Articles | Volume 14, issue 7
https://doi.org/10.5194/gmd-14-4535-2021
© Author(s) 2021. 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-14-4535-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
23 Jul 2021
Development and technical paper |
| 23 Jul 2021
A discrete interaction numerical model for coagulation and fragmentation of marine detritic particulate matter (Coagfrag v.1)
Gwenaëlle Gremion
CORRESPONDING AUTHOR
Institut des sciences de la mer de Rimouski, UQAR, Québec-Océan, Rimouski, Canada
Louis-Philippe Nadeau
CORRESPONDING AUTHOR
Institut des sciences de la mer de Rimouski, UQAR, Québec-Océan, Rimouski, Canada
Christiane Dufresne
Institut des sciences de la mer de Rimouski, UQAR, Québec-Océan, Rimouski, Canada
Irene R. Schloss
Instituto Antártico Argentino, Buenos Aires, Argentina
Centro Austral de Investigaciones Científicas (CADIC-CONICET), Ushuaia, Argentina
Instituto de Ciencias Polares y Ambientales, Universidad Nacional de Tierra del Fuego, Ushuaia, Argentina
Philippe Archambault
ArcticNet, Québec-Océan, Université Laval, Quebec, Canada
Dany Dumont
Institut des sciences de la mer de Rimouski, UQAR, Québec-Océan, Rimouski, Canada
Related authors
Mathieu Casado, Gwenaëlle Gremion, Paul Rosenbaum, Jilda Alicia Caccavo, Kelsey Aho, Nicolas Champollion, Sarah L. Connors, Adrian Dahood, Alfonso Fernandez, Martine Lizotte, Katja Mintenbeck, Elvira Poloczanska, and Gerlis Fugmann
Geosci. Commun., 3, 89–97, https://doi.org/10.5194/gc-3-89-2020, https://doi.org/10.5194/gc-3-89-2020, 2020
Short summary
Short summary
Early-career scientists (ECSs) are rarely invited to act as peer reviewers. Participating in a group peer review of the IPCC Special Report on Ocean and Cryosphere in a Changing Climate, PhD students spent more time reviewing than more established scientists and provided a similar proportion of substantive comments. By soliciting and including ECSs in peer review, the scientific community would reduce the burden on more established scientists and may improve the quality of that process.
Elie Dumas-Lefebvre and Dany Dumont
The Cryosphere, 17, 827–842, https://doi.org/10.5194/tc-17-827-2023, https://doi.org/10.5194/tc-17-827-2023, 2023
Short summary
Short summary
By changing the shape of ice floes, wave-induced sea ice breakup dramatically affects the large-scale dynamics of sea ice. As this process is also the trigger of multiple others, it was deemed relevant to study how breakup itself affects the ice floe size distribution. To do so, a ship sailed close to ice floes, and the breakup that it generated was recorded with a drone. The obtained data shed light on the underlying physics of wave-induced sea ice breakup.
Flavienne Bruyant, Rémi Amiraux, Marie-Pier Amyot, Philippe Archambault, Lise Artigue, Lucas Barbedo de Freitas, Guislain Bécu, Simon Bélanger, Pascaline Bourgain, Annick Bricaud, Etienne Brouard, Camille Brunet, Tonya Burgers, Danielle Caleb, Katrine Chalut, Hervé Claustre, Véronique Cornet-Barthaux, Pierre Coupel, Marine Cusa, Fanny Cusset, Laeticia Dadaglio, Marty Davelaar, Gabrièle Deslongchamps, Céline Dimier, Julie Dinasquet, Dany Dumont, Brent Else, Igor Eulaers, Joannie Ferland, Gabrielle Filteau, Marie-Hélène Forget, Jérome Fort, Louis Fortier, Martí Galí, Morgane Gallinari, Svend-Erik Garbus, Nicole Garcia, Catherine Gérikas Ribeiro, Colline Gombault, Priscilla Gourvil, Clémence Goyens, Cindy Grant, Pierre-Luc Grondin, Pascal Guillot, Sandrine Hillion, Rachel Hussherr, Fabien Joux, Hannah Joy-Warren, Gabriel Joyal, David Kieber, Augustin Lafond, José Lagunas, Patrick Lajeunesse, Catherine Lalande, Jade Larivière, Florence Le Gall, Karine Leblanc, Mathieu Leblanc, Justine Legras, Keith Lévesque, Kate-M. Lewis, Edouard Leymarie, Aude Leynaert, Thomas Linkowski, Martine Lizotte, Adriana Lopes dos Santos, Claudie Marec, Dominique Marie, Guillaume Massé, Philippe Massicotte, Atsushi Matsuoka, Lisa A. Miller, Sharif Mirshak, Nathalie Morata, Brivaela Moriceau, Philippe-Israël Morin, Simon Morisset, Anders Mosbech, Alfonso Mucci, Gabrielle Nadaï, Christian Nozais, Ingrid Obernosterer, Thimoté Paire, Christos Panagiotopoulos, Marie Parenteau, Noémie Pelletier, Marc Picheral, Bernard Quéguiner, Patrick Raimbault, Joséphine Ras, Eric Rehm, Llúcia Ribot Lacosta, Jean-François Rontani, Blanche Saint-Béat, Julie Sansoulet, Noé Sardet, Catherine Schmechtig, Antoine Sciandra, Richard Sempéré, Caroline Sévigny, Jordan Toullec, Margot Tragin, Jean-Éric Tremblay, Annie-Pier Trottier, Daniel Vaulot, Anda Vladoiu, Lei Xue, Gustavo Yunda-Guarin, and Marcel Babin
Earth Syst. Sci. Data, 14, 4607–4642, https://doi.org/10.5194/essd-14-4607-2022, https://doi.org/10.5194/essd-14-4607-2022, 2022
Short summary
Short summary
This paper presents a dataset acquired during a research cruise held in Baffin Bay in 2016. We observed that the disappearance of sea ice in the Arctic Ocean increases both the length and spatial extent of the phytoplankton growth season. In the future, this will impact the food webs on which the local populations depend for their food supply and fisheries. This dataset will provide insight into quantifying these impacts and help the decision-making process for policymakers.
Frédéric Dupont, Dany Dumont, Jean-François Lemieux, Elie Dumas-Lefebvre, and Alain Caya
The Cryosphere, 16, 1963–1977, https://doi.org/10.5194/tc-16-1963-2022, https://doi.org/10.5194/tc-16-1963-2022, 2022
Short summary
Short summary
In some shallow seas, grounded ice ridges contribute to stabilizing and maintaining a landfast ice cover. A scheme has already proposed where the keel thickness varies linearly with the mean thickness. Here, we extend the approach by taking into account the ice thickness and bathymetry distributions. The probabilistic approach shows a reasonably good agreement with observations and previous grounding scheme while potentially offering more physical insights into the formation of landfast ice.
