Articles | Volume 17, issue 10
https://doi.org/10.5194/gmd-17-4095-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-4095-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
26 May 2024
Model evaluation paper |
| 26 May 2024
| 26 May 2024
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI 02912, USA
Baylor Fox-Kemper
Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI 02912, USA
Nobuhiro Suzuki
Institute of Coastal Ocean Dynamics, Helmholtz-Zentrum Hereon, Geesthacht, Germany
Earth, Ocean and Atmospheric Sciences Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 511400, Guangdong, China
Patrick Marchesiello
Institute of Research for Development, LEGOS, Toulouse, France
Peter P. Sullivan
National Center for Atmospheric Research, Boulder, Colorado, USA
Paul S. Hall
Department of Earth, Environmental, and Planetary Sciences, Brown University, Providence, RI 02912, USA
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Peter W. Thorne, John M. Nicklas, John J. Kennedy, Bruce Calvert, Baylor Fox-Kemper, Mark T. Richardson, Adrian Simmons, Ed Hawkins, Robert Rhode, Kathryn Cowtan, Nerilie J. Abram, Axel Andersson, Simon Noone, Phillipe Marbaix, Nathan Lenssen, Dirk Olonscheck, Tristram Walsh, Stephen Outten, Ingo Bethke, Bjorn H. Samset, Chris Smith, Anna Pirani, Jan Fuglestvedt, Lavanya Rajamani, Richard A. Betts, Elizabeth C. Kent, Blair Trewin, Colin Morice, Tim Osborn, Samantha N. Burgess, Oliver Geden, Andrew Parnell, Piers M. Forster, Chris Hewitt, Zeke Hausfather, Valerie Masson-Delmotte, Jochem Marotzke, Nathan Gillett, Sonia I. Seneviratne, Gavin A. Schmidt, Duo Chan, Stefan Brönnimann, Andy Reisinger, Matthew Menne, Maisa Rojas Corradi, Christopher Kadow, Peter Huybers, David B. Stephenson, Emily Wallis, Joeri Rogelj, Andrew Schurer, Karen McKinnon, Panmao Zhai, Fatima Driouech, Wilfran Moufouma Okia, Saeed Vazifehkhah, Sophie Szopa, Christopher J. Merchant, Shoji Hirahara, Masayoshi Ishii, Francois A. Engelbrecht, Qingxiang Li, June-Yi Lee, Alex J. Cannon, Christophe Cassou, Karina von Schuckmann, Amir H. Delju, and Ellie Murtagh
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-825, https://doi.org/10.5194/essd-2025-825, 2026
Preprint under review for ESSD
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We reassess the basis for determining the present level of long-term global warming. Unbiased estimates of both realised warming and anthropogenic warming are possible that approximate a 20-year retrospective mean. Our resulting estimates of 1.40 [1.23–1.58] °C (realised) and 1.34 [1.18–1.50] °C (anthropogenic) as at end of 2024 highlight the urgency of immediate, far-reaching and sustained climate mitigation actions if we are to meet the long term temperature goal of the Paris Agreement.
Peter Van Katwyk, Baylor Fox-Kemper, Sophie Nowicki, Hélène Seroussi, and Karianne J. Bergen
EGUsphere, https://doi.org/10.5194/egusphere-2025-4914, https://doi.org/10.5194/egusphere-2025-4914, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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We developed ISEFlow, a new climate emulator model that predicts how melting ice sheets in Greenland and Antarctica will contribute to future sea levels. Unlike past tools, it uses advanced machine learning to capture complex ice processes, distinguish between different greenhouse gas scenarios, and provide clearer estimates of uncertainty. This makes sea level projections more accurate and reliable, helping scientists and policymakers better plan for climate risks.
Baylor Fox-Kemper, Patricia DeRepentigny, Anne Marie Treguier, Christian Stepanek, Eleanor O’Rourke, Chloe Mackallah, Alberto Meucci, Yevgeny Aksenov, Paul J. Durack, Nicole Feldl, Vanessa Hernaman, Céline Heuzé, Doroteaciro Iovino, Gaurav Madan, André L. Marquez, François Massonnet, Jenny Mecking, Dhrubajyoti Samanta, Patrick C. Taylor, Wan-Ling Tseng, and Martin Vancoppenolle
EGUsphere, https://doi.org/10.5194/egusphere-2025-3083, https://doi.org/10.5194/egusphere-2025-3083, 2025
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The earth system model variables needed for studies of the ocean and sea ice are prioritized and requested.
