Articles | Volume 17, issue 18
https://doi.org/10.5194/gmd-17-6967-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-6967-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
19 Sep 2024
Development and technical paper |
| 19 Sep 2024
| 19 Sep 2024
Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)
Adrien Garinet
CORRESPONDING AUTHOR
LEGOS (CNES/CNRS/IRD/UT3), Université de Toulouse, Toulouse, France
Direction Générale de l'Armement, Ministère des Armées, Paris, France
Marine Herrmann
LEGOS (CNES/CNRS/IRD/UT3), Université de Toulouse, Toulouse, France
Patrick Marsaleix
LEGOS (CNES/CNRS/IRD/UT3), Université de Toulouse, Toulouse, France
Juliette Pénicaud
LEGOS (CNES/CNRS/IRD/UT3), Université de Toulouse, Toulouse, France
Related authors
No articles found.
Quentin Desmet, Marine Herrmann, and Thanh Ngo-Duc
EGUsphere, https://doi.org/10.5194/egusphere-2025-1579, https://doi.org/10.5194/egusphere-2025-1579, 2025
Short summary
Short summary
Climate model performance at the air–sea interface has long been overlooked across the Southeast Asian seas. We thus assess various regional model physics configurations in this regard. Finding one optimal configuration is challenging: reliable rainfall rarely coincides with correct radiative heating. Simulations of rainfall however yield more dissensus, suggesting that this variable should be prioritized, for which the best results are obtained with the cumulus convection scheme of Tiedtke.
Lisa Weiss, Marine Herrmann, Patrick Marsaleix, Matthieu Bompoil, and Christophe Maes
EGUsphere, https://doi.org/10.5194/egusphere-2025-1918, https://doi.org/10.5194/egusphere-2025-1918, 2025
Short summary
Short summary
We developed a high-resolution ocean model to study the dispersion of marine debris across the Indian Ocean, from small coastal scales to the open sea. Our results show that both model resolution and the effect of wind-driven surface waves play a key role in shaping ocean circulation, seasonal energy budgets and floating debris trajectories. High-resolution currents and wave forcing increase the spread and distance traveled by drifting material, especially during monsoon periods.
Thanh Huyen Tran, Alexei Sentchev, Thai To Duy, Marine Herrmann, Sylvain Ouillon, and Kim Cuong Nguyen
Ocean Sci., 21, 1–18, https://doi.org/10.5194/os-21-1-2025, https://doi.org/10.5194/os-21-1-2025, 2025
Short summary
Short summary
For the first time, high-resolution surface current data from high-frequency radar have been obtained along the central and southern coasts of Vietnam, and combined with a modelling approach, this is helping scientists to understand coastal processes. The research showed that the surface circulation is driven not only by winds, but also by other factors. This can enrich public knowledge of the coastal dynamics that govern other environmental impacts along the coasts.
Marine Herrmann, Thai To Duy, and Patrick Marsaleix
Ocean Sci., 20, 1013–1033, https://doi.org/10.5194/os-20-1013-2024, https://doi.org/10.5194/os-20-1013-2024, 2024
Short summary
Short summary
In summer, deep, cold waters rise to the surface along and off the Vietnamese coast. This upwelling of water lifts nutrients, inducing biological activity that is important for fishery resources. Strong tides occur on the shelf off the Mekong Delta. By increasing the mixing of ocean waters and modifying currents, they are a major factor in the development of upwelling on the shelf, accounting for ~75 % of its average summer intensity.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
Short summary
Short summary
A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Caroline Ulses, Claude Estournel, Patrick Marsaleix, Karline Soetaert, Marine Fourrier, Laurent Coppola, Dominique Lefèvre, Franck Touratier, Catherine Goyet, Véronique Guglielmi, Fayçal Kessouri, Pierre Testor, and Xavier Durrieu de Madron
Biogeosciences, 20, 4683–4710, https://doi.org/10.5194/bg-20-4683-2023, https://doi.org/10.5194/bg-20-4683-2023, 2023
Short summary
Short summary
Deep convection plays a key role in the circulation, thermodynamics, and biogeochemical cycles in the Mediterranean Sea, considered to be a hotspot of biodiversity and climate change. In this study, we investigate the seasonal and annual budget of dissolved inorganic carbon in the deep-convection area of the northwestern Mediterranean Sea.
Joelle Habib, Caroline Ulses, Claude Estournel, Milad Fakhri, Patrick Marsaleix, Mireille Pujo-Pay, Marine Fourrier, Laurent Coppola, Alexandre Mignot, Laurent Mortier, and Pascal Conan
Biogeosciences, 20, 3203–3228, https://doi.org/10.5194/bg-20-3203-2023, https://doi.org/10.5194/bg-20-3203-2023, 2023
Short summary
Short summary
The Rhodes Gyre, eastern Mediterranean Sea, is the main Levantine Intermediate Water formation site. In this study, we use a 3D physical–biogeochemical model to investigate the seasonal and interannual variability of organic carbon dynamics in the gyre. Our results show its autotrophic nature and its high interannual variability, with enhanced primary production, downward exports, and onward exports to the surrounding regions during years marked by intense heat losses and deep mixed layers.
Marine Herrmann, Thai To Duy, and Claude Estournel
Ocean Sci., 19, 453–467, https://doi.org/10.5194/os-19-453-2023, https://doi.org/10.5194/os-19-453-2023, 2023
Short summary
Short summary
The South Vietnam upwelling develops in summer along and off the Vietnamese coast. It brings cold and nutrient-rich waters to the surface, allowing photosynthesis essential to marine ecosystems and fishing resources. We show here that its daily variations are mainly due to the wind, thus predictable, in the southern shelf and coastal regions. However, they are more chaotic in the offshore area, and especially in the northern area, due to the influence of eddies of a highly chaotic nature.
Thai To Duy, Marine Herrmann, Claude Estournel, Patrick Marsaleix, Thomas Duhaut, Long Bui Hong, and Ngoc Trinh Bich
Ocean Sci., 18, 1131–1161, https://doi.org/10.5194/os-18-1131-2022, https://doi.org/10.5194/os-18-1131-2022, 2022
Short summary
Short summary
The South Vietnam Upwelling develops in the coastal and offshore regions of the southwestern South China Sea under the influence of summer monsoon winds. Cold, nutrient-rich waters rise to the surface, where photosynthesis occurs and is essential for fishing activity. We have developed a very high-resolution model to better understand the factors that drive the variability of this upwelling at different scales: daily chronology to summer mean of wind and mesoscale to regional circulation.
