Articles | Volume 16, issue 5
https://doi.org/10.5194/gmd-16-1481-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-16-1481-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review and perspective paper
| Highlight paper
| 
09 Mar 2023
Review and perspective paper | Highlight paper |
| 09 Mar 2023
| 09 Mar 2023
Reproducible and relocatable regional ocean modelling: fundamentals and practices
Marine System Modelling, National Oceanography Centre, Liverpool, UK
James Harle
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Jason Holt
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Anna Katavouta
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Dale Partridge
Plymouth Marine Laboratory, Plymouth, UK
Jenny Jardine
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Sarah Wakelin
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Julia Rulent
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Anthony Wise
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Katherine Hutchinson
Laboratoire LOCEAN/IPSL, Paris, France
David Byrne
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Diego Bruciaferri
Met Office, Exeter, UK
Enda O'Dea
Met Office, Exeter, UK
Michela De Dominicis
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Pierre Mathiot
Institut des Géosciences et de l’Environnement, University Grenoble Alpes/CNRS/IRD/G-INP, Grenoble, France
Andrew Coward
Marine System Modelling, National Oceanography Centre, Southampton, UK
Andrew Yool
Marine System Modelling, National Oceanography Centre, Southampton, UK
Julien Palmiéri
Marine System Modelling, National Oceanography Centre, Southampton, UK
Gennadi Lessin
Plymouth Marine Laboratory, Plymouth, UK
Claudia Gabriela Mayorga-Adame
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Valérie Le Guennec
Marine System Modelling, National Oceanography Centre, Liverpool, UK
Institute of Mathematical Sciences, Pusan National University, Busan, South Korea
Alex Arnold
Met Office, Exeter, UK
Clément Rousset
Laboratoire LOCEAN/IPSL, Paris, France
Related authors
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
Short summary
Short summary
Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Juan Manuel Castillo, Huw W. Lewis, Akhilesh Mishra, Ashis Mitra, Jeff Polton, Ashley Brereton, Andrew Saulter, Alex Arnold, Segolene Berthou, Douglas Clark, Julia Crook, Ananda Das, John Edwards, Xiangbo Feng, Ankur Gupta, Sudheer Joseph, Nicholas Klingaman, Imranali Momin, Christine Pequignet, Claudio Sanchez, Jennifer Saxby, and Maria Valdivieso da Costa
Geosci. Model Dev., 15, 4193–4223, https://doi.org/10.5194/gmd-15-4193-2022, https://doi.org/10.5194/gmd-15-4193-2022, 2022
Short summary
Short summary
A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land, and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air–sea coupling is included.
Marina Tonani, Peter Sykes, Robert R. King, Niall McConnell, Anne-Christine Péquignet, Enda O'Dea, Jennifer A. Graham, Jeff Polton, and John Siddorn
Ocean Sci., 15, 1133–1158, https://doi.org/10.5194/os-15-1133-2019, https://doi.org/10.5194/os-15-1133-2019, 2019
Short summary
Short summary
A new high-resolution ocean model at 1.5 km has replaced the 7 km system for delivering short-term forecasts of the North-West European Shelf seas. The products (temperature, salinity, currents, and sea surface height) are available on the Copernicus Marine Service catalogue. This study focuses on the high-resolution impact on the quality of the products delivered to the users. Results show that the high-resolution model is better at resolving the variability of the physical variables.
Jennifer A. Graham, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame
Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, https://doi.org/10.5194/gmd-11-681-2018, 2018
Short summary
Short summary
This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15 (Atlantic Margin Model, 1.5 km resolution). The current forecast system has a resolution of 7 km. While this is sufficient to represent large-scale circulation, many dynamical features (such as eddies, frontal jets, and internal tides) can only begin to be resolved at 0–1 km resolution. Here we introduce AMM15 and demonstrate its ability to represent the mean state and variability of the region.
Jozef Skákala, David Ford, Keith Haines, Amos Lawless, Matthew J. Martin, Philip Browne, Marcin Chrust, Stefano Ciavatta, Alison Fowler, Daniel Lea, Matthew Palmer, Andrea Rochner, Jennifer Waters, Hao Zuo, Deep S. Banerjee, Mike Bell, Davi M. Carneiro, Yumeng Chen, Susan Kay, Dale Partridge, Martin Price, Richard Renshaw, Georgy Shapiro, and James While
Ocean Sci., 21, 1709–1734, https://doi.org/10.5194/os-21-1709-2025, https://doi.org/10.5194/os-21-1709-2025, 2025
Short summary
Short summary
UK marine data assimilation (MDA) involves a closely collaborating research community. In this paper, we offer both an overview of the state of the art and a vision for the future across all of the main areas of UK MDA, ranging from physics to biogeochemistry to coupled DA. We discuss the current UK MDA stakeholder applications, highlight theoretical developments needed to advance our systems, and reflect upon upcoming opportunities with respect to hardware and observational missions.
Adrian Peter Martin, Noelie Benoist, Brian Bett, Anieke Brombacher, Jennifer Durden, Sophy Oliver, and Andrew Yool
EGUsphere, https://doi.org/10.5194/egusphere-2025-2180, https://doi.org/10.5194/egusphere-2025-2180, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Although seemingly inhospitable, under huge pressure and with permanent darkness, the seafloor has a diversity of organisms. They are almost entirely dependent on food sinking down through the ocean onto the seafloor. This model allows us to study how these organisms survive in this hostile environment. Making use of evidence that biological characteristics, like lifetime, vary with size and temperature, this model can simulate the fate of seafloor creatures from bacteria to large sea cucumbers.
Dale Partridge, Deep Banerjee, David Ford, Ke Wang, Jozef Skakala, Juliane Wihsgott, Prathyush Menon, Susan Kay, Daniel Clewley, Andrea Rochner, Emma Sullivan, and Matthew Palmer
EGUsphere, https://doi.org/10.5194/egusphere-2025-3346, https://doi.org/10.5194/egusphere-2025-3346, 2025
This preprint is open for discussion and under review for Ocean Science (OS).
Short summary
Short summary
This study outlines the development and testing of a Digital Twin Ocean (DTO) framework, aimed at improving coastal ocean forecasts through the use of autonomous underwater gliders. A fleet of gliders were deployed in the western English Channel during August–September 2024 to collect measurements of temperature, salinity, chlorophyll and oxygen, aiming to track the movement of the harmful algal bloom Karenia mikimotoi.
Samantha Siedlecki, Stanley Nmor, Gennadi Lessin, Kelly Kearney, Subhadeep Rakshit, Colleen Petrik, Jessica Luo, Cristina Schultz, Dalton Sasaki, Kayla Gillen, Anh Pham, Christopher Somes, Damian Brady, Jeremy Testa, Christophe Rabouille, Isa Elegbede, and Olivier Sulpis
EGUsphere, https://doi.org/10.5194/egusphere-2025-1846, https://doi.org/10.5194/egusphere-2025-1846, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
Benthic biogeochemical models are essential for simulating seafloor carbon cycling and climate feedbacks, yet vary widely in structure and assumptions. This paper introduces SedBGC_MIP, a community initiative to compare existing models, refine key processes, and assess uncertainty. We highlight discrepancies through case studies and introduce needs including observational benchmarks. Ultimately, we seek to improve climate and resource projections.
Robert J. Wilson, Yuri Artioli, Giovanni Galli, James Harle, Jason Holt, Ana M. Queirós, and Sarah Wakelin
Ocean Sci., 21, 1255–1270, https://doi.org/10.5194/os-21-1255-2025, https://doi.org/10.5194/os-21-1255-2025, 2025
Short summary
Short summary
Marine heatwaves are of growing concern around the world. We use a state-of-the-art ensemble of downscaled climate models to project how often heatwaves will occur in the future across northwestern Europe under a high-emission scenario. The projections show that, without emission reductions, heatwaves will occur more than half of the time in the future. We show that the seafloor is expected to experience much more frequent heatwaves than the sea surface in the future.
Yavor Kostov, Paul R. Holland, Kelly A. Hogan, James A. Smith, Nicolas C. Jourdain, Pierre Mathiot, Anna Olivé Abelló, Andrew H. Fleming, and Andrew J. S. Meijers
EGUsphere, https://doi.org/10.5194/egusphere-2025-2423, https://doi.org/10.5194/egusphere-2025-2423, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Icebergs ground when they reach shallow topography such as Bear Ridge in the Amundsen Sea. Grounded icebergs can block the transport of sea-ice and create areas of higher and lower sea-ice concentration. We introduce a physically and observationally motivated representation of grounding in an ocean model. In addition, we improve the way simulated icebergs respond to winds, ocean currents, and density differences in sea water. We analyse the forces acting on freely floating and grounded icebergs.
Claire K. Yung, Xylar S. Asay-Davis, Alistair Adcroft, Christopher Y. S. Bull, Jan De Rydt, Michael S. Dinniman, Benjamin K. Galton-Fenzi, Daniel Goldberg, David E. Gwyther, Robert Hallberg, Matthew Harrison, Tore Hattermann, David M. Holland, Denise Holland, Paul R. Holland, James R. Jordan, Nicolas C. Jourdain, Kazuya Kusahara, Gustavo Marques, Pierre Mathiot, Dimitris Menemenlis, Adele K. Morrison, Yoshihiro Nakayama, Olga Sergienko, Robin S. Smith, Alon Stern, Ralph Timmermann, and Qin Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2025-1942, https://doi.org/10.5194/egusphere-2025-1942, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
ISOMIP+ compares 12 ocean models that simulate ice-ocean interactions in a common, idealised, static ice shelf cavity setup, aiming to assess and understand inter-model variability. Models simulate similar basal melt rate patterns, ocean profiles and circulation but differ in ice-ocean boundary layer properties and spatial distributions of melting. Ice-ocean boundary layer representation is a key area for future work, as are realistic-domain ice sheet-ocean model intercomparisons.
Yushi Morioka, Eric Maisonnave, Sébastien Masson, Clement Rousset, Luis Kornblueh, Marco Giorgetta, Masami Nonaka, and Swadhin K. Behera
EGUsphere, https://doi.org/10.5194/egusphere-2025-2258, https://doi.org/10.5194/egusphere-2025-2258, 2025
Short summary
Short summary
Ocean mesoscale eddies, which have a horizontal scale with an order of 100 km, play a prominent role in global ocean heat transport that regulates Earth climate. Here we newly develop an eddy-permitting climate model to demonstrate that the increased ocean model resolution improves representation of air-sea interaction in the western and eastern boundary current regions, while the improved sea ice model physics benefit realistic simulation of sea ice variability.
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.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Justine Caillet, Nicolas C. Jourdain, Pierre Mathiot, Fabien Gillet-Chaulet, Benoit Urruty, Clara Burgard, Charles Amory, Mondher Chekki, and Christoph Kittel
Earth Syst. Dynam., 16, 293–315, https://doi.org/10.5194/esd-16-293-2025, https://doi.org/10.5194/esd-16-293-2025, 2025
Short summary
Short summary
Internal climate variability, resulting from processes intrinsic to the climate system, modulates the Antarctic response to climate change by delaying or offsetting its effects. Using climate and ice-sheet models, we highlight that irreducible internal climate variability significantly enlarges the likely range of Antarctic contribution to sea-level rise until 2100. Thus, we recommend considering internal climate variability as a source of uncertainty for future ice-sheet projections.
David A. Stappard, Jamie D. Wilson, Andrew Yool, and Toby Tyrrell
EGUsphere, https://doi.org/10.5194/egusphere-2025-436, https://doi.org/10.5194/egusphere-2025-436, 2025
Short summary
Short summary
This research explores nutrient limitations in oceanic primary production. While traditional experiments identify the immediate limiting nutrient at specific locations, this study aims to identify the ultimate limiting nutrient (ULN), which governs long-term productivity. A mathematical model incorporating nitrogen, phosphorus, and iron nutrient cycles is used. The model's results are compared with ocean observational data to assess its effectiveness in investigating the ULN.
