Articles | Volume 14, issue 4
https://doi.org/10.5194/gmd-14-2265-2021
© 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-14-2265-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
30 Apr 2021
Model description paper |
| 30 Apr 2021
| 30 Apr 2021
MESMO 3: Flexible phytoplankton stoichiometry and refractory dissolved organic matter
Department of Earth & Environmental Sciences, University of Minnesota,
Minneapolis, Minnesota, USA
Tatsuro Tanioka
Department of Earth & Environmental Sciences, University of Minnesota,
Minneapolis, Minnesota, USA
current affiliation: Department of Earth System Science, University
of California Irvine, Irvine, California, USA
Jacob Zahn
Department of Earth & Environmental Sciences, University of Minnesota,
Minneapolis, Minnesota, USA
Related authors
Tatsuro Tanioka and Katsumi Matsumoto
Biogeosciences, 17, 2939–2954, https://doi.org/10.5194/bg-17-2939-2020, https://doi.org/10.5194/bg-17-2939-2020, 2020
Short summary
Short summary
We conducted an extensive literature survey (meta-analysis) on how the C : N : P ratio varies with change in key environmental drivers. We found that the expected reduction in nutrients and warming under the future climate change scenario is likely to result in increased C : P and C : N of marine phytoplankton. Further, our findings highlight the greater stoichiometric plasticity of eukaryotes over prokaryotes, which provide us insights on how to understand and model plankton.
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
K. Matsumoto, K. Tokos, A. Huston, and H. Joy-Warren
Geosci. Model Dev., 6, 477–494, https://doi.org/10.5194/gmd-6-477-2013, https://doi.org/10.5194/gmd-6-477-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
Tatsuro Tanioka and Katsumi Matsumoto
Biogeosciences, 17, 2939–2954, https://doi.org/10.5194/bg-17-2939-2020, https://doi.org/10.5194/bg-17-2939-2020, 2020
Short summary
Short summary
We conducted an extensive literature survey (meta-analysis) on how the C : N : P ratio varies with change in key environmental drivers. We found that the expected reduction in nutrients and warming under the future climate change scenario is likely to result in increased C : P and C : N of marine phytoplankton. Further, our findings highlight the greater stoichiometric plasticity of eukaryotes over prokaryotes, which provide us insights on how to understand and model plankton.
M. Eby, A. J. Weaver, K. Alexander, K. Zickfeld, A. Abe-Ouchi, A. A. Cimatoribus, E. Crespin, S. S. Drijfhout, N. R. Edwards, A. V. Eliseev, G. Feulner, T. Fichefet, C. E. Forest, H. Goosse, P. B. Holden, F. Joos, M. Kawamiya, D. Kicklighter, H. Kienert, K. Matsumoto, I. I. Mokhov, E. Monier, S. M. Olsen, J. O. P. Pedersen, M. Perrette, G. Philippon-Berthier, A. Ridgwell, A. Schlosser, T. Schneider von Deimling, G. Shaffer, R. S. Smith, R. Spahni, A. P. Sokolov, M. Steinacher, K. Tachiiri, K. Tokos, M. Yoshimori, N. Zeng, and F. Zhao
Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, https://doi.org/10.5194/cp-9-1111-2013, 2013
K. Matsumoto, K. Tokos, A. Huston, and H. Joy-Warren
Geosci. Model Dev., 6, 477–494, https://doi.org/10.5194/gmd-6-477-2013, https://doi.org/10.5194/gmd-6-477-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
Related subject area
Oceanography
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
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 1: 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
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Great Lakes Waves Forecast System on High-Resolution Unstructured Meshes
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
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
Impact of high resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
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
Studying multi-scale ocean dynamics and their contribution to water, heat and salt budgets in the South China Sea: evaluation of a high-resolution configuration of an online closed-budget hydrodynamical ocean model (SYMPHONIE version 249)
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
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
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
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
Short summary
Short summary
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
Short summary
Short summary
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
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., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-167, https://doi.org/10.5194/gmd-2023-167, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
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 winter time (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 GL.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
EGUsphere, https://doi.org/10.5194/egusphere-2023-1715, https://doi.org/10.5194/egusphere-2023-1715, 2023
Short summary
Short summary
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 study of QG equations on realistic domains. We release a Pytorch implementation to ease future machine-learning developments on top of the presented method.
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.
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. Discuss., https://doi.org/10.5194/gmd-2023-123, https://doi.org/10.5194/gmd-2023-123, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
High resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least the same important for obtaining faithful simulations.