Gaël Many, Caroline Ulses, Claude Estournel, and Patrick Marsaleix
Biogeosciences, 18, 5513–5538, https://doi.org/10.5194/bg-18-5513-2021, https://doi.org/10.5194/bg-18-5513-2021, 2021
Short summary
Short summary
The Gulf of Lion shelf is one of the most productive areas in the Mediterranean. A model is used to study the mechanisms that drive the particulate organic carbon (POC). The model reproduces the annual cycle of primary production well. The shelf appears as an autotrophic ecosystem with a high production and as a source of POC for the adjacent basin. The increase in temperature induced by climate change could impact the trophic status of the shelf.
Caroline Ulses, Claude Estournel, Marine Fourrier, Laurent Coppola, Fayçal Kessouri, Dominique Lefèvre, and Patrick Marsaleix
Biogeosciences, 18, 937–960, https://doi.org/10.5194/bg-18-937-2021, https://doi.org/10.5194/bg-18-937-2021, 2021
Short summary
Short summary
We analyse the seasonal cycle of O2 and estimate an annual O2 budget in the north-western Mediterranean deep-convection region, using a numerical model. We show that this region acts as a large sink of atmospheric O2 and as a major source of O2 for the western Mediterranean Sea. The decrease in the deep convection intensity predicted in recent projections may have important consequences on the overall uptake of O2 in the Mediterranean Sea and on the O2 exchanges with the Atlantic Ocean.
Violaine Piton, Marine Herrmann, Florent Lyard, Patrick Marsaleix, Thomas Duhaut, Damien Allain, and Sylvain Ouillon
Geosci. Model Dev., 13, 1583–1607, https://doi.org/10.5194/gmd-13-1583-2020, https://doi.org/10.5194/gmd-13-1583-2020, 2020
Short summary
Short summary
Consequences of tidal dynamics on hydro-sedimentary processes are a recurrent issue in estuarine and coastal processes studies, and accurate tidal solutions are a prerequisite for modeling sediment transport. This study presents the implementation and optimization of a model configuration in terms of bathymetry and bottom friction and assess the influence of these parameters on tidal solutions, in a macro-tidal environment: the Gulf of Tonkin (Vietnam).
Related subject area
Oceanography
PIBM 1.0: an individual-based model for simulating phytoplankton acclimation, diversity, and evolution in the ocean
An effective communication topology for performance optimization: a case study of the finite-volume wave modeling (FVWAM)
GREAT v1.0: Global Real-time Early Assessment of Tsunamis
Using automatic calibration to improve the physics behind complex numerical models: an example from a 3D lake model using Delft3D (v6.02.10) and DYNO-PODS (v1.0)
Improvements to the Met Office's global ocean–sea ice forecasting system including model and data assimilation changes
Resolution dependence of interlinked Southern Ocean biases in global coupled HadGEM3 models
PyESPERv1.01.01: A Python implementation of empirical seawater property estimation routines (ESPERs)
Modelling Microplastic Dynamics in Estuaries: A Comprehensive Review, Challenges and Recommendations
A new global high-resolution wave model for the tropical ocean using WAVEWATCH III version 7.14
DINO: A Diabatic Model of Pole-to-Pole Ocean Dynamics to Assess Subgrid Parameterizations across Horizontal Scales
sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
Offline Fennel: A High-Performance and Computationally Efficient Biogeochemical Model within the Regional Ocean Modeling System (ROMS)
The Ross Sea and Amundsen Sea Ice–Sea Model (RAISE v1.0): a high-resolution ocean–sea ice–ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)
CRITER 1.0: A coarse reconstruction with iterative refinement network for sparse spatio-temporal satellite data
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0
HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development
Comparing an idealized deterministic-stochastic model (SUP model, version 1) of the tide-and-wind driven sea surface currents in the Gulf of Trieste to HF Radar observations
ISWFM-NSCS v2.0: advancing the internal solitary wave forecasting model with background currents and horizontally inhomogeneous stratifications
Impacts of CICE sea ice model and ERA atmosphere on an Antarctic MetROMS ocean model, MetROMS-UHel-v1.0
DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
An optimal transformation method for inferring ocean tracer sources and sinks
Data-driven rolling model for global wave height
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
Wave forecast investigations on downscaling, source terms, and tides for Aotearoa New Zealand
Experimental design for the Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2)
Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids
Modelling the water isotope distribution in the Mediterranean Sea using a high-resolution oceanic model (NEMO-MED12-watiso v1.0): evaluation of model results against in situ observations
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0
A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study of Quatsino Sound, British Columbia
An optimal transformation method applied to diagnose the ocean carbon budget
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 2: Towards a better representation of total alkalinity when modeling the carbonate system and air–sea CO2 fluxes
Development of a novel storm surge inundation model framework for efficient prediction
Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth
DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
StraitFlux – precise computations of water strait fluxes on various modeling grids
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Great Lakes wave forecast system on high-resolution unstructured meshes
Iria Sala and Bingzhang Chen
Geosci. Model Dev., 18, 4155–4182, https://doi.org/10.5194/gmd-18-4155-2025, https://doi.org/10.5194/gmd-18-4155-2025, 2025
Short summary
Short summary
Phytoplankton, tiny photosynthetic organisms, produce nearly half of Earth's oxygen. To analyze their physiology, diversity, and evolution in the ocean, we developed a model that treats phytoplankton as individual particles. Moreover, our model considers phytoplankton size, temperature, and light traits and allows for mutations in phytoplankton cells. Thus, our model provides a valuable tool for advancing the study of phytoplankton physiology, diversity, and evolution.
Renbo Pang, Fujiang Yu, Yuanyong Gao, Ye Yuan, Liang Yuan, and Zhiyi Gao
Geosci. Model Dev., 18, 4119–4136, https://doi.org/10.5194/gmd-18-4119-2025, https://doi.org/10.5194/gmd-18-4119-2025, 2025
Short summary
Short summary
The application of distributed graph communication topology in Earth models has rarely been studied. We tested and compared this topology with the traditional point-to-point communication method using a wave model. We found that this topology with the Intel MPI (message-passing interface) library is more efficient. Additionally, using this topology can greatly improve the performance of the wave model and could help improve the performance of other Earth models.
Usama Kadri, Ali Abdolali, and Maxim Filimonov
Geosci. Model Dev., 18, 3487–3507, https://doi.org/10.5194/gmd-18-3487-2025, https://doi.org/10.5194/gmd-18-3487-2025, 2025
Short summary
Short summary
The GREAT v1.0 software introduces a novel tsunami warning technology for global real-time analysis. It leverages acoustic signals generated by tsunamis, which propagate faster than the tsunami itself, enabling real-time detection and assessment. Integrating various models, the software provides reliable and rapid assessment, maps risk areas, and estimates tsunami amplitude. This advancement reduces false alarms and enhances global tsunami warning systems' accuracy and efficiency.
