Search

Abstract. This study evaluates the impact of increasing resolution on Arctic Ocean simulations using five pairs of matched low- and high-resolution models within the OMIP-2 (Ocean Model Intercomparison Project phase 2) framework. The primary objective is to assess whether a higher resolution can mitigate typical biases in low-resolution models and improve the representation of key climate-relevant variables. We reveal that increasing the horizontal resolution contributes to a reduction in biases in mean temperature and salinity and improves the simulation of the Atlantic water layer and its decadal warming events. A higher resolution also leads to better agreement with observed surface mixed-layer depth, cold halocline base depth and Arctic gateway transports in the Fram and Davis straits. However, the simulation of the mean state and temporal changes in Arctic freshwater content does not show improvement with increased resolution. Not all models achieve improvements for all analyzed ocean variables when spatial resolution is increased so it is crucial to recognize that model numerics and parameterizations also play an important role in faithful simulations. Overall, a higher resolution shows promise in improving the simulation of key Arctic Ocean features and processes, but efforts in model development are required to achieve more accurate representations across all climate-relevant variables.

Advances in coastal modeling and computation provide the opportunity to examine non-hydrostatic and compressible fluid effects at very small scales, but the cost of these new capabilities and the accuracy of these models versus trusted non-hydrostatic codes has yet to be determined. Here the Coastal and Regional Ocean COmmunity model (CROCO, v1.2) and the National Center for Atmospheric Research large-eddy simulation (NCAR-LES) model are compared, with a focus on their simulation accuracy and computational efficiency. These models differ significantly in numerics and capabilities, so they are run on common classic problems of surface-forced, boundary-layer turbulence. In terms of accuracy, we compare turbulence statistics, including the effect of the explicit subgrid-scale (SGS) parameterization, the effect of the second (dilatational) viscosity, and the sensitivity to the speed of sound, which is used as part of the CROCO compressible turbulence formulation. To gauge how far CROCO is from the NCAR-LES, we first compare the NCAR-LES with two other non-hydrostatic Boussinesq approximation LES codes (PALM and Oceananigans), defining the notion and magnitude of accuracy for the LES and CROCO comparison. To judge efficiency of CROCO, strong and weak scaling simulation sets vary different problem sizes and workloads per processor, respectively. Additionally, the effects of 2D decomposition of CROCO and NCAR-LES and supercomputer settings are tested. In summary, the accuracy comparison between CROCO and the NCAR-LES is similar to the NCAR-LES compared to other LES codes. However, the additional capabilities of CROCO (e.g., nesting, non-uniform grid, and realism of ocean configuration in general) and its weakly compressible formulation come with roughly an order of magnitude of additional costs, despite efforts to reduce them by adjusting the second viscosity and speed of sound as far as accuracy allows. However, a new variant of the non-hydrostatic CROCO formulation is cu

Mesoscale and submesoscale processes have crucial impacts on ocean biogeochemistry, importantly enhancing the primary production in nutrient-deficient ocean regions. Yet, the intricate biophysical interplay still holds mysteries. Using targeted high-resolution in situ observations in the South China Sea, we reveal that isopycnal submesoscale stirring serves as the primary driver of vertical nutrient transport to sustain the dome-shaped subsurface chlorophyll maximum (SCM) within a long-lived cyclonic mesoscale eddy. Density surface doming at the eddy core increased light exposure for phytoplankton production, while along-isopycnal submesoscale stirring disrupted the mesoscale coherence and drove significant vertical exchange of tracers. These physical processes play a crucial role in maintaining the elevated phytoplankton biomass in the eddy core. Our findings shed light on the universal mechanism of how mesoscale and submesoscale coupling enhances primary production in ocean cyclonic eddies, highlighting the pivotal role of submesoscale stirring in structuring marine ecosystems.

We study the impact of the Ekman currents and Stokes drift on the surface horizontal transport and mixing properties of the Mediterranean Sea. Finite Size Lyapunov Exponents (FSLE) at the ocean surface are computed over the whole basin using 25 years of satellite altimetry derived geostrophic currents, 10-m wind velocity and wave fields. We find that the transport pathways unveiled by the geostrophic Lagrangian Coherent Structures (LCS) are significantly modified by the ageostrophic currents (i.e., Ekman and Stokes induced velocities), often leading to a decrease of the retention capacity of the eddies. An exhaustive assessment of the regional and temporal variability of the FSLE shows an increase of the horizontal mixing processes, due to the ageostrophic component, up to 37% in regions such as the Gulf of Lion or the Aegean Sea, during the seasons where wind and waves are intense and persistent. Positive trends in the total FSLE (up to 1.2% of the value of FSLE per year in some regions) suggest that Mediterranean Sea has experienced a significant increase in the intensity of the mixing processes over the last decades. Ageostrophic features are considered to play a role in determining the properties of the relative dispersion. Through the analysis of the Lagrangian Anisotropy Index (LAI) using virtual and real pair of drifters, we observe that the particle dispersion is mainly dominated by the zonal flow, and that the ageostrophic currents induce meridional dispersion, particularly in regions where wind and wave are intensified.

