Articles | Volume 13, issue 1
https://doi.org/10.5194/gmd-13-71-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-71-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
09 Jan 2020
Model description paper |
| 09 Jan 2020
| 09 Jan 2020
MOMSO 1.0 – an eddying Southern Ocean model configuration with fairly equilibrated natural carbon
Heiner Dietze
CORRESPONDING AUTHOR
GEOMAR, Helmholtz Centre for Ocean Research Kiel,
Düsternbrooker Weg 20, Kiel, Germany
Institute of Geosciences, University of Kiel, Kiel, Germany
Ulrike Löptien
GEOMAR, Helmholtz Centre for Ocean Research Kiel,
Düsternbrooker Weg 20, Kiel, Germany
Institute of Geosciences, University of Kiel, Kiel, Germany
Julia Getzlaff
GEOMAR, Helmholtz Centre for Ocean Research Kiel,
Düsternbrooker Weg 20, Kiel, Germany
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Cyanobacteria blooms can strongly aggravate eutrophication problems of water bodies. Their controls are, however, not comprehensively understood, which impedes effective management and protection plans. Here we review the current understanding of cyanobacteria blooms. Juxtaposition of respective field and laboratory studies with state-of-the-art mathematical models reveals substantial uncertainty associated with nutrient demands, grazing, and death of cyanobacteria.
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Controlled manipulation of environmental conditions within large enclosures in the ocean, pelagic mesocosms, has become a standard method to explore responses of marine plankton communities to anthropogenic change. Among the challenges of interpreting mesocosm data is the often uncertain role of vertical mixing. This study introduces a mesocosm mixing model that is able to estimate vertical diffusivities and thus provides a tool for future mesocosm data analyses that account for mixing.
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Nitrogen fixation, conducted by specific microorganisms, makes molecular nitrogen available for marine biota. By this means this process exerts major control on the growth of algae in the ocean. This study compares two contemporary paradigms, anticipating the ecological niche of N-fixing organisms in an Earth System Model. We illustrate respective uncertainties in climate projections and suggest specific observations to advance the reliable representation of nitrogen fixation in numerical models.
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Nitrogen fixation, conducted by specific microorganisms, makes molecular nitrogen available for marine biota. By this means this process exerts major control on the growth of algae in the ocean. This study compares two contemporary paradigms, anticipating the ecological niche of N-fixing organisms in an Earth System Model. We illustrate respective uncertainties in climate projections and suggest specific observations to advance the reliable representation of nitrogen fixation in numerical models.
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Markus Schartau, Philip Wallhead, John Hemmings, Ulrike Löptien, Iris Kriest, Shubham Krishna, Ben A. Ward, Thomas Slawig, and Andreas Oschlies
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Heiner Dietze, Julia Getzlaff, and Ulrike Löptien
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The Southern Ocean is a sink for anthropogenic carbon. Projections of how this sink will evolve in an ever-warming climate are based on coupled ocean-circulation–biogeochemical models. This study compares uncertainties of simulated oceanic carbon uptake associated to physical (eddy) parameterizations with those associated wtih (unconstrained) supply of bioavailable iron supply to the surface ocean.
Heiner Dietze and Ulrike Löptien
Ocean Sci., 12, 977–986, https://doi.org/10.5194/os-12-977-2016, https://doi.org/10.5194/os-12-977-2016, 2016
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Winds blowing over the ocean drive ocean currents. The oceanic response to winds is, in turn, influenced by ocean currents. Theoretical considerations suggest that the latter effect is especially pronounced in the Baltic Sea. The study presented here puts theses theoretical considerations in a high-resolution ocean circulation model of the Baltic Sea to the test.
U. Löptien and H. Dietze
Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, https://doi.org/10.5194/os-11-573-2015, 2015
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Marine biogeochemical ocean models are embedded into earth system models - which are, to an increasing degree, applied to project the fate of our warming world. These biogeochemical models generally depend on poorly constrained model parameters. In this study we investigate the the demands on observations for an objective estimation of such parameters. A major result is that even modest noise (10%) inherent to observations can hinder the assignment of reasonable parameters.
U. Löptien and L. Axell
The Cryosphere, 8, 2409–2418, https://doi.org/10.5194/tc-8-2409-2014, https://doi.org/10.5194/tc-8-2409-2014, 2014
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The Baltic Sea is a seasonally ice-covered marginal sea in central northern Europe. In wintertime, on-time shipping depends crucially on sea ice forecasts. Among the forecasting tools heavily applied are numerical models, which suffer from a lack of calibration data because relevant ice properties are difficult (and costly) to monitor. We developed an innovative and inexpensive approach, by using ship speed observations obtained by the automatic identification system (AIS) to asses such models.
