Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6177-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-6177-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
15 Oct 2021
Model description paper |
| 15 Oct 2021
| 15 Oct 2021
S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Jennifer K. McWhorter
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
School of Biological Sciences, the University of Queensland, Brisbane,
Queensland, Australia
Beatriz Arellano Nava
College of Life and Environmental Sciences, University of Exeter,
Exeter, UK
Robert Marsh
University of Southampton, National Oceanography Centre, Southampton,
UK
William Skirving
Coral Reef Watch, National Oceanic and Atmospheric Administration,
College Park, MD, USA
ReefSense Pty Ltd, Cranbrook, Queensland, Australia
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The difficulties in ameliorating global warming and the associated climate change via conventional mitigation are well documented, with all climate model scenarios exceeding 1.5 °C above the preindustrial level in the near future. There is therefore a growing interest in geoengineering to reflect a greater proportion of sunlight back to space and offset some of the global warming. We use a state-of-the-art Earth-system model to investigate two of the most prominent geoengineering strategies.
George Manville, Thomas G. Bell, Jane P. Mulcahy, Rafel Simó, Martí Galí, Anoop S. Mahajan, Shrivardhan Hulswar, and Paul R. Halloran
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We present the first global investigation of controls on seawater dimethylsulfide (DMS) spatial variability over scales of up to 100 km. Sea surface height anomalies, density, and chlorophyll a help explain almost 80 % of DMS variability. The results suggest that physical and biogeochemical processes play an equally important role in controlling DMS variability. These data provide independent confirmation that existing parameterisations of seawater DMS concentration use appropriate variables.
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The third climatological estimation of sea surface dimethyl sulfide (DMS) concentrations based on in situ measurements was created (DMS-Rev3). The update includes a much larger input dataset and includes improvements in the data unification, filtering, and smoothing algorithm. The DMS-Rev3 climatology provides more realistic monthly estimates of DMS, and shows significant regional differences compared to past climatologies.
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
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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.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
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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
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J. H. T. Williams, I. J. Totterdell, P. R. Halloran, and P. J. Valdes
Geosci. Model Dev., 7, 1419–1431, https://doi.org/10.5194/gmd-7-1419-2014, https://doi.org/10.5194/gmd-7-1419-2014, 2014
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Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, https://doi.org/10.5194/bg-10-6225-2013, 2013
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This preprint is open for discussion and under review for Ocean Science (OS).
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Melissa Wood, Ivan D. Haigh, Quan Quan Le, Hung Nghia Nguyen, Hoang Ba Tran, Stephen E. Darby, Robert Marsh, Nikolaos Skliris, and Joël J.-M. Hirschi
Nat. Hazards Earth Syst. Sci., 24, 3627–3649, https://doi.org/10.5194/nhess-24-3627-2024, https://doi.org/10.5194/nhess-24-3627-2024, 2024
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Vasilis Dakos, Chris A. Boulton, Joshua E. Buxton, Jesse F. Abrams, Beatriz Arellano-Nava, David I. Armstrong McKay, Sebastian Bathiany, Lana Blaschke, Niklas Boers, Daniel Dylewsky, Carlos López-Martínez, Isobel Parry, Paul Ritchie, Bregje van der Bolt, Larissa van der Laan, Els Weinans, and Sonia Kéfi
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George Manville, Thomas G. Bell, Jane P. Mulcahy, Rafel Simó, Martí Galí, Anoop S. Mahajan, Shrivardhan Hulswar, and Paul R. Halloran
Biogeosciences, 20, 1813–1828, https://doi.org/10.5194/bg-20-1813-2023, https://doi.org/10.5194/bg-20-1813-2023, 2023
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We present the first global investigation of controls on seawater dimethylsulfide (DMS) spatial variability over scales of up to 100 km. Sea surface height anomalies, density, and chlorophyll a help explain almost 80 % of DMS variability. The results suggest that physical and biogeochemical processes play an equally important role in controlling DMS variability. These data provide independent confirmation that existing parameterisations of seawater DMS concentration use appropriate variables.