Marina Amadori, Abolfazl Irani Rahaghi, Damien Bouffard, and Marco Toffolon
Geosci. Model Dev., 18, 3473–3486, https://doi.org/10.5194/gmd-18-3473-2025, https://doi.org/10.5194/gmd-18-3473-2025, 2025
Short summary
Short summary
Models simplify reality using assumptions, which can sometimes introduce flaws and affect their accuracy. Properly calibrating model parameters is essential, and although automated tools can speed up this process, they may occasionally produce incorrect values due to inconsistencies in the model. We demonstrate that by carefully applying automated tools, we were able to identify and correct a flaw in a widely used model for lake environments.
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc'h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
Geosci. Model Dev., 18, 3405–3425, https://doi.org/10.5194/gmd-18-3405-2025, https://doi.org/10.5194/gmd-18-3405-2025, 2025
Short summary
Short summary
We describe major improvements of the Met Office's global ocean–sea ice forecasting system. The models and the way observations are used to improve the forecasts were changed, which led to a significant error reduction of 1 d forecasts. The new system performance in past conditions, where subsurface observations are scarce, was improved with more consistent ocean heat content estimates. The new system will be of better use for climate studies and will provide improved forecasts for end users.
David Storkey, Pierre Mathiot, Michael J. Bell, Dan Copsey, Catherine Guiavarc'h, Helene T. Hewitt, Jeff Ridley, and Malcolm J. Roberts
Geosci. Model Dev., 18, 2725–2745, https://doi.org/10.5194/gmd-18-2725-2025, https://doi.org/10.5194/gmd-18-2725-2025, 2025
Short summary
Short summary
The Southern Ocean is a key region of the world ocean in the context of climate change studies. We show that the Met Office Hadley Centre coupled model with intermediate ocean resolution struggles to accurately simulate the Southern Ocean. Increasing the frictional drag that the seafloor exerts on ocean currents and introducing a representation of unresolved ocean eddies both appear to reduce the large-scale biases in this model.
Larissa Marie Dias and Brendan Rae Carter
EGUsphere, https://doi.org/10.5194/egusphere-2025-458, https://doi.org/10.5194/egusphere-2025-458, 2025
Short summary
Short summary
The increasing availability of oceanographic physical and chemical data necessitates accompanying methods for optimizing use of this data. This project produced algorithms (PyESPERs) for estimating biogeochemical seawater properties in Python, a freely available coding language. These algorithms were based on Empirical Seawater Property Estimation Routines (ESPERs), which were originally written in the proprietary MATLAB coding language and can be used in studies of marine carbonate chemistry.
Betty John Kaimathuruthy, Isabel Jalón-Rojas, and Damien Sous
EGUsphere, https://doi.org/10.5194/egusphere-2025-529, https://doi.org/10.5194/egusphere-2025-529, 2025
Short summary
Short summary
Studies on plastic pollution have emerged as a rapidly growing field of research. Modelling microplastic transport in estuaries stems from their complex hydrodynamics and diverse particle behaviours affecting the dispersion and retention of microplastics. Our paper reviews key modelling approaches applied in estuaries analyzing their setups and parameterizations. We provide recommendations and future directions to improve the accuracy and modelling strategies for estuarine microplastic research.
Axelle Gaffet, Xavier Bertin, Damien Sous, Héloïse Michaud, Aron Roland, and Emmanuel Cordier
Geosci. Model Dev., 18, 1929–1946, https://doi.org/10.5194/gmd-18-1929-2025, https://doi.org/10.5194/gmd-18-1929-2025, 2025
Short summary
Short summary
This study presents a new global wave model that improves predictions of sea states in tropical areas by using a high-resolution grid and corrected wind fields. The model is validated globally with satellite data and nearshore using in situ data. The model allows for the first time direct comparisons with in situ data collected at 10–30 m water depth, which is very close to shore due to the steep slope usually surrounding volcanic islands.
David Kamm, Julie Deshayes, and Gurvan Madec
EGUsphere, https://doi.org/10.5194/egusphere-2025-1100, https://doi.org/10.5194/egusphere-2025-1100, 2025
Short summary
Short summary
We propose an idealized model of pole-to-pole ocean dynamics designed as a testbed for eddy parameterizations across a range of horizontal scales. While computationally affordable, it is able to capture key metrics of the climate system. By comparing simulations at low, intermediate and high horizontal resolution, we demonstrate its utility for evaluating eddy parameterizations, both in terms of their effect on the mean-state and by diagnosing the unresolved eddy fluxes they aim to represent.
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev., 18, 1561–1573, https://doi.org/10.5194/gmd-18-1561-2025, https://doi.org/10.5194/gmd-18-1561-2025, 2025
Short summary
Short summary
Most of the tools available to model sediment transport do not account for complex physical mechanisms such as surface-wave-driven processes. In this study, a new model, sedInterFoam, allows us to reproduce numerically complex configurations in order to investigate coastal sediment transport applications dominated by surface waves and to gain insight into the complex physical processes associated with breaking waves and morphodynamics.
Júlia Crespin, Jordi Solé, and Miquel Canals
EGUsphere, https://doi.org/10.5194/egusphere-2025-865, https://doi.org/10.5194/egusphere-2025-865, 2025
Short summary
Short summary
This study presents the Offline Fennel model, a tool designed to simulate ocean biogeochemical processes efficiently. By using existing hydrodynamic data, the model significantly reduces computation time from 6 hours to just 30 minutes. We tested its accuracy in the Northern Gulf of Mexico and found it closely matches physical-biogeochemical coupled simulations. This model allows researchers to conduct more tests and simulations without the need for extensive computational resources.
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev., 18, 1375–1393, https://doi.org/10.5194/gmd-18-1375-2025, https://doi.org/10.5194/gmd-18-1375-2025, 2025
Short summary
Short summary
A coupled fine-resolution ocean–ice model is developed for the Ross Sea and adjacent regions in Antarctica, a key area for the formation of global ocean bottom water, the Antarctic Bottom Water (AABW), which affects global ocean circulation. The model has a high skill level in simulating sea ice production driving the AABW source water formation and AABW properties when assessed against observations. A model experiment shows a significant impact of ice shelf melting on the AABW characteristics.
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025, https://doi.org/10.5194/gmd-18-1189-2025, 2025
Short summary
Short summary
Vertical mixing is an important process, for example, for tropical sea surface temperature, but cannot be resolved by ocean models. Comparisons of mixing schemes and settings have usually been done with a single model, sometimes yielding conflicting results. We systematically compare two widely used schemes with different parameter settings in two different ocean models and show that most effects from mixing scheme parameter changes are model-dependent.