Théo Brivoal, Virginie Guemas, Martin Vancoppenolle, Clément Rousset, and Bertrand Decharme
EGUsphere, https://doi.org/10.5194/egusphere-2024-3220, https://doi.org/10.5194/egusphere-2024-3220, 2025
Short summary
Short summary
Snow in polar regions is key to sea ice formation and the Earth's climate, but current climate models simplify snow cover on sea ice. This study integrates an intermediate complexity snow-physics scheme into a sea-ice model designed for climate applications. We show that modelling the temporal changes in properties such as the density and thermal conductivity of the snow layers leads to a more accurate representation of heat transfer between the underlying sea ice and the atmosphere.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
Short summary
Short summary
The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Alex T. Archibald, Bablu Sinha, Maria R. Russo, Emily Matthews, Freya A. Squires, N. Luke Abraham, Stephane J.-B. Bauguitte, Thomas J. Bannan, Thomas G. Bell, David Berry, Lucy J. Carpenter, Hugh Coe, Andrew Coward, Peter Edwards, Daniel Feltham, Dwayne Heard, Jim Hopkins, James Keeble, Elizabeth C. Kent, Brian A. King, Isobel R. Lawrence, James Lee, Claire R. Macintosh, Alex Megann, Bengamin I. Moat, Katie Read, Chris Reed, Malcolm J. Roberts, Reinhard Schiemann, David Schroeder, Timothy J. Smyth, Loren Temple, Navaneeth Thamban, Lisa Whalley, Simon Williams, Huihui Wu, and Mingxi Yang
Earth Syst. Sci. Data, 17, 135–164, https://doi.org/10.5194/essd-17-135-2025, https://doi.org/10.5194/essd-17-135-2025, 2025
Short summary
Short summary
Here, we present an overview of the data generated as part of the North Atlantic Climate System Integrated Study (ACSIS) programme that are available through dedicated repositories at the Centre for Environmental Data Analysis (CEDA; www.ceda.ac.uk) and the British Oceanographic Data Centre (BODC; bodc.ac.uk). The datasets described here cover the North Atlantic Ocean, the atmosphere above (it including its composition), and Arctic sea ice.
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.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
Short summary
Short summary
This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Giovanni Galli, Sarah Wakelin, James Harle, Jason Holt, and Yuri Artioli
Biogeosciences, 21, 2143–2158, https://doi.org/10.5194/bg-21-2143-2024, https://doi.org/10.5194/bg-21-2143-2024, 2024
Short summary
Short summary
This work shows that, under a high-emission scenario, oxygen concentration in deep water of parts of the North Sea and Celtic Sea can become critically low (hypoxia) towards the end of this century. The extent and frequency of hypoxia depends on the intensity of climate change projected by different climate models. This is the result of a complex combination of factors like warming, increase in stratification, changes in the currents and changes in biological processes.
Hannah Chawner, Eric Saboya, Karina E. Adcock, Tim Arnold, Yuri Artioli, Caroline Dylag, Grant L. Forster, Anita Ganesan, Heather Graven, Gennadi Lessin, Peter Levy, Ingrid T. Luijkx, Alistair Manning, Penelope A. Pickers, Chris Rennick, Christian Rödenbeck, and Matthew Rigby
Atmos. Chem. Phys., 24, 4231–4252, https://doi.org/10.5194/acp-24-4231-2024, https://doi.org/10.5194/acp-24-4231-2024, 2024
Short summary
Short summary
The quantity of atmospheric potential oxygen (APO), derived from coincident measurements of carbon dioxide (CO2) and oxygen (O2), has been proposed as a tracer for fossil fuel CO2 emissions. In this model sensitivity study, we examine the use of APO for this purpose in the UK and compare our model to observations. We find that our model simulations are most sensitive to uncertainties relating to ocean fluxes and boundary conditions.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jerry C. Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
Earth Syst. Dynam., 14, 1295–1315, https://doi.org/10.5194/esd-14-1295-2023, https://doi.org/10.5194/esd-14-1295-2023, 2023
Short summary
Short summary
We investigate the flux of carbon from the atmosphere into the land surface and ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same change in the global-mean near-surface temperature. Using this method, we show that the choice of scenario can impact the carbon allocation to the land, ocean, and atmosphere. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
Pierre Mathiot and Nicolas C. Jourdain
Ocean Sci., 19, 1595–1615, https://doi.org/10.5194/os-19-1595-2023, https://doi.org/10.5194/os-19-1595-2023, 2023
Short summary
Short summary
How much the Antarctic ice shelf basal melt rate can increase in response to global warming remains an open question. To achieve this, we compared an ocean simulation under present-day atmospheric condition to a one under late 23rd century atmospheric conditions. The ocean response to the perturbation includes a decrease in the production of cold dense water and an increased intrusion of warmer water onto the continental shelves. This induces a substantial increase in ice shelf basal melt rates.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Revised manuscript not accepted
Short summary
Short summary
For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
Short summary
Short summary
Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
Short summary
Short summary
Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Katherine E. Turner, Doug M. Smith, Anna Katavouta, and Richard G. Williams
Biogeosciences, 20, 1671–1690, https://doi.org/10.5194/bg-20-1671-2023, https://doi.org/10.5194/bg-20-1671-2023, 2023
Short summary
Short summary
We present a new method for reconstructing ocean carbon using climate models and temperature and salinity observations. To test this method, we reconstruct modelled carbon using synthetic observations consistent with current sampling programmes. Sensitivity tests show skill in reconstructing carbon trends and variability within the upper 2000 m. Our results indicate that this method can be used for a new global estimate for ocean carbon content.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
Short summary
Short summary
Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Jane P. Mulcahy, Colin G. Jones, Steven T. Rumbold, Till Kuhlbrodt, Andrea J. Dittus, Edward W. Blockley, Andrew Yool, Jeremy Walton, Catherine Hardacre, Timothy Andrews, Alejandro Bodas-Salcedo, Marc Stringer, Lee de Mora, Phil Harris, Richard Hill, Doug Kelley, Eddy Robertson, and Yongming Tang
Geosci. Model Dev., 16, 1569–1600, https://doi.org/10.5194/gmd-16-1569-2023, https://doi.org/10.5194/gmd-16-1569-2023, 2023
Short summary
Short summary
Recent global climate models simulate historical global mean surface temperatures which are too cold, possibly to due to excessive aerosol cooling. This raises questions about the models' ability to simulate important climate processes and reduces confidence in future climate predictions. We present a new version of the UK Earth System Model, which has an improved aerosols simulation and a historical temperature record. Interestingly, the long-term response to CO2 remains largely unchanged.
Clara Burgard, Nicolas C. Jourdain, Ronja Reese, Adrian Jenkins, and Pierre Mathiot
The Cryosphere, 16, 4931–4975, https://doi.org/10.5194/tc-16-4931-2022, https://doi.org/10.5194/tc-16-4931-2022, 2022
Short summary
Short summary
The ocean-induced melt at the base of the floating ice shelves around Antarctica is one of the largest uncertainty factors in the Antarctic contribution to future sea-level rise. We assess the performance of several existing parameterisations in simulating basal melt rates on a circum-Antarctic scale, using an ocean simulation resolving the cavities below the shelves as our reference. We find that the simple quadratic slope-independent and plume parameterisations yield the best compromise.
Diego Bruciaferri, Marina Tonani, Isabella Ascione, Fahad Al Senafi, Enda O'Dea, Helene T. Hewitt, and Andrew Saulter
Geosci. Model Dev., 15, 8705–8730, https://doi.org/10.5194/gmd-15-8705-2022, https://doi.org/10.5194/gmd-15-8705-2022, 2022
Short summary
Short summary
More accurate predictions of the Gulf's ocean dynamics are needed. We investigate the impact on the predictive skills of a numerical shelf sea model of the Gulf after changing a few key aspects. Increasing the lateral and vertical resolution and optimising the vertical coordinate system to best represent the leading physical processes at stake significantly improve the accuracy of the simulated dynamics. Additional work may be needed to get real benefit from using a more realistic bathymetry.
Stephanie Woodward, Alistair A. Sellar, Yongming Tang, Marc Stringer, Andrew Yool, Eddy Robertson, and Andy Wiltshire
Atmos. Chem. Phys., 22, 14503–14528, https://doi.org/10.5194/acp-22-14503-2022, https://doi.org/10.5194/acp-22-14503-2022, 2022
Short summary
Short summary
We describe the dust scheme in the UKESM1 Earth system model and show generally good agreement with observations. Comparing with the closely related HadGEM3-GC3.1 model, we show that dust differences are not only due to inter-model differences but also to the dust size distribution. Under climate change, HadGEM3-GC3.1 dust hardly changes, but UKESM1 dust decreases because that model includes the vegetation response which, in our models, has a bigger impact on dust than climate change itself.
Yona Silvy, Clément Rousset, Eric Guilyardi, Jean-Baptiste Sallée, Juliette Mignot, Christian Ethé, and Gurvan Madec
Geosci. Model Dev., 15, 7683–7713, https://doi.org/10.5194/gmd-15-7683-2022, https://doi.org/10.5194/gmd-15-7683-2022, 2022
Short summary
Short summary
A modeling framework is introduced to understand and decompose the mechanisms causing the ocean temperature, salinity and circulation to change since the pre-industrial period and into 21st century scenarios of global warming. This framework aims to look at the response to changes in the winds and in heat and freshwater exchanges at the ocean interface in global climate models, throughout the 1850–2100 period, to unravel their individual effects on the changing physical structure of the ocean.
Antony Siahaan, Robin S. Smith, Paul R. Holland, Adrian Jenkins, Jonathan M. Gregory, Victoria Lee, Pierre Mathiot, Antony J. Payne, Jeff K. Ridley, and Colin G. Jones
The Cryosphere, 16, 4053–4086, https://doi.org/10.5194/tc-16-4053-2022, https://doi.org/10.5194/tc-16-4053-2022, 2022
Short summary
Short summary
The UK Earth System Model is the first to fully include interactions of the atmosphere and ocean with the Antarctic Ice Sheet. Under the low-greenhouse-gas SSP1–1.9 (Shared Socioeconomic Pathway) scenario, the ice sheet remains stable over the 21st century. Under the strong-greenhouse-gas SSP5–8.5 scenario, the model predicts strong increases in melting of large ice shelves and snow accumulation on the surface. The dominance of accumulation leads to a sea level fall at the end of the century.
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022, https://doi.org/10.5194/esd-13-1097-2022, 2022
Short summary
Short summary
The El Niño–Southern Oscillation is the main driver for the natural variability of global atmospheric CO2. It modulates the CO2 fluxes in the tropical Pacific with anomalous CO2 influx during El Niño and outflux during La Niña. This relationship is projected to reverse by half of Earth system models studied here under the business-as-usual scenario. This study shows models that simulate a positive bias in surface carbonate concentrations simulate a shift in the ENSO–CO2 flux relationship.
Juan Manuel Castillo, Huw W. Lewis, Akhilesh Mishra, Ashis Mitra, Jeff Polton, Ashley Brereton, Andrew Saulter, Alex Arnold, Segolene Berthou, Douglas Clark, Julia Crook, Ananda Das, John Edwards, Xiangbo Feng, Ankur Gupta, Sudheer Joseph, Nicholas Klingaman, Imranali Momin, Christine Pequignet, Claudio Sanchez, Jennifer Saxby, and Maria Valdivieso da Costa
Geosci. Model Dev., 15, 4193–4223, https://doi.org/10.5194/gmd-15-4193-2022, https://doi.org/10.5194/gmd-15-4193-2022, 2022
Short summary
Short summary
A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land, and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air–sea coupling is included.
Matthew Clark, Robert Marsh, and James Harle
Ocean Sci., 18, 549–564, https://doi.org/10.5194/os-18-549-2022, https://doi.org/10.5194/os-18-549-2022, 2022
Short summary
Short summary
The European Slope Current (SC) is a northward-flowing current running parallel to the UK coastline. It is forced by changes in the density gradient of the wider North Atlantic Ocean. As the North Atlantic has warmed since the late 1990s, these gradients have changed strength and moved, reducing the volume and speed of water feeding into the SC. The SC flows into the North Sea, where changes in the species distribution of some plankton and fish have been seen due to the warming inputs.
Reint Fischer, Delphine Lobelle, Merel Kooi, Albert Koelmans, Victor Onink, Charlotte Laufkötter, Linda Amaral-Zettler, Andrew Yool, and Erik van Sebille
Biogeosciences, 19, 2211–2234, https://doi.org/10.5194/bg-19-2211-2022, https://doi.org/10.5194/bg-19-2211-2022, 2022
Short summary
Short summary
Since current estimates show that only about 1 % of the all plastic that enters the ocean is floating at the surface, we look at subsurface processes that can cause vertical movement of (micro)plastic. We investigate how modelled algal attachment and the ocean's vertical movement can cause particles to sink and oscillate in the open ocean. Particles can sink to depths of > 5000 m in regions with high wind intensity and mainly remain close to the surface with low winds and biological activity.
