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.
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
Preprint under review for BG
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1731, https://doi.org/10.5194/egusphere-2023-1731, 2023
Short summary
Short summary
This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used for UK contributions to CMIP7. Documentation of physical 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 of how SI3 was adapted to work with Met Office coupling methodology, along with thorough documentation of coupling processes in the model.
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.
Hannah Chawner, Karina E. Adcock, Tim Arnold, Yuri Artioli, Caroline Dylag, Grant L. Forster, Anita Ganesan, Heather Graven, Gennadi Lessin, Peter Levy, Ingrid T. Luijx, Alistair Manning, Penelope A. Pickers, Chris Rennick, Christian Rödenbeck, and Matthew Rigby
EGUsphere, https://doi.org/10.5194/egusphere-2023-385, https://doi.org/10.5194/egusphere-2023-385, 2023
Short summary
Short summary
As O2 is uptaken during combustion it can be used to trace fossil fuel (ff) emissions. We combine CO2 and O2 to minimise the biospheric impact using a quantity called atmospheric potential oxygen (APO), providing a method to isolate ff emissions. We model APO and compare with observations, focusing mainly on a site in Norfolk, UK. We attempt to use this to estimate emissions of ffCO2. We find large uncertainty in oceanic O2 emissions estimates, impacting both our model and estimates of ffCO2.
Giovanni Galli, Sarah Wakelin, James Harle, Jason Holt, and Yuri Artioli
EGUsphere, https://doi.org/10.5194/egusphere-2023-1049, https://doi.org/10.5194/egusphere-2023-1049, 2023
Short summary
Short summary
In this work we looked at the projected change in bottom water oxygen content in an ensemble of ocean climate change models of the North Western European Shelf. What emerged is that, 1. oxygen decreases in all models, 2. in the models with the most warming, a change in circulation patterns is tied to the emergence of low oxygen hotspots in the Eastern North Sea, and, 3. in relatively shallow coastal areas increasing in primary production partially mitigates oxygen decline.
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.
Lee de Mora, Ranjini Swaminathan, Richard P. Allan, Jeremy Blackford, Douglas I. Kelley, Phil Harris, Chris D. Jones, Colin G. Jones, Spencer Liddicoat, Robert J. Parker, Tristan Quaife, Jeremy Walton, and Andrew Yool
EGUsphere, https://doi.org/10.5194/egusphere-2022-1483, https://doi.org/10.5194/egusphere-2022-1483, 2023
Short summary
Short summary
We investigated the flux of carbon from the atmosphere into the land surface and the ocean for multiple models and over a range of future scenarios. We did this by comparing simulations after the same amount of change in the global mean near surface temperature. Using this method, we show that the choice of scenario can have a big impact. Scenarios with higher emissions reach the same warming levels sooner, but also with relatively more carbon in the atmosphere.
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.
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.
