Articles | Volume 10, issue 3
https://doi.org/10.5194/gmd-10-1051-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-10-1051-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
07 Mar 2017
Development and technical paper |
| 07 Mar 2017
Application of the adjoint approach to optimise the initial conditions of a turbidity current with the AdjointTurbidity 1.0 model
Samuel D. Parkinson
Department of Earth Science and Engineering, Imperial College London, London, UK
Simon W. Funke
CORRESPONDING AUTHOR
Scientific Computing, Simula Research Laboratory, Fornebu, Norway
Environment Department, University of York, York, UK
Matthew D. Piggott
Department of Earth Science and Engineering, Imperial College London, London, UK
Grantham Institute – Climate Change and the Environment, Imperial College London, London, UK
Peter A. Allison
Department of Earth Science and Engineering, Imperial College London, London, UK
Related authors
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Davor Dundovic, Joseph G. Wallwork, Stephan C. Kramer, Fabien Gillet-Chaulet, Regine Hock, and Matthew D. Piggott
EGUsphere, https://doi.org/10.5194/egusphere-2024-2649, https://doi.org/10.5194/egusphere-2024-2649, 2024
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Accurate numerical studies of glaciers often require high-resolution simulations, which often prove too demanding even for modern computers. In this paper we develop a method that identifies whether different parts of a glacier require high or low resolution based on its physical features, such as its thickness and velocity. We show that by doing so we can achieve a more optimal simulation accuracy for the available computing resources compared to uniform resolution simulations.
Shuaib Rasheed, Simon C. Warder, Yves Plancherel, and Matthew D. Piggott
Nat. Hazards Earth Syst. Sci., 24, 737–755, https://doi.org/10.5194/nhess-24-737-2024, https://doi.org/10.5194/nhess-24-737-2024, 2024
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Here we use a high-resolution bathymetry dataset of the Maldives archipelago, as well as corresponding high numerical model resolution, to carry out a scenario-based tsunami hazard assessment for the entire Maldives archipelago to investigate the potential impact of plausible far-field tsunamis across the Indian Ocean at the island scale. The results indicate that several factors contribute to mitigating and amplifying tsunami waves at the island scale.
Jennifer R. Shadrick, Dylan H. Rood, Martin D. Hurst, Matthew D. Piggott, Klaus M. Wilcken, and Alexander J. Seal
Earth Surf. Dynam., 11, 429–450, https://doi.org/10.5194/esurf-11-429-2023, https://doi.org/10.5194/esurf-11-429-2023, 2023
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This study uses a coastal evolution model to interpret cosmogenic beryllium-10 concentrations and topographic data and, in turn, quantify long-term cliff retreat rates for four chalk sites on the south coast of England. By using a process-based model, clear distinctions between intertidal weathering rates have been recognised between chalk and sandstone rock coast sites, advocating the use of process-based models to interpret the long-term behaviour of rock coasts.
Mariana C. A. Clare, Tim W. B. Leijnse, Robert T. McCall, Ferdinand L. M. Diermanse, Colin J. Cotter, and Matthew D. Piggott
Nat. Hazards Earth Syst. Sci., 22, 2491–2515, https://doi.org/10.5194/nhess-22-2491-2022, https://doi.org/10.5194/nhess-22-2491-2022, 2022
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Assessing uncertainty is computationally expensive because it requires multiple runs of expensive models. We take the novel approach of assessing uncertainty from coastal flooding using a multilevel multifidelity (MLMF) method which combines the efficiency of less accurate models with the accuracy of more expensive models at different resolutions. This significantly reduces the computational cost but maintains accuracy, making previously unfeasible real-world studies possible.
Jennifer R. Shadrick, Martin D. Hurst, Matthew D. Piggott, Bethany G. Hebditch, Alexander J. Seal, Klaus M. Wilcken, and Dylan H. Rood
Earth Surf. Dynam., 9, 1505–1529, https://doi.org/10.5194/esurf-9-1505-2021, https://doi.org/10.5194/esurf-9-1505-2021, 2021
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Here we use topographic and 10Be concentration data to optimise a coastal evolution model. Cliff retreat rates are calculated for two UK sites for the past 8000 years and, for the first time, highlight a strong link between the rate of sea level rise and long-term cliff retreat rates. This method enables us to study past cliff response to sea level rise and so to greatly improve forecasts of future responses to accelerations in sea level rise that will result from climate change.