Philippe Massicotte, Rainer M. W. Amon, David Antoine, Philippe Archambault, Sergio Balzano, Simon Bélanger, Ronald Benner, Dominique Boeuf, Annick Bricaud, Flavienne Bruyant, Gwenaëlle Chaillou, Malik Chami, Bruno Charrière, Jing Chen, Hervé Claustre, Pierre Coupel, Nicole Delsaut, David Doxaran, Jens Ehn, Cédric Fichot, Marie-Hélène Forget, Pingqing Fu, Jonathan Gagnon, Nicole Garcia, Beat Gasser, Jean-François Ghiglione, Gaby Gorsky, Michel Gosselin, Priscillia Gourvil, Yves Gratton, Pascal Guillot, Hermann J. Heipieper, Serge Heussner, Stanford B. Hooker, Yannick Huot, Christian Jeanthon, Wade Jeffrey, Fabien Joux, Kimitaka Kawamura, Bruno Lansard, Edouard Leymarie, Heike Link, Connie Lovejoy, Claudie Marec, Dominique Marie, Johannie Martin, Jacobo Martín, Guillaume Massé, Atsushi Matsuoka, Vanessa McKague, Alexandre Mignot, William L. Miller, Juan-Carlos Miquel, Alfonso Mucci, Kaori Ono, Eva Ortega-Retuerta, Christos Panagiotopoulos, Tim Papakyriakou, Marc Picheral, Louis Prieur, Patrick Raimbault, Joséphine Ras, Rick A. Reynolds, André Rochon, Jean-François Rontani, Catherine Schmechtig, Sabine Schmidt, Richard Sempéré, Yuan Shen, Guisheng Song, Dariusz Stramski, Eri Tachibana, Alexandre Thirouard, Imma Tolosa, Jean-Éric Tremblay, Mickael Vaïtilingom, Daniel Vaulot, Frédéric Vaultier, John K. Volkman, Huixiang Xie, Guangming Zheng, and Marcel Babin
Earth Syst. Sci. Data, 13, 1561–1592, https://doi.org/10.5194/essd-13-1561-2021, https://doi.org/10.5194/essd-13-1561-2021, 2021
Short summary
Short summary
The MALINA oceanographic expedition was conducted in the Mackenzie River and the Beaufort Sea systems. The sampling was performed across seven shelf–basin transects to capture the meridional gradient between the estuary and the open ocean. The main goal of this research program was to better understand how processes such as primary production are influencing the fate of organic matter originating from the surrounding terrestrial landscape during its transition toward the Arctic Ocean.
Mathieu Casado, Gwenaëlle Gremion, Paul Rosenbaum, Jilda Alicia Caccavo, Kelsey Aho, Nicolas Champollion, Sarah L. Connors, Adrian Dahood, Alfonso Fernandez, Martine Lizotte, Katja Mintenbeck, Elvira Poloczanska, and Gerlis Fugmann
Geosci. Commun., 3, 89–97, https://doi.org/10.5194/gc-3-89-2020, https://doi.org/10.5194/gc-3-89-2020, 2020
Short summary
Short summary
Early-career scientists (ECSs) are rarely invited to act as peer reviewers. Participating in a group peer review of the IPCC Special Report on Ocean and Cryosphere in a Changing Climate, PhD students spent more time reviewing than more established scientists and provided a similar proportion of substantive comments. By soliciting and including ECSs in peer review, the scientific community would reduce the burden on more established scientists and may improve the quality of that process.
Anna J. Crawford, Derek Mueller, Gregory Crocker, Laurent Mingo, Luc Desjardins, Dany Dumont, and Marcel Babin
The Cryosphere, 14, 1067–1081, https://doi.org/10.5194/tc-14-1067-2020, https://doi.org/10.5194/tc-14-1067-2020, 2020
Short summary
Short summary
Large tabular icebergs (
ice islands) are symbols of climate change as well as marine hazards. We measured thickness along radar transects over two visits to a 14 km2 Arctic ice island and left automated equipment to monitor surface ablation and thickness over 1 year. We assess variation in thinning rates and calibrate an ice–ocean melt model with field data. Our work contributes to understanding ice island deterioration via logistically complex fieldwork in a remote environment.
Ariadna Celina Nocera, Dany Dumont, and Irene R. Schloss
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-10, https://doi.org/10.5194/bg-2020-10, 2020
Manuscript not accepted for further review
Short summary
Short summary
Zooplankton, which means drifting animals, represents a large class of animals that graze the phytoplankton that grows near the surface of oceans, lakes and estuaries and feed many other organisms of aquatic food webs. It is known that zooplankton migrate vertically every day in the water column to avoid visual predation, a process that is not often represented in ecosystem models. This paper presents a model that simulate this behavior and study its impacts on a coastal ocean environment.
Philippe Massicotte, Rémi Amiraux, Marie-Pier Amyot, Philippe Archambault, Mathieu Ardyna, Laurent Arnaud, Lise Artigue, Cyril Aubry, Pierre Ayotte, Guislain Bécu, Simon Bélanger, Ronald Benner, Henry C. Bittig, Annick Bricaud, Éric Brossier, Flavienne Bruyant, Laurent Chauvaud, Debra Christiansen-Stowe, Hervé Claustre, Véronique Cornet-Barthaux, Pierre Coupel, Christine Cox, Aurelie Delaforge, Thibaud Dezutter, Céline Dimier, Florent Domine, Francis Dufour, Christiane Dufresne, Dany Dumont, Jens Ehn, Brent Else, Joannie Ferland, Marie-Hélène Forget, Louis Fortier, Martí Galí, Virginie Galindo, Morgane Gallinari, Nicole Garcia, Catherine Gérikas Ribeiro, Margaux Gourdal, Priscilla Gourvil, Clemence Goyens, Pierre-Luc Grondin, Pascal Guillot, Caroline Guilmette, Marie-Noëlle Houssais, Fabien Joux, Léo Lacour, Thomas Lacour, Augustin Lafond, José Lagunas, Catherine Lalande, Julien Laliberté, Simon Lambert-Girard, Jade Larivière, Johann Lavaud, Anita LeBaron, Karine Leblanc, Florence Le Gall, Justine Legras, Mélanie Lemire, Maurice Levasseur, Edouard Leymarie, Aude Leynaert, Adriana Lopes dos Santos, Antonio Lourenço, David Mah, Claudie Marec, Dominique Marie, Nicolas Martin, Constance Marty, Sabine Marty, Guillaume Massé, Atsushi Matsuoka, Lisa Matthes, Brivaela Moriceau, Pierre-Emmanuel Muller, Christopher-John Mundy, Griet Neukermans, Laurent Oziel, Christos Panagiotopoulos, Jean-Jacques Pangrazi, Ghislain Picard, Marc Picheral, France Pinczon du Sel, Nicole Pogorzelec, Ian Probert, Bernard Quéguiner, Patrick Raimbault, Joséphine Ras, Eric Rehm, Erin Reimer, Jean-François Rontani, Søren Rysgaard, Blanche Saint-Béat, Makoto Sampei, Julie Sansoulet, Catherine Schmechtig, Sabine Schmidt, Richard Sempéré, Caroline Sévigny, Yuan Shen, Margot Tragin, Jean-Éric Tremblay, Daniel Vaulot, Gauthier Verin, Frédéric Vivier, Anda Vladoiu, Jeremy Whitehead, and Marcel Babin
Earth Syst. Sci. Data, 12, 151–176, https://doi.org/10.5194/essd-12-151-2020, https://doi.org/10.5194/essd-12-151-2020, 2020
Short summary
Short summary
The Green Edge initiative was developed to understand the processes controlling the primary productivity and the fate of organic matter produced during the Arctic spring bloom (PSB). In this article, we present an overview of an extensive and comprehensive dataset acquired during two expeditions conducted in 2015 and 2016 on landfast ice southeast of Qikiqtarjuaq Island in Baffin Bay.