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
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
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 1: Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Impact of high resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
The Met Office operational wave forecasting system: the evolution of the regional and global models
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
Development and validation of a global 1∕32° surface-wave–tide–circulation coupled ocean model: FIO-COM32
Barotropic tides in MPAS-Ocean (E3SM V2): impact of ice shelf cavities
Using the two-way nesting technique AGRIF with MARS3D V11.2 to improve hydrodynamics and estimate environmental indicators
Multidecadal and climatological surface current simulations for the southwestern Indian Ocean at 1∕50° resolution
The tidal effects in the Finite-volumE Sea ice–Ocean Model (FESOM2.1): a comparison between parameterised tidal mixing and explicit tidal forcing
HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic
Moana Ocean Hindcast – a > 25-year simulation for New Zealand waters using the Regional Ocean Modeling System (ROMS) v3.9 model
A nonhydrostatic oceanic regional model, ORCTM v1, for internal solitary wave simulation
How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9
An ensemble Kalman filter-based ocean data assimilation system improved by adaptive observation error inflation (AOEI)
GULF18, a high-resolution NEMO-based tidal ocean model of the Arabian/Persian Gulf
The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment
An ensemble Kalman filter system with the Stony Brook Parallel Ocean Model v1.0
Wind work at the air-sea interface: a modeling study in anticipation of future space missions
Improved upper-ocean thermodynamical structure modeling with combined effects of surface waves and M2 internal tides on vertical mixing: a case study for the Indian Ocean
The bulk parameterizations of turbulent air–sea fluxes in NEMO4: the origin of sea surface temperature differences in a global model study
NeverWorld2: an idealized model hierarchy to investigate ocean mesoscale eddies across resolutions
Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current
Parallel implementation of the SHYFEM (System of HydrodYnamic Finite Element Modules) model
Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)
Evaluation of an emergent feature of sub-shelf melt oscillations from an idealized coupled ice sheet–ocean model using FISOC (v1.1) – ROMSIceShelf (v1.0) – Elmer/Ice (v9.0)
GNOM v1.0: an optimized steady-state model of the modern marine neodymium cycle
Implementation and evaluation of open boundary conditions for sea ice in a regional coupled ocean (ROMS) and sea ice (CICE) modeling system
ROMSPath v1.0: offline particle tracking for the Regional Ocean Modeling System (ROMS)
DINCAE 2.0: multivariate convolutional neural network with error estimates to reconstruct sea surface temperature satellite and altimetry observations
RADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU Octave
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
Short summary
Short summary
We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
Short summary
Short summary
We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
Short summary
Short summary
While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
Short summary
Short summary
Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
Short summary
Short summary
Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
Short summary
Short summary
This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
Short summary
Short summary
A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
Short summary
Short summary
The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
Short summary
Short summary
While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
Short summary
Short summary
We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
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.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
Short summary
Short summary
We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-123, https://doi.org/10.5194/gmd-2023-123, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
High resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least the same important for obtaining faithful simulations.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
Short summary
Short summary
In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
Short summary
Short summary
Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
Short summary
Short summary
An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
Short summary
Short summary
Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
Short summary
Short summary
MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
Short summary
Short summary
Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
Short summary
Short summary
The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
Short summary
Short summary
We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
Short summary
Short summary
4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
Short summary
Short summary
A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Nairita Pal, Kristin N. Barton, Mark R. Petersen, Steven R. Brus, Darren Engwirda, Brian K. Arbic, Andrew F. Roberts, Joannes J. Westerink, and Damrongsak Wirasaet
Geosci. Model Dev., 16, 1297–1314, https://doi.org/10.5194/gmd-16-1297-2023, https://doi.org/10.5194/gmd-16-1297-2023, 2023
Short summary
Short summary
Understanding tides is essential to accurately predict ocean currents. Over the next several decades coastal processes such as flooding and erosion will be severely impacted due to climate change. Tides affect currents along the coastal regions the most. In this paper we show the results of implementing tides in a global ocean model known as MPAS–Ocean. We also show how Antarctic ice shelf cavities affect global tides. Our work points towards future research with tide–ice interactions.
Sébastien Petton, Valérie Garnier, Matthieu Caillaud, Laurent Debreu, and Franck Dumas
Geosci. Model Dev., 16, 1191–1211, https://doi.org/10.5194/gmd-16-1191-2023, https://doi.org/10.5194/gmd-16-1191-2023, 2023
Short summary
Short summary
The nesting AGRIF library is implemented in the MARS3D hydrodynamic model, a semi-implicit, free-surface numerical model which uses a time scheme as an alternating-direction implicit (ADI) algorithm. Two applications at the regional and coastal scale are introduced. We compare the two-nesting approach to the classic offline one-way approach, based on an in situ dataset. This method is an efficient means to significantly improve the physical hydrodynamics and unravel ecological challenges.
