Articles | Volume 10, issue 1
https://doi.org/10.5194/gmd-10-453-2017
© 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-10-453-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
01 Feb 2017
Model description paper |
| 01 Feb 2017
Bottom RedOx Model (BROM v.1.1): a coupled benthic–pelagic model for simulation of water and sediment biogeochemistry
Evgeniy V. Yakushev
CORRESPONDING AUTHOR
Norwegian Institute for Water Research (NIVA), Gaustadalléen 21,
0349 Oslo, Norway
P.P. Shirshov Institute of Oceanology RAS, Nakhimovskiy prosp. 36,
117991, Moscow, Russia
Elizaveta A. Protsenko
Norwegian Institute for Water Research (NIVA), Gaustadalléen 21,
0349 Oslo, Norway
P.P. Shirshov Institute of Oceanology RAS, Nakhimovskiy prosp. 36,
117991, Moscow, Russia
Jorn Bruggeman
Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth, PL1 3DH, UK
Philip Wallhead
Norwegian Institute for Water Research (NIVA Vest), Thormøhlensgate
53 D, 5006 Bergen, Norway
Svetlana V. Pakhomova
Norwegian Institute for Air Research (NILU), P.O. Box 100, 2027
Kjeller, Norway
P.P. Shirshov Institute of Oceanology RAS, Nakhimovskiy prosp. 36,
117991, Moscow, Russia
Norwegian University of Science and Technology (NTNU), 7491
Trondheim, Norway
Shamil Kh. Yakubov
P.P. Shirshov Institute of Oceanology RAS, Nakhimovskiy prosp. 36,
117991, Moscow, Russia
Richard G. J. Bellerby
State Key Laboratory for Estuarine and Coastal Research, East China
Normal University, Shanghai, China
Norwegian Institute for Water Research (NIVA Vest), Thormøhlensgate
53 D, 5006 Bergen, Norway
Raoul-Marie Couture
Norwegian Institute for Water Research (NIVA), Gaustadalléen 21,
0349 Oslo, Norway
University of Waterloo, Earth and Environmental Sciences, Ecohydrology
Group, 200 University Avenue West, N2L3G2, Waterloo, Canada
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Shamil Yakubov, Philip Wallhead, Elizaveta Protsenko, and Evgeniy Yakushev
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-299, https://doi.org/10.5194/gmd-2017-299, 2017
Preprint withdrawn
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Aquatic biogeochemical processes can strongly interact, especially in polar regions, with processes occurring in adjacent ice and sediment layers, yet there are few modelling tools to simulate these systems in a fully coupled manner. We have developed a 1D transport model that allows simultaneous simulation of the biogeochemistry of 3 different media: ice, water, and sediments. Description of transportation processes in ice, water, and sediments for both solutes and solids was provided.
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Melt from the Greenland ice sheet and sea ice both influence light and nutrient availability in the Arctic coastal ocean. We use a 3D coupled hydrodynamic–biogeochemical model to evaluate the relative importance of these processes for timing, distribution, and magnitude of phytoplankton production in Disko Bay, west Greenland. Our study indicates that decreasing sea ice and more freshwater discharge can work synergistically and increase primary productivity of the coastal ocean around Greenland.
Xiaoshuang Li, Richard Garth James Bellerby, Jianzhong Ge, Philip Wallhead, Jing Liu, and Anqiang Yang
Geosci. Model Dev., 13, 5103–5117, https://doi.org/10.5194/gmd-13-5103-2020, https://doi.org/10.5194/gmd-13-5103-2020, 2020
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We have developed an ANN model to predict pH using 11 cruise datasets from 2013 to 2017,
demonstrated its reliability using three cruise datasets during 2018 and applied it to
retrieve monthly pH for the period 2000 to 2016 on the East China Sea shelf using the
ANN model in combination with input variables from the Changjiang biology Finite-Volume
Coastal Ocean Model. This approach may be a valuable tool for understanding the seasonal
variation of pH in poorly observed regions.
Shamil Yakubov, Philip Wallhead, Elizaveta Protsenko, and Evgeniy Yakushev
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-299, https://doi.org/10.5194/gmd-2017-299, 2017
Preprint withdrawn
Short summary
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Aquatic biogeochemical processes can strongly interact, especially in polar regions, with processes occurring in adjacent ice and sediment layers, yet there are few modelling tools to simulate these systems in a fully coupled manner. We have developed a 1D transport model that allows simultaneous simulation of the biogeochemistry of 3 different media: ice, water, and sediments. Description of transportation processes in ice, water, and sediments for both solutes and solids was provided.
Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies
Biogeosciences, 14, 1647–1701, https://doi.org/10.5194/bg-14-1647-2017, https://doi.org/10.5194/bg-14-1647-2017, 2017
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Plankton models have become an integral part in marine ecosystem and biogeochemical research. These models differ in complexity and in their number of parameters. How values are assigned to parameters is essential. An overview of major methodologies of parameter estimation is provided. Aspects of parameter identification in the literature are diverse. Individual findings could be better synthesized if notation and expertise of the different scientific communities would be reasonably merged.