U. Löptien and H. Dietze
Earth Syst. Sci. Data, 6, 367–374, https://doi.org/10.5194/essd-6-367-2014, https://doi.org/10.5194/essd-6-367-2014, 2014
H. Dietze, U. Löptien, and K. Getzlaff
Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, https://doi.org/10.5194/gmd-7-1713-2014, 2014
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Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
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We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
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Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
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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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Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
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HIDRA3 is a novel deep-learning model for predicting sea levels and storm surges, offering significant improvements over previous models and numerical simulations. It utilizes data from multiple tide gauges, enhancing predictions even with limited historical data and during sensor outages. With its advanced architecture, HIDRA3 outperforms the current state-of-the-art models by achieving up to 15 % lower mean absolute error, proving effective for coastal flood forecasting in diverse conditions.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
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Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
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Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
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The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
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The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
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.
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-100, https://doi.org/10.5194/gmd-2024-100, 2024
Revised manuscript accepted for GMD
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This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
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.
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.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-58, https://doi.org/10.5194/gmd-2024-58, 2024
Revised manuscript accepted for GMD
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We developed a physical ocean model called the Hindcast of the Salish Sea (HOTSSea) that recreates conditions throughout the Salish Sea from 1980 to 2018, filling in the gaps in patchy measurements. The model predicts physical ocean properties with sufficient accuracy to be useful for a variety of applications. The model corroborates observed ocean temperature trends and was used to examine areas with few observations. Results indicate that some seasons and areas are warming faster than others.
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.
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.
Cited articles
Abernathey, R. J., Marshal, J., and Ferreira, D.: The dependence of Southern Ocean meridional overturning on wind stress, Ocean Model., 72, 1–16, https://doi.org/10.1016/j.ocemod.2013.07.004, 2011. a, b
Abernathey, R. P., Cerovecki, I., Holland, P. R., Newsom, E. Mazloff, M., and Talley, L. D.: Water-mass transformation by sea ice in the upper branch of the Southern Ocean overturning, Nature, 9, 596–601, https://doi.org/10.1038/ngeo2749, 2016. a, b, c
Adcroft, A. and Campin, J.-M.: Rescaled height coordinates for accurate representation of free-surface flows in ocean circulation models, Ocean Model., 7, 269–284, https://doi.org/10.1016/j.ocemod.2003.09.003, 2004. a
Anderson, R. F., Ali, S., Bradtmiller, L. I., Nielsen, S. H. H., Fleisher, M. Q., Anderson, B. E., and Burckle, L. H.: Wind-driven upwelling in the Southern Ocean and the deglacial rise in atmospheric CO2, Science, 323, 1443–1448, https://doi.org/10.1126/science.1167441, 2009. a
Antonov, J. I., Seidov, D., Boyer, T. P., Locarnini, A., Mishonov, A. V., Garcia, H. E., Baranova, O. K., Zweng, M. M., and Johnson, D. R.: World Ocean Atlas 2009, Volume 2: Salinity, edited by: Levitus, S., NOAA Atlas NESDIS 69, U.S. Government Printing Office, Washington DC, 184 pp., 2010. a, b, c, d, e, f
Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamical processes of the UCLA general circulation model, Methods in Computational Physics, edited by: Chang, J., Academic Press, Vol. 17, 173–265, https://doi.org/10.1016/B978-0-12-460817-7.50009-4, 1977. a
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Treguier, A.-M., Le Sommer, J., Beckmann,
A., Biastoch, A., Böning, C., Dengg, J., Derval, C., Durand, E., Gulev, S., Remy, E., Tlandier, C.,
Theetten, S., Maltrud, M., McClean, J., and De Cuevas, B.: Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy permitting resolution, Ocean Dynam., 56, 543–567, https://doi.org/10.1007/s10236-006-0082-1, 2006. a
Bernardello, R., Marinov, I., Palter, J. P., Sarmiento, J. L., Galbraith, E. D., and Slater, R. .D.: Response of the Ocean Natural Carbon Storage to Projected Twenty-First-Century Climate Change, J. Climate, 27, 2033–2053, https://doi.org/10.1175/JCLI-D-13-00343.1, 2014. a
Böning, C. W., Dispert, A., Visbeck, M., Rintoul, S. R., and Schwarzkopf, F. U: The response of the Antarctic Circumpolar Current to recent climate change, Nat. Geosci., 1, 864–869, https://doi.org/10.1038/ngeo362, 2008. a
Boyd, P. W. and Ellwood, M. J.: The biogeochemical cycle of iron in the ocean, Nat. Geosci., 3, 675–682, https://doi.org/10.1038/ngeo964, 2010. a
Campin, J.-M., Adcroft, A., Hill, C., and Marshall, J.: Conservation of properties in a free-surface model, Ocean Model., 221–244, https://doi.org/10.1016/S1463-5003(03)00009-X, 2004. a
Carpenter Jr., R. L., Droegmeier, K. K., Woodward, P. R., and Hane, C. E.: Application of the Piecewise Parabolic Method (PPM) to Meteorological Modeling, Mon. Weather Rev., 118, 586–612, https://doi.org/10.1175/1520-0493(1990)118<0586:AOTPPM>2.0.CO;2, 1989. a
Chidichimo, M. P., Donohue, K. A., Watts, D. R., and Tracey, K. L.: Baroclinic transport time series of the Antarctic Circumpolar Current measured in Drake Passage, J. Phys. Oceanogr., 44, 1829–1853, https://doi.org/10.1175/JPO-D-13-071.1, 2014. a
Chu, P. C. and Fan, C.: An inverse model for calculation of global volume transport from wind and hydrographic data, J. Marine Syst., 65, 376–399, https://doi.org/10.1016/j.jmarsys.2005.06.010, 2007. a
Colella, P. and Woodward, P. R.: The Piecewise Parabolic Method (PPM) for Gas-Dynamical Simulations, J. Comput. Phys., 54, 174–201, https://doi.org/10.1016/0021-9991(84)90143-8, 1984. a
Condie, S. A. and Dunn, J. R.: Seasonal characteristics of the surface mixed layer in the Australasian region: implications for primary production regimes and biogeography, Mar. Freshwater Res., 57, 569–590, https://doi.org/10.1071/MF06009, 2006. a, b, c
Corden, J. and Kreitzer, D.: Consistency of Floating-Point Results using the Intel Compiler or Why doesn't my application always give the same answer? Software Services Group, Intel Corporation, 1–25, available at: https://software.intel.com/sites/default/files/managed/3b/37/FP_Consistency_121918.pdf (last access: 6 January 2020), 2018. a
Cunningham, S. A., Alderson, S. G., King, B. A., and Brandon, M. A.: Transport and variability of the Antarctic Circumpolar Current in the Drake Passage, J. Geophys. Res., 108, 8084, https://doi.org/10.1029/2001JC001147, 2003. a
Delworth, T. L., Rosati, A., Anderson, W., Adcroft, A. J., Balaji, V., Benson, R., Dixon, K., Griffies, S. M., Lee, H.-C., Pacanowski, R. C., Vecchi, G. A., Wittenberg, A. T., Zeng, F., and Zhang, R.: Simulated Climate and Climate Change in the GFDL CM2.5 High-Resolution Coupled Climate Model, J. Climate, 25, 2755–2781, https://doi.org/10.1175/JCLI-D-11-00316.1, 2012. a
DeVries, T., Holzer, M., and Primeau, F.: Recent increase in oceanic carbon uptake driven by weaker upper-ocean overturning, Nature, 542, 215–218, https://doi.org/10.1038/nature21068, 2017. a
Dietze, H.: Dietze et al. 2018, available at: http://data.geomar.de/thredds/catalog/open_access/dietze_et_al_2018_gmd/catalog.html, last access: 19 December 2018. a
Dietze, H. and Kriest, I.: 137Cs off Fukushima Dai-ichi, Japan – model based estimates of dilution and fate, Ocean Sci., 8, 319–332, https://doi.org/10.5194/os-8-319-2012, 2012. a, b
Dietze, H. and Loeptien, U.: Revisiting “nutrient trapping” in global coupled biogeochemical ocean circulation models, Global Biogeochem. Cy., 27, 1–20, https://doi.org/10.1002/gbc.20029, 2013. a