Darren R. Clark, Andrew P. Rees, Charissa M. Ferrera, Lisa Al-Moosawi, Paul J. Somerfield, Carolyn Harris, Graham D. Quartly, Stephen Goult, Glen Tarran, and Gennadi Lessin
Biogeosciences, 19, 1355–1376, https://doi.org/10.5194/bg-19-1355-2022, https://doi.org/10.5194/bg-19-1355-2022, 2022
Short summary
Short summary
Measurements of microbial processes were made in the sunlit open ocean during a research cruise (AMT19) between the UK and Chile. These help us to understand how microbial communities maintain the function of remote ecosystems. We find that the nitrogen cycling microbes which produce nitrite respond to changes in the environment. Our insights will aid the development of models that aim to replicate and ultimately project how marine environments may respond to ongoing climate change.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
Short summary
Short summary
We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
Julia Rulent, Lucy M. Bricheno, J. A. Mattias Green, Ivan D. Haigh, and Huw Lewis
Nat. Hazards Earth Syst. Sci., 21, 3339–3351, https://doi.org/10.5194/nhess-21-3339-2021, https://doi.org/10.5194/nhess-21-3339-2021, 2021
Short summary
Short summary
High coastal total water levels (TWLs) can lead to flooding and hazardous conditions for coastal communities and environment. In this research we are using numerical models to study the interactions between the three main components of the TWL (waves, tides, and surges) on UK and Irish coasts during winter 2013/14. The main finding of this research is that extreme waves and surges can indeed happen together, even at high tide, but they often occurred simultaneously 2–3 h before high tide.
Josué Bock, Martine Michou, Pierre Nabat, Manabu Abe, Jane P. Mulcahy, Dirk J. L. Olivié, Jörg Schwinger, Parvadha Suntharalingam, Jerry Tjiputra, Marco van Hulten, Michio Watanabe, Andrew Yool, and Roland Séférian
Biogeosciences, 18, 3823–3860, https://doi.org/10.5194/bg-18-3823-2021, https://doi.org/10.5194/bg-18-3823-2021, 2021
Short summary
Short summary
In this study we analyse surface ocean dimethylsulfide (DMS) concentration and flux to the atmosphere from four CMIP6 Earth system models over the historical and ssp585 simulations.
Our analysis of contemporary (1980–2009) climatologies shows that models better reproduce observations in mid to high latitudes. The models disagree on the sign of the trend of the global DMS flux from 1980 onwards. The models agree on a positive trend of DMS over polar latitudes following sea-ice retreat dynamics.
Andrew Yool, Julien Palmiéri, Colin G. Jones, Lee de Mora, Till Kuhlbrodt, Ekatarina E. Popova, A. J. George Nurser, Joel Hirschi, Adam T. Blaker, Andrew C. Coward, Edward W. Blockley, and Alistair A. Sellar
Geosci. Model Dev., 14, 3437–3472, https://doi.org/10.5194/gmd-14-3437-2021, https://doi.org/10.5194/gmd-14-3437-2021, 2021
Short summary
Short summary
The ocean plays a key role in modulating the Earth’s climate. Understanding this role is critical when using models to project future climate change. Consequently, it is necessary to evaluate their realism against the ocean's observed state. Here we validate UKESM1, a new Earth system model, focusing on the realism of its ocean physics and circulation, as well as its biological cycles and productivity. While we identify biases, generally the model performs well over a wide range of properties.
Anna Katavouta and Richard G. Williams
Biogeosciences, 18, 3189–3218, https://doi.org/10.5194/bg-18-3189-2021, https://doi.org/10.5194/bg-18-3189-2021, 2021
Short summary
Short summary
Diagnostics of the latest-generation Earth system models reveal the ocean will continue to absorb a large fraction of the anthropogenic carbon released to the atmosphere in the next century, with the Atlantic Ocean storing a large amount of this carbon relative to its size. The ability of the ocean to absorb carbon will reduce in the future as the ocean warms and acidifies. This reduction is larger in the Atlantic Ocean due to a weakening of the meridional overturning with changes in climate.
Jane P. Mulcahy, Colin Johnson, Colin G. Jones, Adam C. Povey, Catherine E. Scott, Alistair Sellar, Steven T. Turnock, Matthew T. Woodhouse, Nathan Luke Abraham, Martin B. Andrews, Nicolas Bellouin, Jo Browse, Ken S. Carslaw, Mohit Dalvi, Gerd A. Folberth, Matthew Glover, Daniel P. Grosvenor, Catherine Hardacre, Richard Hill, Ben Johnson, Andy Jones, Zak Kipling, Graham Mann, James Mollard, Fiona M. O'Connor, Julien Palmiéri, Carly Reddington, Steven T. Rumbold, Mark Richardson, Nick A. J. Schutgens, Philip Stier, Marc Stringer, Yongming Tang, Jeremy Walton, Stephanie Woodward, and Andrew Yool
Geosci. Model Dev., 13, 6383–6423, https://doi.org/10.5194/gmd-13-6383-2020, https://doi.org/10.5194/gmd-13-6383-2020, 2020
Short summary
Short summary
Aerosols are an important component of the Earth system. Here, we comprehensively document and evaluate the aerosol schemes as implemented in the physical and Earth system models, HadGEM3-GC3.1 and UKESM1. This study provides a useful characterisation of the aerosol climatology in both models, facilitating the understanding of the numerous aerosol–climate interaction studies that will be conducted for CMIP6 and beyond.
Svetlana Jevrejeva, Lucy Bricheno, Jennifer Brown, David Byrne, Michela De Dominicis, Andy Matthews, Stefanie Rynders, Hindumathi Palanisamy, and Judith Wolf
Nat. Hazards Earth Syst. Sci., 20, 2609–2626, https://doi.org/10.5194/nhess-20-2609-2020, https://doi.org/10.5194/nhess-20-2609-2020, 2020
Short summary
Short summary
We explore the role of waves, storm surges and sea level rise for the Caribbean region with a focus on the eastern Caribbean islands. We simulate past extreme events, suggesting a storm surge might reach 1.5 m and coastal wave heights up to 12 m offshore and up to 5 m near the coast of St Vincent. We provide sea level projections of up to 2.2 m by 2100. Our work provides quantitative evidence for policy-makers, scientists and local communities to actively protect against climate change.
Lee de Mora, Alistair A. Sellar, Andrew Yool, Julien Palmieri, Robin S. Smith, Till Kuhlbrodt, Robert J. Parker, Jeremy Walton, Jeremy C. Blackford, and Colin G. Jones
Geosci. Commun., 3, 263–278, https://doi.org/10.5194/gc-3-263-2020, https://doi.org/10.5194/gc-3-263-2020, 2020
Short summary
Short summary
We use time series data from the first United Kingdom Earth System Model (UKESM1) to create six procedurally generated musical pieces for piano. Each of the six pieces help to explain either a scientific principle or a practical aspect of Earth system modelling. We describe the methods that were used to create these pieces, discuss the limitations of this pilot study and list several approaches to extend and expand upon this work.
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris D. Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Olivier Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Emilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, Rachel M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry F. Tjiputra, Andy Wiltshire, Tongwen Wu, and Tilo Ziehn
Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, https://doi.org/10.5194/bg-17-4173-2020, 2020
Short summary
Short summary
Since the preindustrial period, land and ocean have taken up about half of the carbon emitted into the atmosphere by humans. Comparison of different earth system models with the carbon cycle allows us to assess how carbon uptake by land and ocean differs among models. This yields an estimate of uncertainty in our understanding of how land and ocean respond to increasing atmospheric CO2. This paper summarizes results from two such model intercomparison projects that use an idealized scenario.
Lester Kwiatkowski, Olivier Torres, Laurent Bopp, Olivier Aumont, Matthew Chamberlain, James R. Christian, John P. Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G. John, Andrew Lenton, Hongmei Li, Nicole S. Lovenduski, James C. Orr, Julien Palmieri, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Charles A. Stock, Alessandro Tagliabue, Yohei Takano, Jerry Tjiputra, Katsuya Toyama, Hiroyuki Tsujino, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, and Tilo Ziehn
Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, https://doi.org/10.5194/bg-17-3439-2020, 2020
Short summary
Short summary
We assess 21st century projections of marine biogeochemistry in the CMIP6 Earth system models. These models represent the most up-to-date understanding of climate change. The models generally project greater surface ocean warming, acidification, subsurface deoxygenation, and euphotic nitrate reductions but lesser primary production declines than the previous generation of models. This has major implications for the impact of anthropogenic climate change on marine ecosystems.
David J. Webb, Andrew C. Coward, and Helen M. Snaith
Ocean Sci., 16, 565–574, https://doi.org/10.5194/os-16-565-2020, https://doi.org/10.5194/os-16-565-2020, 2020
Short summary
Short summary
In conflict with conventional theory, recent analysis of data from a high-resolution global ocean model showed that the North Equatorial Counter Current was responsible for the unusually warm water which triggered the strong El Niños of 1982–83 and 1997–98. In this paper some of the key physics deduced from the model results are tested against satellite data from the 1997–98 event. The results show that the model closely followed reality during the period, further supporting the new mechanisms.
Malcolm J. Roberts, Alex Baker, Ed W. Blockley, Daley Calvert, Andrew Coward, Helene T. Hewitt, Laura C. Jackson, Till Kuhlbrodt, Pierre Mathiot, Christopher D. Roberts, Reinhard Schiemann, Jon Seddon, Benoît Vannière, and Pier Luigi Vidale
Geosci. Model Dev., 12, 4999–5028, https://doi.org/10.5194/gmd-12-4999-2019, https://doi.org/10.5194/gmd-12-4999-2019, 2019
Short summary
Short summary
We investigate the role that horizontal grid spacing plays in global coupled climate model simulations, together with examining the efficacy of a new design of simulation experiments that is being used by the community for multi-model comparison. We found that finer grid spacing in both atmosphere and ocean–sea ice models leads to a general reduction in bias compared to observations, and that once eddies in the ocean are resolved, several key climate processes are greatly improved.
Marina Tonani, Peter Sykes, Robert R. King, Niall McConnell, Anne-Christine Péquignet, Enda O'Dea, Jennifer A. Graham, Jeff Polton, and John Siddorn
Ocean Sci., 15, 1133–1158, https://doi.org/10.5194/os-15-1133-2019, https://doi.org/10.5194/os-15-1133-2019, 2019
Short summary
Short summary
A new high-resolution ocean model at 1.5 km has replaced the 7 km system for delivering short-term forecasts of the North-West European Shelf seas. The products (temperature, salinity, currents, and sea surface height) are available on the Copernicus Marine Service catalogue. This study focuses on the high-resolution impact on the quality of the products delivered to the users. Results show that the high-resolution model is better at resolving the variability of the physical variables.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Alex Arnold, Joachim Fallmann, Andrew Saulter, Jennifer Graham, Mike Bush, John Siddorn, Tamzin Palmer, Adrian Lock, John Edwards, Lucy Bricheno, Alberto Martínez-de la Torre, and James Clark
Geosci. Model Dev., 12, 2357–2400, https://doi.org/10.5194/gmd-12-2357-2019, https://doi.org/10.5194/gmd-12-2357-2019, 2019
Short summary
Short summary
In the real world the atmosphere, oceans and land surface are closely interconnected, and yet the prediction systems used for weather and ocean forecasting tend to treat them in isolation. This paper describes the third version of a regional modelling system which aims to represent the feedback processes between sky, sea and land. The main innovation introduced in this version enables waves to affect the underlying ocean. Coupled results from four different month-long simulations are analysed.
Matthew P. Couldrey, Kevin I. C. Oliver, Andrew Yool, Paul R. Halloran, and Eric P. Achterberg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-16, https://doi.org/10.5194/bg-2019-16, 2019
Revised manuscript not accepted
Short summary
Short summary
Determining how much carbon dioxide (CO2) the oceans absorb is key to predicting human-caused climate change. A computer model of the ocean shows how the North Atlantic will change up to the end of the century. Year-to-year variations are mostly caused by changes in ocean temperature and seawater chemistry, altering CO2 solubility. By 2100, human emissions cause the biggest changes. The near term changes are physically driven, which may be more predictable than biological changes.
Dale Partridge, Tobias Friedrich, and Brian S. Powell
Geosci. Model Dev., 12, 195–213, https://doi.org/10.5194/gmd-12-195-2019, https://doi.org/10.5194/gmd-12-195-2019, 2019
Short summary
Short summary
This paper demonstrates the improvements made to an operational ocean forecast model around the Hawaiian Islands by performing a reanalysis of the model over a 10-year period. Using a number of different measurements we show the role a variety of observations play in producing the forecast, in particular the contribution of high-frequency radar.
