drift vector that drives LT is determined from spectral wave simulations. During maximum TC winds, LT substantially enhances the entrainment of cool water, causing rapid OSBL deepening. This coincides with relatively strong wave forcing, weak inertial currents, and shallow OSBL depth , measured by smaller ratios of , where denotes a Stokes drift decay length scale. LT directly affects a near-surface layer whose depth is estimated from enhanced anisotropy ratios of velocity variances. During rapid OSBL deepening, is proportional to , and LT efficiently transports momentum in coherent structures, locally enhancing shear instabilities in a deeper shear-driven layer, which is controlled by LT. After the TC passes, inertial currents are stronger and is greater while is shallower and proportional to . During this time, the LT-affected surface layer is too shallow to directly influence the deeper shear-driven layer, so that both layers are weakly coupled. At the same time, LT reduces surface currents that play a key role in the surface energy input at a later stage. These two factors contribute to relatively small TKE levels and entrainment rates after TC passage. Therefore, our study illustrates that inertial currents need to be taken into account for a complete understanding of LT and its effects on OSBL dynamics in TC conditions.
Reichl, Brandon G., et al., December 2016: Impact of Sea-State-Dependent Langmuir Turbulence on the Ocean Response to a Tropical Cyclone. Monthly Weather Review, 144(12), DOI:10.1175/MWR-D-16-0074.1. Abstract
Tropical cyclones are fueled by the air–sea heat flux, which is reduced when the ocean surface cools due to mixed layer deepening and upwelling. Wave-driven Langmuir turbulence can significantly modify these processes. This study investigates the impact of sea-state-dependent Langmuir turbulence on the three-dimensional ocean response to a tropical cyclone in coupled wave–ocean simulations. The Stokes drift is computed from the simulated wave spectrum using the WAVEWATCH III wave model and passed to the three-dimensional Princeton Ocean Model. The Langmuir turbulence impact is included in the vertical mixing of the ocean model by adding the Stokes drift to the shear of the vertical mean current and by including Langmuir turbulence enhancements to the K-profile parameterization (KPP) scheme. Results are assessed by comparing simulations with explicit (sea-state dependent) and implicit (independent of sea state) Langmuir turbulence parameterizations, as well as with turbulence driven by shear alone. The results demonstrate that the sea-state-dependent Langmuir turbulence parameterization significantly modifies the three-dimensional ocean response to a tropical cyclone. This is due to the reduction of upwelling and horizontal advection where the near-surface currents are reduced by Langmuir turbulence. The implicit scheme not only misses the impact of sea-state dependence on the surface cooling, but it also misrepresents the impact of the Langmuir turbulence on the Eulerian advection. This suggests that explicitly resolving the sea-state-dependent Langmuir turbulence will lead to increased accuracy in predicting the ocean response in coupled tropical cyclone–ocean models.