Matjaž Zupančič Muc, Vitjan Zavrtanik, Alexander Barth, Aida Alvera-Azcarate, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-208, https://doi.org/10.5194/gmd-2024-208, 2025
Revised manuscript accepted for GMD
Short summary
Short summary
Accurate sea surface temperature data (SST) is crucial for weather forecasting and climate modeling, but satellite observations are often incomplete. We developed a new method called CRITER, which uses machine learning to fill in the gaps in SST data. Our two-stage approach reconstructs large-scale patterns and refines details. Tested on Mediterranean, Adriatic, and Atlantic seas data, CRITER outperforms current methods, reducing errors by up to 44 %.
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev., 18, 605–620, https://doi.org/10.5194/gmd-18-605-2025, https://doi.org/10.5194/gmd-18-605-2025, 2025
Short summary
Short summary
HIDRA3 is a deep-learning model for predicting sea levels and storm surges, offering significant improvements over previous models and numerical simulations. It utilizes data from multiple tide gauges, enhancing predictions even with limited historical data and during sensor outages. With its advanced architecture, HIDRA3 outperforms current state-of-the-art models by achieving a mean absolute error of up to 15 % lower, proving effective for coastal flood forecasting under diverse conditions.
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev., 18, 319–336, https://doi.org/10.5194/gmd-18-319-2025, https://doi.org/10.5194/gmd-18-319-2025, 2025
Short summary
Short summary
This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev., 18, 211–237, https://doi.org/10.5194/gmd-18-211-2025, https://doi.org/10.5194/gmd-18-211-2025, 2025
Short summary
Short summary
We developed a 3D ocean model called the Hindcast of the Salish Sea (HOTSSea v1) that recreates physical conditions throughout the Salish Sea from 1980 to 2018. It was not clear that acceptable accuracy could be achieved because of computational and data limitations, but the model's predictions agreed well with observations. When we used the model to examine ocean temperature trends in areas that lack observations, it indicated that some seasons and areas are warming faster than others.
Sofia Flora, Laura Ursella, and Achim Wirth
EGUsphere, https://doi.org/10.5194/egusphere-2024-3391, https://doi.org/10.5194/egusphere-2024-3391, 2025
Short summary
Short summary
We developed a hierarchy of idealized deterministic-stochastic models to simulate the sea surface currents in the Gulf of Trieste. They include tide-and-wind driven sea surface current components, resolving the slowly varying part of the flow and a stochastic signal, representing the fast-varying small-scale dynamics. The comparison with High Frequency Radar observations shows that the non-Gaussian stochastic model captures the essential dynamics and permits to mimic the observed fat-tailed PDF.
Yankun Gong, Xueen Chen, Jiexin Xu, Zhiwu Chen, Qingyou He, Ruixiang Zhao, Xiao-Hua Zhu, and Shuqun Cai
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-165, https://doi.org/10.5194/gmd-2024-165, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
A new internal solitary wave forecasting (ISW) model in the northern South China Sea (ISWFM-NSCS v2.0) improves ISW predictions by incorporating background currents and inhomogeneous stratifications. Additionally, viscosity and diffusivity coefficients are optimized to maintain stable stratifications, extending the forecasting period. Sensitivity experiments illustrate that ISWFM-NSCS v2.0 significantly enhances predictions of various wave properties.
Cecilia Äijälä, Yafei Nie, Lucía Gutiérrez-Loza, Chiara De Falco, Siv Kari Lauvset, Bin Cheng, David A. Bailey, and Petteri Uotila
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-213, https://doi.org/10.5194/gmd-2024-213, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The sea ice around Antarctica has experienced record lows in recent years. To understand these changes, models are needed. MetROMS-UHel is a new version of an ocean–sea ice model with updated sea ice code and the atmospheric data. We investigate the effect of our updates on different variables with a focus on sea ice and show an improved sea ice representation as compared with observations.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 2024
Short summary
Short summary
We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the ocean capture of atmospheric carbon dioxide, which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
Short summary
Short summary
Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
Short summary
Short summary
We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
Short summary
Short summary
We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Xinxin Wang, Jiuke Wang, Wenfang Lu, Changming Dong, Hao Qin, and Haoyu Jiang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-181, https://doi.org/10.5194/gmd-2024-181, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Large-scale wave modeling is essential for science and society, typically relying on resource-intensive numerical methods to simulate wave dynamics. In this study, we introduce a rolling AI-based method for modeling global significant wave height. Our model achieves accuracy comparable to traditional numerical methods while significantly improving speed, making it operable on standard laptops. This work demonstrates AI's potential to enhance the accuracy and efficiency of global wave modeling.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
Short summary
Short summary
Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Rafael Santana, Richard Gorman, Emily Lane, Stuart Moore, Cyprien Bosserelle, Glen Reeve, and Christo Rautenbach