Peter Van Katwyk, Baylor Fox-Kemper, Sophie Nowicki, Hélène Seroussi, and Karianne J. Bergen
EGUsphere, https://doi.org/10.5194/egusphere-2025-870, https://doi.org/10.5194/egusphere-2025-870, 2025
Preprint archived
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We present ISEFlow, a machine learning emulator that predicts how the melting of the Antarctic and Greenland ice sheets will contribute to sea level. ISEFlow is fast and accurate, allowing scientists to explore different climate scenarios with greater confidence. ISEFlow distinguishes between high and low emissions scenarios, helping us understand how today’s choices impact future sea levels. ISEFlow supports more reliable climate predictions and helps scientists study the future of ice sheets.
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.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872, https://doi.org/10.5194/gmd-16-3849-2023, https://doi.org/10.5194/gmd-16-3849-2023, 2023
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The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
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
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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.
Takaya Uchida, Julien Le Sommer, Charles Stern, Ryan P. Abernathey, Chris Holdgraf, Aurélie Albert, Laurent Brodeau, Eric P. Chassignet, Xiaobiao Xu, Jonathan Gula, Guillaume Roullet, Nikolay Koldunov, Sergey Danilov, Qiang Wang, Dimitris Menemenlis, Clément Bricaud, Brian K. Arbic, Jay F. Shriver, Fangli Qiao, Bin Xiao, Arne Biastoch, René Schubert, Baylor Fox-Kemper, William K. Dewar, and Alan Wallcraft
Geosci. Model Dev., 15, 5829–5856, https://doi.org/10.5194/gmd-15-5829-2022, https://doi.org/10.5194/gmd-15-5829-2022, 2022
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Ocean and climate scientists have used numerical simulations as a tool to examine the ocean and climate system since the 1970s. Since then, owing to the continuous increase in computational power and advances in numerical methods, we have been able to simulate increasing complex phenomena. However, the fidelity of the simulations in representing the phenomena remains a core issue in the ocean science community. Here we propose a cloud-based framework to inter-compare and assess such simulations.
Xue Zheng, Qing Li, Tian Zhou, Qi Tang, Luke P. Van Roekel, Jean-Christophe Golaz, Hailong Wang, and Philip Cameron-Smith
Geosci. Model Dev., 15, 3941–3967, https://doi.org/10.5194/gmd-15-3941-2022, https://doi.org/10.5194/gmd-15-3941-2022, 2022
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We document the model experiments for the future climate projection by E3SMv1.0. At the highest future emission scenario, E3SMv1.0 projects a strong surface warming with rapid changes in the atmosphere, ocean, sea ice, and land runoff. Specifically, we detect a significant polar amplification and accelerated warming linked to the unmasking of the aerosol effects. The impact of greenhouse gas forcing is examined in different climate components.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
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The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Qing Li, Jorn Bruggeman, Hans Burchard, Knut Klingbeil, Lars Umlauf, and Karsten Bolding
Geosci. Model Dev., 14, 4261–4282, https://doi.org/10.5194/gmd-14-4261-2021, https://doi.org/10.5194/gmd-14-4261-2021, 2021
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Different ocean vertical mixing schemes are usually developed in different modeling framework, making the comparison across such schemes difficult. Here, we develop a consistent framework for testing, comparing, and applying different ocean mixing schemes by integrating CVMix into GOTM, which also extends the capability of GOTM towards including the effects of ocean surface waves. A suite of test cases and toolsets for developing and evaluating ocean mixing schemes is also described.
Qing Li and Luke Van Roekel
Geosci. Model Dev., 14, 2011–2028, https://doi.org/10.5194/gmd-14-2011-2021, https://doi.org/10.5194/gmd-14-2011-2021, 2021
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Physical processes in the ocean span multiple spatial and temporal scales. Simultaneously resolving all these in a simulation is computationally challenging. Here we develop a more efficient technique to better study the interactions across scales, particularly focusing on the ocean surface turbulent mixing, by coupling a global ocean circulation model MPAS-Ocean and a large eddy simulation model PALM. The latter is customized and ported on a GPU to further accelerate the computation.