Julien Palmiéri, Jean-Claude Dutay, Fabrizio D'Ortenzio, Loïc Houpert, Nicolas Mayot, and Laurent Bopp
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-423, https://doi.org/10.5194/bg-2018-423, 2018
Manuscript not accepted for further review
Short summary
Short summary
In this model study, we highlight the importance of the subsurface phytoplankton dynamic in the Mediterranean sea. Comparing surface chlorophyll annual cycle to vertically integrated one, we show how important the subsurface phytoplankton community is, throughout the Mediterranean. It shows that surface chlorophyll is incomplete and cannot alone be considered a good proxy of the total phytoplankton biomass. Then, we decrypt some deep chlorophyll maximum mechanisms in the low production area.
Ben A. Ward, Jamie D. Wilson, Ros M. Death, Fanny M. Monteiro, Andrew Yool, and Andy Ridgwell
Geosci. Model Dev., 11, 4241–4267, https://doi.org/10.5194/gmd-11-4241-2018, https://doi.org/10.5194/gmd-11-4241-2018, 2018
Short summary
Short summary
A novel configuration of an Earth system model includes a diverse plankton community. The model – EcoGEnIE – is sufficiently complex to reproduce a realistic, size-structured plankton community, while at the same time retaining the efficiency to run to a global steady state (~ 10k years). The increased capabilities of EcoGEnIE will allow future exploration of ecological communities on much longer timescales than have so far been examined in global ocean models and particularly for past climate.
Lee de Mora, Andrew Yool, Julien Palmieri, Alistair Sellar, Till Kuhlbrodt, Ekaterina Popova, Colin Jones, and J. Icarus Allen
Geosci. Model Dev., 11, 4215–4240, https://doi.org/10.5194/gmd-11-4215-2018, https://doi.org/10.5194/gmd-11-4215-2018, 2018
Short summary
Short summary
Climate change is expected to have a significant impact on the Earth's weather, ice caps, land surface, and ocean. Computer models of the Earth system are the only tools available to make predictions about how the climate may change in the future. However, in order to trust the model predictions, we must first demonstrate that the models have a realistic description of the past. The BGC-val toolkit was built to rapidly and simply evaluate the behaviour of models of the Earth's oceans.
Andrew R. Porter, Jeremy Appleyard, Mike Ashworth, Rupert W. Ford, Jason Holt, Hedong Liu, and Graham D. Riley
Geosci. Model Dev., 11, 3447–3464, https://doi.org/10.5194/gmd-11-3447-2018, https://doi.org/10.5194/gmd-11-3447-2018, 2018
Short summary
Short summary
Developing computer models in the earth-system domain is a complex and expensive process that can have a duration measured in years. The supercomputers required to run these models, however, are evolving fast with a proliferation of technologies and associated programming models. As a result there is a need that models be "performance portable" between different supercomputers. This paper investigates a way of doing this through a separation of the concerns of performance and natural science.
Jennifer A. Graham, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame
Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, https://doi.org/10.5194/gmd-11-681-2018, 2018
Short summary
Short summary
This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15 (Atlantic Margin Model, 1.5 km resolution). The current forecast system has a resolution of 7 km. While this is sufficient to represent large-scale circulation, many dynamical features (such as eddies, frontal jets, and internal tides) can only begin to be resolved at 0–1 km resolution. Here we introduce AMM15 and demonstrate its ability to represent the mean state and variability of the region.
Huw W. Lewis, Juan Manuel Castillo Sanchez, Jennifer Graham, Andrew Saulter, Jorge Bornemann, Alex Arnold, Joachim Fallmann, Chris Harris, David Pearson, Steven Ramsdale, Alberto Martínez-de la Torre, Lucy Bricheno, Eleanor Blyth, Victoria A. Bell, Helen Davies, Toby R. Marthews, Clare O'Neill, Heather Rumbold, Enda O'Dea, Ashley Brereton, Karen Guihou, Adrian Hines, Momme Butenschon, Simon J. Dadson, Tamzin Palmer, Jason Holt, Nick Reynard, Martin Best, John Edwards, and John Siddorn
Geosci. Model Dev., 11, 1–42, https://doi.org/10.5194/gmd-11-1-2018, https://doi.org/10.5194/gmd-11-1-2018, 2018
Short summary
Short summary
In the real world the atmosphere, oceans and land surface are closely interconnected, and yet prediction systems tend to treat them in isolation. Those feedbacks are often illustrated in natural hazards, such as when strong winds lead to large waves and coastal damage, or when prolonged rainfall leads to saturated ground and high flowing rivers. For the first time, we have attempted to represent some of the feedbacks between sky, sea and land within a high-resolution forecast system for the UK.
Bertrand Bonan, Nancy K. Nichols, Michael J. Baines, and Dale Partridge
Nonlin. Processes Geophys., 24, 515–534, https://doi.org/10.5194/npg-24-515-2017, https://doi.org/10.5194/npg-24-515-2017, 2017
Short summary
Short summary
We develop data assimilation techniques for numerical models using moving mesh methods. Moving meshes are valuable for explicitly tracking interfaces and boundaries in evolving systems. The application of the techniques is demonstrated on a one-dimensional
model of an ice sheet. It is shown, using various types of observations, that
the techniques predict the evolution of the edges of the ice sheet and its height accurately and efficiently.
Enda O'Dea, Rachel Furner, Sarah Wakelin, John Siddorn, James While, Peter Sykes, Robert King, Jason Holt, and Helene Hewitt
Geosci. Model Dev., 10, 2947–2969, https://doi.org/10.5194/gmd-10-2947-2017, https://doi.org/10.5194/gmd-10-2947-2017, 2017
Short summary
Short summary
An update to an ocean modelling configuration for the European North West Shelf is described. It is assessed against observations and climatologies for 1981–2012. Sensitivities in the model configuration updates are assessed to understand changes in the model system. The model improves upon an existing model of the region, although there remain some areas with significant biases. The paper highlights the dependence upon the quality of the river inputs.
Jason Holt, Patrick Hyder, Mike Ashworth, James Harle, Helene T. Hewitt, Hedong Liu, Adrian L. New, Stephen Pickles, Andrew Porter, Ekaterina Popova, J. Icarus Allen, John Siddorn, and Richard Wood
Geosci. Model Dev., 10, 499–523, https://doi.org/10.5194/gmd-10-499-2017, https://doi.org/10.5194/gmd-10-499-2017, 2017
Short summary
Short summary
Accurately representing coastal and shelf seas in global ocean models is one of the grand challenges of Earth system science. Here, we explore what the options are for improving this by exploring what the important physical processes are that need to be represented. We use a simple scale analysis to investigate how large the resulting models would need to be. We then compare this with how computer power is increasing to provide estimates of when this might be feasible in the future.
Helene T. Hewitt, Malcolm J. Roberts, Pat Hyder, Tim Graham, Jamie Rae, Stephen E. Belcher, Romain Bourdallé-Badie, Dan Copsey, Andrew Coward, Catherine Guiavarch, Chris Harris, Richard Hill, Joël J.-M. Hirschi, Gurvan Madec, Matthew S. Mizielinski, Erica Neininger, Adrian L. New, Jean-Christophe Rioual, Bablu Sinha, David Storkey, Ann Shelly, Livia Thorpe, and Richard A. Wood
Geosci. Model Dev., 9, 3655–3670, https://doi.org/10.5194/gmd-9-3655-2016, https://doi.org/10.5194/gmd-9-3655-2016, 2016
Short summary
Short summary
We examine the impact in a coupled model of increasing atmosphere and ocean horizontal resolution and the frequency of coupling between the atmosphere and ocean. We demonstrate that increasing the ocean resolution from 1/4 degree to 1/12 degree has a major impact on ocean circulation and global heat transports. The results add to the body of evidence suggesting that ocean resolution is an important consideration when developing coupled models for weather and climate applications.
Svitlana Liubartseva, Giovanni Coppini, Nadia Pinardi, Michela De Dominicis, Rita Lecci, Giuseppe Turrisi, Sergio Cretì, Sara Martinelli, Paola Agostini, Palmalisa Marra, and Francesco Palermo
Nat. Hazards Earth Syst. Sci., 16, 2009–2020, https://doi.org/10.5194/nhess-16-2009-2016, https://doi.org/10.5194/nhess-16-2009-2016, 2016
Short summary
Short summary
An innovative fully operational 24/7 web-based decision support system, WITOIL (Where Is The Oil), has been developed to support oil pollution response. The system meets the real-time requirements in terms of performance and dynamic service delivery. Comprehensive computational resources and network bandwidth efficiently support the multi-user regime. The eight-language graphical user interface incorporates a great variety of user services, e.g., help and support, tooltips, and video tutorials.
Claudie Beaulieu, Harriet Cole, Stephanie Henson, Andrew Yool, Thomas R. Anderson, Lee de Mora, Erik T. Buitenhuis, Momme Butenschön, Ian J. Totterdell, and J. Icarus Allen
Biogeosciences, 13, 4533–4553, https://doi.org/10.5194/bg-13-4533-2016, https://doi.org/10.5194/bg-13-4533-2016, 2016
Short summary
Short summary
Regime shifts have been suggested in the late 1970s and late 1980s in the Gulf of Alaska with important consequences for fisheries. Here we investigate the ability of a suite of ocean biogeochemical models of varying complexity to simulate these regime shifts. Our results demonstrate that ocean models can successfully simulate regime shifts in the Gulf of Alaska region, thereby improving our understanding of how changes in physical conditions are propagated from lower to upper trophic levels.
Heather Cannaby, Matthew D. Palmer, Tom Howard, Lucy Bricheno, Daley Calvert, Justin Krijnen, Richard Wood, Jonathan Tinker, Chris Bunney, James Harle, Andrew Saulter, Clare O'Neill, Clare Bellingham, and Jason Lowe
Ocean Sci., 12, 613–632, https://doi.org/10.5194/os-12-613-2016, https://doi.org/10.5194/os-12-613-2016, 2016
Short summary
Short summary
The Singapore government commissioned a modelling study of regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events. We find that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century, these being 0.52 m(0.74 m) under the RCP 4.5(8.5) scenario.
Momme Butenschön, James Clark, John N. Aldridge, Julian Icarus Allen, Yuri Artioli, Jeremy Blackford, Jorn Bruggeman, Pierre Cazenave, Stefano Ciavatta, Susan Kay, Gennadi Lessin, Sonja van Leeuwen, Johan van der Molen, Lee de Mora, Luca Polimene, Sevrine Sailley, Nicholas Stephens, and Ricardo Torres
Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, https://doi.org/10.5194/gmd-9-1293-2016, 2016
Short summary
Short summary
ERSEM 15.06 is a model for marine biogeochemistry and the lower trophic levels of the marine food web. It comprises a pelagic and benthic sub-model including the microbial food web and the major biogeochemical cycles of carbon, nitrogen, phosphorus, silicate, and iron using dynamic stochiometry. Further features include modules for the carbonate system and calcification. We present full mathematical descriptions of all elements along with examples at various scales up to 3-D applications.
B. Bonan, M. J. Baines, N. K. Nichols, and D. Partridge
The Cryosphere, 10, 1–14, https://doi.org/10.5194/tc-10-1-2016, https://doi.org/10.5194/tc-10-1-2016, 2016
Short summary
Short summary
This paper introduce a moving-point approach to model the flow of ice sheets. This particular moving-grid numerical approach is based on the conservation of local masses. This allows the ice sheet margins to be tracked explicitly. A finite-difference moving-point scheme is derived and applied in a simplified context (1-D). The conservation method is also suitable for 2-D scenarios. This paper is a first step towards applications of the conservation method to realistic 2-D cases.
A. Guyennon, M. Baklouti, F. Diaz, J. Palmieri, J. Beuvier, C. Lebaupin-Brossier, T. Arsouze, K. Béranger, J.-C. Dutay, and T. Moutin
Biogeosciences, 12, 7025–7046, https://doi.org/10.5194/bg-12-7025-2015, https://doi.org/10.5194/bg-12-7025-2015, 2015
Short summary
Short summary
Dissolved organic carbon (DOC) has already been identified as a potentially significant source of carbon export in the Mediterranean Sea, though in situ export estimations are scarce. This work provides a thorough analysis at basin scale of carbon export with the coupled model NEMO-MED12/Eco3M-MED model. The seasonality and the processes of particulate and dissolved carbon production are also investigated. DOC export appears to be dominant in most regions, especially in the eastern basin.
T. R. Anderson, W. C. Gentleman, and A. Yool
Geosci. Model Dev., 8, 2231–2262, https://doi.org/10.5194/gmd-8-2231-2015, https://doi.org/10.5194/gmd-8-2231-2015, 2015
Short summary
Short summary
Ecosystem models provide a powerful tool for simulating ocean biology. Care must be exercised when selecting appropriate equations and parameter values to represent chosen marine ecosystems. Here, we present an efficient plankton model testbed, using simplified physics and coded in the freely available language R. Multiple runs can be undertaken for different ocean sites, permitting thorough evaluation of ecosystem model performance. The testbed also serves as an excellent resource for teaching.