Noam S. Vogt-Vincent and Helen L. Johnson
Geosci. Model Dev., 16, 1163–1178, https://doi.org/10.5194/gmd-16-1163-2023, https://doi.org/10.5194/gmd-16-1163-2023, 2023
Short summary
Short summary
Ocean currents transport things over large distances across the ocean surface. Predicting this transport is key for tackling many environmental problems, such as marine plastic pollution and coral reef resilience. However, doing this requires a good understanding ocean currents, which is currently lacking. Here, we present and validate state-of-the-art simulations for surface currents in the southwestern Indian Ocean, which will support future marine dispersal studies across this region.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
Short summary
Short summary
Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
Short summary
Short summary
We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Joao Marcos Azevedo Correia de Souza, Sutara H. Suanda, Phellipe P. Couto, Robert O. Smith, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 211–231, https://doi.org/10.5194/gmd-16-211-2023, https://doi.org/10.5194/gmd-16-211-2023, 2023
Short summary
Short summary
The current paper describes the configuration and evaluation of the Moana Ocean Hindcast, a > 25-year simulation of the ocean state around New Zealand using the Regional Ocean Modeling System v3.9. This is the first open-access, long-term, continuous, realistic ocean simulation for this region and provides information for improving the understanding of the ocean processes that affect the New Zealand exclusive economic zone.
Hao Huang, Pengyang Song, Shi Qiu, Jiaqi Guo, and Xueen Chen
Geosci. Model Dev., 16, 109–133, https://doi.org/10.5194/gmd-16-109-2023, https://doi.org/10.5194/gmd-16-109-2023, 2023
Short summary
Short summary
The Oceanic Regional Circulation and Tide Model (ORCTM) is developed to reproduce internal solitary wave dynamics. The three-dimensional nonlinear momentum equations are involved with the nonhydrostatic pressure obtained via solving the Poisson equation. The validation experimental results agree with the internal wave theories and observations, demonstrating that the ORCTM can successfully describe the life cycle of nonlinear internal solitary waves under different oceanic environments.
David E. Gwyther, Shane R. Keating, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 157–178, https://doi.org/10.5194/gmd-16-157-2023, https://doi.org/10.5194/gmd-16-157-2023, 2023
Short summary
Short summary
Ocean eddies are important for weather, climate, biology, navigation, and search and rescue. Since eddies change rapidly, models that incorporate or assimilate observations are required to produce accurate eddy timings and locations, yet the model accuracy is rarely assessed below the surface. We use a unique type of ocean model experiment to assess three-dimensional eddy structure in the East Australian Current and explore two pathways in which this subsurface structure is being degraded.
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi
Geosci. Model Dev., 15, 9057–9073, https://doi.org/10.5194/gmd-15-9057-2022, https://doi.org/10.5194/gmd-15-9057-2022, 2022
Short summary
Short summary
An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.
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.
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, https://doi.org/10.5194/gmd-15-8613-2022, 2022
Short summary
Short summary
Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410, https://doi.org/10.5194/gmd-15-8395-2022, https://doi.org/10.5194/gmd-15-8395-2022, 2022
Short summary
Short summary
We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
Hector S. Torres, Patrice Klein, Jinbo Wang, Alexander Wineteer, Bo Qiu, Andrew F. Thompson, Lionel Renault, Ernesto Rodriguez, Dimitris Menemenlis, Andrea Molod, Christopher N. Hill, Ehud Strobach, Hong Zhang, Mar Flexas, and Dragana Perkovic-Martin
Geosci. Model Dev., 15, 8041–8058, https://doi.org/10.5194/gmd-15-8041-2022, https://doi.org/10.5194/gmd-15-8041-2022, 2022
Short summary
Short summary
Wind work at the air-sea interface is the scalar product of winds and currents and is the transfer of kinetic energy between the ocean and the atmosphere. Using a new global coupled ocean-atmosphere simulation performed at kilometer resolution, we show that all scales of winds and currents impact the ocean dynamics at spatial and temporal scales. The consequential interplay of surface winds and currents in the numerical simulation motivates the need for a winds and currents satellite mission.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
Short summary
Short summary
We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
Giulia Bonino, Doroteaciro Iovino, Laurent Brodeau, and Simona Masina
Geosci. Model Dev., 15, 6873–6889, https://doi.org/10.5194/gmd-15-6873-2022, https://doi.org/10.5194/gmd-15-6873-2022, 2022
Short summary
Short summary
The sea surface temperature (SST) is highly influenced by the transfer of energy driven by turbulent air–sea fluxes (TASFs). In the NEMO ocean general circulation model, TASFs are computed by means of bulk formulas. Bulk formulas require the choice of a given bulk parameterization, which influences the magnitudes of the TASFs. Our results show that parameterization-related SST differences are primarily sensitive to the wind stress differences across parameterizations.