Dietze, H., Löptien, U., and Getzlaff, K.: MOMBA 1.1 – a high-resolution Baltic Sea configuration of GFDL's Modular Ocean Model, Geosci. Model Dev., 7, 1713–1731, https://doi.org/10.5194/gmd-7-1713-2014, 2014. a, b, c
Dufour, C. O., Griffies, S. M., de Souza, G. F., Frenger, I., Morrison, A. K., Palter, J. B., Sarmiento, J. L.,
Galbraith, E. D., Dunne, J. P., Anderson, W. G., and Slater, R. D: Role of mesoscale eddies in cross-frontal transport of heat and biogeochemical tracers in the Southern Ocean, J. Phys. Oceanogr., 45, 3057–3081, https://doi.org/10.1175/JPO-D-14-0240.1, 2015. a
Fratantoni, D. M.: North Atlantic surface circulation during the 1990's observed with satellite-tracked drifters, J. Geophys. Res., 106, 22067–22093, https://doi.org/10.1029/2000JC000730, 2001. a, b
Getzlaff, J., Dietze, H., and Oschlies, A.: Simulated effects of southern hemispheric wind changes on the Pacific oxygen minimum zone, Geophys. Res. Lett., 43, 728–734, https://doi.org/10.1002/2015GL066841, 2016. a
Griffies, S. M. and Hallberg, R. W.: Biharmonic friction with a Smagorinsky-like viscosity for use in large-scale eddy-permitting ocean models, Mon. Weather Rev., 128, 2935–2946, https://doi.org/10.1175/1520-0493(2000)128<2935:BFWASL>2.0.CO;2, 2000. a, b
Grotti, M., Soggia, F., Ianni, C., and Frache, R.: Trace metals distribution in coastal sea ice of Terra Nova Bay, Ross Sea, Antarctica, Antarct. Sci., 17, 289–300, https://doi.org/10.1017/S0954102005002695, 2005. a
Hall, A. and Visbeck, M.: Synchronous variability in the Southern Hemisphere atmosphere, sea ice, and ocean resulting from the Annular Mode, J. Climate, 15, 3043–3057, https://doi.org/10.1175/1520-0442(2002)015<3043:SVITSH>2.0.CO, 2002. a
Hallberg, R. and Gnanadesikan, A.: The role of eddies in determining the structure and response of the wind-driven southern hemisphere overturning: results from the modeling eddies in the southern ocean (MESO) project, J. Phys. Oceanogr., 36, 2232–2252, https://doi.org/10.1175/JPO2980.1, 2006. a, b, c
Heinze, C., Meyer, S., Goris, N., Anderson, L., Steinfeldt, R., Chang, N., Le Quéré, C., and Bakker, D. C. E.: The ocean carbon sink – impacts, vulnerabilities and challenges, Earth Syst. Dynam., 6, 327–358, https://doi.org/10.5194/esd-6-327-2015, 2015. a
Hidake, K. and Tsuchiya, M.: On the Antarctic Circumpolar Current, J. Mar. Res., 12, 214–222, 1953. a
Hogg, A. McC., Meredith, M. P., Blundell, J. R., and Wilson, C.: Eddy heat flux in the Southern Ocean: Response to variable wind forcing, J. Climate, 21, 608–620, https://doi.org/10.1175/2007JCLI1925.1, 2008. a
Holte, J., Talley, L. D., Gilson, J., and Roemmich, D.: An Argo mixed layer climatology and database, Geophys. Res. Lett., 44, 5618–5626, https://doi.org/10.1002/2017GL073426, 2017. a, b, c, d
Hordoir, R., Axell, L., Höglund, A., Dieterich, C., Fransner, F., Gröger, M., Liu, Y., Pemberton, P., Schimanke, S., Andersson, H., Ljungemyr, P., Nygren, P., Falahat, S., Nord, A., Jönsson, A., Lake, I., Döös, K., Hieronymus, M., Dietze, H., Löptien, U., Kuznetsov, I., Westerlund, A., Tuomi, L., and Haapala, J.: Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas – research and operational applications, Geosci. Model Dev., 12, 363–386, https://doi.org/10.5194/gmd-12-363-2019, 2019. a
Hunke, E. C. and Dukowicz, J. K.: An Elastic-Viscous-Plastic Model for Sea Ice Dynamics, J. Phys. Oceanogr., 27, 1849–1867, https://doi.org/10.1175/1520-0485(1997)027<1849:AEVPMF>2.0.CO;2, 1997. a
Jochum, M., Danabasoglu, G., Holland, M., Kwon, Y.-O., and Large, W. G.: Ocean viscosity and climate, J. Geophys. Res., 113, C06017, https://doi.org/10.1029/2007JC004515, 2008. a
Keller, D. P., Oschlies, A., and Eby, M.: A new marine ecosystem model for the University of Victoria Earth System Climate Model, Geosci. Model Dev., 5, 1195–1220, https://doi.org/10.5194/gmd-5-1195-2012, 2012. a, b
Köhler, J., Martins, M. S., Serra, N., and Stammer, D.: Quality assessment of spaceborne sea surface salinity observations over the northern North Atlantic, J. Geophys. Res.-Oceans, 120, 94–112, https://doi.org/10.1002/2014JC010067, 2015. a, b
Langlais, C. E., Lenton, A., Matear, R., Monselesan, D., and Legresy, B., Cougnon, E., and Rintoul, S.: Stationary Rossby waves dominate subduction of anthropogenic carbon in the Southern Ocean, Nature, 7, 17076, https://doi.org/10.1038/s41598-017-17292-3, 2017. a
Lannuzel, D., Schoemann, V., de Jong, J., Chou, L., Delille, B., Becquevort, S., and Tison, J.: Iron study during a time series in the western Weddell pack ice, Mar. Chem., 108, 85–95, https://doi.org/10.1016/j.marchem.2007.10.006, 2008. a