Shrivardhan Hulswar, Rafel Simó, Martí Galí, Thomas G. Bell, Arancha Lana, Swaleha Inamdar, Paul R. Halloran, George Manville, and Anoop Sharad Mahajan
Earth Syst. Sci. Data, 14, 2963–2987, https://doi.org/10.5194/essd-14-2963-2022, https://doi.org/10.5194/essd-14-2963-2022, 2022
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Emma L. Worthington, Ben I. Moat, David A. Smeed, Jennifer V. Mecking, Robert Marsh, and Gerard D. McCarthy
Ocean Sci., 17, 285–299, https://doi.org/10.5194/os-17-285-2021, https://doi.org/10.5194/os-17-285-2021, 2021
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Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-16, https://doi.org/10.5194/bg-2019-16, 2019
Revised manuscript not accepted
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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.
Robert Marsh, Ivan D. Haigh, Stuart A. Cunningham, Mark E. Inall, Marie Porter, and Ben I. Moat
Ocean Sci., 13, 315–335, https://doi.org/10.5194/os-13-315-2017, https://doi.org/10.5194/os-13-315-2017, 2017
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To the west of Britain and Ireland, a strong ocean current follows the steep slope that separates the deep Atlantic and the continental shelf. This “Slope Current” exerts an Atlantic influence on the North Sea and its ecosystems. Using a combination of computer modelling and archived data, we find that the Slope Current weakened over 1988–2007, reducing Atlantic influence on the North Sea, due to a combination of warming of the subpolar North Atlantic and weakening winds to the west of Scotland.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
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This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
R. Marsh, A. E. Hickman, and J. Sharples
Geosci. Model Dev., 8, 3163–3178, https://doi.org/10.5194/gmd-8-3163-2015, https://doi.org/10.5194/gmd-8-3163-2015, 2015
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Our relatively shallow shelf seas are warmed at the surface in spring and summer, while strong tidal currents act to mix away the surface warmth. These competing effects strongly influence the conditions for seasonal growth of the phytoplankton that support marine food webs. We have developed a versatile framework for fast computer modelling of shelf seas, to explore seasonal and year-to-year variations of warming and plankton productivity, tested against observations in different regions.
P. R. Halloran, B. B. B. Booth, C. D. Jones, F. H. Lambert, D. J. McNeall, I. J. Totterdell, and C. Völker
Biogeosciences, 12, 4497–4508, https://doi.org/10.5194/bg-12-4497-2015, https://doi.org/10.5194/bg-12-4497-2015, 2015
Short summary
Short summary
The oceans currently take up around a quarter of the carbon dioxide (CO2) emitted by human activity. While stored in the ocean, this CO2 is not causing global warming. Here we explore high latitude North Atlantic CO2 uptake across a set of climate model simulations, and find that the models show a peak in ocean CO2 uptake around the middle of the century after which time CO2 uptake begins to decline. We identify the causes of this long-term change and interannual variability in the models.
R. Marsh, V. O. Ivchenko, N. Skliris, S. Alderson, G. R. Bigg, G. Madec, A. T. Blaker, Y. Aksenov, B. Sinha, A. C. Coward, J. Le Sommer, N. Merino, and V. B. Zalesny
Geosci. Model Dev., 8, 1547–1562, https://doi.org/10.5194/gmd-8-1547-2015, https://doi.org/10.5194/gmd-8-1547-2015, 2015
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Calved icebergs account for around 50% of total freshwater input to the ocean from the Greenland and Antarctic ice sheets. As they melt, icebergs interact with the ocean. We have developed and tested interactive icebergs in a state-of-the-art global ocean model, showing how sea ice, temperatures, and currents are disturbed by iceberg melting. With this new model capability, we are better prepared to predict how future increases in iceberg numbers might influence the oceans and climate.