Gustavo M. Marques, Nora Loose, Elizabeth Yankovsky, Jacob M. Steinberg, Chiung-Yin Chang, Neeraja Bhamidipati, Alistair Adcroft, Baylor Fox-Kemper, Stephen M. Griffies, Robert W. Hallberg, Malte F. Jansen, Hemant Khatri, and Laure Zanna
Geosci. Model Dev., 15, 6567–6579, https://doi.org/10.5194/gmd-15-6567-2022, https://doi.org/10.5194/gmd-15-6567-2022, 2022
Short summary
Short summary
We present an idealized ocean model configuration and a set of simulations performed using varying horizontal grid spacing. While the model domain is idealized, it resembles important geometric features of the Atlantic and Southern oceans. The simulations described here serve as a framework to effectively study mesoscale eddy dynamics, to investigate the effect of mesoscale eddies on the large-scale dynamics, and to test and evaluate eddy parameterizations.
David E. Gwyther, Colette Kerry, Moninya Roughan, and Shane R. Keating
Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022, https://doi.org/10.5194/gmd-15-6541-2022, 2022
Short summary
Short summary
The ocean current flowing along the southeastern coast of Australia is called the East Australian Current (EAC). Using computer simulations, we tested how surface and subsurface observations might improve models of the EAC. Subsurface observations are particularly important for improving simulations, and if made in the correct location and time, can have impact 600 km upstream. The stability of the current affects model estimates could be capitalized upon in future observing strategies.
Giorgio Micaletto, Ivano Barletta, Silvia Mocavero, Ivan Federico, Italo Epicoco, Giorgia Verri, Giovanni Coppini, Pasquale Schiano, Giovanni Aloisio, and Nadia Pinardi
Geosci. Model Dev., 15, 6025–6046, https://doi.org/10.5194/gmd-15-6025-2022, https://doi.org/10.5194/gmd-15-6025-2022, 2022
Short summary
Short summary
The full exploitation of supercomputing architectures requires a deep revision of the current climate models. This paper presents the parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). Optimized numerical libraries were used to partition the model domain and solve the sparse linear system of equations in parallel. The performance assessment demonstrates a good level of scalability with a realistic configuration used as a benchmark.
Young-Kwang Choi, Fengyan Shi, Matt Malej, Jane M. Smith, James T. Kirby, and Stephan T. Grilli
Geosci. Model Dev., 15, 5441–5459, https://doi.org/10.5194/gmd-15-5441-2022, https://doi.org/10.5194/gmd-15-5441-2022, 2022
Short summary
Short summary
The multi-grid-nesting technique is an important methodology used for modeling transoceanic tsunamis and coastal effects. In this study, we developed a two-way nesting interface in a multi-grid-nesting system for the Boussinesq wave model FUNWAVE-TVD. The interface acts as a
backboneof the nesting framework, handling data input, output, time sequencing, and internal interactions between grids at different scales.
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022, https://doi.org/10.5194/gmd-15-5421-2022, 2022
Short summary
Short summary
We use a coupled ice–ocean model to explore an oscillation feature found in several contributing models to MISOMIP1. The oscillation is closely related to the discretized grounding line retreat and likely strengthened by the buoyancy–melt feedback and/or melt–geometry feedback near the grounding line, and frequent ice–ocean coupling. Our model choices have a non-trivial impact on mean melt and ocean circulation strength, which might be interesting for the coupled ice–ocean community.