Related subject area
Oceanography
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
The Met Office operational wave forecasting system: the evolution of the regional and global models
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
Development and validation of a global 1∕32° surface-wave–tide–circulation coupled ocean model: FIO-COM32
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) (Part I): Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: A numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths.
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Design and Evaluation of an Efficient High-Precision Ocean Surface Wave Model with a Multiscale Grid System (MSG_Wav1.0)
Reproducible and relocatable regional ocean modelling: fundamentals and practices
Barotropic tides in MPAS-Ocean (E3SM V2): impact of ice shelf cavities
Using the two-way nesting technique AGRIF with MARS3D V11.2 to improve hydrodynamics and estimate environmental indicators
Multidecadal and climatological surface current simulations for the southwestern Indian Ocean at 1∕50° resolution
A flexible z-coordinate approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
The tidal effects in the Finite-volumE Sea ice–Ocean Model (FESOM2.1): a comparison between parameterised tidal mixing and explicit tidal forcing
HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic
Moana Ocean Hindcast – a > 25-year simulation for New Zealand waters using the Regional Ocean Modeling System (ROMS) v3.9 model
A nonhydrostatic oceanic regional model, ORCTM v1, for internal solitary wave simulation
How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9
An ensemble Kalman filter-based ocean data assimilation system improved by adaptive observation error inflation (AOEI)
GULF18, a high-resolution NEMO-based tidal ocean model of the Arabian/Persian Gulf
The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment
An ensemble Kalman filter system with the Stony Brook Parallel Ocean Model v1.0
Wind work at the air-sea interface: a modeling study in anticipation of future space missions
Improved upper-ocean thermodynamical structure modeling with combined effects of surface waves and M2 internal tides on vertical mixing: a case study for the Indian Ocean
The bulk parameterizations of turbulent air–sea fluxes in NEMO4: the origin of sea surface temperature differences in a global model study
NeverWorld2: an idealized model hierarchy to investigate ocean mesoscale eddies across resolutions
Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current
Parallel implementation of the SHYFEM (System of HydrodYnamic Finite Element Modules) model
Block-structured, equal-workload, multi-grid-nesting interface for the Boussinesq wave model FUNWAVE-TVD (Total Variation Diminishing)
Evaluation of an emergent feature of sub-shelf melt oscillations from an idealized coupled ice sheet–ocean model using FISOC (v1.1) – ROMSIceShelf (v1.0) – Elmer/Ice (v9.0)
GNOM v1.0: an optimized steady-state model of the modern marine neodymium cycle
Implementation and evaluation of open boundary conditions for sea ice in a regional coupled ocean (ROMS) and sea ice (CICE) modeling system
ROMSPath v1.0: offline particle tracking for the Regional Ocean Modeling System (ROMS)
DINCAE 2.0: multivariate convolutional neural network with error estimates to reconstruct sea surface temperature satellite and altimetry observations
RADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU Octave
IBI-CCS: a regional high-resolution model to simulate sea level in western Europe
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-33, https://doi.org/10.5194/gmd-2023-33, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
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. Discuss., https://doi.org/10.5194/gmd-2023-19, https://doi.org/10.5194/gmd-2023-19, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Surface waves that propagate in the ocean or in 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 simple solutions to the governing equations exists under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open source lisence.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
EGUsphere, https://doi.org/10.5194/egusphere-2023-469, https://doi.org/10.5194/egusphere-2023-469, 2023
Short summary
Short summary
The 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 OMIP-2 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.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-24, https://doi.org/10.5194/gmd-2023-24, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Ocean surface waves play an important role at 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 WW3, and can achieve the goals of efficient and high-precision wave simulation.
Jeff Polton, James Harle, Jason Holt, Anna Katavouta, Dale Partridge, Jenny Jardine, Sarah Wakelin, Julia Rulent, Anthony Wise, Katherine Hutchinson, David Byrne, Diego Bruciaferri, Enda O'Dea, Michela De Dominicis, Pierre Mathiot, Andrew Coward, Andrew Yool, Julien Palmiéri, Gennadi Lessin, Claudia Gabriela Mayorga-Adame, Valérie Le Guennec, Alex Arnold, and Clément Rousset
Geosci. Model Dev., 16, 1481–1510, https://doi.org/10.5194/gmd-16-1481-2023, https://doi.org/10.5194/gmd-16-1481-2023, 2023
Short summary
Short summary
The aim is to increase the capacity of the modelling community to respond to societally important questions that require ocean modelling. The concept of reproducibility for regional ocean modelling is developed: advocating methods for reproducible workflows and standardised methods of assessment. Then, targeting the NEMO framework, we give practical advice and worked examples, highlighting key considerations that will the expedite development cycle and upskill the user community.
Nairita Pal, Kristin N. Barton, Mark R. Petersen, Steven R. Brus, Darren Engwirda, Brian K. Arbic, Andrew F. Roberts, Joannes J. Westerink, and Damrongsak Wirasaet
Geosci. Model Dev., 16, 1297–1314, https://doi.org/10.5194/gmd-16-1297-2023, https://doi.org/10.5194/gmd-16-1297-2023, 2023
Short summary
Short summary
Understanding tides is essential to accurately predict ocean currents. Over the next several decades coastal processes such as flooding and erosion will be severely impacted due to climate change. Tides affect currents along the coastal regions the most. In this paper we show the results of implementing tides in a global ocean model known as MPAS–Ocean. We also show how Antarctic ice shelf cavities affect global tides. Our work points towards future research with tide–ice interactions.
Sébastien Petton, Valérie Garnier, Matthieu Caillaud, Laurent Debreu, and Franck Dumas
Geosci. Model Dev., 16, 1191–1211, https://doi.org/10.5194/gmd-16-1191-2023, https://doi.org/10.5194/gmd-16-1191-2023, 2023
Short summary
Short summary
The nesting AGRIF library is implemented in the MARS3D hydrodynamic model, a semi-implicit, free-surface numerical model which uses a time scheme as an alternating-direction implicit (ADI) algorithm. Two applications at the regional and coastal scale are introduced. We compare the two-nesting approach to the classic offline one-way approach, based on an in situ dataset. This method is an efficient means to significantly improve the physical hydrodynamics and unravel ecological challenges.
Noam S. Vogt-Vincent and Helen L. Johnson
Geosci. Model Dev., 16, 1163–1178, https://doi.org/10.5194/gmd-16-1163-2023, https://doi.org/10.5194/gmd-16-1163-2023, 2023
Short summary
Short summary
Ocean currents transport things over large distances across the ocean surface. Predicting this transport is key for tackling many environmental problems, such as marine plastic pollution and coral reef resilience. However, doing this requires a good understanding ocean currents, which is currently lacking. Here, we present and validate state-of-the-art simulations for surface currents in the southwestern Indian Ocean, which will support future marine dispersal studies across this region.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-13, https://doi.org/10.5194/gmd-2023-13, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
We propose a z-coordinate vertical algorithm for coastal ocean models which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation, independently of the vertical resolution, in a stable and accurate fashion. With simple analysis and realistic numerical experiments we show that it can be used to simulate effectively coastal flows with wetting and drying.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
Short summary
Short summary
Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
Short summary
Short summary
We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Joao Marcos Azevedo Correia de Souza, Sutara H. Suanda, Phellipe P. Couto, Robert O. Smith, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 211–231, https://doi.org/10.5194/gmd-16-211-2023, https://doi.org/10.5194/gmd-16-211-2023, 2023
Short summary
Short summary
The current paper describes the configuration and evaluation of the Moana Ocean Hindcast, a > 25-year simulation of the ocean state around New Zealand using the Regional Ocean Modeling System v3.9. This is the first open-access, long-term, continuous, realistic ocean simulation for this region and provides information for improving the understanding of the ocean processes that affect the New Zealand exclusive economic zone.