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
J. H. T. Williams, I. J. Totterdell, P. R. Halloran, and P. J. Valdes
Geosci. Model Dev., 7, 1419–1431, https://doi.org/10.5194/gmd-7-1419-2014, https://doi.org/10.5194/gmd-7-1419-2014, 2014
L. Bopp, L. Resplandy, J. C. Orr, S. C. Doney, J. P. Dunne, M. Gehlen, P. Halloran, C. Heinze, T. Ilyina, R. Séférian, J. Tjiputra, and M. Vichi
Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, https://doi.org/10.5194/bg-10-6225-2013, 2013
O. D. Andrews, N. L. Bindoff, P. R. Halloran, T. Ilyina, and C. Le Quéré
Biogeosciences, 10, 1799–1813, https://doi.org/10.5194/bg-10-1799-2013, https://doi.org/10.5194/bg-10-1799-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
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This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev., 18, 211–237, https://doi.org/10.5194/gmd-18-211-2025, https://doi.org/10.5194/gmd-18-211-2025, 2025
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We developed a 3D ocean model called the Hindcast of the Salish Sea (HOTSSea v1) that recreates physical conditions throughout the Salish Sea from 1980 to 2018. It was not clear that acceptable accuracy could be achieved because of computational and data limitations, but the model's predictions agreed well with observations. When we used the model to examine ocean temperature trends in areas that lack observations, it indicated that some seasons and areas are warming faster than others.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 2024
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We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the ocean capture of atmospheric carbon dioxide, which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
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Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
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We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
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We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
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Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Axelle Gaffet, Xavier Bertin, Damien Sous, Héloïse Michaud, Aron Roland, and Emmanuel Cordier
EGUsphere, https://doi.org/10.5194/egusphere-2024-2610, https://doi.org/10.5194/egusphere-2024-2610, 2024
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This study presents a new global wave model that improves predictions of sea-states in tropical areas. By employing advanced techniques to correct wind field errors and simulate distant swells, our new global wave model allows for the first time direct comparisons in shallow waters close to shore. The model's predictions were validated both globally using satellite data and nearshore with data collected around several tropical islands.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
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Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
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We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
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Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
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Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
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Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
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Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
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Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
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The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
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The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
EGUsphere, https://doi.org/10.5194/egusphere-2024-2281, https://doi.org/10.5194/egusphere-2024-2281, 2024
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Vertical mixing is an important process e.g. for tropical sea surface temperature, but cannot be resolved by ocean models. Comparisons of mixing schemes and settings have usually been done with a single model, sometimes yielding conflicting results. We systematically compare two widely used schemes, TKE and KPP, with different parameter settings, in two different ocean models, and show that most effects from mixing scheme parameter changes are model dependent.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
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Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-128, https://doi.org/10.5194/gmd-2024-128, 2024
Revised manuscript accepted for GMD
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A coupled fine-resolution ocean-ice model is developed for the Ross Sea and adjacent regions in Antarctica, a key area for the formation of global ocean bottom water — the Antarctic Bottom Water (AABW) that affects the world ocean circulation. The model has high skills in simulating sea ice production driving the AABW source water formation and water mass properties when assessed against observations. A model experiment shows significant impact of ice shelf melting on the AABW characteristics.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
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This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
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We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-16, https://doi.org/10.5194/gmd-2024-16, 2024
Revised manuscript accepted for GMD
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Most of the tools available to model sediment transport do not account for complex physical mechanisms such as surface wave driven processes. In this study, a new model sedInterFoam allows to reproduce numerically complex configurations to investigate coastal sediment transport applications dominated by surface waves and gain insight into the complex physical processes associated with breaking waves and morphodynamics.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
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Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
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The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
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In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
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., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
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
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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.
Cited articles
Amante, C. and Eakins, B. W.: ETOPO1 1 Arc-Minute Global Relief Model:
Procedures, Data Sources and Analysis, NOAA Tech. Memo., NESDIS NGDC-24,
https://doi.org/10.1594/PANGAEA.769615, 2009.
Australian Institute of Marine Science (AIMS): NRSYON: Northern Australia Automated Marine Weather and Oceanographic Stations, Sites: [Yongala], https://doi.org/10.25845/5c09bf93f315d, 2020.
Bahamondes Dominguez, A. A., Hickman, A. E., Marsh, R., and Moore, C. M.: Constraining the response of phytoplankton to zooplankton grazing and photo-acclimation in a temperate shelf sea with a 1-D model – towards S2P3 v8.0, Geosci. Model Dev., 13, 4019–4040, https://doi.org/10.5194/gmd-13-4019-2020, 2020.
Barnes, M. K., Tilstone, G. H., Suggett, D. J., Widdicombe, C. E., Bruun,
J., Martinez-Vicente, V., and Smyth, T. J.: Temporal variability in total,
micro- and nano-phytoplankton primary production at a coastal site in the
Western English Channel, Prog. Oceanogr., 137 (Part B), 470–483,
https://doi.org/10.1016/j.pocean.2015.04.017, 2015.