Fenjuan Hu, Karsten Bolding, Jorn Bruggeman, Erik Jeppesen, Morgens R. Flindt, Luuk van Gerven, Jan H. Janse, Annette B. G. Janssen, Jan J. Kuiper, Wolf M. Mooij, and Dennis Trolle
Geosci. Model Dev., 9, 2271–2278, https://doi.org/10.5194/gmd-9-2271-2016, https://doi.org/10.5194/gmd-9-2271-2016, 2016
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We present a redesign and further development of a complex and well-known aquatic ecosystem model (PCLake) into the Framework for Aquatic Biogeochemical Models (FABM). So PCLake can run in different hydrodynamic environments, ranging from 0-D to 3-D. We introduce the methods and technical details about how the model was re-designed into a modular structure and the new features of PCLake enabled by FABM. We further present a benchmark test case to verify the new model implementation.
Momme Butenschön, James Clark, John N. Aldridge, Julian Icarus Allen, Yuri Artioli, Jeremy Blackford, Jorn Bruggeman, Pierre Cazenave, Stefano Ciavatta, Susan Kay, Gennadi Lessin, Sonja van Leeuwen, Johan van der Molen, Lee de Mora, Luca Polimene, Sevrine Sailley, Nicholas Stephens, and Ricardo Torres
Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, https://doi.org/10.5194/gmd-9-1293-2016, 2016
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ERSEM 15.06 is a model for marine biogeochemistry and the lower trophic levels of the marine food web. It comprises a pelagic and benthic sub-model including the microbial food web and the major biogeochemical cycles of carbon, nitrogen, phosphorus, silicate, and iron using dynamic stochiometry. Further features include modules for the carbonate system and calcification. We present full mathematical descriptions of all elements along with examples at various scales up to 3-D applications.
Jonathan Beecham, Jorn Bruggeman, John Aldridge, and Steven Mackinson
Geosci. Model Dev., 9, 947–964, https://doi.org/10.5194/gmd-9-947-2016, https://doi.org/10.5194/gmd-9-947-2016, 2016
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This paper is a description of how very different higher and lower trophic level models (Ecopath with Ecosim) and ERSEM, respectively, can be coupled together using a metadata coupling system together with a number of examples of short- and long-range projections for end to end modelling.
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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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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.
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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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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
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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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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.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
EGUsphere, https://doi.org/10.5194/egusphere-2024-613, https://doi.org/10.5194/egusphere-2024-613, 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 and compromise their realism. We illustrate here the spurious effect that tides can have on simulations of South East Asia. Although they play an important role in setting the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. The paper also provides insights on how to reduce these errors.
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-95, https://doi.org/10.5194/egusphere-2024-95, 2024
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Global climate models do not reliably simulate sea-level change arising from 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 2nd 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.
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.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-237, https://doi.org/10.5194/gmd-2023-237, 2024
Revised manuscript accepted for GMD
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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.
Qian Wang, Fei Chai, Yang Zhang, Yinglong Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-236, https://doi.org/10.5194/gmd-2023-236, 2024
Revised manuscript accepted for GMD
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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.
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.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
EGUsphere, https://doi.org/10.5194/egusphere-2023-1876, https://doi.org/10.5194/egusphere-2023-1876, 2023
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Harness AI for better ocean insights. BGC-Argo floats collect deep ocean data, yet forecasting vital nutrient levels is a challenge. Our novel AI approach, PPCon, learns from Argo float measurements and provides improved nutrient predictions. This enhances our understanding of ocean dynamics and nutrient distribution.
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.
Jan David Zika and Sohail Taimoor
EGUsphere, https://doi.org/10.5194/egusphere-2023-1220, https://doi.org/10.5194/egusphere-2023-1220, 2023
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We describe a method to relate the fluxes of heat and fresh water at the sea surface, to the resulting distribution of sea water among categories such as warm and salty, cold and salty, etc. 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.
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.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
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An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
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Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
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MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
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Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
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Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
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The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
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We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
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4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
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A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Cited articles
Alldredge, A. L. and Gotschalk, C.: In situ settling behavior of marine snow, Limnol. Oceanogr., 33, 339–35, https://doi.org/10.4319/lo.1988.33.3.0339, 1988.
Aller, R. C.: Transport and reactions in the bioirrigated zone, in: The Benthic Boundary Layer: Transport Processes and Biogeochemistry, edited by: Boudreau, B. and Jørgensen, B. B., Oxford Press, 2001.
Almroth, E., Tengberg, A., Andersson, J. H., Pakhomova, S., and Hall, P. O. J.: Effects of resuspension on benthic fluxes of oxygen, nutrients, dissolved inorganic carbon, iron and manganese in the Gulf of Finland, Baltic Sea, Cont. Shelf Res., 29, 807–818, https://doi.org/10.1016/j.csr.2008.12.011, 2009.
Anderson, J. J., Okubo, A., Robbins, A. S., and Richards, F. A.: A model for nitrite and nitrate distributions in oceanic oxygen minimum zones, Deep-Sea Res., 29, 1113–1140, 1982.