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Marques, G. M., Loose, N., Yankovsky, E., Steinberg, J. M., Chang, C.-Y., Bhamidipati, N., Adcroft, A., Fox-Kemper, B., Griffies, S. M., Hallberg, R. W., Jansen, M. F., Khatri, H., & Zanna, L. NeverWorld2: an idealized model hierarchy to investigate ocean mesoscale eddies across resolutions. Geoscientific Model Development, 15(17), (2022): 6567–6579, https://doi.org/10.5194/gmd-15-6567-2022., We describe an idealized primitive-equation model for studying mesoscale turbulence and leverage a hierarchy of grid resolutions to make eddy-resolving calculations on the finest grids more affordable. The model has intermediate complexity, incorporating basin-scale geometry with idealized Atlantic and Southern oceans and with non-uniform ocean depth to allow for mesoscale eddy interactions with topography. The model is perfectly adiabatic and spans the Equator and thus fills a gap between quasi-geostrophic models, which cannot span two hemispheres, and idealized general circulation models, which generally include diabatic processes and buoyancy forcing. We show that the model solution is approaching convergence in mean kinetic energy for the ocean mesoscale processes of interest and has a rich range of dynamics with circulation features that emerge only due to resolving mesoscale turbulence., This research has been supported by the US Department of Commerce (grant no. NA18OAR4320123), the Division of Ocean Sciences (grant nos. 1912420, 1912332, 1912357, 1912163, and 1912302), the Division of Atmospheric and Geospace Sciences (grant no. 1852977), and the Climate Program Office (grant nos. NA19OAR4310364, NA19OAR4310365, and NA19OAR4310366).

The ocean mixed layer is the interface between the ocean interior and the atmosphere or sea ice, and plays a key role in climate variability. It is thus critical that numerical models used in climate studies are capable of a good representation of the mixed layer, especially its depth. Here we evaluate the mixed layer depth (MLD) in six pairs of non-eddying (1° resolution) and eddy-rich (up to 1/16°) models from the Ocean Model Intercomparison Project (OMIP), forced by a common atmospheric state. For model validation, we use an updated MLD dataset computed from observations using the OMIP protocol (a constant density threshold). In winter, low resolution models exhibit large biases in the deep water formation regions. These biases are reduced in eddy-rich models but not uniformly across models and regions. The improvement is most noticeable in the mode water formation regions of the northern hemisphere. Results in the Southern Ocean are more contrasted, with biases of either sign remaining at high resolution. In eddy-rich models, mesoscale eddies control the spatial variability of MLD in winter. Contrary to a hypothesis that the deepening of the mixed layer in anticyclones would make the MLD larger globally, eddy-rich models tend to have a shallower mixed layer at most latitudes than coarser models do. In addition, our study highlights the sensitivity of the MLD computation to the choice of a reference level and the spatio-temporal sampling, which motivates new recommendations for MLD computation in future model intercomparison projects.

This work evaluates the fidelity of various upper-ocean turbulence parameterizations subject to realistic monsoon forcing and presents a finite-time ensemble vector (EV) method to better manage the design and numerical principles of these parameterizations. The EV method emphasizes the dynamics of a turbulence closure multimodel ensemble and is applied to evaluate 10 different ocean surface boundary layer (OSBL) parameterizations within a single-column (SC) model against two boundary layer large-eddy simulations (LES). Both LES include realistic surface forcing, but one includes wind-driven shear turbulence only, while the other includes additional Stokes forcing through the wave-average equations that generate Langmuir turbulence. The finite-time EV framework focuses on what constitutes the local behavior of the mixed layer dynamical system and isolates the forcing and ocean state conditions where turbulence parameterizations most disagree. Identifying disagreement provides the potential to evaluate SC models comparatively against the LES. Observations collected during the 2018 monsoon onset in the Bay of Bengal provide a case study to evaluate models under realistic and variable forcing conditions. The case study results highlight two regimes where models disagree 1) during wind-driven deepening of the mixed layer and 2) under strong diurnal forcing.

A process study using large-eddy simulations is carried out to explore the dominant 1-D processes that affect mixed layer (ML) properties during an event of summer Monsoon Intra-seasonal Oscillations (MISO) in the Bay of Bengal (BOB). These simulations use realistic air-sea fluxes and initial conditions that were collected during the summer 2018 MISO-BOB field experiment to explore the roles of thermal inversion layer (TIL) and Langmuir turbulence (LT) in modulating ML properties. The simulations span an active period with heavy rain and strong winds and a break period with strong solar heat flux and little rain. The mixed layer depth (MLD), sea surface temperature (SST) and sea surface salinity (SSS) are most affected by the presence of near-inertial oscillations, solar heating and precipitation, all of which occur at different timescales. The subsurface warming induced by the TIL reduces the SST variability at the MISO timescale when compared with the simulation without TIL. Comparison of simulations with and without LT indicates that LT enhances subsurface warming during the active phase and reduces diurnal SST modulation during the break phase. Simulations with 1-D mixing models show a wide disparity in the evolution of MLD, SST, and SSS. © 2023. American Geophysical Union. All Rights Reserved.

