Articles | Volume 16, issue 4
https://doi.org/10.5194/gmd-16-1297-2023
© Author(s) 2023. 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-16-1297-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
23 Feb 2023
Development and technical paper |
| 23 Feb 2023
| 23 Feb 2023
Barotropic tides in MPAS-Ocean (E3SM V2): impact of ice shelf cavities
Nairita Pal
CORRESPONDING AUTHOR
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Centre for Ocean, River, Atmosphere and Land Sciences, Indian Institute of Technology, Kharagpur, 721302, India
Kristin N. Barton
Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA
Mark R. Petersen
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Steven R. Brus
Argonne National Laboratory, Lemont, IL 60439, USA
Darren Engwirda
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Brian K. Arbic
Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI 48109, USA
Andrew F. Roberts
Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Joannes J. Westerink
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, USA
Damrongsak Wirasaet
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, 156 Fitzpatrick Hall, Notre Dame, IN 46556, USA
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Dylan Schlichting, Katherine Smith, Mark Petersen, Robert Hetland, Kyle Hinson, and Darren Engwirda
EGUsphere, https://doi.org/10.5194/egusphere-2026-1567, https://doi.org/10.5194/egusphere-2026-1567, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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River plumes can strongly influence coastal dynamics but are poorly resolved in global ocean models. Building on a companion study, we perform high-resolution simulations of the Mississippi–Atchafalaya (M-A) plume with the Model for Prediction Across Scales–Ocean (MPAS-O), a global model, and compare with a limited-domain Regional Ocean Modeling System configuration. MPAS-O qualitatively captures the M-A plume seasonality but fails to generate realistic eddies on the Texas–Louisiana shelf.
Kyle E. Hinson, Dylan R. Schlichting, Robert D. Hetland, Darren Engwirda, Katherine M. Smith, Mark R. Petersen, and Kaila Uyeda
EGUsphere, https://doi.org/10.5194/egusphere-2026-1566, https://doi.org/10.5194/egusphere-2026-1566, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
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Physical dynamics of ocean flows at fine spatial scales are challenging for regional and global scale ocean models due to high computational effort associated with smaller grid cell sizes. We compared two ocean models: a regional model (ROMS; Regional Ocean Modeling System) and global model (MPAS-O; Model for Prediction Across Scales – Ocean) across a range of resolutions (10 km to 100 m) in an idealized domain, and found that their similarities may hold promise for future coupling between them.
Mark R. Petersen, Xylar S. Asay-Davis, Alice M. Barthel, Carolyn Branecky Begeman, Siddhartha Bishnu, Steven R. Brus, Philip W. Jones, Hyun-Gyu Kang, Youngsung Kim, Azamat Mametjanov, Brian J. O'Neill, James R. Overfelt, Kieran K. Ringel, Katherine M. Smith, Sarat Sreepathi, Luke P. Van Roekel, and Maciej Waruszewski
Geosci. Model Dev., 19, 3569–3594, https://doi.org/10.5194/gmd-19-3569-2026, https://doi.org/10.5194/gmd-19-3569-2026, 2026
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Ocean models are used to predict currents, temperature, and salinity of the earth's oceans, much like weather forecasting. As supercomputer hardware changes with evolving technology, models must be updated, and sometimes rewritten. Here we document Omega, a new ocean model that was designed to run on the world's fastest supercomputers. Testing shows that Omega accurately solves the model equations, and runs efficiently on many different computer architectures, including exascale computers.
Anthony Chen, He Wang, Brian Arbic, and Robert Krasny
EGUsphere, https://doi.org/10.48550/arXiv.2602.01416, https://doi.org/10.48550/arXiv.2602.01416, 2026
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Self Attraction and Loading (SAL) is an important force that affects many oceanic motions, including tides. Computing SAL is challenging and ocean models neglected to include the impacts of SAL for a long time. Recent work has proposed a method for incorporating the effects of SAL, but the method has several limitations that limit the accuracy. This work proposes an alternative method. Tests of this new method in an ocean model indicate that it reduces the amount of error in the modeled tides.
Rémi Laxenaire, Eric P. Chassignet, Xiaobiao Xu, Alan J. Wallcraft, Luna Hiron, Brian K. Arbic, Maarten C. Buijsman, Miguel Solano, and Shane Elipot
EGUsphere, https://doi.org/10.5194/egusphere-2025-6355, https://doi.org/10.5194/egusphere-2025-6355, 2026
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Fast-changing currents shape surface energy and drive interior mixing of heat and salt. Because they are hard to observe globally, we use numerical models to quantify their impacts. We evaluate seven North and Equatorial Atlantic simulations with varying parameterizations, comparing modeled currents with those from observed surface buoy tracks. We show results are sensitive to model grid and seafloor resolution, tides and wind variability, with contrasting offshore and nearshore responses.