Cited articles
Auclair, F., Bordois, L., Dossmann, Y., Duhaut, T., Paci, A., Ulses, C., and Nguyen, C.: A non-hydrostatic non-Boussinesq algorithm for free-surface ocean modelling, Ocean Model., 132, 12–29, https://doi.org/10.1016/j.ocemod.2018.07.011, 2018. a, b
Auclair, F., Benshila, R., Capet, X., Debreu, L., Dumas, F., Jullien, S., and Marchesiello, P.: Coastal and Regional Ocean COmmunity model, https://www.croco-ocean.org/, last access: 8 May 2024. a
Bachman, S. D., Fox-Kemper, B., and Pearson, B.: A Scale-Aware Subgrid Model for Quasigeostrophic Turbulence, J. Geophys. Res.-Oceans, 122, 1529–1554, https://doi.org/10.1002/2016JC012265, 2017. a
Beets, C. and Koren, B.: Large-eddy simulation with accurate implicit subgrid-scale diffusion, Department of Numerical Mathematics Rep., NM-R9601, pp. 24, 1996. a
Borges, R., Carmona, M., Costa, B., and Don, W. S.: An improved weighted essentially non-oscillatory scheme for hyperbolic conservation laws, J. Comput. Phys., 227, 3191–3211, https://doi.org/10.1016/j.jcp.2007.11.038, 2008. a
Computational and Information Systems Laboratory: Cheyenne: HPE/SGI ICE XA System (Climate Simulation Laboratory), National Center for Atmospheric Research, Boulder, Colorado, https://doi.org/10.5065/D6RX99HX, 2019. a
Deardorff, J. W.: Stratocumulus-Capped Mixed Layers Derived from a Three-Dimensional Model, Bound.-Lay. Meteorol., 18, 495–527, https://doi.org/10.1007/BF00119502, 1980. a, b
Debreu, L., Auclair, F., Benshila, R., Capet, X., Dumas, F., Julien, S., and Marchesiello, P.: Multiresolution in CROCO (Coastal and Regional Ocean Community model), in: EGU General Assembly Conference Abstracts, EGU2016-15272-1, 2016. a
Fan, X., Fox-Kemper, B., Suzuki, N., Li, Q., Marchesiello, P., Auclair, F., Sullivan, P., and Hall, P.: CROCO code as used in “Comparison of the Coastal and Regional Ocean Community Model (CROCO) and NCAR-LES in Non-hydrostatic Simulations”, Zenodo [code], https://doi.org/10.5281/zenodo.8431670, 2023a. a, b
Fan, X., Fox-Kemper, B., Suzuki, N., Li, Q., Marchesiello, P., Auclair, F., Sullivan, P., and Hall, P.: NCAR-LES code as used in “Comparison of the Coastal and Regional Ocean Community Model (CROCO) and NCAR-LES in Non-hydrostatic Simulations”, Zenodo [code], https://doi.org/10.5281/zenodo.8431732, 2023b. a, b
Fan, X., Li, Q., Fox-Kemper, B., and Nobuhiro, S.: Data for Comparison of the coastal and regional ocean community model (CROCO) and NCAR-LES in non-hydrostatic simulations, Brown University Open Data Collection, Brown Digital Repository [data set], https://doi.org/10.26300/vpdb-v266, 2023c. a, b
Fox, D. G. and Orszag, S. A.: Pseudospectral approximation to two-dimensional turbulence, J. Comput. Phys., 11, 612–619, https://doi.org/10.1016/0021-9991(73)90141-1, 1973. a
Fox-Kemper, B., Adcroft, A., Boening, Claus W., C. W., Chassignet, E. P., Curchitser, E., Danabasoglu, G., Eden, C., England, M. H., Gerdes, R., Greatbatch, R. J., Griffies, S. M., Hallberg, R. W., Hanert, E., Heimbach, P., Hewitt, H. T., Hill, C. N., Komuro, Y., Legg, S., Le Sommer, J., Masina, S., Marsland, S. J., Penny, S. G., Qiao, F., Ringler, T. D., Treguier, A. M., Tsujino, H., Uotila, P., and Yeager, S. G.: Challenges and Prospects in Ocean Circulation Models, Front. Mar. Sci., 6, 65, https://doi.org/10.3389/fmars.2019.00065, 2019. a, b
Haidvogel, D. B., Arango, H., Budgell, W. P., Cornuelle, B. D., Curchitser, E., Di Lorenzo, E., Fennel, K., Geyer, W. R., Hermann, A. J., Lanerolle, L., Levin, J., McWilliams, J. C., Miller, A. J., Moore, A. M., Powell, T. M., Shchepetkin, A. F., Sherwood, C. R., Signell, R. P., Warner, J. C., and Wilkin, J.: Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System, J. Comput. Phys., 227, 3595–3624, 2008. a
Lemarié, F., Debreu, L., Madec, G., Demange, J., Molines, J.-M., and Honnorat, M.: Stability constraints for oceanic numerical models: implications for the formulation of time and space discretizations, Ocean Model., 92, 124–148, 2015. a