Arndt, S. and Regnier, P.: A model for the benthic-pelagic coupling of silica in estuarine ecosystems: sensitivity analysis and system scale simulation, Biogeosciences, 4, 331–352, https://doi.org/10.5194/bg-4-331-2007, 2007.
Bektursunova, R. and L'Heureux, I.: A reaction-transport model of periodic precipitation of pyrite in anoxic marine sediments, Chem. Geol., 287, 158–170, https://doi.org/10.1016/j.chemgeo.2011.06.004, 2011.
Berner, R. A.: Principles of Chemical Sedimentology, McGraw-Hill Inc., 1971.
Berner, R. A. Early Diagenesis: A Theoretical Approach, Princeton Series in Geochemistry, 1, 241 pp., 1980.
Blackford, J. C., Allen, J. I., and Gilbert, F. J.: Ecosystem dynamics at six contrasting sites: A generic modelling study, J. Marine Syst., 52, 191–215, https://doi.org/10.1016/j.jmarsys.2004.02.004, 2004.
Blackwelder, P., Hood, T., Alvarez-Zarikian, C., Nelsen, T. A., and McKee, B.: Benthic foraminifera from the necop study area impacted by the Mississippi River plume and seasonal hypoxia, Quarternary Int., 31, 19–36, https://doi.org/10.1016/1040-6182(95)00018-E, 1996.
Boudreau, B. P.: A method-of-lines code for carbon and nutrient diagenesis in aquatic sediments, Comput. Geosci., 22, 479–496, https://doi.org/10.1016/0098-3004(95)00115-8, 1996.
Boudreau, B. P.: Diagenetic models and their implementation, Modelling transport and reactions in aquatic sediments, https://doi.org/10.1007/978-3-642-60421-8, 1997.
Boudreau, B. P. and Jorgensen, B. B.: The Benthic Boundary Layer: Transport Processes and Biogeochemistry, edited by: Boudreau, B. P. and Jorgensen, B. B., Oxford University Press, 1st Edn., 2001.
Brezonik, P. L. and Arnold, W. A.: Water Chemistry An Introduction to the Chemistry of Natural and Engineered Aquatic Systems, Oxford University Press, New York, 1st Edn., 2011.
Brigolin, D., Lovato, T., Rubino, A., and Pastres, R.: Coupling early-diagenesis and pelagic biogeochemical models for estimating the seasonal variability of N and P fluxes at the sediment-water interface: Application to the northwestern Adriatic coastal zone, J. Marine Syst., 87, 239–255, https://doi.org/10.1016/j.jmarsys.2011.04.006, 2011.
Bruggeman, J. and Bolding, K.: A general framework for aquatic biogeochemical models, Environ. Modell. Softw., 61, 249–265, https://doi.org/10.1016/j.envsoft.2014.04.002, 2014.
Burchard, H., Bolding, K., Kühn, W., Meister, A., Neumann, T., and Umlauf, L.: Description of a flexible and extendable physical-biogeochemical model system for the water column, J. Marine Syst., 61 (3–4 Spec. Iss.), 180–211, https://doi.org/10.1016/j.jmarsys.2005.04.011, 2006.
Butenschön, M., Zavatarelli, M., and Vichi, M.: Sensitivity of a marine coupled physical biogeochemical model to time resolution, integration scheme and time splitting method, Ocean Model., 52–53, 36–53, https://doi.org/10.1016/j.ocemod.2012.04.008, 2012.
Butenschön, M., Clark, J., Aldridge, J. N., Allen, J. I., Artioli, Y., Blackford, J., Bruggeman, J., Cazenave, P., Ciavatta, S., Kay, S., Lessin, G., van Leeuwen, S., van der Molen, J., de Mora, L., Polimene, L., Sailley, S., Stephens, N., and Torres, R.: ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels, Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, 2016.
Canfield, D. E., Thamdrup, B., and Kristensen, E.: Aquatic geomicrobiology, in: Advances in Marine Biology, edited by: Southward, A. J., Tyler, P. A., Young, C. M., and Fuiman, L. A., Elsevier Academic Press, Amsterdam, vol. 48, 640 pp., 2005.
Cerco, C. F., Noel, M. R., and Kim, S.-C.: Three-dimensional Management Model for Lake Washington, Part II: Eutrophication Modeling and Skill Assessment, Lake Reserv. Manage., 22, 115–131, https://doi.org/10.1080/07438140609353889, 2006.
Cooper, D. C. and Morse, J. W.: The Chemistry of Offatts Bayou, Texas: A Seasonally Highly Sulfidic Basin, Estuaries, 19, 595, https://doi.org/10.2307/1352520, 1996.
Couture, R. M., Shafei, B., Van Cappellen, P., Tessier, A., and Gobeil, C.: Non-steady state modeling of arsenic diagenesis in lake sediments, Environ. Sci. Technol., 44, 197–203, https://doi.org/10.1021/es902077q, 2010.
Dade, W. B., Hogg, A. J., and Boudreau, B. P.: Physics of Flow Above the Sediment-Water Interface, in: The Benthic Boundary Layer, edited by: Boudreau, B. P. and Jorgensen, B. B., Oxford University Press, New York, 4–43, 2001.