Hao Huang, Pengyang Song, Shi Qiu, Jiaqi Guo, and Xueen Chen
Geosci. Model Dev., 16, 109–133, https://doi.org/10.5194/gmd-16-109-2023, https://doi.org/10.5194/gmd-16-109-2023, 2023
Short summary
Short summary
The Oceanic Regional Circulation and Tide Model (ORCTM) is developed to reproduce internal solitary wave dynamics. The three-dimensional nonlinear momentum equations are involved with the nonhydrostatic pressure obtained via solving the Poisson equation. The validation experimental results agree with the internal wave theories and observations, demonstrating that the ORCTM can successfully describe the life cycle of nonlinear internal solitary waves under different oceanic environments.
David E. Gwyther, Shane R. Keating, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 157–178, https://doi.org/10.5194/gmd-16-157-2023, https://doi.org/10.5194/gmd-16-157-2023, 2023
Short summary
Short summary
Ocean eddies are important for weather, climate, biology, navigation, and search and rescue. Since eddies change rapidly, models that incorporate or assimilate observations are required to produce accurate eddy timings and locations, yet the model accuracy is rarely assessed below the surface. We use a unique type of ocean model experiment to assess three-dimensional eddy structure in the East Australian Current and explore two pathways in which this subsurface structure is being degraded.
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi
Geosci. Model Dev., 15, 9057–9073, https://doi.org/10.5194/gmd-15-9057-2022, https://doi.org/10.5194/gmd-15-9057-2022, 2022
Short summary
Short summary
An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.
Diego Bruciaferri, Marina Tonani, Isabella Ascione, Fahad Al Senafi, Enda O'Dea, Helene T. Hewitt, and Andrew Saulter
Geosci. Model Dev., 15, 8705–8730, https://doi.org/10.5194/gmd-15-8705-2022, https://doi.org/10.5194/gmd-15-8705-2022, 2022
Short summary
Short summary
More accurate predictions of the Gulf's ocean dynamics are needed. We investigate the impact on the predictive skills of a numerical shelf sea model of the Gulf after changing a few key aspects. Increasing the lateral and vertical resolution and optimising the vertical coordinate system to best represent the leading physical processes at stake significantly improve the accuracy of the simulated dynamics. Additional work may be needed to get real benefit from using a more realistic bathymetry.
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, https://doi.org/10.5194/gmd-15-8613-2022, 2022
Short summary
Short summary
Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410, https://doi.org/10.5194/gmd-15-8395-2022, https://doi.org/10.5194/gmd-15-8395-2022, 2022
Short summary
Short summary
We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
Hector S. Torres, Patrice Klein, Jinbo Wang, Alexander Wineteer, Bo Qiu, Andrew F. Thompson, Lionel Renault, Ernesto Rodriguez, Dimitris Menemenlis, Andrea Molod, Christopher N. Hill, Ehud Strobach, Hong Zhang, Mar Flexas, and Dragana Perkovic-Martin
Geosci. Model Dev., 15, 8041–8058, https://doi.org/10.5194/gmd-15-8041-2022, https://doi.org/10.5194/gmd-15-8041-2022, 2022
Short summary
Short summary
Wind work at the air-sea interface is the scalar product of winds and currents and is the transfer of kinetic energy between the ocean and the atmosphere. Using a new global coupled ocean-atmosphere simulation performed at kilometer resolution, we show that all scales of winds and currents impact the ocean dynamics at spatial and temporal scales. The consequential interplay of surface winds and currents in the numerical simulation motivates the need for a winds and currents satellite mission.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
Short summary
Short summary
We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
Giulia Bonino, Doroteaciro Iovino, Laurent Brodeau, and Simona Masina
Geosci. Model Dev., 15, 6873–6889, https://doi.org/10.5194/gmd-15-6873-2022, https://doi.org/10.5194/gmd-15-6873-2022, 2022
Short summary
Short summary
The sea surface temperature (SST) is highly influenced by the transfer of energy driven by turbulent air–sea fluxes (TASFs). In the NEMO ocean general circulation model, TASFs are computed by means of bulk formulas. Bulk formulas require the choice of a given bulk parameterization, which influences the magnitudes of the TASFs. Our results show that parameterization-related SST differences are primarily sensitive to the wind stress differences across parameterizations.
Gustavo M. Marques, Nora Loose, Elizabeth Yankovsky, Jacob M. Steinberg, Chiung-Yin Chang, Neeraja Bhamidipati, Alistair Adcroft, Baylor Fox-Kemper, Stephen M. Griffies, Robert W. Hallberg, Malte F. Jansen, Hemant Khatri, and Laure Zanna
Geosci. Model Dev., 15, 6567–6579, https://doi.org/10.5194/gmd-15-6567-2022, https://doi.org/10.5194/gmd-15-6567-2022, 2022
Short summary
Short summary
We present an idealized ocean model configuration and a set of simulations performed using varying horizontal grid spacing. While the model domain is idealized, it resembles important geometric features of the Atlantic and Southern oceans. The simulations described here serve as a framework to effectively study mesoscale eddy dynamics, to investigate the effect of mesoscale eddies on the large-scale dynamics, and to test and evaluate eddy parameterizations.
David E. Gwyther, Colette Kerry, Moninya Roughan, and Shane R. Keating
Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022, https://doi.org/10.5194/gmd-15-6541-2022, 2022
Short summary
Short summary
The ocean current flowing along the southeastern coast of Australia is called the East Australian Current (EAC). Using computer simulations, we tested how surface and subsurface observations might improve models of the EAC. Subsurface observations are particularly important for improving simulations, and if made in the correct location and time, can have impact 600 km upstream. The stability of the current affects model estimates could be capitalized upon in future observing strategies.
Giorgio Micaletto, Ivano Barletta, Silvia Mocavero, Ivan Federico, Italo Epicoco, Giorgia Verri, Giovanni Coppini, Pasquale Schiano, Giovanni Aloisio, and Nadia Pinardi
Geosci. Model Dev., 15, 6025–6046, https://doi.org/10.5194/gmd-15-6025-2022, https://doi.org/10.5194/gmd-15-6025-2022, 2022
Short summary
Short summary
The full exploitation of supercomputing architectures requires a deep revision of the current climate models. This paper presents the parallelization of the three-dimensional hydrodynamic model SHYFEM (System of HydrodYnamic Finite Element Modules). Optimized numerical libraries were used to partition the model domain and solve the sparse linear system of equations in parallel. The performance assessment demonstrates a good level of scalability with a realistic configuration used as a benchmark.
Young-Kwang Choi, Fengyan Shi, Matt Malej, Jane M. Smith, James T. Kirby, and Stephan T. Grilli
Geosci. Model Dev., 15, 5441–5459, https://doi.org/10.5194/gmd-15-5441-2022, https://doi.org/10.5194/gmd-15-5441-2022, 2022
Short summary
Short summary
The multi-grid-nesting technique is an important methodology used for modeling transoceanic tsunamis and coastal effects. In this study, we developed a two-way nesting interface in a multi-grid-nesting system for the Boussinesq wave model FUNWAVE-TVD. The interface acts as a
backboneof the nesting framework, handling data input, output, time sequencing, and internal interactions between grids at different scales.