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.
Ngoc Bich Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
EGUsphere, https://doi.org/10.5194/egusphere-2023-547, https://doi.org/10.5194/egusphere-2023-547, 2023
Short summary
Short summary
Seawater flows from the Pacific to the Indian Oceans through different straits of the South China Sea, forming the South China Sea Throughflow. We present the high-resolution model built for the study of water, heat and salt fluxes involved in this flow. The model is evaluated by comparing with observations. We moreover show that important discards are observed while calculating offline the net heat and salt flux and the inflow and outflow of water, heat and salt.
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.
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.
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.
Cited articles
Anderson, L. A. and Sarmiento, J. L.: Redfield ratios of remineralization
determined by nutrient data analysis, Global Biogeochem. Cy., 8,
65–80, https://doi.org/10.1029/93GB03318, 1994.
Archer, D., Eby, M., Brovkin, V., Ridgwell, A., Cao, L., Mikolajewicz, U.,
Caldeira, K., Matsumoto, K., Munhoven, G., Montenegro, A., and Tokos, K.:
Atmospheric Lifetime of Fossil Fuel Carbon Dioxide, Annu. Rev. Earth Pl.
Sc., 37, 117–134, https://doi.org/10.1146/annurev.earth.031208.100206, 2009.
Arteaga, L., Pahlow, M., and Oschlies, A.: Global patterns of phytoplankton
nutrient and light colimitation inferred from an optimality-based model,
Global Biogeochem. Cy., 28, 648–661, https://doi.org/10.1002/2013GB004668, 2014.
Balch, W. M., Bates, N. R., Lam, P. J., Twining, B. S., Rosengard, S. Z.,
Bowler, B. C., Drapeau, D. T., Garley, R., Lubelczyk, L. C., Mitchell, C.,
and Rauschenberg, S.: Factors regulating the Great Calcite Belt in the
Southern Ocean and its biogeochemical significance, Global Biogeochem.
Cy., 30, 1124–1144, https://doi.org/10.1002/2016GB005414, 2016.
Berelson, W. M., Balch, W. M., Najjar, R., Feely, R. A., Sabine, C., and Lee,
K.: Relating estimates of CaCO3 production, export, and dissolution in the
water column to measurements of CaCO3 rain into sediment traps and
dissolution on the sea floor: A revised global carbonate budget, Global
Biogeochem. Cy., 201, 1–15, https://doi.org/10.1029/2006GB002803, 2007.
Bianchi, D., Weber, T. S., Kiko, R., and Deutsch, C.: Global niche of marine
anaerobic metabolisms expanded by particle microenvironments, Nat. Geosci.,
11, 263–268, https://doi.org/10.1038/s41561-018-0081-0, 2018.
Brzezinski, M. A.: A switch from Si(OH)4 to NO3- depletion in the glacial
Southern Ocean, Geophys. Res. Lett., 29, 1564, https://doi.org/10.1029/2001gl014349, 2002.
Cao, L., Eby, M., Ridgwell, A., Caldeira, K., Archer, D., Ishida, A., Joos, F., Matsumoto, K., Mikolajewicz, U., Mouchet, A., Orr, J. C., Plattner, G.-K., Schlitzer, R., Tokos, K., Totterdell, I., Tschumi, T., Yamanaka, Y., and Yool, A.: The role of ocean transport in the uptake of anthropogenic CO2, Biogeosciences, 6, 375–390, https://doi.org/10.5194/bg-6-375-2009, 2009.
Carr, M. E., Friedrichs, M. A. M., Schmeltz, M., Noguchi Aita, M., Antoine,
D., Arrigo, K. R., Asanuma, I., Aumont, O., Barber, R., Behrenfeld, M.,
Bidigare, R., Buitenhuis, E. T., Campbell, J., Ciotti, A., Dierssen, H.,
Dowell, M., Dunne, J., Esaias, W., Gentili, B., Gregg, W., Groom, S.,
Hoepffner, N., Ishizaka, J., Kameda, T., Le Quéré, C., Lohrenz, S.,
Marra, J., Mélin, F., Moore, K., Morel, A., Reddy, T. E., Ryan, J.,
Scardi, M., Smyth, T., Turpie, K., Tilstone, G., Waters, K., and Yamanaka,
Y.: A comparison of global estimates of marine primary production from ocean
color, Deep-Sea Res. Pt. II, 53, 741–770,
https://doi.org/10.1016/j.dsr2.2006.01.028, 2006.