Davison, W.: Iron and manganese in lakes, Earth-Sci. Rev., 34, 119–163, 1993.
Debolskaya, E. I., Yakushev, E. V., and Kuznetsov, I. S.: Analysis of the hydrophysical structure of the Sea of Azov in the period of the bottom anoxia development, J. Marine Syst., 70, 300–307, https://doi.org/10.1016/j.jmarsys.2007.02.027, 2008.
Diaz, R. J. and Rosenberg, R.: Spreading dead zones and consequences for marine ecosystems, Science, 321, 926–929, https://doi.org/10.1126/science.1156401, 2008.
Dickson, A. G.: The development of the alkalinity concept in marine chemistry, Mar. Chem., 40, 49–63, https://doi.org/10.1016/0304-4203(92)90047-E, 1992.
Fennel, K., Hetland, R., Feng, Y., and DiMarco, S.: A coupled physical-biological model of the Northern Gulf of Mexico shelf: model description, validation and analysis of phytoplankton variability, Biogeosciences, 8, 1881–1899, https://doi.org/10.5194/bg-8-1881-2011, 2011.
Glud, R. N.: Oxygen dynamics of marine sediments, Mar. Biol. Res., 4, 243–289, https://doi.org/10.1080/17451000801888726, 2008.
Gregoire, M. and Lacroix, G.: Study of the oxygen budget of the Black Sea waters using a 3D coupled hydrodynamical – biogeochemical model, J. Marine Syst., 31, 175–202, https://doi.org/10.1016/S0924-7963(01)00052-5, 2001.
He, Y., Stanev, E. V., Yakushev, E., and Staneva, J.: Black Sea biogeochemistry: Response to decadal atmospheric variability during 1960–2000 inferred from numerical modeling, Mar. Environ. Res., 77, 90–102, https://doi.org/10.1016/j.marenvres.2012.02.007, 2012.
Holtappels, M. and Lorke, A.: Estimating turbulent diffusion in a benthic boundary layer, Limnol. Oceanogr.-Meth, 9, 29–41, https://doi.org/10.4319/lom.2011.9.29, 2011.
Hunter, K. S., Wang, Y., and Van Cappellen, P.: Kinetic modeling of microbially-driven redox chemistry of subsurface environments: coupling transport, microbial metabolism and geochemistry, J. Hydrol., 209, 53–80, https://doi.org/10.1016/S0022-1694(98)00157-7, 1998.
Jensen, D. L., Boddum, J. K., Tjell, J. C., and Christensen, T. H.: The solubility of rhodochrosite (MnCO3) and siderite (FeCO3) in anaerobic aquatic environments, Appl. Geochem., 17, 503–511, https://doi.org/10.1016/S0883-2927(01)00118-4, 2002.
Jorgensen, B., Bang, M., and Blackburn, T.: Anaerobic mineralization in marine sediments from the Baltic Sea-North Sea transition, Mar. Ecol. Prog. Ser., 59, 39–54, https://doi.org/10.3354/meps059039, 1990.
Jourabchi, P., Van Cappellen, P., and Regnier, P.: Quantitative interpretation of pH distributions in aquatic sediments: A reaction-transport modeling approach, Am. J. Sci., 305, 919–956, https://doi.org/10.2475/ajs.305.9.919, 2005.
Jourabchi, P., Meile, C., Pasion, L. R., and Van Cappellen, P.: Quantitative interpretation of pore water O2 and pH distributions in deep-sea sediments, Geochim. Cosmochim. Ac., 72, 1350–1364, https://doi.org/10.1016/j.gca.2007.12.012, 2008.
Kamyshny, A., Yakushev, E., Jost, G., and Podymov, O.: Chemical Structure of Pelagic Redox Interfaces, in: The Handbook of Environmental Chemistry, edited by: Yakushev, E., Springer Berlin Heidelberg, 2013.
Katsev, S., Sundby, B., and Mucci, A.: Modeling vertical excursions of the redox boundary in sediments: Application to deep basins of the Arctic Ocean, Limnol. Oceanogr., 51, 1581–1593, https://doi.org/10.4319/lo.2006.51.4.1581, 2006.
Katsev, S., Chaillou, G., Sundby, B., and Mucci, A.: Effects of progressive oxygen depletion on sediment diagenesis and fluxes: A model for the lower St. Lawrence River Estuary, Limnol. Oceanogr., 52, 2555–2568, https://doi.org/10.4319/lo.2007.52.6.2555, 2007.
Konovalov, S. K., Murray, J. W., Luther, G. W., and Tebo, B. M.: Processes controlling the redox budget for the oxic/anoxic water column of the Black Sea, Deep. Res. Pt. II., 53, 1817–1841, https://doi.org/10.1016/j.dsr2.2006.03.013, 2006.
Lancelot, C., Spitz, Y., Gypens, N., Ruddick, K., Becquevort, S., Rousseau, V., Lacroix, G., and Billen, G.: Modelling diatom and Phaeocystis blooms and nutrient cycles in the Southern Bight of the North Sea: The MIRO model, Mar. Ecol. Prog. Ser., 289, 63–78, https://doi.org/10.3354/meps289063, 2005.