Lannuzel, D., Schoemann, V., de Jong, J., Pasquer, B., van der Merwe, P., Masson, F., Tison, J.-L., and Bowie, A.: Distribution of dissolved iron in Antarctic sea ice: Spatial, seasonal, and interannual variability, J. Geophys. Res., 115, G03022, https://doi.org/10.1029/2009jg001031, 2010. a
Large, W. G. and Yeager, S. G.: Diurnal to decadal global forcing for ocean and sea-ice models: the data sets and flux climatologies, NCAR Technical Note, TN-460, 2004. a
Large, W. G., McWilliams, J. C., and Doney, S. C.: Oceanic vertical mixing – A review and a model with nonlocal boundary-layer parameterization, Rev. Geophys., 32, 363–403, https://doi.org/10.1029/94RG01872, 1994. a
Lenton, A. and Matear, R. J.: Role of the southern annular mode 80 (SAM) in Southern Ocean CO2 uptake, Global Biogeochem. Cy., 21, GB2016, https://doi.org/10.1029/2006GB002714, 2007. a
Le Quéreé, C., Raupach, M. R., Canadell, J. G., Marland, G., Bopp, L., Ciais, P., Conway, T. J., Doney, S. C.,
Feely, R. A., Foster, P., Friedlingstein, P., Gurney, K., Houghton, R. A., House, J. I., Huntingford, C., Levy, P. E.,
Lomas, M. R., Majkut, J., Metzl, N., Ometto, J. P., Peters, G. P., Prentice, I. C., Randerson, J. T., Running, S. W.,
Sarmiento, J. L., Schuster, U., Sitch, S., Takahashi, T., Viovy, N., van der Werf, G. R., and Woodward, F. I.: Trends in the sources and sinks of carbon dioxide, Nat. Geosci., 2, 831–836, https://doi.org/10.1038/NGEO689, 2009. a
Lévy, M., Estublier, A., and Madec, G.: Choice of an Advection Scheme for Biogeochemical Models, Geophys. Res. Lett., 28, 3725–3728, https://doi.org/10.1029/2001GL012947, 2001. a
Limpasuvan, V. and Hartmann, D. L.: Eddies and the annular modes of climate variability, Geophys. Res. Lett., 26, 3133–3136, https://doi.org/10.1029/1999GL010478, 1999. a
Liu, N., Eden, C., Dietze, H., Wu, D., and Lin, X.: Model-based estimates of the heat budget in the East China Sea, J. Geophys. Res.-Oceans, 115, C08026, https://doi.org/10.1029/2009JC005869, 2010. a
Löptien, U. and Dietze, H.: Constraining parameters in marine pelagic ecosystem models – is it actually feasible with typical observations of standing stocks?, Ocean Sci., 11, 573–590, https://doi.org/10.5194/os-11-573-2015, 2015. a
Löptien, U. and Dietze, H.: Effects of parameter indeterminancy in pelagic biogeochemical modules of Earth System Models on projections into a warming future: The scale of the problem, Global Biogeochem. Cy., 31, 1155–1172, https://doi.org/10.1002/2017GB005690, 2017. a
Löptien, U. and Dietze, H.: Reciprocal bias compensation and ensuing uncertainties in model-based climate projections: pelagic biogeochemistry versus ocean mixing, Biogeosciences, 16, 1865–1881, https://doi.org/10.5194/bg-16-1865-2019, 2019. a, b, c
Lovenduski, N. S., Gruber, N., and Doney, S. C.: Toward a mechanistic understanding of the decadal trends in the Southern Ocean carbon sink, Global Biogeochem. Cy., 22, GB3016, https://doi.org/10.1029/2007GB003139, 2008. a
Marinov, I., Gnanadesikan, A., Toggweiler, J. R., and Sarmiento, J. L.: The Southern Ocean biogeochemical divide, Nature, 441, 964–967, https://doi.org/10.1038/nature04883, 2006. a
Marshall, G. J.: Trends in the Southern Annular Mode from observations and reanalyses, J. Climate, 16, 4134–4143, https://doi.org/10.1175/1520-0442(2003)016<4134:TITSAM>2.0.CO;2, 2003. a
Marshall, J. and Radko, T.: Residual-Mean Solutions for the Antarctic Circumpolar Current and Its Associated Overturning Circulation, J. Phys. Oceanogr., 33, 11, 2341–2354, https://doi.org/10.1175/1520-0485(2003)033<2341:RSFTAC>2.0.CO;2, 2003. a, b
Marshall J. and Speer K.: Closure of the meridional overturning circulation through Southern Ocean upwelling, Nat. Geosci., 5, 171–180, https://doi.org/10.1038/ngeo1391, 2012. a
Mawji, E., Schlitzer, R., Dodas, E. M., Abadie, C., Abouchami, W., Anderson, R. F., Baars, O., Bakker, K., Baskaran, M.,
Bates, N. R., Bluhm, K., Bowie, A., Bown, J., Boye, M., Boyle, E. A., Branellec, P., Bruland, K. W., Brzezinski, M. A.,
Bucciarelli, E., Buesseler, K., Butler, E., Cai, P., Cardinal, D., Casciotti, K., Chaves, J., Cheng, H., Chever, F., Church, T. M.,
Colman, A. S., Conway, T. M., Croot, P. L., Cutter, G. A., de Baar, H. J. W., de Souza, G. F., Dehairs, F., Deng, F., Dieu, H. T.,