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-110, https://doi.org/10.5194/gmd-2024-110, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This research explores improving wave forecasts in New Zealand, particularly at Banks Peninsula and Baring Head. We used detailed models, finding that forecasts at Baring Head improved significantly due to its strong tidal currents, but changes at Banks Peninsula were minimal. The study demonstrates that local conditions greatly influence the effectiveness of wave prediction models, highlighting the need for tailored approaches in coastal forecasting to enhance accuracy in the predictions.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
Short summary
Short summary
Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
Short summary
Short summary
We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
Short summary
Short summary
Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
Short summary
Short summary
Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
Short summary
Short summary
Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
Short summary
Short summary
Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
Short summary
Short summary
The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
Short summary
Short summary
The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
Short summary
Short summary
Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
Short summary
Short summary
This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
Short summary
Short summary
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
Short summary
Short summary
Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
Short summary
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
Short summary
Short summary
The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
Short summary
Short summary
In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
Short summary
Short summary
Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
Short summary
Short summary
Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
Short summary
Short summary
The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
Short summary
Short summary
A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
Short summary
Short summary
We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
Short summary
Short summary
Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
Short summary
Short summary
This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Cited articles
Adcroft, A. and Campin, J.-M.: Rescaled Height Coordinates for Accurate Representation of Free-Surface Flows in Ocean Circulation Models, Ocean Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003, 2004. a
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013. a
Alford, M. H., Gregg, M. C., and Ilyas, M.: Diapycnal Mixing in the Banda Sea: Results of the First Microstructure Measurements in the Indonesian Throughflow, Geophys. Res. Lett., 26, 2741–2744, https://doi.org/10.1029/1999GL002337, 1999. a
Álvarez, Ó., Izquierdo, A., González, C. J., Bruno, M., and Mañanes, R.: Some Considerations about Non-Hydrostatic vs. Hydrostatic Simulation of Short-Period Internal Waves. A Case Study: The Strait of Gibraltar, Cont. Shelf Res., 181, 174–186, https://doi.org/10.1016/j.csr.2019.05.016, 2019. a
Apel, J. R., Holbrook, J. R., Liu, A. K., and Tsai, J. J.: The Sulu Sea Internal Soliton Experiment, J. Phys. Oceanogr., 15, 1625–1651, https://doi.org/10.1175/1520-0485(1985)015<1625:TSSISE>2.0.CO;2, 1985. a, b, c
Arbic, B. K.: Incorporating Tides and Internal Gravity Waves within Global Ocean General Circulation Models: A Review, Prog. Oceanogr., 206, 102824, https://doi.org/10.1016/j.pocean.2022.102824, 2022. a
Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC), SEANOE [data set], https://doi.org/10.17882/42182, 2000. a
Banerjee, T., Danilov, S., and Klingbeil, K.: Discrete variance decay analysis of spurious mixing, Ocean Model., accepted, 2024. a
Bendinger, A., Cravatte, S., Gourdeau, L., Brodeau, L., Albert, A., Tchilibou, M., Lyard, F., and Vic, C.: Regional modeling of internal-tide dynamics around New Caledonia – Part 1: Coherent internal-tide characteristics and sea surface height signature, Ocean Sci., 19, 1315–1338, https://doi.org/10.5194/os-19-1315-2023, 2023. a
Berntsen, J., Xing, J., and Davies, A. M.: Numerical Studies of Flow over a Sill: Sensitivity of the Non-Hydrostatic Effects to the Grid Size, Ocean Dynam., 59, 1043–1059, https://doi.org/10.1007/s10236-009-0227-0, 2009. a
Blumberg, A. F. and Mellor, G. L.: A Description of a Three-Dimensional Coastal Ocean Circulation Model, in: Three-Dimensional Coastal Ocean Models, American Geophysical Union (AGU), 1–16, ISBN 978-1-118-66504-6, https://agupubs.onlinelibrary.wiley.com/doi/10.1029/CO004p0001 (last access: 28 August 2024), 1987. a
Bryan, F.: Parameter Sensitivity of Primitive Equation Ocean General Circulation Models, J. Phys. Oceanogr., 17, 970–985, https://doi.org/10.1175/1520-0485(1987)017<0970:PSOPEO>2.0.CO;2, 1987. a
Burchard, H. and Bolding, K.: Comparative Analysis of Four Second-Moment Turbulence Closure Models for the Oceanic Mixed Layer, J. Phys. Oceanogr., 31, 1943–1968, https://doi.org/10.1175/1520-0485(2001)031<1943:CAOFSM>2.0.CO;2, 2001. a
Burchard, H. and Rennau, H.: Comparative Quantification of Physically and Numerically Induced Mixing in Ocean Models, Ocean Model., 20, 293–311, https://doi.org/10.1016/j.ocemod.2007.10.003, 2008. a, b
Castruccio, F. S., Curchitser, E. N., and Kleypas, J. A.: A Model for Quantifying Oceanic Transport and Mesoscale Variability in the Coral Triangle of the Indonesian/Philippines Archipelago, J. Geophys. Res.-Oceans, 118, 6123–6144, https://doi.org/10.1002/2013JC009196, 2013. a
Cushman-Roisin, B. and Beckers, J.-M.: Introduction to Geophysical Fluid Dynamics: Physical and Numerical Aspects, no. v. 101 in International Geophysics Series, 2nd edn., Academic Press, Waltham, MA, ISBN 978-0-12-088759-0, 2011. a
Damien, P., Bosse, A., Testor, P., Marsaleix, P., and Estournel, C.: Modeling Postconvective Submesoscale Coherent Vortices in the Northwestern Mediterranean Sea, J. Geophys. Res.-Oceans, 122, 9937–9961, https://doi.org/10.1002/2016JC012114, 2017. a
Donlon, C. J., Martin, M., Stark, J., Roberts-Jones, J., Fiedler, E., and Wimmer, W.: The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) System, Remote Sens. Environ., 116, 140–158, https://doi.org/10.1016/j.rse.2010.10.017, 2012. a