Lee, J. Y., Tett, P., Jones, K., Jones, S., Luyten, P., Smith, C., and Wild-Allen, K.: The PROWQM physical-biological model with benthicpelagic coupling applied to the northern North Sea, J. Sea Res., 48, 287–331, https://doi.org/10.1016/S1385-1101(02)00182-X, 2002.
Lewis, E. and Wallace, D.: Program developed for CO2 system calculations, 4735, 1–21, 1998.
Lopes, F., Viollier, E., Thiam, A., Michard, G., Abril, G., Groleau, A., Prévot, F., Carrias, J.-F., Albéric, P., and Jézéquel, D.: Biogeochemical modelling of anaerobic vs. aerobic methane oxidation in a meromictic crater lake (Lake Pavin, France), Appl. Geochem., 26, 1919–1932, https://doi.org/10.1016/j.apgeochem.2011.06.021, 2011.
Luff, R. and Moll, A.: Seasonal dynamics of the North Sea sediments using a three-dimensional coupled sediment-water model system, Cont. Shelf Res., 24, 1099–1127, https://doi.org/10.1016/j.csr.2004.03.010, 2004.
Luff, R., Haeckel, M. and Wallmann, K.: Robust and fast FORTRAN and MATLAB libraries to calculate pH distributions in marine systems, Comput. Geosci., 27, 157–169, https://doi.org/10.1016/S0098-3004(00)00097-2, 2001.
McCarthy, M. J., McNeal, K. S., Morse, J. W., and Gardner, W. S.: Bottom-water hypoxia effects on sediment-water interface nitrogen transformations in a seasonally hypoxic, shallow bay (Corpus Christi Bay, TX, USA), Estuar. Coasts, 31, 521–531, https://doi.org/10.1007/s12237-008-9041-z, 2008.
Meile, C., Koretsky, C. M., and Van Cappellen, P.: Quantifying bioirrigation in aquatic sedimnets: An inverse modeling approach, Limnol. Oceanogr., 1, 164–177, 2001.
Meire, L., Soetaert, K. E. R., and Meysman, F. J. R.: Impact of global change on coastal oxygen dynamics and risk of hypoxia, Biogeosciences, 10, 2633–2653, https://doi.org/10.5194/bg-10-2633-2013, 2013.
Meysman, F. J. R., Boudreau, B. P., and Middelburg, J. J.: Modeling reactive transport in sediments subject to bioturbation and compaction, Geochim. Cosmochim. Ac., 69, 3601–3617, https://doi.org/10.1016/j.gca.2005.01.004, 2005.
Millero, F. J.: Thermodynamics of the carbon dioxide system in the oceans, Geochim. Cosmochim. Ac., 59, 661–677, https://doi.org/10.1016/0016-7037(94)00354-O, 1995.
Mobley, C. D. and Boss, E. S.: Improved irradiances for use in ocean heating, primary production, and photo-oxidation calculations, Appl. Optics, 51, 6549–6560, https://doi.org/10.1364/AO.51.006549, 2012.
Morgan, J. J.: Manganese and its role in biological processes, in: Metal ions in biological systems, edited by: Sigel, A. and Sigel, H. Marcel Dekker, Inc., Basel, New York, 31, 1–30, 2000.
Morse, J. W. and Eldridge, P. M.: A non-steady state diagenetic model for changes in sediment biogeochemistry in response to seasonally hypoxic/anoxic conditions in the “dead zone” of the Louisiana shelf, Mar. Chem., 106, 239–255, https://doi.org/10.1016/j.marchem.2006.02.003, 2007.
Munhoven, G.: Mathematics of the total alkalinity–pH equation – pathway to robust and universal solution algorithms: the SolveSAPHE package v1.0.1, Geosci. Model Dev., 6, 1367–1388, https://doi.org/10.5194/gmd-6-1367-2013, 2013.
Nightingale, P. D., Malin, G., Law, C. S., Watson, A. J., Liss, P. S., Liddicoat, M. I., Boutin, J., and Upstill-Goddard, R. C.: In situ evaluation of air-sea gas exchange parameterizations using novel conservative and volatile tracers, Global Biogeochem. Cy., 14, 373–387, https://doi.org/10.1029/1999GB900091, 2000.
Pakhomova, S. V., Hall, P. O. J., Kononets, M. Y., Rozanov, A. G., Tengberg, A., and Vershinin, A. V.: Fluxes of iron and manganese across the sediment-water interface under various redox conditions, Mar. Chem., 107, 319–331, https://doi.org/10.1016/j.marchem.2007.06.001, 2007.
Paraska, D. W., Hipsey, M. R., and Salmon, S. U.: Sediment diagenesis models: Review of approaches, challenges and opportunities, Environ. Model. Softw., 61, 297–325, https://doi.org/10.1016/j.envsoft.2014.05.011, 2014.
Pavlidou, A., Kontoyiannis, H., Anagnostou, C., Siokou–Frangou, I., Pagou, K., Krasakopoulou, E., Assimakopoulou, G., Zervoudaki, S., Zeri, C., Chatzianestis, J., and Psyllidou-Giouranovits, R.: Biogeochemical Characteristics in the Elefsis Bay (Aegean Sea, Eastern Mediterranean) in Relation to Anoxia and Climate Changes, in: The Handbook of Environmental Chemistry, edited by: Yakushev, E., 161–201, Springer Berlin Heidelberg, 2013.