M. Ayache, J.-C. Dutay, P. Jean-Baptiste, K. Beranger, T. Arsouze, J. Beuvier, J. Palmieri, B. Le-vu, and W. Roether
Ocean Sci., 11, 323–342, https://doi.org/10.5194/os-11-323-2015, https://doi.org/10.5194/os-11-323-2015, 2015
Short summary
Short summary
The anthropogenic tritium invasion, and its decay product helium-3, was simulated for the first time in the Mediterranean Sea, using a high-resolution regional model (NEMO-MED12). The simulation covers the entire tritium (3H) transient generated by the atmospheric nuclear weapons tests performed in the 1950s and early 1960s and run until 2011. The model correctly simulates the main features of the thermohaline circulation in the Mediterranean Sea, with a realistic time compared to observations.
J. C. P. Hemmings, P. G. Challenor, and A. Yool
Geosci. Model Dev., 8, 697–731, https://doi.org/10.5194/gmd-8-697-2015, https://doi.org/10.5194/gmd-8-697-2015, 2015
Short summary
Short summary
Effective calibration of global models is inhibited by the computational demands of 3-D simulations. As a solution for the NEMO-MEDUSA model, we present an efficient emulator of surface chlorophyll as a function of MEDUSA’s biogeochemical parameters. The emulator comprises an array of site-based 1-D simulators and a quantification of uncertainty in their predictions. It is able to produce robust probabilistic estimates of 3-D model output rapidly for comparison with satellite chlorophyll.
J. Palmiéri, J. C. Orr, J.-C. Dutay, K. Béranger, A. Schneider, J. Beuvier, and S. Somot
Biogeosciences, 12, 781–802, https://doi.org/10.5194/bg-12-781-2015, https://doi.org/10.5194/bg-12-781-2015, 2015
Short summary
Short summary
Different observational-based estimates of CO2 uptake and resulting
acidification of the Mediterranean Sea vary widely. A new study finds
that even the smallest of those are an upper limit because the approach
used assumes air-sea CO2 equilibrium. Then with a lower limit from new
fine-scale numerical model simulations, the authors bracket
Mediterranean Sea CO2 uptake and acidification rates. They conclude that
its rate of surface acidifcation is much like that for typical ocean
waters.
L. Kwiatkowski, A. Yool, J. I. Allen, T. R. Anderson, R. Barciela, E. T. Buitenhuis, M. Butenschön, C. Enright, P. R. Halloran, C. Le Quéré, L. de Mora, M.-F. Racault, B. Sinha, I. J. Totterdell, and P. M. Cox
Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, https://doi.org/10.5194/bg-11-7291-2014, 2014
B. A. Kelly-Gerreyn, A. P. Martin, B. J. Bett, T. R. Anderson, J. I. Kaariainen, C. E. Main, C. J. Marcinko, and A. Yool
Biogeosciences, 11, 6401–6416, https://doi.org/10.5194/bg-11-6401-2014, https://doi.org/10.5194/bg-11-6401-2014, 2014
Y. Artioli, J. C. Blackford, G. Nondal, R. G. J. Bellerby, S. L. Wakelin, J. T. Holt, M. Butenschön, and J. I. Allen
Biogeosciences, 11, 601–612, https://doi.org/10.5194/bg-11-601-2014, https://doi.org/10.5194/bg-11-601-2014, 2014
J. Holt, C. Schrum, H. Cannaby, U. Daewel, I. Allen, Y. Artioli, L. Bopp, M. Butenschon, B. A. Fach, J. Harle, D. Pushpadas, B. Salihoglu, and S. Wakelin
Biogeosciences Discuss., https://doi.org/10.5194/bgd-11-1909-2014, https://doi.org/10.5194/bgd-11-1909-2014, 2014
Revised manuscript not accepted
E. E. Popova, A. Yool, Y. Aksenov, A. C. Coward, and T. R. Anderson
Biogeosciences, 11, 293–308, https://doi.org/10.5194/bg-11-293-2014, https://doi.org/10.5194/bg-11-293-2014, 2014
A. Yool, E. E. Popova, and T. R. Anderson
Geosci. Model Dev., 6, 1767–1811, https://doi.org/10.5194/gmd-6-1767-2013, https://doi.org/10.5194/gmd-6-1767-2013, 2013
A. Yool, E. E. Popova, A. C. Coward, D. Bernie, and T. R. Anderson
Biogeosciences, 10, 5831–5854, https://doi.org/10.5194/bg-10-5831-2013, https://doi.org/10.5194/bg-10-5831-2013, 2013
S. Henson, H. Cole, C. Beaulieu, and A. Yool
Biogeosciences, 10, 4357–4369, https://doi.org/10.5194/bg-10-4357-2013, https://doi.org/10.5194/bg-10-4357-2013, 2013
Related subject area
Oceanography
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 high-frequency radar observations
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
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
Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)
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
Sofia Flora, Laura Ursella, and Achim Wirth
Geosci. Model Dev., 18, 4685–4712, https://doi.org/10.5194/gmd-18-4685-2025, https://doi.org/10.5194/gmd-18-4685-2025, 2025
Short summary
Short summary
We developed a hierarchy of idealized deterministic–stochastic models to simulate 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 key dynamics and mimics the observed fat-tailed probability distribution.
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.
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.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
Short summary
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.
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.
Cited articles
Adcroft, A. and Marshall, D.: How Slippery Are Piecewise-Constant Coastlines in
Numerical Ocean Models?, Tellus A, 50,
95–108, https://doi.org/10.3402/tellusa.v50i1.14514, 1998. a
Adusumilli, S., Fricker, H. A., Medley, B., Padman, L., and Siegfried, M. R.:
Interannual variations in meltwater input to the Southern Ocean from
Antarctic ice shelves, Nat. Geosci., 13, 616–620,
https://doi.org/10.1038/s41561-020-0616-z, 2020. a
Andreas, E. L., Mahrt, L., and Vickers, D.: An Improved Bulk Air-Sea
Surface Flux Algorithm, Including Spray-mediated Transfer,
Q. J. Roy. Meteor. Soc., 141, 642–654, https://doi.org/10.1002/qj.2424,
2015. a
Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L.: Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation, Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, 2020. a
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. a
Axell, L. B.: Wind-Driven Internal Waves and Langmuir Circulations in a
Numerical Ocean Model of the Southern Baltic Sea,
J. Geophys. Res., 107, 3204, https://doi.org/10.1029/2001JC000922, 2002. a
Bakker, D. C. E., Pfeil, B., Landa, C. S., Metzl, N., O'Brien, K. M., Olsen, A., Smith, K., Cosca, C., Harasawa, S., Jones, S. D., Nakaoka, S., Nojiri, Y., Schuster, U., Steinhoff, T., Sweeney, C., Takahashi, T., Tilbrook, B., Wada, C., Wanninkhof, R., Alin, S. R., Balestrini, C. F., Barbero, L., Bates, N. R., Bianchi, A. A., Bonou, F., Boutin, J., Bozec, Y., Burger, E. F., Cai, W.-J., Castle, R. D., Chen, L., Chierici, M., Currie, K., Evans, W., Featherstone, C., Feely, R. A., Fransson, A., Goyet, C., Greenwood, N., Gregor, L., Hankin, S., Hardman-Mountford, N. J., Harlay, J., Hauck, J., Hoppema, M., Humphreys, M. P., Hunt, C. W., Huss, B., Ibánhez, J. S. P., Johannessen, T., Keeling, R., Kitidis, V., Körtzinger, A., Kozyr, A., Krasakopoulou, E., Kuwata, A., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lo Monaco, C., Manke, A., Mathis, J. T., Merlivat, L., Millero, F. J., Monteiro, P. M. S., Munro, D. R., Murata, A., Newberger, T., Omar, A. M., Ono, T., Paterson, K., Pearce, D., Pierrot, D., Robbins, L. L., Saito, S., Salisbury, J., Schlitzer, R., Schneider, B., Schweitzer, R., Sieger, R., Skjelvan, I., Sullivan, K. F., Sutherland, S. C., Sutton, A. J., Tadokoro, K., Telszewski, M., Tuma, M., van Heuven, S. M. A. C., Vandemark, D., Ward, B., Watson, A. J., and Xu, S.: A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT), Earth Syst. Sci. Data, 8, 383–413, https://doi.org/10.5194/essd-8-383-2016, 2016. a
Baretta, J., Ebenhöh, W., and Ruardij, P.: The European Regional Seas
Ecosystem Model, a Complex Marine Ecosystem Model,
Neth. J. Sea Res., 33, 233–246, https://doi.org/10.1016/0077-7579(95)90047-0, 1995. a
Beck, K.: Test Driven Development: By Example, Addison-Wesley Professional,
ISBN 9780321146533, 2002. a
Belcher, S. E., Grant, A. L. M., Hanley, K. E., Fox-Kemper, B., Van Roekel,
L., Sullivan, P. P., Large, W. G., Brown, A., Hines, A., Calvert, D.,
Rutgersson, A., Pettersson, H., Bidlot, J.-R., Janssen, P. A. E. M., and
Polton, J. A.: A Global Perspective on Langmuir Turbulence in the Ocean
Surface Boundary Layer: FRONTIER, Geophys. Res. Lett., 39, L18605,
https://doi.org/10.1029/2012GL052932, 2012. a
Beljaars, A. C. M.: The parametrization of surface fluxes in large-scale models
under free convection, Q. J. Roy. Meteor. Soc.,
121, 255–270, https://doi.org/10.1002/qj.49712152203, 1995. a
Booij, N., Ris, R. C., and Holthuijsen, L. H.: A third-generation wave model
for coastal regions: 1. Model description and validation, J.
Geophys. Res.-Oceans, 104, 7649–7666, 1999. a
Boyer, T., Baranova, O., Coleman, C., Garcia, H., Grodsky, A., Locarnini, R.,
Mishonov, A., Paver, C., Reagan, J., Seidov, D., Smolyar, I., Weathers, K.,
and Zweng, M.: World Ocean Database 2018, Tech. rep., NOAA Atlas NESDIS 87,
technical Ed.: Mishonov, A. V., 2018a. a
Boyer, T. P., Garcia, H. E., Locarnini, R. A., Zweng, M. M., Mishonov, A. V.,
Reagan, J. R., Weathers, K. A., Baranova, O. K., Seidov, D., and Smolyar,
I. V.: World Ocean Atlas 2018, [data set], https://www.ncei.noaa.gov/archive/accession/NCEI-WOA18 (last access: 20 February 2022), 2018b. a
Breivik, Ø., Mogensen, K., Bidlot, J.-R., Balmaseda, M. A., and Janssen, P.