Dulaquais, G., Echegoyen-Sanz, Y., Edwards, R. L., Fahrbach, E., Fitzsimmons, J., Fleisher, M., Frank, M., Friedrich, J., Fripiat, F.,
Galer, S. J. G., Gamo, T., Solsona, E. G., Gerringa, L. J. A., Godoy, J. M., Gonzalez, S., Grossteffan, E., Hatta, M., Hayes, C. T.,
Heller, M. I., Henderson, G., Huang, K.-F., Jeandel, C., Jenkins, W. J., John, S., Kenna, T. C., Klunder, M., Kretschmer, S.,
Kumamoto, Y., Laan, P., Labatut, M., Lacan, F., Lam, P. J., Lannuzel, D., le Moigne, F., Lechtenfeld, O. J., Lohan, M. C.,
Lu, Y., Masqué, P., McClain, C. R., Measures, C., Middag, R., Moffett, J., Navidad, A., Nishioka, J., Noble, A., Obata, H.,
Ohnemus, D. C., Owens, S., Planchon, F., Pradoux, C., Puigcorbé, V., Quay, P., Radic, A., Rehkämper, M., Remenyi, T.,
Rijkenberg, M. J. A., Rintoul, S., Robinson, L. F., Roeske, T., Rosenberg, M., Rutgers van der Loeff, M., Ryabenko, E., Saito, M. A.,
Roshan, S., Salt, L., Sarthou, G., Schauer, U., Scott, P., Sedwick, P. N., Sha, L., Shiller, A. M., Sigman, D. M., Smethie, W.,
Smith, G. J., Sohrin, Y., Speich, S., Stichel, T., Stutsman, J., Swift, J. H., Tagliabue, A., Thomas, A., Tsunogai, U., Twining, B. S.,
van Aken, H. M., van Heuven, S., van Ooijen, J., van Weerlee, E., Venchiarutti, C., Voelker, A. H. L., Wake, B., Warner, M. J.,
Malcolm, E., Woodward, S., Wu, J., Wyatt, N., Yoshikawa, H., Zheng, X.-Y., Xue, Z., Zieringer, M., and Zimmer, L. A.: The GEOTRACES Intermediate Data Product 2014, Mar. Chem., 177, 1–8, https://doi.org/10.1016/j.marchem.2015.04.005, 2015. a
Mazloff, M. R., Heimbach, P., and Wunsch, C.: An Eddy-Permitting Southern Ocean State Estimate, J. Phys. Oceanogr., 40, 880–899, https://doi.org/10.1175/2009JPO4236.1, 2010. a, b, c, d
McIntosh, P. and McDougall, T.: Isopycnal averaging and the residual mean circulation, J. Phys. Oceanogr., 26, 1655–1660, https://doi.org/10.1175/1520-0485(1996)026<1655:IAATRM>2.0.CO;2, 1996. a
Moro, A., and Lonza, L.: Electricity carbon intensity in European Member States: Impacts on GHG emissions of electric vehicles, Transport. Res. D-Tr. E, 64, 5–14, https://doi.org/10.1016/j.trd.2017.07.012, 2018. a
Munday, D. R., Johnson, H. L., and Marshall, D. P.: Impacts and effects of mesoscale ocean eddies on ocean carbon storage and atmospheric pCO2, Global Biogeochem. Cy., 28, 877–896, https://doi.org/10.1002/2014GB004836, 2014. a
Orr, J. C., Najjar, R. G., Aumont, O., Bopp, L., Bullister, J. L., Danabasoglu, G., Doney, S. C., Dunne, J. P., Dutay, J.-C., Graven, H., Griffies, S. M., John, J. G., Joos, F., Levin, I., Lindsay, K., Matear, R. J., McKinley, G. A., Mouchet, A., Oschlies, A., Romanou, A., Schlitzer, R., Tagliabue, A., Tanhua, T., and Yool, A.: Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP), Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, 2017. a
Pickard, G. L. and Emery, W. J.: Descriptive Physical Oceanography, An Introduction, Pergamon Press, 5th Edn., 173–176, 1990. a
Raiswell, R., Benning, L. G., Tranter, M., and Tulaczyk, S.: Bioavailable iron in the Southern Ocean: The significance of the iceberg conveyor belt, Geochem. T., 9, 7, https://doi.org/10.1186/1467-4866-9-7, 2008. a
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670, 2003. a, b, c, d, e
Ritter, R., Landschützer, P., Gruber, N.,Fay, A. R., Lida, Y., Jones, S., Nakaoka, S., Park, G.-H., Peylin, P., Rödenbeck, C., Rodgers, K. B., Shutler, J. D., and Zeng, J.: Observation-based trends of the Southern Ocean carbon sink, Geophys. Res. Lett., 44, 12339–12348, https://doi.org/10.1002/2017GL074837, 2017. a
Russell, J., Kamenkovich, I., Bitz, C., Ferrari, R., Gille, S. T., Goodman, P. J., Hallberg, R., Johnson, K., Khazmutdinova, K., Marinov, I., Mazloff, M., Riser, S., Sarmiento, J. L., Speer, K., Talley, L. D., and Wanninkhof, R.: Metrics for the Evaluation of the Southern Ocean in Coupled Climate Models and Earth System Models, J. Geophys. Res.-Oceans, 123, 3120–3143, https://doi.org/10.1002/2017JC013461, 2018. a, b
Saenko, O. A., Fyfe, J. C., and England, M. H.: On the response of the oceanic wind-driven circulation to atmospheric CO2 increase, Climate Dynam., 25, 415–426, https://doi.org/10.1007/s00382-005-0032-5, 2005. a
Sallée, J.-B., Shuckburgh, E., Bruneau, N., Meijers, A. J. S., Bracegirdle, T. J., and Wang, Z.: Assessment of Southern Ocean mixed-layer depths in CMIP5 models: Historical bias and forcing response, J. Geophys. Res.-Oceans, 118, 1845–1862, https://doi.org/10.1002/jgrc.20157, 2013a. a, b