Dongyu Feng, Zeli Tan, Darren Engwirda, Jonathan D. Wolfe, Donghui Xu, Chang Liao, Gautam Bisht, James J. Benedict, Tian Zhou, Mithun Deb, Hong-Yi Li, and L. Ruby Leung
Nat. Hazards Earth Syst. Sci., 25, 3619–3639, https://doi.org/10.5194/nhess-25-3619-2025, https://doi.org/10.5194/nhess-25-3619-2025, 2025
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Our study explores how riverine and coastal flooding during hurricanes is influenced by the interaction of atmosphere, land, river, and ocean conditions. Using an advanced Earth system model, we simulate Hurricane Irene to evaluate how meteorological and hydrological uncertainties affect flood modeling. Our findings reveal the importance of a multi-component modeling system, how hydrological conditions play critical roles in flood modeling, and greater flood risks if multiple factors are present.
Chang Liao, Darren Engwirda, Matthew G. Cooper, Mingke Li, and Yilin Fang
Earth Syst. Sci. Data, 17, 2035–2062, https://doi.org/10.5194/essd-17-2035-2025, https://doi.org/10.5194/essd-17-2035-2025, 2025
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Discrete global grid systems, or DGGS, are digital frameworks that help us organize information about our planet. Although scientists have used DGGS in areas like weather and nature, using them in the water cycle has been challenging because some core datasets are missing. We created a way to generate these datasets. We then developed the datasets in the Amazon and Yukon basins, which play important roles in our planet's climate. These datasets may help us improve our water cycle models.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Michel Tchilibou, Loren Carrere, Florent Lyard, Clément Ubelmann, Gérald Dibarboure, Edward D. Zaron, and Brian K. Arbic
Ocean Sci., 21, 325–342, https://doi.org/10.5194/os-21-325-2025, https://doi.org/10.5194/os-21-325-2025, 2025
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Sea level observations along the swaths of the new SWOT (Surface Water and Ocean Topography) mission were used to characterize internal tides at three semidiurnal frequencies off the Amazon shelf in the tropical Atlantic during the SWOT calibration/validation period. The atlases were derived using harmonic analysis and principal component analysis. The SWOT-derived internal tide atlas outperforms the reference atlas previously used to correct SWOT observations.
Sara Calandrini, Darren Engwirda, and Luke Van Roekel
EGUsphere, https://doi.org/10.5194/egusphere-2024-472, https://doi.org/10.5194/egusphere-2024-472, 2024
Preprint withdrawn
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Most modern ocean circulation models only consider the hydrostatic pressure, but for coastal phenomena nonhydrostatic effects become important, creating the need to include the nonhydrostatic pressure. In this work, we present a nonhydrostatic formulation for MPAS-Ocean (MPAS-O NH) and show its correctness on idealized benchmark test cases. MPAS-O NH is the first global nonhydrostatic model at variable resolution and is the first nonhydrostatic ocean model to be fully coupled in a climate model.
Siddhartha Bishnu, Robert R. Strauss, and Mark R. Petersen
Geosci. Model Dev., 16, 5539–5559, https://doi.org/10.5194/gmd-16-5539-2023, https://doi.org/10.5194/gmd-16-5539-2023, 2023
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Here we test Julia, a relatively new programming language, which is designed to be simple to write, but also fast on advanced computer architectures. We found that Julia is both convenient and fast, but there is no free lunch. Our first attempt to develop an ocean model in Julia was relatively easy, but the code was slow. After several months of further development, we created a Julia code that is as fast on supercomputers as a Fortran ocean model.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995, https://doi.org/10.5194/gmd-16-3953-2023, https://doi.org/10.5194/gmd-16-3953-2023, 2023
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Hyein Jeong, Adrian K. Turner, Andrew F. Roberts, Milena Veneziani, Stephen F. Price, Xylar S. Asay-Davis, Luke P. Van Roekel, Wuyin Lin, Peter M. Caldwell, Hyo-Seok Park, Jonathan D. Wolfe, and Azamat Mametjanov
The Cryosphere, 17, 2681–2700, https://doi.org/10.5194/tc-17-2681-2023, https://doi.org/10.5194/tc-17-2681-2023, 2023
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We find that E3SM-HR reproduces the main features of the Antarctic coastal polynyas. Despite the high amount of coastal sea ice production, the densest water masses are formed in the open ocean. Biases related to the lack of dense water formation are associated with overly strong atmospheric polar easterlies. Our results indicate that the large-scale polar atmospheric circulation must be accurately simulated in models to properly reproduce Antarctic dense water formation.