Pearson, T. H. and Rosenberg, R.: Macrobenthic succession in relation to organic enrichment and pollution of the marine environment, Oceanogr. Mar. Biol. Ann. Rev., 16, 229–311, https://doi.org/10.1111/j.1540-5834.2012.00707.x, 1978.
Popova, E. E. and Srokosz, M. A.: Modelling the ecosystem dynamics at the Iceland-Faeroes Front: Biophysical interactions, J. Marine Syst., 77, 182–196, https://doi.org/10.1016/j.jmarsys.2008.12.005, 2009.
Queirós, A. M., Norling, K., Amaro, T., Nunes, J., Cummings, D., Yakushev, E., Sorensen, K., Harris, C., Woodward, M., Danovaro, R., Rastelli, E., Alve, E., Vittor, C. De, Karuza, A., Cibic, T., Monti, M., Ingrosso, G., Fornasaro, D., Beaubien, S. E., Guilini, K., Vanreu, A., Bigalke, N., and Widdicombe, S.: Potential impact of CCS leakage on marine communities, Technical Report, Deliverable 4.1: Potential impact of CCS leakage on marine communitiesWP4; lead beneficiary: Plymouth Marine Laboratory, 2014.
Rabalais, N. N., Turner, R. E., and Scavia, D.: Beyond Science into Policy: Gulf of Mexico Hypoxia and the Mississippi River, Bioscience, 52, 129, https://doi.org/10.1641/0006-3568(2002)052[0129:BSIPGO]2.0.CO;2, 2002.
Raymond, P. A., Zappa, C. J., Butman, D., Bott, T. L., Potter, J., Mulholland, P., Laursen, a. E., McDowell, W. H., and Newbold, D.: Scaling the gas transfer velocity and hydraulic geometry in streams and small rivers, Limnol. Oceanogr. Fluids Environ., 2, 41–53, https://doi.org/10.1215/21573689-1597669, 2012.
Reed, D. C., Slomp, C. P., and Gustafsson, B. G.: Sedimentary phosphorus dynamics and the evolution of bottom-water hypoxia: A coupled benthic-pelagic model of a coastal system, Limnol. Oceanogr., 56, 1075–1092, https://doi.org/10.4319/lo.2011.56.3.1075, 2011.
Richards, F.: Anoxic basins and fjords, in: Chemical Oceanography, edited by: Riley, J. and Skirrow, G., Academic Press, London, 611–645, 1965.
Richardson, K. and Jørgensen, B.: Eutrophication: Definition, history and effects, in: Eutrophication in Coastal Marine Ecosystems, https://doi.org/10.1029/CE052p0001, 1996.
Rickard, D. and Luther, G. W.: Kinetics of pyrite formation by the H2S oxidation of iron (II) monosulfide in aqueous solutions between 25 and 125°C: The mechanism, Geochim. Cosmochim. Ac., 61, 135–147, https://doi.org/10.1016/S0016-7037(96)00322-5, 1997.
Roden, E. E. and Tuttle, J. H.: Sulfide release from estuarine sediments underlying anoxic bottom water, Limnol. Oceanogr., 37, 725–738, https://doi.org/10.4319/lo.1992.37.4.0725, 1992.
Roy, R. N., Roy, L. N., Vogel, K. M., Porter-Moore, C., Pearson, T., Good, C. E., Millero, F. J., and Campbell, D. M.: The dissociation constants of carbonic acid in seawater at salinities 5 to 45 and temperatures 0 to 45°C, Mar. Chem., 44, 249–267, https://doi.org/10.1016/0304-4203(93)90207-5, 1993.
Rutgers Van Der Loeff, M. M. and Boudreau, B. P.: The effect of resuspension on chemical exchanges at the sediment-water interface in the deep sea – A modelling and natural radiotracer approach, J. Marine Syst., 11, 305–342, https://doi.org/10.1016/S0924-7963(96)00128-5, 1997.
Savchuk, O. and Wulff, F.: Biogeochemical Transformations of Nitrogen and Phosphorus in the Environment, Coupling Hydrodynamic and Biogeochemical Processes in Models for the Baltic Proper, 2, 79 pp., 1996.
Savchuk, O. P.: Nutrient biogeochemical cycles in the Gulf of Riga: Scaling up field studies with a mathematical model, J. Marine Syst., 32, 253–280, https://doi.org/10.1016/S0924-7963(02)00039-8, 2002.
Schippers, A. and Jorgensen, B. B.: Biogeochemistry of pyrite and iron sulfide oxidation in marine sediments, Geochim. Cosmochim. Ac., 66, 85–92, https://doi.org/10.1016/S0016-7037(01)00745-1, 2002.
Schlüter, M., Sauter, E., Hansen, H. P., and Suess, E.: Seasonal variations of bioirrigation in coastal sediments: Modelling of field data, Geochim. Cosmochim. Ac., 64, 821–834, https://doi.org/10.1016/S0016-7037(99)00375-0, 2000.