Shuaib Rasheed, Simon C. Warder, Yves Plancherel, and Matthew D. Piggott
Ocean Sci., 17, 319–334, https://doi.org/10.5194/os-17-319-2021, https://doi.org/10.5194/os-17-319-2021, 2021
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Environmental issues arising due to coastal modification and future sea level scenarios are a major environmental hazard facing the Maldives today. Here, we carry out high-resolution tidal modelling of a Maldivian atoll for the first time and show that coastal modification in the island scale is capable of driving large-scale change in the wider atoll basin in a short time, comparable to that of long-term sea level rise scenarios and on par with observations.
Tuomas Kärnä, Stephan C. Kramer, Lawrence Mitchell, David A. Ham, Matthew D. Piggott, and António M. Baptista
Geosci. Model Dev., 11, 4359–4382, https://doi.org/10.5194/gmd-11-4359-2018, https://doi.org/10.5194/gmd-11-4359-2018, 2018
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Unstructured meshes are attractive for coastal ocean modeling, as they allow more accurate representation of complex coastal topography. Unstructured mesh models are, however, often perceived as slow and inaccurate. We present a novel discontinuous Galerkin ocean model: Thetis. We demonstrate that the model is able to simulate baroclinic ocean flows with high accuracy on a triangular prismatic mesh. This work paves the way for highly accurate and efficient three-dimensional coastal ocean models.
C. T. Jacobs and M. D. Piggott
Geosci. Model Dev., 8, 533–547, https://doi.org/10.5194/gmd-8-533-2015, https://doi.org/10.5194/gmd-8-533-2015, 2015
A. S. Candy, A. Avdis, J. Hill, G. J. Gorman, and M. D. Piggott
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-5993-2014, https://doi.org/10.5194/gmdd-7-5993-2014, 2014
Revised manuscript has not been submitted
S. D. Parkinson, J. Hill, M. D. Piggott, and P. A. Allison
Geosci. Model Dev., 7, 1945–1960, https://doi.org/10.5194/gmd-7-1945-2014, https://doi.org/10.5194/gmd-7-1945-2014, 2014
J. Hill, E. E. Popova, D. A. Ham, M. D. Piggott, and M. Srokosz
Ocean Sci., 10, 323–343, https://doi.org/10.5194/os-10-323-2014, https://doi.org/10.5194/os-10-323-2014, 2014
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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.
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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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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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EGUsphere, https://doi.org/10.5194/egusphere-2024-2068, https://doi.org/10.5194/egusphere-2024-2068, 2024
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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.
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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.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
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Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Cited articles
Alnæs, M. S., Logg, A., Ølgaard, K. B., Rognes, M. E., and Wells, G. N.: Unified Form Language: A domain-specific language for weak formulations of partial differential equations, ACM T. Math. Software, 40, 9:1–9:37, https://doi.org/10.1145/2566630, 2012.
Amy, L. A. and Talling, P. J.: Anatomy of turbidites and linked debrites based on long distance (120 × 30 km) bed correlation, Marnoso Arenacea Formation, Northern Apennines, Italy, Sedimentology, 53, 161–212, https://doi.org/10.1111/j.1365-3091.2005.00756.x, 2006.
Balay, S., Adams, M. F., Brown, J., Brune, P., Buschelman, K., Eijkhout, V., Gropp, W. D., Kaushik, D., Knepley, M. G., McInnes, L. C., Rupp, K., Smith, B. F., and Zhang, H.: PETSc Web page (Portable, Extensible Toolkit for Scientific Computation), available at: http://www.mcs.anl.gov/petsc, 2014.
Bonnecaze, R. T., Huppert, H. E., and Lister, J. R.: Particle-driven gravity currents, J. Fluid Mech., 250, 339–339, https://doi.org/10.1017/S002211209300148X, 1993.
Cockburn, B. and Shu, C.-W.: Runge–Kutta discontinuous Galerkin methods for convection-dominated problems, J. Sci. Comput., 16, 173–261, https://doi.org/10.1023/A:1012873910884, 2001.
Dorrell, R. M., Hogg, A. J., and Pritchard, D.: Polydisperse suspensions: Erosion, deposition, and flow capacity, J. Geophys. Res.-Earth, 118, 1939–1955, https://doi.org/10.1002/jgrf.20129, 2013.
Doyle, E. E., Hogg, A. J., Mader, H. M., and Sparks, R. S. J.: Modeling dense pyroclastic basal flows from collapsing columns, Geophys. Res. Lett., 35, L04305, https://doi.org/10.1029/2007GL032585, 2008.