Sallée, J.-B., Shuckburgh, E., Bruneau, N., Meijers, A. J. S., Bracegirdle, T. J., Wang, Z., and Roy, T.: Assessment of Southern Ocean water mass circulation and characteristics in CMIP5 models: Historical bias and forcing response, J. Geophys. Res.-Oceans, 118, 1830–1844, https://doi.org/10.1002/jgrc.20135, 2013b. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o
Schmidtko, S., Heywood, K. J., Thompson, A. F., and Aoki, S.: Multidecadal warming of Antarctic waters, Science, 346, 1227–1231, https://doi.org/10.1126/science.1256117, 2014. a, b, c
Schröder, M. and Fahrbach, E.: On the structure and the transport of the eastern Weddell Gyre, Deep-Sea Res. Pt. II, 46, 501–527, https://doi.org/10.1016/S0967-0645(98)00112-X, 1999. a
Screen, J. A., Gillett, N. G., Stevens, D. P., Marshall, G. J., and Roscoe, H. K.: The role of eddies in the Southern Ocean temperature response to the Southern Annular Mode, J. Climate, 22, 806–818, https://doi.org/10.1175/2008JCLI2416.1, 2009. a
Shapiro, R.: Smoothing, filtering, and boundary effects, Rev. Geophys. Space Phys., 8, 359–387, https://doi.org/10.1029/RG008i002p00359, 1970. a
Simpkins, G. R. and Karpechko, A. Y.: Sensitivity of the southern annular mode to greenhouse gas emission scenarios, Clim. Dynam., 38, 563–572, https://doi.org/10.1007/s00382-011-1121-2, 2012. a
Smagorinsky, J.: General circulation experiments with the primitive equations: I. The basic experiment, Mon. Weather Rev., 91, 99–164, https://doi.org/10.1175/1520-0493(1963)091<0099:GCEWTP>2.3.CO;2, 1963. a
Smagorinsky, J.: Some historical remarks on the use of nonlinear viscosities, in: Large Eddy Simulation of Complex Engineering and Geophysical Flows, edited by: Galperin, B. and Orszag, S. A., Cambridge University Press, 3–36, 1993. a
Smith, K., Robison, B. H., Helly, J. J., Kaufmann, R. S., Ruhl, H. A., Shaw, T. J., Twining, B. S., and Vernet, M.: Free-drifting icebergs: Hot spots of chemical and biological enrichment in the Weddell Sea, Science, 317, 5837, 478–482, https://doi.org/10.1126/science.1142834, 2007. a
Smith, W. and Nelson, D.: Importance of ice edge phytoplankton production in the Southern Ocean, BioScience, 36, 251–257, https://doi.org/10.2307/1310215, 1986. a
Spence, P., Saenko, O. A., Eby, M., and Weaver, A. J.: The Southern Ocean Overturning: Parameterized versus Permitted Eddies, J. Phys. Oceanogr., 39, 1634–1651, https://doi.org/10.1175/2009JPO4120.1, 2009. a
Spence, P., Fyfe, J. C., Montenegro, A., and Weaver, A. J.: Southern Ocean Response to Strengthening Winds in an Eddy-Permitting Global Climate Model, J. Climate, 23, 5332–5343, https://doi.org/10.1175/2010JCLI3098.1, 2010. a
Stacey, M. W., Pond, S., and Nowak, Z. P.: A numerical model of the circulation in Knight Inlet British Columbia, Canada, J. Phys. Oceanogr., 25, 1037–1062, https://doi.org/10.1175/1520-0485(1995)025<1037:ANMOTC>2.0.CO;2, 1995. a
Sweby, P. K.: High Resolution Schemes Using Flux Limiters for Hyperbolic Conservation Laws, SIAM J. Numer. Anal., 21, 995–1011, https://doi.org/10.1137/0721062, 2012. a
Tagliabue, A., Mtshali, T., Aumont, O., Bowie, A. R., Klunder, M. B., Roychoudhury, A. N., and Swart, S.: A global compilation of dissolved iron measurements: focus on distributions and processes in the Southern Ocean, Biogeosciences, 9, 2333–2349, https://doi.org/10.5194/bg-9-2333-2012, 2012. a
Takahashi, T., Sweeney, C., Hales, B., Chipman, D. W., Newberger, T., Goddard, J. G., Iannuzzi, R. A., and Sutherland, S. C.: The changing carbon cycle in the Southern Ocean, Oceanography, 25, 26–37, https://doi.org/10.5670/oceanog.2012.71, 2012. a
Tamsitt V., Drake, H. F., Morrison, A. K., Talley, L. D., Dufour, C. O., Gray, A. R., Griffies, S. M., Mazloff, M. R., Sarmiento, J. L., Wang, J., and Weijer, W.: Spiraling pathways of global deep waters to the surface of the Souther Ocean, Nat. Commun., 8, 172, https://doi.org/10.1038/s41467-017-00197-0, 2017. a, b, c
Thompson, D. W. J. and Solomon, S.: Interpretation of Recent Southern Hemisphere Climate Change,
Science 296, 895–899, https://doi.org/10.1126/science.1069270, 2002. a, b
Thompson, D. W. J., Solomon, S., Kushner, P. J., England, M. H., Grise, K. M., and Karoly, D. J.: Signatures of the Antarctic ozone hole in Southern Hemisphere surface climates change, Nat. Geosci., 4, 741–749, https://doi.org/10.1038/NGEO1296, 2014.