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022, https://doi.org/10.5194/gmd-15-5421-2022, 2022
Short summary
Short summary
We use a coupled ice–ocean model to explore an oscillation feature found in several contributing models to MISOMIP1. The oscillation is closely related to the discretized grounding line retreat and likely strengthened by the buoyancy–melt feedback and/or melt–geometry feedback near the grounding line, and frequent ice–ocean coupling. Our model choices have a non-trivial impact on mean melt and ocean circulation strength, which might be interesting for the coupled ice–ocean community.
Benoît Pasquier, Sophia K. V. Hines, Hengdi Liang, Yingzhe Wu, Steven L. Goldstein, and Seth G. John
Geosci. Model Dev., 15, 4625–4656, https://doi.org/10.5194/gmd-15-4625-2022, https://doi.org/10.5194/gmd-15-4625-2022, 2022
Short summary
Short summary
Neodymium isotopes in seawater have the potential to provide key information about ocean circulation, both today and in the past. This can shed light on the underlying drivers of global climate, which will improve our ability to predict future climate change, but uncertainties in our understanding of neodymium cycling have limited use of this tracer. We present a new model of neodymium in the modern ocean that runs extremely fast, matches observations, and is freely available for development.
Pedro Duarte, Jostein Brændshøi, Dmitry Shcherbin, Pauline Barras, Jon Albretsen, Yvonne Gusdal, Nicholas Szapiro, Andreas Martinsen, Annette Samuelsen, Keguang Wang, and Jens Boldingh Debernard
Geosci. Model Dev., 15, 4373–4392, https://doi.org/10.5194/gmd-15-4373-2022, https://doi.org/10.5194/gmd-15-4373-2022, 2022
Short summary
Short summary
Sea ice models are often implemented for very large domains beyond the regions of sea ice formation, such as the whole Arctic or all of Antarctica. In this study, we implement changes in the Los Alamos Sea Ice Model, allowing it to be implemented for relatively small regions within the Arctic or Antarctica and yet considering the presence and influence of sea ice outside the represented areas. Such regional implementations are important when spatially detailed results are required.
Elias J. Hunter, Heidi L. Fuchs, John L. Wilkin, Gregory P. Gerbi, Robert J. Chant, and Jessica C. Garwood
Geosci. Model Dev., 15, 4297–4311, https://doi.org/10.5194/gmd-15-4297-2022, https://doi.org/10.5194/gmd-15-4297-2022, 2022
Short summary
Short summary
ROMSPath is an offline particle tracking model tailored for use with output from Regional Ocean Modeling System (ROMS) simulations. It is an update to an established system, the Lagrangian TRANSport (LTRANS) model, including a number of improvements. These include a modification of the model coordinate system which improved accuracy and numerical efficiency, and added functionality for nested grids and Stokes drift.
Alexander Barth, Aida Alvera-Azcárate, Charles Troupin, and Jean-Marie Beckers
Geosci. Model Dev., 15, 2183–2196, https://doi.org/10.5194/gmd-15-2183-2022, https://doi.org/10.5194/gmd-15-2183-2022, 2022
Short summary
Short summary
Earth-observing satellites provide routine measurement of several ocean parameters. However, these datasets have a significant amount of missing data due to the presence of clouds or other limitations of the employed sensors. This paper describes a method to infer the value of the missing satellite data based on a convolutional autoencoder (a specific type of neural network architecture). The technique also provides a reliable error estimate of the interpolated value.
Olivier Sulpis, Matthew P. Humphreys, Monica M. Wilhelmus, Dustin Carroll, William M. Berelson, Dimitris Menemenlis, Jack J. Middelburg, and Jess F. Adkins
Geosci. Model Dev., 15, 2105–2131, https://doi.org/10.5194/gmd-15-2105-2022, https://doi.org/10.5194/gmd-15-2105-2022, 2022
Short summary
Short summary
A quarter of the surface of the Earth is covered by marine sediments rich in calcium carbonates, and their dissolution acts as a giant antacid tablet protecting the ocean against human-made acidification caused by massive CO2 emissions. Here, we present a new model of sediment chemistry that incorporates the latest experimental findings on calcium carbonate dissolution kinetics. This model can be used to predict how marine sediments evolve through time in response to environmental perturbations.
Alisée A. Chaigneau, Guillaume Reffray, Aurore Voldoire, and Angélique Melet
Geosci. Model Dev., 15, 2035–2062, https://doi.org/10.5194/gmd-15-2035-2022, https://doi.org/10.5194/gmd-15-2035-2022, 2022
Short summary
Short summary
Climate-change-induced sea level rise is a major threat for coastal and low-lying regions. Projections of coastal sea level changes are thus of great interest for coastal risk assessment and have significantly developed in recent years. In this paper, the objective is to provide high-resolution (6 km) projections of sea level changes in the northeastern Atlantic region bordering western Europe. For that purpose, a regional model is used to refine existing coarse global projections.