A. E. M.: Surface Wave Effects in the NEMO Ocean Model: Forced and
Coupled Experiments, J. Geophys. Res.-Oceans, 120,
2973–2992, https://doi.org/10.1002/2014JC010565, 2015. a
Brodeau, L., Barnier, B., Treguier, A.-M., Penduff, T., and Gulev, S.: An
ERA40-based atmospheric forcing for global ocean circulation models, Ocean Model., 31, 88–104, https://doi.org/10.1016/j.ocemod.2009.10.005, 2010. a
Bruciaferri, D., Shapiro, G. I., and Wobus, F.: A Multi-Envelope Vertical
Coordinate System for Numerical Ocean Modelling, Ocean Dynam., 68,
1239–1258, https://doi.org/10.1007/s10236-018-1189-x, 2018. a, b
Bruciaferri, D., Shapiro, G., Stanichny, S., Zatsepin, A., Ezer, T., Wobus, F.,
Francis, X., and Hilton, D.: The Development of a 3D Computational Mesh
to Improve the Representation of Dynamic Processes: The Black Sea Test
Case, Ocean Model., 146, 101534, https://doi.org/10.1016/j.ocemod.2019.101534,
2020. a
Bruciaferri, D., Tonani, M., Lewis, H. W., Siddorn, J. R., Saulter, A.,
Castillo Sanchez, J. M., Valiente, N. G., Conley, D., Sykes, P., Ascione, I.,
and McConnell, N.: The Impact of Ocean-Wave Coupling on the
Upper Ocean Circulation During Storm Events, J. Geophys. Res.-Oceans, 126, e2021JC017343, https://doi.org/10.1029/2021JC017343, 2021. a
Bull, C. Y. S., Jenkins, A., Jourdain, N. C., Vaňková, I., Holland,
P. R., Mathiot, P., Hausmann, U., and Sallée, J.: Remote Control of
Filchner‐Ronne Ice Shelf Melt Rates by the Antarctic Slope Current,
J. Geophys. Res.-Oceans, 126, e2020JC016550, https://doi.org/10.1029/2020JC016550,
2021. a
Butenschön, M., Clark, J., Aldridge, J. N., Allen, J. I., Artioli, Y., Blackford, J., Bruggeman, J., Cazenave, P., Ciavatta, S., Kay, S., Lessin, G., van Leeuwen, S., van der Molen, J., de Mora, L., Polimene, L., Sailley, S., Stephens, N., and Torres, R.: ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels, Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, 2016. a, b
Byrne, D., Polton, J., O'Dea, E., and Williams, J.: A Standardised Validation Framework for Ocean Physics Models: Application to the Northwest European Shelf, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2022-218, in review, 2022. a
Castillo, J. M., Lewis, H. W., Mishra, A., Mitra, A., Polton, J., Brereton, A., Saulter, A., Arnold, A., Berthou, S., Clark, D., Crook, J., Das, A., Edwards, J., Feng, X., Gupta, A., Joseph, S., Klingaman, N., Momin, I., Pequignet, C., Sanchez, C., Saxby, J., and Valdivieso da Costa, M.: The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at kilometre scale, Geosci. Model Dev., 15, 4193–4223, https://doi.org/10.5194/gmd-15-4193-2022, 2022. a, b
Cavaleri, L., Abdalla, S., Benetazzo, A., Bertotti, L., Bidlot, J.-R., Breivik,
Ø., Carniel, S., Jensen, R., Portilla-Yandun, J., Rogers, W., Roland,
A., Sanchez-Arcilla, A., Smith, J., Staneva, J., Toledo, Y., van Vledder,
G., and van der Westhuysen, A.: Wave Modelling in Coastal and Inner Seas,
Prog. Oceanogr., 167, 164–233, https://doi.org/10.1016/j.pocean.2018.03.010,
2018. a
Chen, C., Beardsley, R., and Cowles, G.: An Unstructured Grid,
Finite-Volume Coastal Ocean Model (FVCOM) System, Oceanography,
19, 78–89, https://doi.org/10.5670/oceanog.2006.92, 2006. a
Cheng, K.-Y., Harris, L. M., and Sun, Y. Q.: Enhancing the accessibility of unified modeling systems: GFDL System for High-resolution prediction on Earth-to-Local Domains (SHiELD) v2021b in a container, Geosci. Model Dev., 15, 1097–1105, https://doi.org/10.5194/gmd-15-1097-2022, 2022. a
Craig, P. D. and Banner, M. L.: Modeling Wave-Enhanced Turbulence in the Ocean
Surface Layer, J. Phys. Oceanogr., 24, 2546–2559,
https://doi.org/10.1175/1520-0485(1994)024<2546:MWETIT>2.0.CO;2, 1994. a
Danilov, S.: Ocean Modeling on Unstructured Meshes, Ocean Model., 69,
195–210, https://doi.org/10.1016/j.ocemod.2013.05.005, 2013. a
De Dominicis, M., Polton, J. A., Payo, M. P., and Brown, J.:
JMMP-Group/SEVERN-SWOT: V0.2.0, Zenodo [code], https://doi.org/10.5281/zenodo.7473198,
2022. a, b, c
de Mora, L., Butenschön, M., and Allen, J. I.: The assessment of a global marine ecosystem model on the basis of emergent properties and ecosystem function: a case study with ERSEM, Geosci. Model Dev., 9, 59–76, https://doi.org/10.5194/gmd-9-59-2016, 2016. a
Depoorter, M. A., Bamber, J. L., Griggs, J. A., Lenaerts, J. T. M., Ligtenberg,
S. R. M., van den Broeke, M. R., and Moholdt, G.: Calving fluxes and basal
melt rates of Antarctic ice shelves, Nature, 502, 89–92,
https://doi.org/10.1038/nature12567, 2013. a
Dorrell, R. M., Lloyd, C. J., Lincoln, B. J., Rippeth, T. P., Taylor, J. R.,
Caulfield, C.-c. P., Sharples, J., Polton, J. A., Scannell, B. D., Greaves,
D. M., Hall, R. A., and Simpson, J. H.: Anthropogenic Mixing in
Seasonally Stratified Shelf Seas by Offshore Wind Farm
Infrastructure, Front. Mar. Sci., 9, 830927,
https://doi.org/10.3389/fmars.2022.830927, 2022. a
Echevin, V., Gévaudan, M., Espinoza-Morriberón, D., Tam, J., Aumont, O., Gutierrez, D., and Colas, F.: Physical and biogeochemical impacts of RCP8.5 scenario in the Peru upwelling system, Biogeosciences, 17, 3317–3341, https://doi.org/10.5194/bg-17-3317-2020, 2020. a
Edson, J. B., Jampana, V., Weller, R. A., Bigorre, S. P., Plueddemann, A. J.,
Fairall, C. W., Miller, S. D., Mahrt, L., Vickers, D., and Hersbach, H.: On
the Exchange of Momentum over the Open Ocean, J. Phys.
Oceanogr., 43, 1589–1610, https://doi.org/10.1175/JPO-D-12-0173.1, 2013. a
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of
Barotropic Ocean Tides, J. Atmos. Ocean. Tech.,
19, 183–204, https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2, 2002. a
England, M. R., Wagner, T. J. W., and Eisenman, I.:
Modeling the breakup of tabular icebergs, Sci. Adv., 6, eabd1273,
https://doi.org/10.1126/sciadv.abd1273, 2020. a
Éthé, C., Person, R., and Aumont, O.: NEMO-PISCES 1D Demonstration guide,
Zenodo [code], https://doi.org/10.5281/zenodo.7139521, 2022. a, b
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J. B.:
Bulk Parameterization of Air-Sea Fluxes: Updates and Verification for the
COARE Algorithm, J. Climate, 16, 571–591,
https://doi.org/10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2, 2003. a
Felgate, S. L., Barry, C. D. G., Mayor, D. J., Sanders, R., Carrias, A., Young,
A., Fitch, A., Mayorga-Adame, C. G., Andrews, G., Brittain, H., Cryer, S. E.,
Evans, C. D., Goddard-Dwyer, M., Holt, J. T., Hughes, B. K., Lapworth, D. J.,
Pinder, A., Price, D. M., Rosado, S., and Evans, C.: Conversion of Forest
to Agriculture Increases Colored Dissolved Organic Matter in a
Subtropical Catchment and Adjacent Coastal Environment,
J.
Geophys. Res.-Biogeo., 126, e2021JG006295, https://doi.org/10.1029/2021JG006295, 2021. a
Flather, R. A.: A tidal model of the northwest European continental shelf,
Memoires Societe Royales des Sciences de Liege, Series 6, 141–164, 1976. a
Foldvik, A., Gammelsrød, T., and Tørresen, T.: Circulation and water
masses on the southern Weddell Sea shelf, AGU Books, in: Oceanology of the Antarctic Continental Shelf, edited by: Jacobs, S. S., 5–20,
https://doi.org/10.1029/AR043p0005, 1985. a
Fox-Kemper, B., Hewitt, H., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S.,
Edwards, T., Golledge, N., Hemer, M., Kopp, R., Krinner, G., Mix, A., Notz,
D., Nowicki, S., Nurhati, I., Ruiz, L., Sallée, J.-B., Slangen, A., and Yu,
Y.: Ocean, Cryosphere and Sea Level Change, Cambridge
University Press, Cambridge, United Kingdom and New York, NY, USA,
1211–1362, https://doi.org/10.1017/9781009157896.011, 2021. a
Ge, J., Torres, R., Chen, C., Liu, J., Xu, Y., Bellerby, R., Shen, F.,
Bruggeman, J., and Ding, P.: Influence of suspended sediment front on
nutrients and phytoplankton dynamics off the Changjiang Estuary: A
FVCOM-ERSEM coupled model experiment, J. Mar. Syst., 204,
103292, https://doi.org/10.1016/j.jmarsys.2019.103292, 2020. a
Gentile, E. S., Gray, S. L., Barlow, J. F., Lewis, H. W., and Edwards, J. M.:
The Impact of Atmosphere-Ocean-Wave Coupling on the Near-Surface Wind
Speed in Forecasts of Extratropical Cyclones, Bounda.-Lay. Meteorol., https://doi.org/10.1007/s10546-021-00614-4, 2021. a
Good, S. A., Martin, M. J., and Rayner, N. A.: EN4: Quality Controlled
Ocean Temperature and Salinity Profiles and Monthly Objective Analyses with
Uncertainty Estimates: THE EN4 DATA SET, J. Geophys. Res.-Oceans, 118, 6704–6716, https://doi.org/10.1002/2013JC009067, 2013. a
Graham, J. A., O'Dea, E., Holt, J., Polton, J., Hewitt, H. T., Furner, R., Guihou, K., Brereton, A., Arnold, A., Wakelin, S., Castillo Sanchez, J. M., and Mayorga Adame, C. G.: AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf, Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, 2018. a
Grant, A. L. M. and Belcher, S. E.: Characteristics of Langmuir Turbulence
in the Ocean Mixed Layer, J. Phys. Oceanogr., 39,
1871–1887, https://doi.org/10.1175/2009JPO4119.1, 2009. a
Greenberg, D. A., Dupont, F., Lyard, F. H., Lynch, D. R., and Werner, F. E.:
Resolution Issues in Numerical Models of Oceanic and Coastal Circulation,
Cont. Shelf Res., 27, 1317–1343, https://doi.org/10.1016/j.csr.2007.01.023,
2007. a
Griffies, S. M., Böning, C., Bryan, F. O., Chassignet, E. P., Gerdes, R.,
Hasumi, H., Hirst, A., Treguier, A.-M., and Webb, D.: Developments in Ocean
Climate Modelling, Ocean Model., 2, 123–192,
https://doi.org/10.1016/S1463-5003(00)00014-7, 2000. a
Griffiths, S. D.: Kelvin Wave Propagation along Straight Boundaries in
C-grid Finite-Difference Models, J. Computat. Phys., 255,
639–659, https://doi.org/10.1016/j.jcp.2013.08.040, 2013. a
Hacker, J. P., Exby, J., Gill, D., Jimenez, I., Maltzahn, C., See, T.,
Mullendore, G., and Fossell, K.: A Containerized Mesoscale Model and
Analysis Toolkit to Accelerate Classroom Learning, Collaborative Research,
and Uncertainty Quantification, B. Am. Meteor.
Soc., 98, 1129–1138, https://doi.org/10.1175/BAMS-D-15-00255.1, 2017. a
Haidvogel, D. B. and Beckmann, A.: Numerical Ocean Circulation Modeling, Imperial
College Press, Distributed by World Scientific Pub., London, River Edge,
NJ, ISBN 1-86094-114-1, 1999. a
Harley, M. D., Masselink, G., Ruiz de Alegría-Arzaburu, A., Valiente,
N. G., and Scott, T.: Single Extreme Storm Sequence Can Offset Decades of
Shoreline Retreat Projected to Result from Sea-Level Rise, Commun.
Earth Environ., 3, s43247-022-00437-2, https://doi.org/10.1038/s43247-022-00437-2, 2022. a
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P.,
Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R.,
Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del
Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P.,
Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant,
T. E.: Array programming with NumPy, Nature, 585, 357–362,
https://doi.org/10.1038/s41586-020-2649-2, 2020. a
Hashemi, M. R., Neill, S. P., and Davies, A. G.: A coupled tide-wave model for
the NW European shelf seas,
Geophys. Astro. Fluid,
109, 234–253, https://doi.org/10.1080/03091929.2014.944909, 2015. a
Hasselmann, K.: Wave-driven Inertial Oscillations,
Geophysical Fluid Dynamics,
1, 463–502, https://doi.org/10.1080/03091927009365783, 1970. a
Hinrichs, I., Gouretski, V., Pätsch, J., Emeis, K.-C., and Stammer, D.:
North Sea Biogeochemical Climatology (Version 1.1), World Data Center for Climate (WDCC) [data set],
https://doi.org/10.1594/WDCC/NSBClim_v1.1, 2017. a
Holt, J. and Proctor, R.: The Seasonal Circulation and Volume Transport on the
Northwest European Continental Shelf: A Fine-Resolution Model Study,
J. Geophys. Res., 113, C06021, https://doi.org/10.1029/2006JC004034,
2008. a
Holt, J., Harle, J., Proctor, R., Michel, S., Ashworth, M., Batstone, C.,
Allen, I., Holmes, R., Smyth, T., Haines, K., Bretherton, D., and Smith, G.:
Modelling the Global Coastal Ocean, Philos. T. Roy.