Dukhovskoy, D. S., Morey, S. L., Martin, P. J., O'Brien, J. J., and Cooper, C.: Application of a Vanishing, Quasi-Sigma, Vertical Coordinate for Simulation of High-Speed, Deep Currents over the Sigsbee Escarpment in the Gulf of Mexico, Ocean Model., 28, 250–265, https://doi.org/10.1016/j.ocemod.2009.02.009, 2009. a
Estournel, C., Marsaleix, P., and Ulses, C.: A New Assessment of the Circulation of Atlantic and Intermediate Waters in the Eastern Mediterranean, Prog. Oceanogr., 198, 102673, https://doi.org/10.1016/j.pocean.2021.102673, 2021. a
E.U. Copernicus Marine Service Information (CMEMS): Global Ocean Physics Reanalysis (GLORYS12V1), Marine Data Store (MDS) [data set], https://doi.org/10.48670/moi-00021, 2023a. a, b
E.U. Copernicus Marine Service Information (CMEMS): Global Ocean OSTIA Sea Surface Temperature and Sea Ice Reprocessed, Marine Data Store (MDS) [data set], https://doi.org/10.48670/moi-00168, 2023b. a
Ffield, A. and Gordon, A. L.: Vertical Mixing in the Indonesian Thermocline, J. Phys. Oceanogr., 22, 184–195, https://doi.org/10.1175/1520-0485(1992)022<0184:VMITIT>2.0.CO;2, 1992. a
Ffield, A. and Gordon, A. L.: Tidal Mixing Signatures in the Indonesian Seas, J. Phys. Oceanogr., 26, 1924–1937, https://doi.org/10.1175/1520-0485(1996)026<1924:TMSITI>2.0.CO;2, 1996. a
Fox-Kemper, B., Adcroft, A., Böning, C. W., Chassignet, E. P., Curchitser, E., Danabasoglu, G., Eden, C., England, M. H., Gerdes, R., Greatbatch, R. J., Griffies, S. M., Hallberg, R. W., Hanert, E., Heimbach, P., Hewitt, H. T., Hill, C. N., Komuro, Y., Legg, S., Le Sommer, J., Masina, S., Marsland, S. J., Penny, S. G., Qiao, F., Ringler, T. D., Treguier, A. M., Tsujino, H., Uotila, P., and Yeager, S. G.: Challenges and Prospects in Ocean Circulation Models, Frontiers in Marine Science, 6, 65, https://doi.org/10.3389/fmars.2019.00065, 2019. a
Garinet, A.: Spurious numerical mixing in a regional configuration of the Symphonie ocean model over the South-East asian Seas (3.1.2 of the Symphonie ocean model.), Zenodo [data set], https://doi.org/10.5281/zenodo.10715502, 2024. a
Gerdes, R., Köberle, C., and Willebrand, J.: The Influence of Numerical Advection Schemes on the Results of Ocean General Circulation Models, Clim. Dynam., 5, 211–226, https://doi.org/10.1007/BF00210006, 1991. a
Gibson, A. H., Hogg, A. M., Kiss, A. E., Shakespeare, C. J., and Adcroft, A.: Attribution of Horizontal and Vertical Contributions to Spurious Mixing in an Arbitrary Lagrangian–Eulerian Ocean Model, Ocean Model., 119, 45–56, https://doi.org/10.1016/j.ocemod.2017.09.008, 2017. a, b, c
Gonzalez, N.: Modélisation Multi-Échelle Du Détroit de Gibraltar et de Son Rôle de Régulateur Du Climat Méditerranéen, PhD thesis, Université de Toulouse, Université Toulouse III – Paul Sabatier, 2023. a
Gonzalez, N., Waldman, R., Sannino, G., Giordani, H., and Somot, S.: Understanding Tidal Mixing at the Strait of Gibraltar: A High-Resolution Model Approach, Prog. Oceanogr., 212, 102980, https://doi.org/10.1016/j.pocean.2023.102980, 2023. a, b
Good, S., Fiedler, E., Mao, C., Martin, M. J., Maycock, A., Reid, R., Roberts-Jones, J., Searle, T., Waters, J., While, J., and Worsfold, M.: The Current Configuration of the OSTIA System for Operational Production of Foundation Sea Surface Temperature and Ice Concentration Analyses, Remote Sens., 12, 720, https://doi.org/10.3390/rs12040720, 2020. a
Gordon, A.: Oceanography of the Indonesian Seas and Their Throughflow, oceanog, 18, 14–27, https://doi.org/10.5670/oceanog.2005.01, 2005. a
Griffies, S. M. and Hallberg, R. W.: Biharmonic Friction with a Smagorinsky-Like Viscosity for Use in Large-Scale Eddy-Permitting Ocean Models, Mon. Weather Rev., 128, 2935–2946, https://doi.org/10.1175/1520-0493(2000)128<2935:BFWASL>2.0.CO;2, 2000. a
Griffies, S. M., Pacanowski, R. C., and Hallberg, R. W.: Spurious Diapycnal Mixing Associated with Advection in a z-Coordinate Ocean Model, Mon. Weather Rev., 128, 538–564, https://doi.org/10.1175/1520-0493(2000)128<0538:SDMAWA>2.0.CO;2, 2000. a, b, c, d
Griffies, S. M., Adcroft, A., and Hallberg, R. W.: A Primer on the Vertical Lagrangian-Remap Method in Ocean Models Based on Finite Volume Generalized Vertical Coordinates, J. Adv. Model. Earth Sy., 12, e2019MS001954, https://doi.org/10.1029/2019MS001954, 2020. a
Hatayama, T., Awaji, T., and Akitomo, K.: Tidal Currents in the Indonesian Seas and Their Effect on Transport and Mixing, J. Geophys. Res.-Oceans, 101, 12353–12373, https://doi.org/10.1029/96JC00036, 1996. a
Hecht, M. W.: Cautionary Tales of Persistent Accumulation of Numerical Error: Dispersive Centered Advection, Ocean Model., 35, 270–276, https://doi.org/10.1016/j.ocemod.2010.07.005, 2010. a
Herrmann, M., To Duy, T., and Estournel, C.: Intraseasonal variability of the South Vietnam upwelling, South China Sea: influence of atmospheric forcing and ocean intrinsic variability, Ocean Sci., 19, 453–467, https://doi.org/10.5194/os-19-453-2023, 2023. a
Holmes, R. M., Zika, J. D., Griffies, S. M., Hogg, A. M., Kiss, A. E., and England, M. H.: The Geography of Numerical Mixing in a Suite of Global Ocean Models, J. Adv. Model. Earth Sy., 13, e2020MS002333, https://doi.org/10.1029/2020MS002333, 2021. a, b, c
Hoyer, S. and Hamman, J.: Xarray: N-D Labeled Arrays and Datasets in Python, Journal of Open Research Software, 5, 10, https://doi.org/10.5334/jors.148, 2017. a
Ilıcak, M., Adcroft, A. J., Griffies, S. M., and Hallberg, R. W.: Spurious Dianeutral Mixing and the Role of Momentum Closure, Ocean Model., 45–46, 37–58, https://doi.org/10.1016/j.ocemod.2011.10.003, 2012. a
Iskandar, M. R., Jia, Y., Sasaki, H., Furue, R., Kida, S., Suga, T., and Richards, K. J.: Effects of High-Frequency Flow Variability on the Pathways of the Indonesian Throughflow, J. Geophys. Res.-Oceans, 128, e2022JC019610, https://doi.org/10.1029/2022JC019610, 2023. a
Jochum, M. and Potemra, J.: Sensitivity of Tropical Rainfall to Banda Sea Diffusivity in the Community Climate System Model, J. Climate, 21, 6445–6454, https://doi.org/10.1175/2008JCLI2230.1, 2008. a