Beaman, R.: Project 3DGBR: a high-resolution depth model for the Great
Barrier Reef and Coral Sea, MTSRF Final Report Project 2.5i.1a, Reef and Rainforest Research Centre MTSRF Final Report Marine and Tropical Sciences Research Facility, James Cook University, available at: https://www.deepreef.org/images/stories/publications/reports/Project3DGBRFinal_RRRC2010.pdf (last access: 1 July 2021), 2010.
Booth, B. B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., and
Bellouin, N.: Erratum: Aerosols implicated as a prime driver of
twentieth-century North Atlantic climate variability, Nature, 484,
228–232, https://doi.org/10.1038/nature11138, 2012.
Bowen, B. W., Gaither, M. R., DiBattista, J. D., Iacchei, M., Andrews, K.
R., Grant, W. S., Toonen, R. J., and Briggs, J. C.: Comparative
phylogeography of the ocean planet, P. Natl. Acad. Sci. USA, 113, 7962–7969,
https://doi.org/10.1073/pnas.1602404113, 2016.
Canuto, V. M., Howard, A., Cheng, Y., and Dubovikov, M. S.: Ocean
turbulence. Part I: One-point closure model-momentum and heat vertical
diffusivities, J. Phys. Oceanogr., 31, 1413–1426,
https://doi.org/10.1175/1520-0485(2001)031<1413:OTPIOP>2.0.CO;2, 2001.
Capuzzo, E., Lynam, C. P., Barry, J., Stephens, D., Forster, R. M.,
Greenwood, N., McQuatters-Gollop, A., Silva, T., van Leeuwen, S. M., and
Engelhard, G. H.: A decline in primary production in the North Sea over 25
years, associated with reductions in zooplankton abundance and fish stock
recruitment, Glob. Chang. Biol., 24, e352–e364, https://doi.org/10.1111/gcb.13916, 2018.
Chen, T., Rossow, W. B., and Zhang, Y.: Radiative effects of cloud-type
variations, J. Climate, 13, 264–286, https://doi.org/10.1175/1520-0442(2000)013<0264:REOCTV>2.0.CO;2, 2000.
Chiswell, S. M.: Annual cycles and spring blooms in phytoplankton: Don't
abandon Sverdrup completely, Mar. Ecol. Prog. Ser., 443, 39–50,
https://doi.org/10.3354/meps09453, 2011.
Chiswell, S. M., Calil, P. H. R., and Boyd, P. W.: Spring blooms and annual
cycles of phytoplankton: A unified perspective, J. Plankton Res., 37, 500–508,
https://doi.org/10.1093/plankt/fbv021, 2015.
Darecki, M. and Stramski, D.: An evaluation of MODIS and SeaWiFS bio-optical
algorithms in the Baltic Sea, Remote Sens. Environ., 89, 326–350,
https://doi.org/10.1016/j.rse.2003.10.012, 2004.
Doney, S. C.: The Growing Human Footprint on Coastal and Open-Ocean Biogeochemistry, Science, 328, 1512–1516, https://doi.org/10.1126/science.1185198, 2010.
Donner, S. D., Skirving, W. J., Little, C. M., Oppenheimer, M., and
Hoegh-Gulberg, O.: Global assessment of coral bleaching and required rates
of adaptation under climate change, Glob. Chang. Biol., 11, 2251–2265,
https://doi.org/10.1111/j.1365-2486.2005.01073.x, 2005.
Dooley, H. D.: Hypotheses concerning the circulation of the northern North
Sea, ICES J. Mar. Sci., 36, 54–61, https://doi.org/10.1093/icesjms/36.1.54, 1974.
Egbert, G. D. and Erofeeva, S. Y.: Efficient inverse modeling of barotropic
ocean tides, J. Atmos. Ocean. Technol., 19, 183–204,
https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2, 2002.
Findlay, H. S., Yool, A., Nodale, M., and Pitchford, J. W.: Modelling of
autumn plankton bloom dynamics, J. Plankton Res., 28, 209–220,
https://doi.org/10.1093/plankt/fbi114, 2006.
Furnas, M. J. and Mitchell, A. W.: Phytoplankton dynamics in the central
Great Barrier Reef-I. Seasonal changes in biomass and community structure
and their relation to intrusive activity, Cont. Shelf Res., 6, 363–384,
https://doi.org/10.1016/0278-4343(86)90078-6, 1986.
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, J. Geophys. Res. Ocean., 118, 6704–6716,
https://doi.org/10.1002/2013JC009067, 2013.
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.