Schneider, B., Nausch, G., Kubsch, H., and Petersohn, I.: Accumulation of total CO2 during stagnation in the Baltic Sea deep water and its relationship to nutrient and oxygen concentrations, Mar. Chem., 77, 277–291, https://doi.org/10.1016/S0304-4203(02)00008-7, 2002.
Sell, K. S. and Morse, J. W.: Dissolved Fe2+ and ∑ H2S Behavior in Sediments Seasonally Overlain by Hypoxic-to-anoxic Waters as Determined by CSV Microelectrodes, Aquat. Geochem., 12, 179–198, https://doi.org/10.1007/s10498-005-4574-2, 2006.
Sen Gupta, B. K., Turner, R. E., and Rabalais, N. N.: Seasonal oxygen depletion in continental-shelf waters of Louisiana: Historical record of benthic foraminifers, Geology, 24, 227–230, https://doi.org/10.1130/0091-7613(1996)024<0227:SODICS>2.3.CO;2, 1996.
Soetaert, K. and Middelburg, J. J.: Modeling eutrophication and oligotrophication of shallow-water marine systems: The importance of sediments under stratified and well-mixed conditions, Hydrobiologia, 629, 239–254, https://doi.org/10.1007/s10750-009-9777-x, 2009.
Soetaert, K., Herman, P. M. J., and Middelburg, J. J.: A model of early diagenetic processes from the shelf to abyssal depths, Geochim. Cosmochim. Ac., 60, 1019–1040, https://doi.org/10.1016/0016-7037(96)00013-0, 1996.
Soetaert, K., Middelburg, J. J., Herman, P. M. J., and Buis, K.: On the coupling of benthic and pelagic biogeochemical models, Earth-Science On the coupling of benthic and pelagic biogeochemical models, April 2016, 173–201, https://doi.org/10.1016/S0012-8252(00)00004-0, 2000.
Soetaert, K., Herman, P. M. J., Middelburg, J. J., Heip, C., Smith, C. L., Tett, P., and Wild-allen, K.: Numerical modelling of the shelf break ecosystem?: reproducing benthic and pelagic measurements, Deep Sea Res. Pt. II, 48, 3141–3177, 2001.
Soetaert, K., Hofmann, A. F., Middelburg, J. J., Meysman, F. J. R., and Greenwood, J.: The effect of biogeochemical processes on pH (Reprinted from Marine Chemistry, vol 105, pg 30–51, 2007), Mar. Chem., 106, 380–401, https://doi.org/10.1016/j.marchem.2007.06.008, 2007.
Sohma, A., Sekiguchi, Y., Kuwae, T., and Nakamura, Y.: A benthic-pelagic coupled ecosystem model to estimate the hypoxic estuary including tidal flat-Model description and validation of seasonal/daily dynamics, Ecol. Modell., 215, 10–39, https://doi.org/10.1016/j.ecolmodel.2008.02.027, 2008.
Stanev, E. V., He, Y., Staneva, J., and Yakushev, E.: Mixing in the Black Sea detected from the temporal and spatial variability of oxygen and sulfide – Argo float observations and numerical modelling, Biogeosciences, 11, 5707–5732, https://doi.org/10.5194/bg-11-5707-2014, 2014.
Tebo, B. M.: Manganese(II) oxidation in the suboxic zone of the Black Sea, Deep Sea Res. Pt., 38, S883–S905, https://doi.org/10.1016/S0198-0149(10)80015-9, 1991.
Tebo, B. M., Ghiorse, W. C., van Waasbergen, L. G., Siering, P. L., and Caspi, R.: Bacterially mediated mineral formation: Insights into manganese(II) oxidation from molecular genetic and biochemical studies, in: Geomicrobiology: Interactions Between Microbes and Minerals. The Mineralogical Society of America, Washington, D.C., 225–266, 1997.
Thorpe, S. A.: The Turbulent Ocean, Cambridge University Press, 2005.
UNESCO, Progress on oceanographic tables and standards 1983–1986: Work and recommendations of the UNESCO/SCOR/ICES/IAPSO Joint Panel. chap. 7.5: Oxygen solubility. UNESCO Technical Papers in Marine Science No. 50, 11 pp., 1986.
Umlauf, L., Burchard, H. and Bolding, K.: General ocean turbulence model, Source code documentation, Balt. Sea Res. Inst. Warn. Tech. Rep, 63, p. 346, 2005.
Van Cappellen, P. and Wang, Y. F.: Cycling of iron and manganese in surface sediments: A general theory for the coupled transport and reaction of carbon, oxygen, nitrogen, sulfur, iron, and manganese, Am. J. Sci., 296, 197–243, https://doi.org/10.2475/ajs.296.3.197, 1996.
Volkov, I. I.: Geokhimiya Sery v Osadkakh Okeana (Geochemistry of Sulfur in Ocean Sediments), Nauka, Moscow, 1984.
Wanninkhof, R.: Relationship between wind speed and gas exchange over the ocean revisited, Limnol. Oceanogr., 12, 351–362, https://doi.org/10.4319/lom.2014.12.351, 2014.