a, b
Turner, J., Bracegirdle, T. J., Phillips, T., Marshall, G. J., and Hosking, J. S.: An Initial Assessment of Antarctic Sea Ice Extent in the CMIP5 Models, J. Climate, 26, 1473–1484, https://doi.org/10.1175/JCLI-D-12-00068.1, 2013. a, b
van der Merwe, P., Lannuzel, D., Nichols, C. A. M., Meiners, K., Heil, P., Norman, L., Thomas, D. N., and Bowie, A. R.: Biogeochemical observations during the winter-spring transition in East Antarctic sea ice: Evidence of iron and exopolysaccharide controls, Mar. Chem., 115, 163–175, https://doi.org/10.1016/j.marchem.2009.08.001, 2009. a
van Heuven, S. M., Hoppema, M., Jones, E. M., and de Baar, H. J.: Rapid invasion of anthropogenic CO2 into the deep circulation of the Weddell Gyre, Philos. T. Roy. Soc. A, 372, 20130056, https://doi.org/10.1098/rsta.2013.0056, 2014. a
Verdy, A. and Mazloff, M. R.: A data assimilating model for estimating Southern Ocean biogeochemistry, J. Geophys. Res.-Oceans, 122, 6968–6988, https://doi.org/10.1002/2016JC012650, 2017. a
Verdy, A., Dutkiewicz, S., Follows, M. J., Marshall, J., and Czaja, A.: Carbon dioxide and oxygen fluxes in the Southern Ocean: Mechanisms of interannual variability, Global Biogeochem. Cy., 21, GB2020, https://doi.org/10.1029/2006GB002916, 2007. a
Viebahn, J. and Eden, C.: Towards the impact of eddies on the response of the Southern Ocean to climate change, Ocean Model., 34, 150–165, https://doi.org/10.1016/j.ocemod.2010.05.005, 2010. a, b, c
Williams, G. D., Herraiz-Borreguero, L., Roquet, F., Tamura, T., Ohshima, K. I., Fukamachi, Y., Fraser, A. D., Gao, L., Chen, H., McMahon, C. R., Harcourt, R., and Hindell, M.: The suppression of Antarctic bottom water formation by melting ice shelves in Prydz Bay, Nat. Commun., 7, 12577, https://doi.org/10.1038/ncomms12577, 2016. a
Whithworth, T.: Monitoring the transport of the Antarctic Circumpolar Current at Drake Passage, J. Phys. Oceanogr., 13, 2045–2057, https://doi.org/10.1175/1520-0485(1983)013,2045:MTTOTA.2.0.CO;2, 1983. a
Yongliang, D., Hongwei, L., Weidong, Y., and Yijun, H.: The mean properties and variations of the Southerm Hemisphere subpolar gyres estimated by Simple Ocean Data Assimilation (SODA) products, Acta Oceanol. Sin., 35, 8–13, https://doi.org/10.1007/s13131-016-0901-2, 2016. a, b
Zickfeld, K., Fyfe, J. C., Saenko, O. A., Eby, M., and Weaver, A. J.: Response of the global carbon cycle to human-induced changes in Southern Hemisphere winds, Geophys. Res. Lett., 34, L12712, https://doi.org/10.1029/2006GL028797, 2007. a
Short summary
We present a new near-global coupled biogeochemical ocean-circulation model configuration of the Southern Ocean. The configuration features both a relatively equilibrated oceanic carbon inventory and an explicit representation of mesoscale eddies. In this paper, we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean carbon uptake dynamics on decadal timescales.
We present a new near-global coupled biogeochemical ocean-circulation model configuration of the...