Cited articles
Ackleh, A. S.:
Parameter estimation in a structured algal coagulation-fragmentation model,
Nonlinear Anal.-Theor.,
28, 837–854, https://doi.org/10.1016/0362-546X(95)00195-2, 1997. a
Alldredge, A.:
The carbon, nitrogen and mass content of marine snow as a function of aggregate size,
Deep-Sea Res. Pt. I,
45, 529–541, https://doi.org/10.1016/S0967-0637(97)00048-4, 1998. a, b
Alldredge, A. L., Granata, T. C., Gotschalk, C. C., and Dickey, T. D.:
The physical strength of marine snow and its implications for particle disaggregation in the ocean,
Limnol. Oceanogr.,
35, 1415–1428, https://doi.org/10.4319/lo.1990.35.7.1415, 1990. a, b, c
Anderson, T. and Gentleman, W.:
The legacy of Gordon Arthur Riley (1911–1985) and the development of mathematical models in biological oceanography,
J. Mar. Res.,
70, 1–30, https://doi.org/10.1357/002224012800502390, 2012. a
Anderson, T. R.:
Plankton functional type modelling: running before we can walk?,
J. Plankton Res.,
27, 1073–1081, https://doi.org/10.1093/plankt/fbi076, 2005. a
Anderson, T. R., Gentleman, W., and Sinha, B.:
Influence of grazing formulations on the emergent properties of a complex ecosystem model in a global ocean general circulation model,
Prog. Oceanogr.,
87, 201–213, https://doi.org/10.1016/j.pocean.2010.06.003, 2010. a
Aumont, O., Maier-Reimer, E., Blain, S., and Monfray, P.:
An ecosystem model of the global ocean including Fe, Si, P colimitations,
Global Biogeochem. Cy.,
17, 1060, https://doi.org/10.1029/2001GB001745, 2003. a, b
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. a
Banse, K.:
New views on the degradation and disposition of organic particles as collected by sediment traps in the open sea,
Deep-Sea Res.,
37, 1177–1195, https://doi.org/10.1016/0198-0149(90)90058-4, 1990. a
Blackford, J. and Radford, P.:
A structure and methodology for marine ecosystem modelling,
Neth. J. Sea Res.,
33, 247–260, https://doi.org/10.1016/0077-7579(95)90048-9, 1995. a
Boyd, P., Claustre, H., Levy, M., Siegel, D., and Weber, T.:
Multi-facted particle pumps drive carbon sequestration in the ocean,
Nature,
568, 327–335, https://doi.org/10.1038/s41586-019-1098-2, 2019. a
Burd, A. B.:
Modeling particle aggregation using size class and size spectrum approaches,
J. Geophys. Res.,
118, 3431–3443, https://doi.org/10.1002/jgrc.20255, 2013. a
Burd, A. B., Chanton, J. P., Daly, K. L., Gilbert, S., Passow, U., and Quigg, A.:
The science behind marine-oil snow and MOSSFA: past, present, and future,
Prog. Oceanogr.,
187, https://doi.org/10.1016/j.pocean.2020.102398, 2020. a
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. a
De La Rocha, C. L. and Passow, U.:
Factors influencing the sinking of POC and the efficiency of the biological carbon pump,
Deep-Sea Res. Pt. II,
54, 639–658, https://doi.org/10.1016/j.dsr2.2007.01.004, 2007. a, b
Denman, K.:
Modelling planktonic ecosystems: parameterizing complexity,
Prog. Oceanogr.,
57, 429–452, https://doi.org/10.1016/S0079-6611(03)00109-5, 2003. a
Denman, K., Brasseur, G., Chidthaisong, A., Ciais, P., Cox, P., Dickinson, R., Hauglustaine, D., Heinze, C., Holland, E., Jacob, D., Lohmann, U., Ramachandran, S., da Silva Dias, P., Wofsy, S., and Zhang, X.:
2007: Couplings Between Changes in the Climate System and Biogeochemistry,
in: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change,
edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., Tignor, M., and Miller, H.,
Cambridge University Press, Cambridge, UK and New York, NY, USA,
availabale at: https://www.ipcc.ch/site/assets/uploads/2018/02/ar4-wg1-chapter7-1.pdf (last access: 28 June 2021), 2007. a
Dilling, L. and Alldredge, A. L.:
Fragmentation of marine snow by swimming macrozooplankton: A new process impacting carbon cycling in the sea,
Deep-Sea Res. Pt. I,
47, 1227–1245, https://doi.org/10.1016/S0967-0637(99)00105-3, 2000. a, b
Dissanayake, A. L., Burd, A. B., Daly, K. L., Francis, S., and Passow, U.:
Numerical modeling of the interactions of oil, marine snow, and riverine sediments in the ocean,
J. Geophys. Res.-Oceans,
123, 5388–5405, https://doi.org/10.1029/2018JC013790, 2018. a
Doney, S., Kleypas, J., Sarmiento, J., and Falkowski, P.:
The US JGOFS Synthesis and Modeling Project – An introduction,
Deep-Sea Res. Pt. II,
49, 1–20, https://doi.org/10.1016/S0967-0645(01)00092-3, 2002. a
Doney, S. C., Glover, D. M., and Najjar, R. G.:
A new coupled, one-dimensional biological-physical model for the upper ocean: Applications to the JGOFS Bermuda Atlantic Time-series Study (BATS) site,
Deep-Sea Res. Pt. II,
43, 591–624, https://doi.org/10.1016/0967-0645(95)00104-2, 1996. a, b
Doney, S. C., Lindsay, K., and Moore, J. K.:
Global Ocean Carbon Cycle Modeling, vol. 4,
in: Ocean Biogeochemistry,
edited by: Fasham, M.,
Springer, Verlag Berlin Heidelberg, 217–238, https://doi.org/10.1007/978-3-642-55844-3_10, 2003. a, b
Dutkiewicz, S., Follows, M. J., and Parekh, P.:
Interactions of the iron and phosphorus cycles: A three-dimensional model study,
Global Biogeochem. Cy.,
19, GB1021, https://doi.org/10.1029/2004GB002342, 2005. a, b
Engel, A.:
The role of transparent exopolymer particles (TEP) in the increase in apparent particle stickiness during the decline of a diatom bloom,
J. Plankton Res.,
22, 485–497, https://doi.org/10.1093/plankt/22.3.485, 2000. a
Fasham, M., Ducklow, H. W., and McKelvie, M.:
A nitrogen-based model of plankton dynamics in the oceanic mixed layer,
J. Mar. Res.,
48, 591–639, https://doi.org/10.1357/002224090784984678, 1990. a
Flynn, K. J.:
Castles built on sand: dysfunctionality in plankton models and the inadequacy of dialogue between biologists and modellers,
J. Plankton Res.,
27, 1205–1210, https://doi.org/10.1093/plankt/fbi099, 2005. a
Gelbard, F., Tambour, Y., and Seinfeld, J. H.:
Sectional representations for simulating aerosol dynamics,
J. Colloid Interf. Sci.,
76, 541–556, https://doi.org/10.1016/0021-9797(80)90394-X, 1980. a, b
Gloege, L., Mc Kinley, G. A., Mouw, C., and Ciochetto, A. B.:
Global evaluation of particulate organic carbon flux parametrizations and implications for atmospheric pCO2,
Global Biogeochem. Cy.,
31, 1192–1215, https://doi.org/10.1002/2016GB005535, 2017. a
Goldthwait, S., Yen, J., Brown, J., and Alldredge, A.:
Quantification of marine snow fragmentation by swimming euphausiids,
Limnol. Oceanogr.,
49, 940–952, https://doi.org/10.4319/lo.2004.49.4.0940, 2004. a, b
Green, E. P. and Dagg, M. J.:
Mesozooplankton associations with medium to large marine snow aggregates in the northern Gulf of Mexico,
J. Plankton Res.,