Juricke, S., Danilov, S., Koldunov, N., Oliver, M., Sein, D. V., Sidorenko, D., and Wang, Q.: A Kinematic Kinetic Energy Backscatter Parametrization: From Implementation to Global Ocean Simulations, J. Adv. Model. Earth Sy., 12, e2020MS002175, https://doi.org/10.1029/2020MS002175, 2020a. a, b, c
Juricke, S., Danilov, S., Koldunov, N., Oliver, M., and Sidorenko, D.: Ocean Kinetic Energy Backscatter Parametrization on Unstructured Grids: Impact on Global Eddy-Permitting Simulations, J. Adv. Model. Earth Sy., 12, e2019MS001855, https://doi.org/10.1029/2019MS001855, 2020b. a, b
Katavouta, A., Polton, J. A., Harle, J. D., and Holt, J. T.: Effect of Tides on the Indonesian Seas Circulation and Their Role on the Volume, Heat and Salt Transports of the Indonesian Throughflow, J. Geophys. Res.-Oceans, 127, e2022JC018524, https://doi.org/10.1029/2022JC018524, 2022. a, b, c, d
Kent, J., Whitehead, J. P., Jablonowski, C., and Rood, R. B.: Determining the Effective Resolution of Advection Schemes. Part I: Dispersion Analysis, J. Comput. Phys., 278, 485–496, https://doi.org/10.1016/j.jcp.2014.01.043, 2014. a
Klingbeil, K., Mohammadi-Aragh, M., Gräwe, U., and Burchard, H.: Quantification of Spurious Dissipation and Mixing – Discrete Variance Decay in a Finite-Volume Framework, Ocean Model., 81, 49–64, https://doi.org/10.1016/j.ocemod.2014.06.001, 2014. a
Klingbeil, K., Burchard, H., Danilov, S., Goetz, C., and Iske, A.: Reducing Spurious Diapycnal Mixing in Ocean Models, in: Energy Transfers in Atmosphere and Ocean, edited by Eden, C. and Iske, A., Mathematics of Planet Earth, Springer International Publishing, Cham, 245–286, ISBN 978-3-030-05704-6, https://doi.org/10.1007/978-3-030-05704-6_8, 2019. a
Koch-Larrouy, A., Madec, G., Bouruet-Aubertot, P., Gerkema, T., Bessières, L., and Molcard, R.: On the Transformation of Pacific Water into Indonesian Throughflow Water by Internal Tidal Mixing, Geophys. Res. Lett., 34, L04604, https://doi.org/10.1029/2006GL028405, 2007. a, b, c
Koch-Larrouy, A., Lengaigne, M., Terray, P., Madec, G., and Masson, S.: Tidal Mixing in the Indonesian Seas and Its Effect on the Tropical Climate System, Clim. Dynam., 34, 891–904, https://doi.org/10.1007/s00382-009-0642-4, 2010. a
Kolodziejczyk, N., Hamon, M., Boutin, J., Vergely, J.-L., Reverdin, G., Supply, A., and Reul, N.: Objective Analysis of SMOS and SMAP Sea Surface Salinity to Reduce Large-Scale and Time-Dependent Biases from Low to High Latitudes, J. Atmos. Ocean. Tech., 38, 405–421, https://doi.org/10.1175/JTECH-D-20-0093.1, 2021. a, b
Large, W. G. and Yeager, S.: Diurnal to decadal global forcing for ocean and sea-ice models: The data sets and flux climatologies (No. NCAR/TN-460+STR), University Corporation for Atmospheric Research, https://doi.org/10.5065/D6KK98Q6, 2004. a, b
Leclair, M. and Madec, G.:
Lee, M.-M., Coward, A. C., and Nurser, A. J. G.: Spurious Diapycnal Mixing of the Deep Waters in an Eddy-Permitting Global Ocean Model, J. Phys. Oceanogr., 32, 1522–1535, https://doi.org/10.1175/1520-0485(2002)032<1522:SDMOTD>2.0.CO;2, 2002. a, b
Lemarié, F., Debreu, L., Madec, G., Demange, J., Molines, J. M., and Honnorat, M.: Stability Constraints for Oceanic Numerical Models: Implications for the Formulation of Time and Space Discretizations, Ocean Model., 92, 124–148, https://doi.org/10.1016/j.ocemod.2015.06.006, 2015. a
Leonard, B. P.: A Stable and Accurate Convective Modelling Procedure Based on Quadratic Upstream Interpolation, Comput. Method. Appl. M., 19, 59–98, https://doi.org/10.1016/0045-7825(79)90034-3, 1979. a
Lyard, F. H., Allain, D. J., Cancet, M., Carrère, L., and Picot, N.: FES2014 global ocean tide atlas: design and performance, Ocean Sci., 17, 615–649, https://doi.org/10.5194/os-17-615-2021, 2021. a
Madec, G., Bourdallé-Badie, R., Chanut, J., Clementi, E., Coward, A., Ethé, C., Iovino, D., Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S., Mocavero, S., Rousset, C., Storkey, D., Müeller, S., Nurser, G., Bell, M., Samson, G., Mathiot, P., Mele, F., and Moulin, A.: NEMO Ocean Engine, Tech. Rep., Zenodo, https://doi.org/10.5281/zenodo.1472492, 2022. a
Marchesiello, P., Debreu, L., and Couvelard, X.: Spurious Diapycnal Mixing in Terrain-Following Coordinate Models: The Problem and a Solution, Ocean Model., 26, 156–169, https://doi.org/10.1016/j.ocemod.2008.09.004, 2009. a, b
Megann, A.: Estimating the Numerical Diapycnal Mixing in an Eddy-Permitting Ocean Model, Ocean Model., 121, 19–33, https://doi.org/10.1016/j.ocemod.2017.11.001, 2018. a, b
Megann, A.: Quantifying Numerical Mixing in a Tidally Forced Global Eddy-Permitting Ocean Model, Ocean Model., 188, 102329, https://doi.org/10.1016/j.ocemod.2024.102329, 2024. a
Megann, A., Chanut, J., and Storkey, D.: Assessment of the z∼ Time-Filtered Arbitrary Lagrangian-Eulerian Coordinate in a Global Eddy-Permitting Ocean Model, J. Adv. Model. Earth Sy., 14, e2022MS003056, https://doi.org/10.1029/2022MS003056, 2022. a, b
Meredith, M. and Naveira Garabato, A.: Ocean Mixing, Elsevier, ISBN 978-0-12-821512-8, https://doi.org/10.1016/C2019-0-03674-6, 2022. a
Nagai, T. and Hibiya, T.: Combined Effects of Tidal Mixing in Narrow Straits and the Ekman Transport on the Sea Surface Temperature Cooling in the Southern Indonesian Seas, J. Geophys. Res.-Oceans, 125, e2020JC016314, https://doi.org/10.1029/2020JC016314, 2020. a
Nagai, T., Hibiya, T., and Syamsudin, F.: Direct Estimates of Turbulent Mixing in the Indonesian Archipelago and Its Role in the Transformation of the Indonesian Throughflow Waters, Geophys. Res. Lett., 48, e2020GL091731, https://doi.org/10.1029/2020GL091731, 2021. a
Nguyen-Duy, T., Ayoub, N. K., Marsaleix, P., Toublanc, F., De Mey-Frémaux, P., Piton, V., Herrmann, M., Duhaut, T., Tran, M. C., and Ngo-Duc, T.: Variability of the Red River Plume in the Gulf of Tonkin as Revealed by Numerical Modeling and Clustering Analysis, Front. Mar. Sci., 8, 772139, https://doi.org/10.3389/fmars.2021.772139, 2021. a, b
Niwa, Y. and Hibiya, T.: Estimation of Baroclinic Tide Energy Available for Deep Ocean Mixing Based on Three-Dimensional Global Numerical Simulations, J. Oceanogr., 67, 493–502, https://doi.org/10.1007/s10872-011-0052-1, 2011. a