Doyle, E. E., Hogg, A. J., Mader, H. M., and Sparks, R. S. J.: A two-layer model for the evolution and propagation of dense and dilute regions of pyroclastic currents, J. Volcanol. Geoth. Res., 190, 365–378, https://doi.org/10.1016/j.jvolgeores.2009.12.004, 2010.
Farrell, P. E., Piggott, M. D., Gorman, G. J., Ham, D. A., Wilson, C. R., and Bond, T. M.: Automated continuous verification for numerical simulation, Geosci. Model Dev., 4, 435–449, https://doi.org/10.5194/gmd-4-435-2011, 2011.
Farrell, P. E., Ham, D. A., Funke, S. W., and Rognes, M. E.: Automated derivation of the adjoint of high-level transient finite element programs, J. Sci. Comput., 35, C369–C393, https://doi.org/10.1137/120873558, 2013.
Fukushima, Y., Parker, G., and Pantin, H. M.: Prediction of ignitive turbidity currents in Scripps Submarine Canyon, Mar. Geol., 67, 55–81, https://doi.org/10.1016/0025-3227(85)90148-3, 1985.
Funke, S. W. and Farrell, P. E.: A framework for automated PDE-constrained optimisation, arXiv:1302.3894, 2013.
Funke, S. W., Farrell, P. E., and Piggott, M. D.: Tidal turbine array optimisation using the adjoint approach, Renew. Energ., 63, 658–673, https://doi.org/10.1016/j.renene.2013.09.031, 2014.
Gandolfi, G., Paganelli, L., and Zuffa, G. G.: Petrology and dispersal pattern in the Marnoso-arenacea Formation (Miocene, Northern Apennines), Int. J. Sediment. Res., 53, 493–507, https://doi.org/10.1306/212F8215-2B24-11D7-8648000102C1865D, 1983.
Garcia, M. H.: Depositional turbidity currents laden with poorly sorted sediment, J. Hydraul. Eng.-ASCE, 120, 1240–1263, https://doi.org/10.1061/(ASCE)0733-9429(1994)120:11(1240), 1994.
Giles, M. B. and Pierce, N. A.: An introduction to the adjoint approach to design, Flow Turbul. Combust., 65, 393–415, 2000.
Hallworth, M. A., Hogg, A. J., and Huppert, H. E.: Effects of external flow on compositional and particle gravity currents, J. Fluid Mech., 359, 109–142, https://doi.org/10.1017/S0022112097008409, 1998.
Harris, T. C., Hogg, A. J., and Huppert, H. E.: A mathematical framework for the analysis of particle–driven gravity currents, P. Roy. Soc. A-Math. Phy., 457, 1241–1272, https://doi.org/10.1098/rspa.2000.0728, 2001.
Harris, T. C., Hogg, A. J., and Huppert, H. E.: Polydisperse particle-driven gravity currents, J. Fluid Mech., 472, 333–371, https://doi.org/10.1017/S0022112002002379, 2002.
Heezen, B. C. and Ewing, W. M.: Turbidity currents and submarine slumps, and the 1929 Grand Banks earthquake, Am. J. Sci., 250, 849–873, 1952.
Hogg, A. J.: Lock-release gravity currents and dam-break flows, J. Fluid Mech., 569, 61–87, https://doi.org/10.1017/S0022112006002588, 2006.
Hoult, D. P.: Oil spreading on the sea, Annu. Rev. Fluid Mech., 4, 341–368, https://doi.org/10.1146/annurev.fl.04.010172.002013, 1972.
Huang, H., Imran, J., and Pirmez, C.: Nondimensional parameters of depth-averaged gravity flow models, J. Hydraul. Res., 47, 455–465, https://doi.org/10.1080/00221686.2009.9522021, 2009.
Huppert, H. E. and Simpson, J. E.: The slumping of gravity currents, J. Fluid Mech., 99, 785–799, https://doi.org/10.1017/S0022112080000894, 1980.
Jorge, N. and Stephen, J. W.: Numerical optimization, Springer, 1999.
Kneller, B. and Buckee, C.: The structure and fluid mechanics of turbidity currents: a review of some recent studies and their geological implications, Sedimentology, 47, 62–94, https://doi.org/10.1046/j.1365-3091.2000.047s1062.x, 2000.
Kuzmin, D.: A vertex-based hierarchical slope limiter for p-adaptive discontinuous Galerkin methods, J. Comput. Appl. Math., 233, 3077–3085, https://doi.org/10.1016/j.cam.2009.05.028, 2010.
Lamb, H.: Hydrodynamics, Cambridge University Press, 1993.