Soc. A, 367, 939–951,
https://doi.org/10.1098/rsta.2008.0210, 2009. a
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, b, c
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci.
Eng., 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. a
Huthnance, J. M.: Circulation, Exchange and Water Masses at the Ocean Margin:
The Role of Physical Processes at the Shelf Edge, Prog. Oceanogr.,
35, 353–431, 1995. a
Jardine, J., Katavouta, A., Polton, J., Holt, J., and Wakelin, S.:
NOC-MSM/SANH: South Asian Nitrogen Hub Regional Ocean Modelling.
NEMOv3.6, Zenodo [code], https://doi.org/10.5281/ZENODO.6423248, 2022. a, b, c
Joughin, I., Smith, B. E., and Holland, D. M.: Sensitivity of 21st century sea
level to ocean-induced thinning of Pine Island Glacier, Antarctica,
Geophys. Res. Lett., 37, L20502, https://doi.org/10.1029/2010GL044819, 2010. a
Kara, A. B., Wallcraft, A. J., and Hurlburt, H. E.: A New Solar Radiation
Penetration Scheme for Use in Ocean Mixed Layer Studies: An
Application to the Black Sea Using a Fine-Resolution Hybrid
Coordinate Ocean Model (HYCOM), J. Phys. Oceanogr., 35,
13–32, 2005. a
Kay, S., Clark, J., Hall, A., Marsh, J., and Fernandes, J.: Marine
biogeochemistry data for the Northwest European Shelf and Mediterranean Sea
from 2006 up to 2100 derived from climate projections, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set],
https://doi.org/10.24381/cds.dcc9295c, 2020. a
Komen, G. J., Cavaleri, L., Donelan, M., Hasselmann, K., Hasselmann, S., and
Janssen, P.: Dynamics and modelling of ocean waves, Cambridge University Press, ISBN 9780521577816, 1996. a
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
Large, W. G. and Yeager, S.: The global climatology of an interannually varying
air-sea flux data set, Clim. Dynam., 33, 341–364,
https://doi.org/10.1007/s00382-008-0441-3, 2009. a
Lear, D., Herman, P., Van Hoey, G., Schepers, L., Tonné, N., Lipizer, M.,
Muller-Karger, F., Appeltans, W., Kissling, W., Holdsworth, N., Edwards, M.,
Pecceu, E., Nygård, H., Canonico, G., Birchenough, S., Graham, G., Deneudt,
K., Claus, S., and Oset, P.: Supporting the essential – Recommendations for
the development of accessible and interoperable marine biological data
products, Mar. Policy, 117, 103958, https://doi.org/10.1016/j.marpol.2020.103958,
2020. a, b
Legg, S., Hallberg, R. W., and Girton, J. B.: Comparison of Entrainment in
Overflows Simulated by Z-Coordinate, Isopycnal and Non-Hydrostatic Models,
Ocean Model., 11, 69–97, https://doi.org/10.1016/j.ocemod.2004.11.006, 2006. a
Lewis, E. L. and Perkin, R. G.: Ice pumps and their rates, J. Geophys. Res., 91, 11756, https://doi.org/10.1029/JC091iC10p11756, 1986. a
Lewis, H. W., Castillo Sanchez, J. M., Arnold, A., Fallmann, J., Saulter, A., Graham, J., Bush, M., Siddorn, J., Palmer, T., Lock, A., Edwards, J., Bricheno, L., Martínez-de la Torre, A., and Clark, J.: The UKC3 regional coupled environmental prediction system, Geosci. Model Dev., 12, 2357–2400, https://doi.org/10.5194/gmd-12-2357-2019,
2019a. a, b, c
Lewis, H. W., Castillo Sanchez, J. M., Siddorn, J., King, R. R., Tonani, M., Saulter, A., Sykes, P., Pequignet, A.-C., Weedon, G. P., Palmer, T., Staneva, J., and Bricheno, L.: Can wave coupling improve operational regional ocean forecasts for the north-west European Shelf?, Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, 2019b. a
Li, X., Shokr, M., Hui, F., Chi, Z., Heil, P., Chen, Z., Yu, Y., Zhai, M., and
Cheng, X.: The spatio-temporal patterns of landfast ice in Antarctica during
2006–2011 and 2016–2017 using high-resolution SAR imagery, Remote Sens. Environ., 242, 111736,
https://doi.org/10.1016/j.rse.2020.111736, 2020. a
Liu, X., Dunne, J. P., Stock, C. A., Harrison, M. J., Adcroft, A., and
Resplandy, L.: Simulating Water Residence Time in the Coastal Ocean: A Global
Perspective, Geophys. Res. Lett., 46, 13910–13919,
https://doi.org/10.1029/2019GL085097, 2019. a
Longuet-Higgins, M. and Stewart, R.: Radiation stresses in water waves; a
physical discussion, with applications, Deep-Sea Res. Pt. I, 11, 529–562, https://doi.org/10.1016/0011-7471(64)90001-4,
1964. 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, b
Lévy, M., Gavart, M., Mémery, L., Caniaux, G., and Paci, A.: A
four-dimensional mesoscale map of the spring bloom in the northeast Atlantic
(POMME experiment): Results of a prognostic model, J. Geophys. Res.-Oceans, 110, C07S21, https://doi.org/10.1029/2004JC002588, 2005. a
Madec, G. and Team, N. S.: NEMO ocean engine, Zenodo [code], https://doi.org/10.5281/zenodo.1464816, 2022. a
Marchesiello, P., McWilliams, J. C., and Shchepetkin, A.: Open boundary
conditions for long-term integration of regional oceanic models, Ocean
Model., 3, 1–20, https://doi.org/10.1016/S1463-5003(00)00013-5, 2001. a
Marsh, R., Ivchenko, V. O., Skliris, N., Alderson, S., Bigg, G. R., Madec, G., Blaker, A. T., Aksenov, Y., Sinha, B., Coward, A. C., Le Sommer, J., Merino, N., and Zalesny, V. B.: NEMO–ICB (v1.0): interactive icebergs in the NEMO ocean model globally configured at eddy-permitting resolution, Geosci. Model Dev., 8, 1547–1562, https://doi.org/10.5194/gmd-8-1547-2015, 2015. a
Marshall, J., Adcroft, A., Hill, C., Perelman, L., and Heisey, C.: A
Finite-Volume, Incompressible Navier Stokes Model for Studies of the
Ocean on Parallel Computers, J. Geophys. Res.-Oceans, 102,
5753–5766, https://doi.org/10.1029/96JC02775, 1997. a
Masselink, G., Scott, T., Poate, T., Russell, P., Davidson, M., and Conley, D.:
The Extreme 2013/2014 Winter Storms: Hydrodynamic Forcing and Coastal
Response along the Southwest Coast of England,
Earth Surf. Proc. Land., 41, 378–391, https://doi.org/10.1002/esp.3836, 2016. a
Mathiot, P. and Hutchinson, K.: NEMO Demonstrator: Worked Example of
WED025, Zenodo [code], https://doi.org/10.5281/ZENODO.6817000, 2022. a, b
Mathiot, P., Jenkins, A., Harris, C., and Madec, G.: Explicit representation and parametrised impacts of under ice shelf seas in the z* coordinate ocean model NEMO 3.6, Geosci. Model Dev., 10, 2849–2874, https://doi.org/10.5194/gmd-10-2849-2017, 2017. a
Mayorga, E., Seitzinger, S. P., Harrison, J. A., Dumont, E., Beusen, A. H.,
Bouwman, A., Fekete, B. M., Kroeze, C., and Van Drecht, G.: Global Nutrient
Export from WaterSheds 2 (NEWS 2): Model development and implementation,
Environ. Model. Softw., 25, 837–853,
https://doi.org/10.1016/j.envsoft.2010.01.007, 2010. a
Mayorga Adame, C., Polton, J. A., Acevedo, S., and Holt, J.:
NOC-MSM/Belize_workshop: Belize Workshop (Regional NEMO
Ocean in Docker Container), Zenodo [code], https://doi.org/10.5281/ZENODO.6451433, 2022. a
McWilliams, J. C., Sullivan, P. P., and Moeng, C.-H.: Langmuir Turbulence in
the Ocean, J. Fluid Mech., 334, 1–30,
https://doi.org/10.1017/S0022112096004375, 1997. a
Mellor, G. L., Oey, L.-Y., and Ezer, T.: Sigma Coordinate Pressure Gradient
Errors and the Seamount Problem, J. Atmos. Ocean.
Tech., 15, 1122–1131,
https://doi.org/10.1175/1520-0426(1998)015<1122:SCPGEA>2.0.CO;2, 1998. a
Melton, J. R., Arora, V. K., Wisernig-Cojoc, E., Seiler, C., Fortier, M., Chan, E., and Teckentrup, L.: CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance, Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020, 2020. a
Merino, N., Le Sommer, J., Durand, G., Jourdain, N. C., Madec, G., Mathiot,
P., and Tournadre, J.: Antarctic icebergs melt over the Southern Ocean:
Climatology and impact on sea ice, Ocean Model., 104, 99–110,
https://doi.org/10.1016/j.ocemod.2016.05.001, 2016. a
Morlighem, M., Rignot, E., Binder, T., Blankenship, D., Drews, R., Eagles, G.,
Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., Goel, V., Greenbaum,
J. S., Gudmundsson, H., Guo, J., Helm, V., Hofstede, C., Howat, I., Humbert,
A., Jokat, W., Karlsson, N. B., Lee, W. S., Matsuoka, K., Millan, R.,
Mouginot, J., Paden, J., Pattyn, F., Roberts, J., Rosier, S., Ruppel, A.,
Seroussi, H., Smith, E. C., Steinhage, D., Sun, B., van den Broeke, M. R.,
van Ommen, T. D., van Wessem, M., and Young, D. A.: Deep glacial troughs and
stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet,
Nat. Geosci., 13, 132–137, https://doi.org/10.1038/s41561-019-0510-8, 2020. a
Myriokefalitakis, S., Ito, A., Kanakidou, M., Nenes, A., Krol, M. C., Mahowald, N. M., Scanza, R. A., Hamilton, D. S., Johnson, M. S., Meskhidze, N., Kok, J. F., Guieu, C., Baker, A. R., Jickells, T. D., Sarin, M. M., Bikkina, S., Shelley, R., Bowie, A., Perron, M. M. G., and Duce, R. A.: Reviews and syntheses: the GESAMP atmospheric iron deposition model intercomparison study, Biogeosciences, 15, 6659–6684, https://doi.org/10.5194/bg-15-6659-2018, 2018. a
NEMO Consortium: NEMO Development Strategy 2023–2027,
Zenodo [code], https://doi.org/10.5281/zenodo.7361464, 2022. a
Olsen, A., Key, R. M., van Heuven, S., Lauvset, S. K., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Pérez, F. F., and Suzuki, T.: The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean, Earth Syst. Sci. Data, 8, 297–323, https://doi.org/10.5194/essd-8-297-2016, 2016. a
Partridge, D.: ACCORD: Addressing Challenges of Coastal Communities through
Ocean Research for Developing Economies Regional Ocean Modelling
Biogeochemistry, Zenodo [code], https://doi.org/10.5281/zenodo.6940832, 2022a. a
Partridge, D.: SANH: South Asian Nitrogen Hub Regional Ocean Modelling
Biogeochemistry, Zenodo [code], https://doi.org/10.5281/zenodo.6907302, 2022b. a, b
Polton, J., Harle, J., de Dominicis, M., and Katavouta, A.:
NOC-MSM/SEAsia: SEAsia, Zenodo [code], https://doi.org/10.5281/ZENODO.6483233,
2022a. a, b, c, d
Polton, J. A., Byrne, D., Wise, A., Holt, J., Katavouta, A., Rulent, J., Gardner, T., Cazaly, M., Hearn, M., Jennings, R., Luong, Q., Loch, S., Gorman, L., and de Mora, L.: British-Oceanographic-Data-Centre/COAsT: v3.2.0 (v3.2.0), Zenodo [code], https://doi.org/10.5281/zenodo.7352697, 2022b. a
Polton, J. A. and Belcher, S. E.: Langmuir Turbulence and Deeply Penetrating
Jets in an Unstratified Mixed Layer, J. Geophys. Res., 112,
C09020, https://doi.org/10.1029/2007JC004205, 2007. a
Polton, J. A., Lewis, D. M., and Belcher, S. E.: The Role of Wave-Induced
Coriolis-Stokes Forcing on the Wind-Driven Mixed Layer,
J. Phys. Oceanogr., 35, 444–457, https://doi.org/10.1175/JPO2701.1,
2005. a
Polton, J. A., Brereton, A., and Holgate, S.: A NEMO Regional Model of the
Bay of Bengal and East Arabian Sea (BoBEAS) Implemented with
MPI across Docker Containers, Zenodo [code], https://doi.org/10.5281/ZENODO.6103525,