19, 435–447, https://doi.org/10.1093/plankt/19.4.435, 1997. a
Gregory, J.:
The density of particle aggregates,
Water Sci. Technol.,
36-4, 1–13, https://doi.org/10.1016/S0273-1223(97)00452-6, 1997. a
Gremion, G. and Nadeau, L.-P.:
Source code and user manual of the Coagfrag Model (Version 1),
Zenodo,
2021-01-11, https://doi.org/10.5281/zenodo.4432896, 2021. a, b
Hansen, K.:
Abundance Distributions; Large Scale Features,
Springer International Publishing, Cham, https://doi.org/10.1007/978-3-319-90062-9_8, pp. 205–251, 2018. a
Hill, P. S.:
Reconciling aggregation theory with observed vertical fluxes following phytoplankton blooms,
J. Geophys. Res.-Oceans,
97, 2295–2308, https://doi.org/10.1029/91JC02808, 1992. a
Hill, P. S.:
Sectional and discrete representations of floc breakage in agitated suspensions,
Deep-Sea Res. Pt. I,
43, 679–702, https://doi.org/10.1016/0967-0637(96)00030-1, 1996. a
Hood, R. R., Laws, E. A., Armstrong, R. A., Bates, N. R., Brown, C. W., Carlson, C. A., Chaig, F., Doneyh, S. C., Falkowskii, P. G., Feelyj, R. A., Friedrichsk, M., Landryl, M. R., Moorem, J. K., Nelsonn, D. M., Richardson, T. L., Salihoglup, B., Schartauq, M., Tooleh, D. A., and D., W. J.:
Pelagic functional group modeling: Progress, challenges and prospects,
Deep-Sea Res. Pt. II,
53, 459–512, https://doi.org/10.1016/j.dsr2.2006.01.025, 2006. a
Jackson, G. A.:
A model of the formation of marine algal flocs by physical coagulation processes,
Deep-Sea Res.,
37, 1197–1211, https://doi.org/10.1016/0198-0149(90)90038-W, 1990. a
Jackson, G. A.:
Effect of coagulation on a model planktonic food web,
Deep-Sea Res. Pt. I,
48, 95–123, https://doi.org/10.1016/S0967-0637(00)00040-6, 2001. a, b, c
Jackson, G. A. and Burd, A. B.:
Aggregation in the Marine Environment, Environ. Sci. Technol., 32, 2805–2814, https://doi.org/10.1021/es980251w, 1998. a
Jackson, G. A. and Burd, A. B.:
Simulating aggregate dynamics in ocean biogeochemical models,
Prog. Oceanogr.,
133, 55–65, https://doi.org/10.1016/j.pocean.2014.08.014, 2015. a, b
Jackson, G. A., Logan, B. E., Alldredge, A. L., and Dam, H. G.:
Combining particle size spectra from a mesocosm experiment measured using photographic and aperture impedance (Coulter and Elzone) techniques,
Deep-Sea Res. Pt. II,
42, 139–157, https://doi.org/10.1016/0967-0645(95)00009-F, 1995. a, b
Jackson, G. A., Maffione, R., Costello, D. K., Alldredge, A. L., Logan, B. E., and Dam, H. G.:
Particle size spectra between 1 µm and 1 cm at Monterey Bay determined using multiple instruments,
Deep-Sea Res. Pt. I,
44, 1739–1767, https://doi.org/10.1016/S0967-0637(97)00029-0, 1997. a, b, c
Jokulsdottir, T. and Archer, D.: A stochastic, Lagrangian model of sinking biogenic aggregates in the ocean (SLAMS 1.0): model formulation, validation and sensitivity, Geosci. Model Dev., 9, 1455–1476, https://doi.org/10.5194/gmd-9-1455-2016, 2016. a
Kang, I.-S., Ahn, M.-S., Miura, H., and Subramanian, A.:
Chapter 14 – GCMs With Full Representation of Cloud Microphysics and Their MJO Simulations,
in: Sub-Seasonal to Seasonal Prediction,
edited by: Robertson, A. W. and Vitart, F.,
Elsevier, the Netherlands, UK, USA, https://doi.org/10.1016/B978-0-12-811714-9.00014-0, pp. 305–319, 2019. a
Karakaş, G., Nowald, N., Schäfer-Neth, C., Iversen, M., Barkmann, W., Fischer, G., Marchesiello, P., and Schlitzer, R.:
Impact of particle aggregation on vertical fluxes of organic matter,
Prog. Oceanogr.,
83, 331–341, https://doi.org/10.1016/j.pocean.2009.07.047, 2009. a
Kearney, K., Hermann, A., Cheng, W., Ortiz, I., and Aydin, K.: A coupled pelagic–benthic–sympagic biogeochemical model for the Bering Sea: documentation and validation of the BESTNPZ model (v2019.08.23) within a high-resolution regional ocean model, Geosci. Model Dev., 13, 597–650, https://doi.org/10.5194/gmd-13-597-2020, 2020. a
Khain, A. P., Beheng, K. D., Heymsfield, A., Korolev, A., Krichak, S. O., Levin, Z., Pinsky, M., Phillips, V., Prabhakaran, T., Teller, A., van den Heever, S. C., and Yano, J.-I.:
Representation of microphysical processes in cloud-resolving models: Spectral (bin) microphysics versus bulk parameterization,
Rev. Geophys.,
53, 247–322, https://doi.org/10.1002/2014RG000468, 2015. a
Kishi, M. J., Kashiwai, M., Ware, D. M., Megrey, B. A., Eslinger, D. L., Werner, F. E., Noguchi-Aita, M., Azumaya, T., Fujii, M., Hashimoto, S., Huang, D., Iizumi, H., Ishida, Y., Kang, S., Kantakov, G. A., Kim, H.-C., Komatsu, K., Navrotsky, V. V., Smith, S. L., Tadokoro, K., Tsuda, A., Yamamura, O., Yamanaka, Y., Yokouchi, K. Yoshie, N., Zhang, J., Zuenko, Y. I., and Zvalinsky, V. I.:
NEMURO–a lower trophic level model for the North Pacific marine ecosystem,
Ecol. Model.,
202, 12–25, https://doi.org/10.1016/j.ecolmodel.2006.08.021, 2007. a
Kiørboe, T.:
Colonization of marine snow aggregates by invertebrate zooplankton: Abundance, scaling, and possible role,
Limnol. Oceanogr.,
45, 479–484, https://doi.org/10.4319/lo.2000.45.2.0479, 2000. a
Kiørboe, T. and Thygesen, U. H.:
Fluid motion and solute distribution around sinking aggregates. II. Implications for remote detection by colonizing zooplankters,
Mar. Ecol.-Prog. Ser.,
211, 15–25, https://doi.org/10.3354/meps211015, 2001. a
Kiørboe, T., Andersen, K. P., and Dam, H. G.:
Coagulation efficiency and aggregate formation in marine phytoplankton,
Mar. Biol.,
107, 235–245, https://doi.org/10.1007/BF01319822, 1990. a
Kobayashi, M., Adachi, Y., and Ooi, S.:
Breakup of Fractal Flocs in a Turbulent Flow,
Langmuir,
15, 4351–4356, https://doi.org/10.1021/la980763o, 1999. a
Kriest, I.:
Different parameterizations of marine snow in a 1D-model and their influence on representation of marine snow, nitrogen budget and sedimentation,
Deep-Sea Res. Pt. I,
49, 2133–2162, https://doi.org/10.1016/S0967-0637(02)00127-9, 2002. a, b
Kriest, I. and Evans, G. T.:
Representing phytoplankton aggregates in biogeochemical models,
Deep-Sea Res. Pt. I,
46, 1841–1859, https://doi.org/10.1016/S0967-0637(99)00032-1, 1999. a
Lee, J. K., Samanta, D., Nam, H. G., and Zare, R. N.:
Spontaneous formation of gold nanostructures in aqueous microdroplets,
Nat. Commun.,
9, 1–9, 2018. a
Leles, S. G., Valentin, J. L., and Figueiredo, G. M.:
Evaluation of the complexity and performance of marine planktonic trophic models,
An. Acad. Bras. Cienc.,
88, 1971–1991, https://doi.org/10.1590/0001-3765201620150588, 2016. a
Le Moigne, F.:
Pathways of Organic Carbon Downward Transport by the Oceanic Biological Carbon Pump,
Front. Mar. Sci.,
6, 634, https://doi.org/10.3389/fmars.2019.00634, 2019. a
Le Quéré, C.:
Reply to Horizons Article 'Plankton functional type modelling: running before we can walk' Anderson (2005): I. Abrupt changes in marine ecosystems?,
J. Plankton Res.,
28, 871–872, https://doi.org/10.1093/plankt/fbl014, 2006. a
Le Quéré, C., Harrison, S. P., Prentice, I. C., Buitenhuis, E. T., Aumont, O., Bopp, L., Claustre, H., Cotrim Da Cunha, L., Geider, R., Giraud, X., Klaas, C., Kohfeld, K. E., Legendre, L., Manizza, M., Platt, T., Rivkin, R. B., Sathyendranath, S., Uitz, J., Watson, A. J., and Wolf-Gladrow, D.:
Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models,
Glob. Change Biol.,
11, 2016–2040, https://doi.org/10.1111/j.1365-2486.2005.1004.x, 2005. a
Li, X., Passow, U., and Logan, B. E.:
Fractal dimensions of small (15–200 µm) particles in Eastern Pacific coastal waters,
Deep-Sea Res. Pt. I,
45, 115–131, https://doi.org/10.1016/S0967-0637(97)00058-7, 1998. a
Li, X. Y., Zhang, J. J., and Lee, J. H.:
Modelling particle size distribution dynamics in marine waters,
Water Res.,
38, 1305–1317, https://doi.org/10.1016/j.watres.2003.11.010, 2004. a, b
Lima, I. D., Olson, D. B., and Doney, S. C.:
Intrinsic dynamics and stability properties of size-structured pelagic ecosystem models,
J. Plankton Res.,
24, 533–556, https://doi.org/10.1093/plankt/24.6.533, 2002. a
McCave, I.:
Size spectra and aggregation of suspended particles in the deep ocean,
Deep-Sea Res.,
31, 329–352, https://doi.org/10.1016/0198-0149(84)90088-8, 1984. a, b, c
Monroy, P., Hernández-García, E., Rossi, V., and López, C.:
Modeling the dynamical sinking of biogenic particles in oceanic flow,
Nonlinear Proc. Geoph.,
24, 293–305, https://doi.org/10.5194/npg-24-293-2017, 2017. a
Moore, J. K., Doney, S. C., Kleypas, J. A., Glover, D. M., and Fung, I. Y.:
An intermediate complexity marine ecosystem model for the global domain,
Deep-Sea Res. Pt. II,
49, 403–462, https://doi.org/10.1016/S0967-0645(01)00108-4, 2002. a
Neumann, T.:
Towards a 3-D ecosystem model of the Baltic Sea,
J. Marine Syst.,
25, 405–419, https://doi.org/10.1016/S0924-7963(00)00030-0, 2000. a
Oriekhova, O. and Stoll, S.:
Heteroaggregation of nanoplastic particles in the presence of inorganic colloids and natural organic matter,
Environ. Sci.-Nano,
5, 792–799, https://doi.org/10.1039/C7EN01119A, 2018. a
Palmer, J. R. and Totterdell, I. J.:
Production and export in a global ocean ecosystem model,
Deep-Sea Res. Pt. I,
48, 1169–1198, https://doi.org/10.1016/S0967-0637(00)00080-7, 2001. a, b
Passow, U. and Carlson, C. A.:
The biological pump in a high CO2 world,
Mar. Ecol.-Prog. Ser.,
470, 249–271, https://doi.org/10.3354/meps09985, 2012. a
Pego, R. L.:
Lectures on dynamics in models of coarsening and coagulation,
in: Dynamics in models of coarsening, coagulation, condensation and quantization,
World Scientific, Pittsburgh, USA,
available at: https://www.math.cmu.edu/CNA/Publications/publications2006/001abs/06-CNA-001.pdf (last access: 28 June 2021), pp. 1–61, 2007. a
Ploug, H. and Grossart, H.-P.:
Bacterial growth and grazing on diatom aggregates: Respiratory carbon turnover as a function of aggregate size and sinking velocity,
Limnol. Oceanogr.,
45, 1467–1475, https://doi.org/10.4319/lo.2000.45.7.1467, 2000. a
Pruppacher, H. R. and Klett, J. D.:
Microphysics of clouds and precipitation, no. v. 18 in Atmos. Oceanogr. Sciences Library,
Springer, Dordrecht, New York, https://doi.org/10.1007/978-0-306-48100-0, 2010. a, b
Raick, C., Soetaert, K., and Grégoire, M.:
Model complexity and performance: How far can we simplify?,
Prog. Oceanogr.,
70, 27–57, https://doi.org/10.1016/j.pocean.2006.03.001, 2006. a
Riley, G. A.:
Factors controlling phytoplankton populations on Georges Bank,
J. Mar. Res.,
6, 54–73,
available at: http://images.peabody.yale.edu/publications/jmr/jmr06-01-04.pdf (last access: 28 June 2021), 1946. a
Sarmiento, J. L.and Slater, R. D., Fasham, M. J. R., Ducklow, H. W., Toggweiler, J. R., and Evans, G. T.:
A seasonal three-dimensional ecosystem model of nitrogen cycling in the North Atlantic euphotic zone,
Global Biogeochem. Cy.,
7, 417–450, https://doi.org/10.1029/93GB00375, 1993. a
Stemmann, L., Picheral, M., and Gorsky, G.:
Diel variation in the vertical distribution of particulate matter (> 0.15 mm) in the NW Mediterranean Sea investigated with the Underwater Video Profiler,
Deep-Sea Res. Pt. I,
47, 505–531, https://doi.org/10.1016/S0967-0637(99)00100-4, 2000. a
Stemmann, L., Jackson, G. A., and Ianson, D.:
A vertical model of particle size distributions and fluxes in the midwater column that includes biological and physical processes–Part I: model formulation,
Deep-Sea Res. Pt. I,
51, 865–884, https://doi.org/10.1016/j.dsr.2004.03.001, 2004. a, b
Vichi, M., Pinardi, N., and Masina, S.:
A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part I: Theory,
J. Mar. Sys.,
64, 89–109, https://doi.org/10.1016/j.jmarsys.2006.03.006, 2007. a
von Smoluchowski, M.:
Drei Vorträge über Diffusion, Brownsche Molekularbewegung und Koagulation von Kolloidteilchen,
Phys. Z.,
17, 557–571, https://fbc.pionier.net.pl/id/oai:jbc.bj.uj.edu.pl:387533, 1916. a
Ward, B. A., Dutkiewicz, S., Jahn, O., and Follows, M. J.:
A size-structured food-web model for the global ocean,
Limnol. Oceanogr.,
57, 1877–1891, https://doi.org/10.4319/lo.2012.57.6.1877, 2012. a
Wiggert, J., Murtugudde, R., and Christian, J.:
Annual ecosystem variability in the tropical Indian Ocean: Results of a coupled bio-physical ocean general circulation model,
Deep-Sea Res. Pt. II,
53, 644–676, https://doi.org/10.1016/j.dsr2.2006.01.027, 2006. a, b
Yool, A., Popova, E. E., and Anderson, T. R.: Medusa-1.0: a new intermediate complexity plankton ecosystem model for the global domain, Geosci. Model Dev., 4, 381–417, https://doi.org/10.5194/gmd-4-381-2011, 2011. a
Zahnow, J. C., Maerz, J., and Feudel, U.:
Particle-based modeling of aggregation and fragmentation processes: Fractal-like aggregates,
Physica D,
240, 882–893, https://doi.org/10.1016/j.physd.2011.01.003, 2011. a
Short summary
An accurate description of detritic organic particles is key to improving estimations of carbon export into the ocean abyss in ocean general circulation models. Yet, most parametrization are numerically impractical due to the required number of tracers needed to resolve the particle size spectrum. Here, a new parametrization that aims to minimize the tracers number while accurately describing the particles dynamics is developed and tested in a series of idealized numerical experiments.
An accurate description of detritic organic particles is key to improving estimations of carbon...