Lesshafft, L., Meiburg, E., Kneller, B., and Marsden, A.: Towards inverse modeling of turbidity currents: The inverse lock-exchange problem, Comput. Geosci., 37, 521–529, https://doi.org/10.1016/j.cageo.2010.09.015, 2011.
Logg, A., Mardal, K.-A., and Wells, G.: Automated solution of differential equations by the finite element method: The FEniCS book, vol. 84, Springer Science & Business Media, 2012.
Lowe, D. R.: Sediment Gravity Flows, Geology of Continental Slope, 27, 75–82, https://doi.org/10.2110/pec.79.27.0075, 1979.
Lucchi, F. R. and Valmori, E.: Basin-wide turbidites in a Miocene, over-supplied deep-sea plain: a geometrical analysis, Sedimentology, 27, 241–270, https://doi.org/10.1111/j.1365-3091.1980.tb01177.x, 1980.
Menemenlis, D., Campin, J.-M., Heimbach, P., Hill, C., Lee, T., Nguyen, A., Schodlok, M., and Zhang, H.: ECCO2: High resolution global ocean and sea ice data synthesis, Mercator Ocean Quarterly Newsletter, 31, 13–21, 2008.
Middleton, G. V.: Experiments on density and turbidity currents, I. Motion of the head, Can. J. Earth Sci., 3, 523–546, https://doi.org/10.1139/e66-038, 1966.
Naruse, H.: Tsunami-genic turbidity currents: observation and estimation of flow condition by numerical simulations, in: Apennine Workshop: future research directions for submarine flows, AGU Publications, 2013.
Parker, G., Fukushima, Y., and Pantin, H. M.: Self-accelerating turbidity currents, J. Fluid Mech., 171, 145–81, https://doi.org/10.1017/S0022112086001404, 1986.
Parkinson, S. D., Hill, J., Piggott, M. D., and Allison, P. A.: Direct numerical simulations of particle-laden density currents with adaptive, discontinuous finite elements, Geosci. Model Dev., 7, 1945–1960, https://doi.org/10.5194/gmd-7-1945-2014, 2014.
Peraire, J. and Persson, P. O.: The compact discontinuous Galerkin (CDG) method for elliptic problems, J. Sci. Comput., 30, 1806–1824, https://doi.org/10.1137/070685518, 2008.
Rowley, P.: Inverse modelling of a pyroclastic turbidite, in: Apennine Workshop: future research directions for submarine flows, 2013.
Sequeiros, O. E., Cantelli, A., Viparelli, E., White, J. D. L., Garcia, M. H., and Parker, G.: Modeling turbidity currents with nonuniform sediment and reverse buoyancy, Water Resour. Res., 45, 1–28, https://doi.org/10.1029/2008WR007422, 2009.
Talling, P. J., Amy, L. A., and Wynn, R. B.: New insight into the evolution of large-volume turbidity currents: comparison of turbidite shape and previous modelling results, Sedimentology, 54, 737–769, https://doi.org/10.1111/j.1365-3091.2007.00858.x, 2007a.
Talling, P. J., Amy, L. A., Wynn, R. B., Blackbourn, G., and Gibson, O.: Evolution of turbidity currents deduced from extensive thin turbidites: Marnoso Arenacea Formation (Miocene), Italian Apennines, J. Sediment. Res., 77, 172–196, https://doi.org/10.2110/jsr.2007.018, 2007b.
Talling, P. J., Wynn, R. B., Masson, D. G., Frenz, M., Cronin, B. T., Schiebel, R., Akhmetzhanov, A. M., Dallmeier-Tiessen, S., Benetti, S., Weaver, P. P. E., Georgiopoulou, A., Zühlsdorff, C., and Amy, L. A.: Onset of submarine debris flow deposition far from original giant landslide, Nature, 450, 541–544, https://doi.org/10.1038/nature06313, 2007c.
Talling, P. J., Masson, D. G., Sumner, E. J., and Malgesini, G.: Subaqueous sediment density flows: Depositional processes and deposit types, Sedimentology, 59, 1937–2003, https://doi.org/10.1111/j.1365-3091.2012.01353.x, 2012.
Ungarish, M.: An introduction to gravity currents and intrusions, CRC Press, 2010.
Wächter, A. and Biegler, L. T.: Line search filter methods for nonlinear programming: Motivation and global convergence, J. Optimization, 16, 1–31, https://doi.org/10.1137/S1052623403426556, 2005.
Wächter, A. and Biegler, L. T.: On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Math. Program., 106, 25–57, https://doi.org/10.1007/s10107-004-0559-y, 2006.