Li, Q. and Fox-Kemper, B.: Assessing the Effects of Langmuir Turbulence on the Entrainment Buoyancy Flux in the Ocean Surface Boundary Layer, J. Phys. Oceanogr., 47, 2863–2886, https://doi.org/10.1175/JPO-D-17-0085.1, 2017. a, b, c, d
Li, Q. and Fox-Kemper, B.: Anisotropy of Langmuir Turbulence and the Langmuir-Enhanced Mixed Layer Entrainment, Phys. Rev. Fluids, 5, 013803, https://doi.org/10.1103/PhysRevFluids.5.013803, 2020. a
Lilly, D. K.: On the numerical simulation of buoyant convection, Tellus, 14, 148–172, https://doi.org/10.3402/tellusa.v14i2.9537, 1962. a, b
Marchesiello, P., Auclair, F., Debreu, L., McWilliams, J., Almar, R., Benshila, R., and Dumas, F.: Tridimensional nonhydrostatic transient rip currents in a wave-resolving model, Ocean Model., 163, 101816, https://doi.org/10.1016/j.ocemod.2021.101816, 2021. a, b
Maronga, B., Gryschka, M., Heinze, R., Hoffmann, F., Kanani-Sühring, F., Keck, M., Ketelsen, K., Letzel, M. O., Sühring, M., and Raasch, S.: The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives, Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, 2015. a
McWilliams, J. C.: A uniformly valid model spanning the regimes of geostrophic and isotopic, stratified turbulence: Balanced turbulence, J. Atmos. Sci., 42, 1773–1774, 1985. 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.: Users guide for a three dimensional, primitive equation, numerical ocean model, Program in Atmospheric and Oceanic Sciences, Princeton University Princeton, NJ, 1998. a
Monin, A. and Obukhov, A.: Basic laws of turbulent mixing in the surface layer of the atmosphere, Contrib. Geophys. Inst. Acad. Sci. USSR, 151, e187, 1954. a
Orszag, S. A.: On the Elimination of Aliasing in Finite-Difference Schemes by Filtering High-Wavenumber Components, J. Atmos. Sci., 28, 1074–1074, https://doi.org/10.1175/1520-0469(1971)028<1074:OTEOAI>2.0.CO;2, 1971. a
Raasch, S. and Schröter, M.: PALM – A Large-Eddy Simulation Model Performing on Massively Parallel Computers, Meteorol. Z., 10, 363–372, https://doi.org/10.1127/0941-2948/2001/0010-0363, 2001. a, b
Ramadhan, A., Wagner, G., Hill, C., Campin, J.-M., Churavy, V., Besard, T., Souza, A., Edelman, A., Ferrari, R., and Marshall, J.: Oceananigans.Jl: Fast and Friendly Geophysical Fluid Dynamics on GPUs, J. Open Source Softw., 5, 2018, https://doi.org/10.21105/joss.02018, 2020. a, b
Skitka, J., Marston, J. B., and Fox-Kemper, B.: Reduced-Order Quasilinear Model of Ocean Boundary-Layer Turbulence, J. Phys. Oceanogr., 50, 537–558, https://doi.org/10.1175/JPO-D-19-0149.1, 2020. a
Smagorinsky, J.: General circulation experiments with the primitive equations: I. The basic experiment, Mon. Weather Rev., 91, 99–164, 1963. a
Sullivan, P., McWilliams, J., and Moeng, C.: A grid nesting method for large-eddy simulation of planetary boundary-layer flows, Bound.-Lay. Meteorol., 80, 167–202, https://doi.org/10.1007/BF00119016, 1996. a
Sullivan, P. P. and Patton, E. G.: The Effect of Mesh Resolution on Convective Boundary Layer Statistics and Structures Generated by Large-Eddy Simulation, J. Atmos. Sci., 68, 2395–2415, https://doi.org/10.1175/JAS-D-10-05010.1, 2011. a, b
Verstappen, R.: How Much Eddy Dissipation Is Needed to Counterbalance the Nonlinear Production of Small, Unresolved Scales in a Large-Eddy Simulation of Turbulence?, Comput. Fluids, 176, 276–284, https://doi.org/10.1016/j.compfluid.2016.12.016, 2018. a
Wedi, N. P. and Smolarkiewicz, P. K.: A framework for testing global non-hydrostatic models, Q. J. Roy. Meteor. Soc., 135, 469–484, 2009. a
Wicker, L. J. and Skamarock, W. C.: Time-Splitting Methods for Elastic Models Using Forward Time Schemes, Mon. Weather Rev., 130, 2088–2097, https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2, 2002. a
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and...