Nugroho, D.: La Marée Dans Un Modèle de Circulation Générale Dans Les Mers Indonésiennes, PhD thesis, Université de Toulouse, Université Toulouse III – Paul Sabatier, 2017. a
Nugroho, D., Koch-Larrouy, A., Gaspar, P., Lyard, F., Reffray, G., and Tranchant, B.: Modelling Explicit Tides in the Indonesian Seas: An Important Process for Surface Sea Water Properties, Mar. Pollut. Bull., 131, 7–18, https://doi.org/10.1016/j.marpolbul.2017.06.033, 2018. a, b
Piton, V., Herrmann, M., Marsaleix, P., Duhaut, T., Ngoc, T. B., Tran, M. C., Shearman, K., and Ouillon, S.: Influence of Winds, Geostrophy and Typhoons on the Seasonal Variability of the Circulation in the Gulf of Tonkin: A High-Resolution 3D Regional Modeling Study, Regional Studies in Marine Science, 45, 101849, https://doi.org/10.1016/j.rsma.2021.101849, 2021. a
Polzin, K. L., Toole, J. M., Ledwell, J. R., and Schmitt, R. W.: Spatial Variability of Turbulent Mixing in the Abyssal Ocean, Science, 276, 93–96, https://doi.org/10.1126/science.276.5309.93, 1997. a
Purwandana, A., Cuypers, Y., Bouruet-Aubertot, P., Nagai, T., Hibiya, T., and Atmadipoera, A. S.: Spatial Structure of Turbulent Mixing Inferred from Historical CTD Datasets in the Indonesian Seas, Prog. Oceanogr., 184, 102312, https://doi.org/10.1016/j.pocean.2020.102312, 2020. a
Ray, R. D. and Susanto, R. D.: Tidal Mixing Signatures in the Indonesian Seas from High-Resolution Sea Surface Temperature Data, Geophys. Res. Lett., 43, 8115–8123, https://doi.org/10.1002/2016GL069485, 2016. a
Rougier, N. P.: Scientific Visualization: Python + Matplotlib, https://hal.science/hal-03427242v1 (last access: 19 August 2024), 2021. a
Sanderson, B. G.: Order and Resolution for Computational Ocean Dynamics, J. Phys. Oceanogr., 28, 1271–1286, https://doi.org/10.1175/1520-0485(1998)028<1271:OARFCO>2.0.CO;2, 1998. a
Sasaki, H., Kida, S., Furue, R., Nonaka, M., and Masumoto, Y.: An Increase of the Indonesian Throughflow by Internal Tidal Mixing in a High-Resolution Quasi-Global Ocean Simulation, Geophys. Res. Lett., 45, 8416–8424, https://doi.org/10.1029/2018GL078040, 2018. a
Siegelman, L., Klein, P., Rivière, P., Thompson, A. F., Torres, H. S., Flexas, M., and Menemenlis, D.: Enhanced Upward Heat Transport at Deep Submesoscale Ocean Fronts, Nat. Geosci., 13, 50–55, https://doi.org/10.1038/s41561-019-0489-1, 2020. a
Soufflet, Y., Marchesiello, P., Lemarié, F., Jouanno, J., Capet, X., Debreu, L., and Benshila, R.: On Effective Resolution in Ocean Models, Ocean Model., 98, 36–50, https://doi.org/10.1016/j.ocemod.2015.12.004, 2016. a, b
Sprintall, J., Gordon, A. L., Wijffels, S. E., Feng, M., Hu, S., Koch-Larrouy, A., Phillips, H., Nugroho, D., Napitu, A., Pujiana, K., Susanto, R. D., Sloyan, B., Peña-Molino, B., Yuan, D., Riama, N. F., Siswanto, S., Kuswardani, A., Arifin, Z., Wahyudi, A. J., Zhou, H., Nagai, T., Ansong, J. K., Bourdalle-Badié, R., Chanut, J., Lyard, F., Arbic, B. K., Ramdhani, A., and Setiawan, A.: Detecting Change in the Indonesian Seas, Front. Mar. Sci., 6, 257, https://doi.org/10.3389/fmars.2019.00257, 2019. a, b, c
Susanto, R. D. and Ray, R. D.: Seasonal and Interannual Variability of Tidal Mixing Signatures in Indonesian Seas from High-Resolution Sea Surface Temperature, Remote Sensing, 14, 1934, https://doi.org/10.3390/rs14081934, 2022. a
Thakur, R., Arbic, B. K., Menemenlis, D., Momeni, K., Pan, Y., Peltier, W. R., Skitka, J., Alford, M. H., and Ma, Y.: Impact of Vertical Mixing Parameterizations on Internal Gravity Wave Spectra in Regional Ocean Models, Geophys. Res. Lett., 49, e2022GL099614, https://doi.org/10.1029/2022GL099614, 2022. a
To Duy, T., Herrmann, M., Estournel, C., Marsaleix, P., Duhaut, T., Bui Hong, L., and Trinh Bich, N.: The role of wind, mesoscale dynamics, and coastal circulation in the interannual variability of the South Vietnam Upwelling, South China Sea – answers from a high-resolution ocean model, Ocean Sci., 18, 1131–1161, https://doi.org/10.5194/os-18-1131-2022, 2022. a, b
Tranchant, B., Reffray, G., Greiner, E., Nugroho, D., Koch-Larrouy, A., and Gaspar, P.: Evaluation of an operational ocean model configuration at
Trinh, N. B., Herrmann, M., Ulses, C., Marsaleix, P., Duhaut, T., To Duy, T., Estournel, C., and Shearman, R. K.: New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4, Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, 2024. a
Webb, D. J., de Cuevas, B. A., and Richmond, C. S.: Improved Advection Schemes for Ocean Models, J. Atmos. Ocean. Tech., 15, 1171–1187, https://doi.org/10.1175/1520-0426(1998)015<1171:IASFOM>2.0.CO;2, 1998. a, b, c
Winther, N. G., Morel, Y. G., and Evensen, G.: Efficiency of High Order Numerical Schemes for Momentum Advection, J. Marine Syst., 67, 31–46, https://doi.org/10.1016/j.jmarsys.2006.08.004, 2007. a, b
Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., André, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbéoch, M., Ignaszewski, M., Baringer, M. O., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouët, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourlès, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P.-Y., Rannou, J.-P., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P.-M., Vélez-Belchí, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S.-D., and Park, H.-M.: Argo Data 1999–2019: Two Million Temperature-Salinity Profiles and Subsurface Velocity Observations From a Global Array of Profiling Floats, Front. Mar. Sci., 7, 700, https://doi.org/10.3389/fmars.2020.00700, 2020. a
Wunsch, C. and Ferrari, R.: Vertical Mixing, Energy, and the General Circulation of the Oceans, Ann. Rev. Fluid Mech., 36, 281–314, https://doi.org/10.1146/annurev.fluid.36.050802.122121, 2004. a
Zalesak, S. T.: Fully Multidimensional Flux-Corrected Transport Algorithms for Fluids, J. Comput. Phys., 31, 335–362, https://doi.org/10.1016/0021-9991(79)90051-2, 1979. a
Zaron, E. D.: Baroclinic Tidal Sea Level from Exact-Repeat Mission Altimetry, J. Phys. Oceanogr., 49, 193–210, https://doi.org/10.1175/JPO-D-18-0127.1, 2019. a
Short summary
Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations...