Gaspard Geoffroy, Jonas Nycander, Maarten C. Buijsman, Jay F. Shriver, and Brian K. Arbic
Ocean Sci., 19, 811–835, https://doi.org/10.5194/os-19-811-2023, https://doi.org/10.5194/os-19-811-2023, 2023
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The ocean state is sensitive to the mixing originating from internal tides (ITs). To date, our knowledge of the magnitude and spatial distribution of this mixing mostly relies on uncertain modeling. Here, we use novel observations from autonomous floats to validate the spatial variability in the semidiurnal IT in a realistic ocean simulation. The numerical simulation is found to correctly reproduce the main spatial patterns of the observed tidal energy but to be biased low at the global scale.
Olawale James Ikuyajolu, Luke Van Roekel, Steven R. Brus, Erin E. Thomas, Yi Deng, and Sarat Sreepathi
Geosci. Model Dev., 16, 1445–1458, https://doi.org/10.5194/gmd-16-1445-2023, https://doi.org/10.5194/gmd-16-1445-2023, 2023
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Wind-generated waves play an important role in modifying physical processes at the air–sea interface, but they have been traditionally excluded from climate models due to the high computational cost of running spectral wave models for climate simulations. To address this, our work identified and accelerated the computationally intensive section of WAVEWATCH III on GPU using OpenACC. This allows for high-resolution modeling of atmosphere–wave–ocean feedbacks in century-scale climate integrations.
Dongyu Feng, Zeli Tan, Darren Engwirda, Chang Liao, Donghui Xu, Gautam Bisht, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Hydrol. Earth Syst. Sci., 26, 5473–5491, https://doi.org/10.5194/hess-26-5473-2022, https://doi.org/10.5194/hess-26-5473-2022, 2022
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Sea level rise, storm surge and river discharge can cause coastal backwater effects in downstream sections of rivers, creating critical flood risks. This study simulates the backwater effects using a large-scale river model on a coastal-refined computational mesh. By decomposing the backwater drivers, we revealed their relative importance and long-term variations. Our analysis highlights the increasing strength of backwater effects due to sea level rise and more frequent storm surge.
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.
Adrian K. Turner, William H. Lipscomb, Elizabeth C. Hunke, Douglas W. Jacobsen, Nicole Jeffery, Darren Engwirda, Todd D. Ringler, and Jonathan D. Wolfe
Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, https://doi.org/10.5194/gmd-15-3721-2022, 2022
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We present the dynamical core of the MPAS-Seaice model, which uses a mesh consisting of a Voronoi tessellation with polygonal cells. Such a mesh allows variable mesh resolution in different parts of the domain and the focusing of computational resources in regions of interest. We describe the velocity solver and tracer transport schemes used and examine errors generated by the model in both idealized and realistic test cases and examine the computational efficiency of the model.
Milena Veneziani, Wieslaw Maslowski, Younjoo J. Lee, Gennaro D'Angelo, Robert Osinski, Mark R. Petersen, Wilbert Weijer, Anthony P. Craig, John D. Wolfe, Darin Comeau, and Adrian K. Turner
Geosci. Model Dev., 15, 3133–3160, https://doi.org/10.5194/gmd-15-3133-2022, https://doi.org/10.5194/gmd-15-3133-2022, 2022
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We present an Earth system model (ESM) simulation, E3SM-Arctic-OSI, with a refined grid to better resolve the Arctic ocean and sea-ice system and low spatial resolution elsewhere. The configuration satisfactorily represents many aspects of the Arctic system and its interactions with the sub-Arctic, while keeping computational costs at a fraction of those necessary for global high-resolution ESMs. E3SM-Arctic can thus be an efficient tool to study Arctic processes on climate-relevant timescales.
David A. Griffin, Mike Herzfeld, Mark Hemer, and Darren Engwirda
Geosci. Model Dev., 14, 5561–5582, https://doi.org/10.5194/gmd-14-5561-2021, https://doi.org/10.5194/gmd-14-5561-2021, 2021
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In support of the developing ocean renewable energy sector, and indeed all mariners, we have developed a new tidal model for Australian waters and thoroughly evaluated it using a new compilation of tide gauge and current meter data. We show that while there is certainly room for improvement, the model provides useful predictions of tidal currents for about 80 % (by area) of Australian shelf waters. So we intend to commence publishing tidal current predictions for those regions soon.
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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.
Understanding tides is essential to accurately predict ocean currents. Over the next several...