Benoît Pasquier, Sophia K. V. Hines, Hengdi Liang, Yingzhe Wu, Steven L. Goldstein, and Seth G. John
Geosci. Model Dev., 15, 4625–4656, https://doi.org/10.5194/gmd-15-4625-2022, https://doi.org/10.5194/gmd-15-4625-2022, 2022
Short summary
Short summary
Neodymium isotopes in seawater have the potential to provide key information about ocean circulation, both today and in the past. This can shed light on the underlying drivers of global climate, which will improve our ability to predict future climate change, but uncertainties in our understanding of neodymium cycling have limited use of this tracer. We present a new model of neodymium in the modern ocean that runs extremely fast, matches observations, and is freely available for development.
Pedro Duarte, Jostein Brændshøi, Dmitry Shcherbin, Pauline Barras, Jon Albretsen, Yvonne Gusdal, Nicholas Szapiro, Andreas Martinsen, Annette Samuelsen, Keguang Wang, and Jens Boldingh Debernard
Geosci. Model Dev., 15, 4373–4392, https://doi.org/10.5194/gmd-15-4373-2022, https://doi.org/10.5194/gmd-15-4373-2022, 2022
Short summary
Short summary
Sea ice models are often implemented for very large domains beyond the regions of sea ice formation, such as the whole Arctic or all of Antarctica. In this study, we implement changes in the Los Alamos Sea Ice Model, allowing it to be implemented for relatively small regions within the Arctic or Antarctica and yet considering the presence and influence of sea ice outside the represented areas. Such regional implementations are important when spatially detailed results are required.
Elias J. Hunter, Heidi L. Fuchs, John L. Wilkin, Gregory P. Gerbi, Robert J. Chant, and Jessica C. Garwood
Geosci. Model Dev., 15, 4297–4311, https://doi.org/10.5194/gmd-15-4297-2022, https://doi.org/10.5194/gmd-15-4297-2022, 2022
Short summary
Short summary
ROMSPath is an offline particle tracking model tailored for use with output from Regional Ocean Modeling System (ROMS) simulations. It is an update to an established system, the Lagrangian TRANSport (LTRANS) model, including a number of improvements. These include a modification of the model coordinate system which improved accuracy and numerical efficiency, and added functionality for nested grids and Stokes drift.
Alexander Barth, Aida Alvera-Azcárate, Charles Troupin, and Jean-Marie Beckers
Geosci. Model Dev., 15, 2183–2196, https://doi.org/10.5194/gmd-15-2183-2022, https://doi.org/10.5194/gmd-15-2183-2022, 2022
Short summary
Short summary
Earth-observing satellites provide routine measurement of several ocean parameters. However, these datasets have a significant amount of missing data due to the presence of clouds or other limitations of the employed sensors. This paper describes a method to infer the value of the missing satellite data based on a convolutional autoencoder (a specific type of neural network architecture). The technique also provides a reliable error estimate of the interpolated value.
Olivier Sulpis, Matthew P. Humphreys, Monica M. Wilhelmus, Dustin Carroll, William M. Berelson, Dimitris Menemenlis, Jack J. Middelburg, and Jess F. Adkins
Geosci. Model Dev., 15, 2105–2131, https://doi.org/10.5194/gmd-15-2105-2022, https://doi.org/10.5194/gmd-15-2105-2022, 2022
Short summary
Short summary
A quarter of the surface of the Earth is covered by marine sediments rich in calcium carbonates, and their dissolution acts as a giant antacid tablet protecting the ocean against human-made acidification caused by massive CO2 emissions. Here, we present a new model of sediment chemistry that incorporates the latest experimental findings on calcium carbonate dissolution kinetics. This model can be used to predict how marine sediments evolve through time in response to environmental perturbations.
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