Halloran, P.: PaulHalloran/S2P3Rv2.0: S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales SUBMISSION (v1.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.4147559, 2020a.
Halloran, P.: S2P3Rv2.0 bias data, Zenodo [data set], https://doi.org/10.5281/zenodo.4018815, 2020b.
Haywood, J. and Boucher, O.: Estimates of the direct and indirect radiative
forcing due to tropospheric aerosols: A review, Rev. Geophys., 38, 513–543,
https://doi.org/10.1029/1999RG000078, 2000.
Hersbach, H., De Rosnay, P., Bell, B., Schepers, D., Simmons, A., Soci, C.,
Abdalla, S., Balmaseda, A., Balsamo, G., Bechtold, P., Berrisford, P.,
Bidlot, J., De Boisséson, E., Bonavita, M., Browne, P., Buizza, R.,
Dahlgren, P., Dee, D., Dragani, R., Diamantakis, M., Flemming, J., Forbes,
R., Geer, A., Haiden, T., Hólm, E., Haimberger, L., Hogan, R.,
Horányi, A., Janisková, M., Laloyaux, P., Lopez, P.,
Muñoz-Sabater, J., Peubey, C., Radu, R., Richardson, D., Thépaut,
J.-N., Vitart, F., Yang, X., Zsótér, E., and Zuo, H.: Operational
global reanalysis: progress, future directions and synergies with NWP
including updates on the ERA5 production status, ERA Rep. Ser., Document Number 27,
https://doi.org/10.21957/tkic6g3wm, 2018.
Hersbach, H., Bell, B., Berrisford, P., Horányi, A., Sabater, J. M.,
Nicolas, J., Radu, R., Schepers, D., Simmons, A., Soci, C., and Dee, D.:
Global reanalysis: goodbye ERA-Interim, hello ERA5, ECMWF Newsl., Newsletter number 159, pp. 17–24,
https://doi.org/10.21957/vf291hehd7, 2019.
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. Trans. R. Soc. A, 367, 939–951, https://doi.org/10.1098/rsta.2008.0210, 2009.
Holt, J., Butenschön, M., Wakelin, S. L., Artioli, Y., and Allen, J. I.: Oceanic controls on the primary production of the northwest European continental shelf: model experiments under recent past conditions and a potential future scenario, Biogeosciences, 9, 97–117, https://doi.org/10.5194/bg-9-97-2012, 2012.
Integrated Marine Observing System (IMOS): GBRHIS: Heron Island South Shelf Mooring component of the GBR Mooring Array, available at: https://apps.aims.gov.au/metadata/view/9a19eaa5-6069-4ed6-b004-5f7590664881, (last access: 21 September 2021), 2009a.
Integrated Marine Observing System (IMOS): GBRLSH: Lizard Island Shelf Mooring component of the GBR Mooring Array, available at: https://apps.aims.gov.au/metadata/view/ee39900f-141e-43a6-8261-0164267c8f95 (last access: 21 September 2021), 2009b.
Integrated Marine Observing System (IMOS): GBROTE: One Tree Island Shelf Mooring component of the GBR Mooring Array, available at: https://apps.aims.gov.au/metadata/view/05c9319d-ebde-4ba5-8c25-08ea82cbe77f (last access: 21 September 2021), 2009c.
Integrated Marine Observing System (IMOS): GBRPPS: Palm Passage Shelf Mooring component of the GBR Mooring Array, available at: https://apps.aims.gov.au/metadata/view/11c307bd-89bf-4616-b3df-52645ca56b6e (last access: 21 September 2021), 2009d.
Integrated Marine Observing System (IMOS): IMOS – ANMN National Reference Station (NRS) Ningaloo Mooring (NRSNIN), available at: https://apps.aims.gov.au/metadata/view/a581c961-8632-497f-bc5e-2002957577ec (last access: 21 September 2021), 2017.
Integrated Marine Observing System (IMOS): Facility for the Automated
Intelligent Monitoring of Marine Systems – FAIMMS, available at: https://apps.aims.gov.au/metadata/view/d63dc150-0d02-11dd-bbbb-00008a07204e, last access: 1 July 2021.
Kwiatkowski, L., Halloran, P. R., Mumby, P. J., and Stephenson, D. B.: What
spatial scales are believable for climate model projections of sea surface
temperature?, Clim. Dynam., 43, 1483–1496, https://doi.org/10.1007/s00382-013-1967-6,
2014.