With the increase in computational power, ocean models with kilometer-scale resolution have emerged over the last decade. These models have been used for quantifying the energetic exchanges between spatial scales, informing the design of eddy parametrizations, and preparing observing networks. The increase in resolution, however, has drastically increased the size of model outputs, making it difficult to transfer and analyze the data. It remains, nonetheless, of primary importance to assess more systematically the realism of these models. Here, we showcase a cloud-based analysis framework proposed by the Pangeo project that aims to tackle such distribution and analysis challenges. We analyze the output of eight submesoscale-permitting simulations, all on the cloud, for a crossover region of the upcoming Surface Water and Ocean Topography (SWOT) altimeter mission near the Gulf Stream separation. The cloud-based analysis framework (i) minimizes the cost of duplicating and storing ghost copies of data and (ii) allows for seamless sharing of analysis results amongst collaborators. We describe the framework and provide example analyses (e.g., sea-surface height variability, submesoscale vertical buoyancy fluxes, and comparison to predictions from the mixed-layer instability parametrization). Basin- to global-scale, submesoscale-permitting models are still at their early stage of development; their cost and carbon footprints are also rather large. It would, therefore, benefit the community to document the different model configurations for future best practices. We also argue that an emphasis on data analysis strategies would be crucial for improving the models themselves.

The ocean surface boundary layer links the atmosphere to the ocean. At the air-sea interface, ocean surface waves play an important role in momentum, energy and gas exchange. A new parameterization with wave-induced mixing is developed based on a set of Large Eddy Simulation experiments under different wind speeds and mixed layer depths. The new parameterization scheme is then incorporated into a one-dimensional turbulence model for verification. The inclusion of wave-induced mixing reduces the excessively high surface temperature simulated in summer and reduces the underestimation of the mixed layer depth in winter. Compared to the observation at Ocean Station Papa, the parameterization scheme with wave effects produces statistically more accurate results than the parameterization scheme without wave effects.

Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 101(6), (2020): E744-E762, doi:10.1175/BAMS-D-19-0015.1., From 11 April to 11 June 2018 a new type of ocean observing platform, the Saildrone surface vehicle, collected data on a round-trip, 60-day cruise from San Francisco Bay, down the U.S. and Mexican coast to Guadalupe Island. The cruise track was selected to optimize the science team’s validation and science objectives. The validation objectives include establishing the accuracy of these new measurements. The scientific objectives include validation of satellite-derived fluxes, sea surface temperatures, and wind vectors and studies of upwelling dynamics, river plumes, air–sea interactions including frontal regions, and diurnal warming regions. On this deployment, the Saildrone carried 16 atmospheric and oceanographic sensors. Future planned cruises (with open data policies) are focused on improving our understanding of air–sea fluxes in the Arctic Ocean and around North Brazil Current rings., The Saildrone data collection mission was sponsored by the Saildrone Award, an annual data collection mission awarded by Saildrone Inc., and the Schmidt Family Foundation. The research was funded by the NASA Physical Oceanography Program Grant 80NSSC18K0837 and 80NSSC18K1441. The work by T. M. Chin, J. Vazquez-Cuerzo, and V. Tsontos was carried out at the Jet Propulsion Laboratory (JPL), California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). Piero L.F. Mazzini was supported by California Sea Grant Award NA18OAR4170073. We thank CeNCOOS for providing the HF radar data in the Gulf of the Farallones. Jose Gomez-Valdes was supported by CONACYT Grant 257125, and by CICESE. Work by Joel Scott and Ivona Cetinic was supported through NASA PACE. The work by Lisan Yu was supported by NOAA Ocean Observing and Monitoring Division under Grant NA14OAR4320158.

The Ocean State Ocean Model (OSOM) is an application of the Regional Ocean Modeling System spanning the Rhode Island waterways, including Narragansett Bay, Mt. Hope Bay, larger rivers, and the Block Island Shelf circulation from Long Island to Nantucket. This study discusses the physical aspects of the estuary (Narragansett and Mount Hope Bays and larger rivers) to evaluate physical circulation predictability. This estimate is intended to help decide if a forecast and prediction system is warranted, to prepare for coupling with biogeochemistry and fisheries models with widely disparate timescales, and to find the spin-up time needed to establish the climatological circulation of the region. Perturbed initial condition ensemble simulations are combined with metrics from information theory to quantify the predictability of the OSOM forecast system–i.e., how long anomalies from different initial conditions persist. The predictability timescale in this model agrees with readily estimable timescales such as the freshwater flushing timescale evaluated using the total exchange flow (TEF) framework, indicating that the estuarine dynamics rather than chaotic transport is the dominant model behavior limiting predictions. The predictability of the OSOM is ∼7–40 days, varying with parameters, region, and season.