Wersin, P.: The Fe(II)-CO2-H2O system in anoxic natural waters: equilibria and surface chemistry, Swiss Fed. Inst. Technol., Dissertation ETH No.9230, 1990.
Wijsman, J. W. M., Herman, P. M. J., Middelburg, J. J., and Soetaert, K.: A Model for Early Diagenetic Processes in Sediments of the Continental Shelf of the Black Sea, Estuar. Coast. Shelf S., 54, 403–421, https://doi.org/10.1006/ecss.2000.0655, 2002.
Wolf-Gladrow, D. A., Zeebe, R. E., Klaas, C., Körtzinger, A., and Dickson, A. G.: Total alkalinity: The explicit conservative expression and its application to biogeochemical processes, Mar. Chem., 106, 287–300, https://doi.org/10.1016/j.marchem.2007.01.006, 2007.
Wollast, R.: Rate and mechanism of dissolution of carbonates in the system CaCO3-MgCO3, Aquatic chemical kinetics: reaction rates of processes in natural waters, Chemistry, in: Aquatic Chemical Kinetics: Reaction Rates of Processes in Natural Waters, edited by: Stumm, W., 431–445, 1990.
Yakushev, E.: RedOx Layer Model: A Tool for Analysis of the Water Column Oxic/Anoxic Interface Processes, in: Chemical Structure of Pelagic Redox Interfaces: Observation and Modeling, edited by: Yakushev, E. V. Springer-Verlag Berlin Heidelberg, 203–234, 2013.
Yakushev, E., Pakhomova, S., Sørenson, K., and Skei, J.: Importance of the different manganese species in the formation of water column redox zones: Observations and modeling, Mar. Chem., 117, 59–70, https://doi.org/10.1016/j.marchem.2009.09.007, 2009.
Yakushev, E. V and Neretin, L. N.: One-dimensional modeling of nitrogen and sulfur cycles in the aphotic zones of the Black and Arabian Seas, Global Biogeochem. Cy., 11, 401–414, https://doi.org/10.1029/97GB00782, 1997.
Yakushev, E. V., Pollehne, F., Jost, G., Kuznetsov, I., Schneider, B., and Umlauf, L.: Redox Layer Model (ROLM): A Tool for Analysis of the Water Column Oxic/anoxic Interface Processes, Warnemunde, 2006.
Yakushev, E. V., Pollehne, F., Jost, G., Kuznetsov, I., Schneider, B., and Umlauf, L.: Analysis of the water column oxic/anoxic interface in the Black and Baltic seas with a numerical model, Mar. Chem., 107, 388–410, https://doi.org/10.1016/j.marchem.2007.06.003, 2007.
Yakushev, E. V., Chasovnikov, V. K., Murray, J. W., Pakhomova, S. V., Podymov, O. I., and Stunzhas, P. A.: Vertical hydrochemical structure of the black sea, Handb. Environ. Chem. Vol. 5 Water Pollut., 52007, 277–307, https://doi.org/10.1007/698_5_088, 2008.
Yakushev, E. V., Kuznetsov, I. S., Podymov, O. I., Burchard, H., Neumann, T., and Pollehne, F.: Modeling the influence of oxygenated inflows on the biogeochemical structure of the Gotland Sea, central Baltic Sea: Changes in the distribution of manganese, Comput. Geosci., 37, 398–409, https://doi.org/10.1016/j.cageo.2011.01.001, 2011.
Yakushev, E. V., Debolskaya, E. I., Kuznetsov, I. S., and Staalstrøm, A.: Modelling of the Meromictic Fjord Hunnbunn (Norway) with an Oxygen Depletion Model (OxyDep), edited by: Yakushev, E. V., Handb. Environ. Chem., July 2011, https://doi.org/10.1007/698_2011_110, 2013a.
Yakushev, E. V., Sorensen, K., and Sørensen, K.: On seasonal changes of the carbonate system in the Barents Sea: observations and modeling, Mar. Biol. Res., 9, 822–830, https://doi.org/10.1080/17451000.2013.775454, 2013b.
Yu, L., Fennel, K., Laurent, A., Murrell, M. C., and Lehrter, J. C.: Numerical analysis of the primary processes controlling oxygen dynamics on the Louisiana shelf, Biogeosciences, 12, 2063–2076, https://doi.org/10.5194/bg-12-2063-2015, 2015.
Zeebe, R. E. and Wolf-Gladrow, D.: CO2 in Seawater, Equilibrium, Kinetics, Isotopes, Elsevier, 2001.
Short summary
This paper presents a new benthic–pelagic biogeochemical model (BROM) that combines a relatively simple pelagic ecosystem model with a detailed biogeochemical model of the coupled cycles of N, P, Si, C, O, S, Mn, Fe in the water column, benthic boundary layer, and sediments, with a focus on oxygen and redox state. BROM should be of interest for the study of a range of environmental applications in addition to hypoxia, such as benthic nutrient recycling, redox biogeochemistry, and eutrophication.
This paper presents a new benthic–pelagic biogeochemical model (BROM) that combines a...