Lenhart, H. J., Radach, G., and Ruardij, P.: The effects of river input on
the ecosystem dynamics in the continental coastal zone of the North Sea
using ERSEM, J. Sea Res., 38, 249–274, https://doi.org/10.1016/S1385-1101(97)00049-X,
1997.
Levitus, S.: Climatological Atlas of the World Ocean, EOS, 64, 962–963, https://doi.org/10.1029/EO064i049p00962-02, 1983.
Marsh, R., Hickman, A. E., and Sharples, J.: S2P3-R (v1.0): a framework for efficient regional modelling of physical and biological structures and processes in shelf seas, Geosci. Model Dev., 8, 3163–3178, https://doi.org/10.5194/gmd-8-3163-2015, 2015.
Marsh, R., Haigh, I. D., Cunningham, S. A., Inall, M. E., Porter, M., and Moat, B. I.: Large-scale forcing of the European Slope Current and associated inflows to the North Sea, Ocean Sci., 13, 315–335, https://doi.org/10.5194/os-13-315-2017, 2017.
Merchant, C. J., Embury, O., Bulgin, C. E., Block, T., Corlett, G. K.,
Fiedler, E., Good, S. A., Mittaz, J., Rayner, N. A., Berry, D., Eastwood,
S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., and Donlon, C.:
Satellite-based time-series of sea-surface temperature since 1981 for
climate applications, Sci. data, 6, 223, https://doi.org/10.1038/s41597-019-0236-x,
2019.
Mora, C., Wei, C.-L., Rollo, A., Amaro, T., Baco, A. R., Billett, D., Bopp,
L., Chen, Q., Collier, M., Danovaro, R., Gooday, A. J., Grupe, B. M.,
Halloran, P. R., Ingels, J., Jones, D. O. B., Levin, L. A., Nakano, H.,
Norling, K., Ramirez-Llodra, E., Rex, M., Ruhl, H. A., Smith, C. R.,
Sweetman, A. K., Thurber, A. R., Tjiputra, J. F., Usseglio, P., Watling, L.,
Wu, T., and Yasuhara, M.: Biotic and Human Vulnerability to Projected
Changes in Ocean Biogeochemistry over the 21st Century, PLoS Biol., 11, e1001682,
https://doi.org/10.1371/journal.pbio.1001682, 2013.
Sathyendranath, S., Brewin, R. J. W., Brockmann, C., Brotas, V., Calton, B.,
Chuprin, A., Cipollini, P., Couto, A. B., 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. S., Müller, D., Regner, P., Roy, S., Steele, C. J.,
Steinmetz, F., Swinton, J., Taberner, M., Thompson, A., Valente, A.,
Zühlke, M., Brando, V. E., Feng, H., Feldman, G., Franz, B. A., Frouin,
R., Gould, R. W., Hooker, S. B., Kahru, M., Kratzer, S., Mitchell, B. G.,
Muller-Karger, F. E., Sosik, H. M., Voss, K. J., 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.
Sathyendranath, S., Jackson, T., Brockmann, C., Brotas, V., Calton, B.,
Chuprin, A., Clements, O., Cipollini, P., Danne, O., Dingle, J., Donlon, C.,
Grant, M., Groom, S., Krasemann, H., Lavender, S., Mazeran, C., Mélin,
F., Moore, T. S., Müller, D., Regner, P., Steinmetz, F., Steele, C.,
Swinton, J., Valente, A., Zühlke, M., Feldman, G., Franz, B., Frouin,
R., Werdell, J., and Platt, T.: ESA Ocean Colour Climate Change Initiative
(Ocean_Colour_cci): Global chlorophyll-a data
products gridded on a sinusoidal projection, Version 4.2, Cent. Environ.
Data Anal., Centre for Environmental Data Analysis, available at:
https://catalogue.ceda.ac.uk/uuid/99348189bd33459cbd597a58c30d8d10 (last access: 1 August 2021),
2020.
Sharples, J.: Potential impacts of the spring-neap tidal cycle on shelf sea
primary production, J. Plankton Res., 12, S12–S28, https://doi.org/10.1093/plankt/fbm088,
2008.