2020a. a, b
Polton, J. A., Wise, A., O'Neill, C. K., and O'Dea, E.: AMM7-surge: A
7km Resolution Atlantic Margin Model Surge Configuration Using
NEMOv3.6, Zenodo [code], https://doi.org/10.5281/ZENODO.4022310, 2020b. a
Ponte, R. M., Meyssignac, B., Domingues, C. M., Stammer, D., Cazenave, A., and
Lopez, T.: Guest editorial: relationships between coastal sea level and
large-scale ocean circulation, Surv. Geophys., 40, 1245–1249, 2019. a
Popova, E. E., Yool, A., Coward, A. C., Aksenov, Y. K., Alderson, S. G., de Cuevas, B. A., and Anderson, T. R.: Control of primary production in the Arctic by nutrients and light: insights from a high resolution ocean general circulation model, Biogeosciences, 7, 3569–3591, https://doi.org/10.5194/bg-7-3569-2010, 2010. a
Porter, A. R., Appleyard, J., Ashworth, M., Ford, R. W., Holt, J., Liu, H., and Riley, G. D.: Portable multi- and many-core performance for finite-difference or finite-element codes – application to the free-surface component of NEMO (NEMOLite2D 1.0), Geosci. Model Dev., 11, 3447–3464, https://doi.org/10.5194/gmd-11-3447-2018, 2018. a
Primo, C., Kelemen, F. D., Feldmann, H., Akhtar, N., and Ahrens, B.: A regional atmosphere–ocean climate system model (CCLMv5.0clm7-NEMOv3.3-NEMOv3.6) over Europe including three marginal seas: on its stability and performance, Geosci. Model Dev., 12, 5077–5095, https://doi.org/10.5194/gmd-12-5077-2019, 2019. a
Resplandy, L., Lévy, M., Bopp, L., Echevin, V., Pous, S., Sarma, V. V. S. S., and Kumar, D.: Controlling factors of the oxygen balance in the Arabian Sea's OMZ, Biogeosciences, 9, 5095–5109, https://doi.org/10.5194/bg-9-5095-2012, 2012. a
Richon, C., Dutay, J.-C., Dulac, F., Wang, R., and Balkanski, Y.: Modeling the biogeochemical impact of atmospheric phosphate deposition from desert dust and combustion sources to the Mediterranean Sea, Biogeosciences, 15, 2499–2524, https://doi.org/10.5194/bg-15-2499-2018, 2018. a
Rignot, E., Jacobs, S., Mouginot, J., and Scheuchl, B.: Ice-shelf melting
around antarctica, Science, 341, 266–270, https://doi.org/10.1126/science.1235798, 2013. a, b
Rulent, J.: NOC-MSM/SRIL34, Zenodo [code], https://doi.org/10.5281/zenodo.7464071, 2022. a
Sankar, S., Polimene, L., Marin, L., Menon, N., Samuelsen, A., Pastres, R., and
Ciavatta, S.: Sensitivity of the simulated Oxygen Minimum Zone to
biogeochemical processes at an oligotrophic site in the Arabian Sea,
Ecol. Model., 372, 12–23,
https://doi.org/10.1016/j.ecolmodel.2018.01.016, 2018. a
Sathyendranath, S., Brewin, R., Brockmann, C., Brotas, V., Calton, B., Chuprin,
A., Cipollini, P., Couto, A., Dingle, J., Doerffer, R., Donlon, C., Dowell,
M., Farman, A., Grant, M., Groom, S., Horseman, A., Jackson, T., Krasemann,
H., Lavender, S., Martinez-Vicente, V., Mazeran, C., Mélin, F., Moore, T.,
Müller, D., Regner, P., Roy, S., Steele, C., Steinmetz, F., Swinton, J.,
Taberner, M., Thompson, A., Valente, A., Zühlke, M., Brando, V., Feng, H.,
Feldman, G., Franz, B., Frouin, R., Gould, Jr., R., Hooker, S., Kahru, M.,
Kratzer, S., Mitchell, B., Muller-Karger, F., Sosik, H., Voss, K., Werdell,
J., and Platt, T.: An ocean-colour time series for use in climate studies:
the experience of the Ocean-Colour Climate Change Initiative (OC-CCI),
Sensors, 19, 4285, https://doi.org/10.3390/s19194285, 2019. a
Scambos, T. A., Bohlander, J. A., Shuman, C. A., and Skvarca, P.: Glacier
acceleration and thinning after ice shelf collapse in the Larsen B embayment,
Antarctica, Geophys. Res. Lett., 31, 2001–2004,
https://doi.org/10.1029/2004GL020670, 2004. a
Shchepetkin, A. F. and McWilliams, J. C.: The Regional Oceanic Modeling System
(ROMS): A Split-Explicit, Free-Surface, Topography-Following-Coordinate
Oceanic Model, Ocean Model., 9, 347–404,
https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012. a
Smith, R. S., Mathiot, P., Siahaan, A., Lee, V., Cornford, S. L., Gregory,
J. M., Payne, A. J., Jenkins, A., Holland, P. R., Ridley, J. K., and Jones,
C. G.: Coupling the U.K. Earth System Model to dynamic models of the
Greenland and Antarctic ice sheets,
J. Adv. Model. Earth Sy., e2021MS002520, https://doi.org/10.1029/2021MS002520, 2021. a
Soontiens, N. and Allen, S. E.: Modelling Sensitivities to Mixing and Advection
in a Sill-Basin Estuarine System, Ocean Model., 112, 17–32,
https://doi.org/10.1016/j.ocemod.2017.02.008, 2017. a
Stern, A. A., Adcroft, A., and Sergienko, O.: The effects of Antarctic iceberg
calving-size distribution in a global climate model, J. Geophys.
Res.-Oceans, 121, 5773–5788, https://doi.org/10.1002/2016JC011835, 2016. a
Stokes, G. G.: On the Theory of Oscillatory Waves,
Transactions of the Cambridge Philosophical Society, 8, 441–455, 1847. a
Storkey, D., Blaker, A. T., Mathiot, P., Megann, A., Aksenov, Y., Blockley, E. W., Calvert, D., Graham, T., Hewitt, H. T., Hyder, P., Kuhlbrodt, T., Rae, J. G. L., and Sinha, B.: UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions, Geosci. Model Dev., 11, 3187–3213, https://doi.org/10.5194/gmd-11-3187-2018, 2018. a, b
Tan, J., Fu, J. S., Dentener, F., Sun, J., Emmons, L., Tilmes, S., Sudo, K., Flemming, J., Jonson, J. E., Gravel, S., Bian, H., Davila, Y., Henze, D. K., Lund, M. T., Kucsera, T., Takemura, T., and Keating, T.: Multi-model study of HTAP II on sulfur and nitrogen deposition, Atmos. Chem. Phys., 18, 6847–6866, https://doi.org/10.5194/acp-18-6847-2018, 2018. a
Tolman, H. L., Balasubramaniyan, B., Burroughs, L. D., Chalikov, D. V., Chao,
Y. Y., Chen, H. S., and Gerald, V. M.: Development and implementation of
wind-generated ocean surface wave Modelsat NCEP, Weather Forecast., 17,
311–333, 2002. a
Trotta, F., Fenu, E., Pinardi, N., Bruciaferri, D., Giacomelli, L., Federico,
I., and Coppini, G.: A Structured and Unstructured Grid Relocatable Ocean
Platform for Forecasting (SURF), Physical, Chemical and Biological
Observations and Modelling of Oil Spills in the Mediterranean Sea, 133,
54–75, https://doi.org/10.1016/j.dsr2.2016.05.004, 2016. a
Trotta, F., Federico, I., Pinardi, N., Coppini, G., Causio, S., Jansen, E.,
Iovino, D., and Masina, S.: A Relocatable Ocean Modeling Platform for
Downscaling to Shelf-Coastal Areas to Support Disaster Risk Reduction,
Front. Mar. Sci., 8, 642815, https://doi.org/10.3389/fmars.2021.642815, 2021. a, b
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G.,
Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C. W.,
Bozec, A., Chassignet, E. P., Curchitser, E., Boeira Dias, F., Durack,
P. J., Griffies, S. M., Harada, Y., Ilicak, M., Josey, S. A., Kobayashi, C.,
Kobayashi, S., Komuro, Y., Large, W. G., Le Sommer, J., Marsland, S. J.,
Masina, S., Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.:
JRA-55 based surface dataset for driving ocean-sea-ice models (JRA55-do),
Ocean Model., 130, 79–139, https://doi.org/10.1016/j.ocemod.2018.07.002, 2018. a, b
Valcke, S., T., C., and L., C.: OASIS3-MCT User Guide, CERFACS, Technical
Report, TR/CMGC/15/38, https://www.cerfacs.fr/oa4web/oasis3-mct_3.0/oasis3mct_UserGuide.pdf (last access: 20 February 2022), 2015. a
Valiente, N. G., Saulter, A., Edwards, J. M., Lewis, H. W., Sanchez, J. M.,
Bruciaferri, D., Bunney, C., and Siddorn, J.: The impact of wave model
source terms and coupling strategies to rapidly developing waves across the
north‐west european shelf during extreme events,
Journal of Marine Science and Engineering, 9, 403, https://doi.org/10.3390/jmse9040403, 2021. a
Wakelin, S. L., Artioli, Y., Holt, J. T., Butenschön, M., and Blackford,
J.: Controls on Near-Bed Oxygen Concentration on the Northwest European
Continental Shelf under a Potential Future Climate Scenario, Prog.
Oceanogr., 187, 102400, https://doi.org/10.1016/j.pocean.2020.102400, 2020. a
Wang, S., Dieterich, C., Döscher, R., Höglund, A., Hordoir, R., Meier, H.
E. M., Samuelsson, P., and Schimanke, S.: Development and evaluation of a new
regional coupled atmosphere-ocean model in the North Sea and Baltic Sea,
Tellus A, 67, 24284,
https://doi.org/10.3402/tellusa.v67.24284, 2015. a, b
Wilson, C., Harle, D. J., and Wakelin, D. S.: NEMO Regional Configuration
of the Caribbean, Zenodo [code], https://doi.org/10.5281/ZENODO.3228088, 2019. a, b
Wise, A., Harle, J., Bruciaferri, D., O'Dea, E., and Polton, J.: The Effect of
Vertical Coordinates on the Accuracy of a Shelf Sea Model, Ocean Model.,
170, 101935, https://doi.org/10.1016/j.ocemod.2021.101935, 2022. a, b, c
Wobus, F., Shapiro, G. I., Huthnance, J. M., and Maqueda, M. A.: The Piercing
of the Atlantic Layer by an Arctic Shelf Water Cascade in an
Idealised Study Inspired by the Storfjorden Overflow in Svalbard,
Ocean Model., 71, 54–65, https://doi.org/10.1016/j.ocemod.2013.03.003, 2013. a
Yool, A., Popova, E. E., and Anderson, T. R.: Medusa-1.0: a new intermediate complexity plankton ecosystem model for the global domain, Geosci. Model Dev., 4, 381–417, https://doi.org/10.5194/gmd-4-381-2011, 2011. a
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies, Geosci. Model Dev., 6, 1767–1811, https://doi.org/10.5194/gmd-6-1767-2013, 2013. a
Zektser, I. and Loaiciga, H. A.: Groundwater Fluxes in the Global Hydrologic
Cycle: Past, Present and Future, J. Hydrol., 144, 405–427,
https://doi.org/10.1016/0022-1694(93)90182-9, 1993.
a
Zhao, N. and Nasuno, T.: How Does the Air-Sea Coupling Frequency Affect
Convection During the MJO Passage?, J. Adv. Model. Earth Sy., 12, e2020MS002058, https://doi.org/10.1029/2020MS002058,
2020. a
Executive editor
Reproducibility is fundamental to the scientific method, but really reproducible computational science at the scale of ocean modelling is far from universal. This manuscript addresses the question of what it takes for regional ocean simulations to be reproducible. It should act as a reference point for that community and beyond.
Reproducibility is fundamental to the scientific method, but really reproducible computational...
Short summary
The aim is to increase the capacity of the modelling community to respond to societally important questions that require ocean modelling. The concept of reproducibility for regional ocean modelling is developed: advocating methods for reproducible workflows and standardised methods of assessment. Then, targeting the NEMO framework, we give practical advice and worked examples, highlighting key considerations that will the expedite development cycle and upskill the user community.
The aim is to increase the capacity of the modelling community to respond to societally...
Special issue