Sharples, J., Ross, O. N., Scott, B. E., Greenstreet, S. P. R., and Fraser,
H.: Inter-annual variability in the timing of stratification and the spring
bloom in the North-western North Sea, Cont. Shelf Res., 26, 733–751,
https://doi.org/10.1016/j.csr.2006.01.011, 2006.
Sheehan, P. M. F., Berx, B., Gallego, A., Hall, R. A., Heywood, K. J., and
Queste, B. Y.: Weekly variability of hydrography and transport of
northwestern inflows into the northern North Sea, J. Mar. Syst., 204, 103288,
https://doi.org/10.1016/j.jmarsys.2019.103288, 2020.
Simpson, J. H. and Sharples, J.: Introduction to the Physical and Biological
Oceanography of Shelf Seas, Cambridge University Press, https://doi.org/10.1017/cbo9781139034098, 2012.
Sivyer: Cefas SmartBuoy Monitoring Network, Cefas [data set],
https://doi.org/10.14466/CefasDataHub.10, 2016.
Skirving, W., Heron, M., and Heron, S.: The hydrodynamics of a bleaching
event: Implications for management and monitoring, Coral Reefs and Climate Change: Science and Management, 61,
available at: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/61CE09 (last access: 1 July 2021), 2011.
Smith, S. D. and Banke, E. G.: Variation of the sea surface drag coefficient
with wind speed, Q. J. Roy. Meteor. Soc., 101, 665–673,
https://doi.org/10.1002/qj.49710142920, 1975.
Smyth, T., Atkinson, A., Widdicombe, S., Frost, M., Allen, I., Fishwick, J.,
Queiros, A., Sims, D., and Barange, M.: The Western Channel Observatory, 137, 335–341,
https://doi.org/10.1016/j.pocean.2015.05.020, 2015.
Song, H., Ji, R., Stock, C., Kearney, K., and Wang, Z.: Interannual
variability in phytoplankton blooms and plankton productivity over the Nova
Scotian Shelf and in the Gulf of Maine, Mar. Ecol. Prog. Ser., 426, 105–118,
https://doi.org/10.3354/meps09002, 2011.
Steven, A. D. L., Baird, M. E., Brinkman, R., Car, N. J., Cox, S. J.,
Herzfeld, M., Hodge, J., Jones, E., King, E., Margvelashvili, N., Robillot,
C., Robson, B., Schroeder, T., Skerratt, J., Tickell, S., Tuteja, N.,
Wild-Allen, K., and Yu, J.: eReefs: An operational information system for
managing the Great Barrier Reef, J. Oper. Oceanogr., 12, S12–S28,
https://doi.org/10.1080/1755876X.2019.1650589, 2019.
Sverdrup, H. U.: On conditions for the vernal blooming of phytoplankton,
ICES J. Mar. Sci., 18, 287–295, https://doi.org/10.1093/icesjms/18.3.287, 1953.
Tinker, J. P. and Howes, E. L.: The impacts of climate change on temperature (air and sea), relevant to the coastal and marine environment around the UK, MCCIP Science Review 2020, available at: http://marine.gov.scot/sma/content/impacts-climate-change-temperature-air-and-sea-relevant-coastal-and-marine-environment (last access: 1 July 2021), 2020.
van der Molen, J., Ruardij, P., and Greenwood, N.: A 3D SPM model for
biogeochemical modelling, with application to the northwest European
continental shelf, J. Sea Res., 127, 63–81,
https://doi.org/10.1016/j.seares.2016.12.003, 2017.
Van Hooidonk, R., Maynard, J., Tamelander, J., Gove, J., Ahmadia, G.,
Raymundo, L., Williams, G., Heron, S. F., and Planes, S.: Local-scale
projections of coral reef futures and implications of the Paris Agreement,
Sci. Rep., 6, 39666, https://doi.org/10.1038/srep39666, 2016.
Wafar, M. V. M., Le Corre, P., and Birrien, J. L.: Nutrients and primary
production in permanently well-mixed temperate coastal waters, Estuar.
Coast. Shelf Sci., 17, 431–446, https://doi.org/10.1016/0272-7714(83)90128-2, 1983.
Short summary
This paper describes the latest version of a simple model for simulating coastal oceanography in response to changes in weather and climate. The latest revision of this model makes scientific improvements but focuses on improvements that allow the model to be run simply at large scales and for long periods of time to explore the implications of (for example) future climate change along large areas of coastline.
This paper describes the latest version of a simple model for simulating coastal oceanography in...