Cheng, H., Edwards, R. L., Southon, J., Matsumoto, K., Feinberg, J. M.,
Sinha, A., Zhou, W., Li, H., Li, X., Xu, Y., Chen, S., Tan, M., Wang, Q.,
Wang, Y., Ning, Y., Lawrence Edwards, R., Southon, J., Matsumoto, K.,
Feinberg, J. M., Sinha, A., Zhou, W., Li, H., Li, X., Xu, Y., Chen, S., Tan,
M., Wang, Q., Wang, Y., and Ning, Y.: Atmospheric 14C/12C changes during the
last glacial period from hulu cave, Science, 362, 1293–1297,
https://doi.org/10.1126/science.aau0747, 2018.
Chien, C.-T., Pahlow, M., Schartau, M., and Oschlies, A.: Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 2: Sensitivity analysis and model calibration, Geosci. Model Dev., 13, 4691–4712, https://doi.org/10.5194/gmd-13-4691-2020, 2020.
Claussen, M., Mysak, L., Weaver, A., Crucifix, M., Fichefet, T., Loutre, M.
F., Weber, S., Alcamo, J., Alexeev, V., Berger, A., Calov, R., Ganopolski,
A., Goosse, H., Lohmann, G., Lunkeit, F., Mokhov, I., Petoukhov, V., Stone,
P., and Wang, Z.: Earth system models of intermediate complexity: Closing the
gap in the spectrum of climate system models, Clim. Dynam., 18, 579–586,
https://doi.org/10.1007/s00382-001-0200-1, 2002.
Codispoti, L. A.: An oceanic fixed nitrogen sink exceeding 400 Tg N a−1 vs the concept of homeostasis in the fixed-nitrogen inventory, Biogeosciences, 4, 233–253, https://doi.org/10.5194/bg-4-233-2007, 2007.
Deutsch, C., Sarmiento, J. L., Sigman, D. M., Gruber, N., and Dunne, J. P.:
Spatial coupling of nitrogen inputs and losses in the ocean, Nature,
445, 163–167, https://doi.org/10.1038/nature05392, 2007.
DeVries, T. and Weber, T.: The export and fate of organic matter in the
ocean: New constraints from combining satellite and oceanographic tracer
observations, Global Biogeochem. Cy., 31, 535–555,
https://doi.org/10.1002/2016GB005551, 2017.
Druffel, E. R. M., Williams, P. M., Bauer, J. E., and Ertel, J. R.: Cycling
of dissolved and particulate organic matter in the open ocean, J. Geophys.
Res., 97, 15639, https://doi.org/10.1029/92JC01511, 1992.
Druffel, E. R. M., Griffin, S., Wang, N., Garcia, N. G., McNichol, A. P.,
Key, R. M., and Walker, B. D.: Dissolved Organic Radiocarbon in the Central
Pacific Ocean, Geophys. Res. Lett., 46, 5396–5403,
https://doi.org/10.1029/2019GL083149, 2019.
Dunne, J. P., Armstrong, R. A., Gnanadesikan, A., and Sarmiento, J. L.:
Empirical and mechanistic models for the particle export ratio, Global
Biogeochem. Cy., 19, GB4026, https://doi.org/10.1029/2004GB002390, 2005.
Dunne, J. P., Sarmiento, J. L. ,and Gnanadesikan, A.: A synthesis of global
particle export from the surface ocean and cycling through the ocean
interior and on the seafloor, Global Biogeochem. Cy., 21, 1–16,
https://doi.org/10.1029/2006GB002907, 2007.
Eby, M., Weaver, A. J., Alexander, K., Zickfeld, K., Abe-Ouchi, A., Cimatoribus, A. A., Crespin, E., Drijfhout, S. S., Edwards, N. R., Eliseev, A. V., Feulner, G., Fichefet, T., Forest, C. E., Goosse, H., Holden, P. B., Joos, F., Kawamiya, M., Kicklighter, D., Kienert, H., Matsumoto, K., Mokhov, I. I., Monier, E., Olsen, S. M., Pedersen, J. O. P., Perrette, M., Philippon-Berthier, G., Ridgwell, A., Schlosser, A., Schneider von Deimling, T., Shaffer, G., Smith, R. S., Spahni, R., Sokolov, A. P., Steinacher, M., Tachiiri, K., Tokos, K., Yoshimori, M., Zeng, N., and Zhao, F.: Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity, Clim. Past, 9, 1111–1140, https://doi.org/10.5194/cp-9-1111-2013, 2013.
Edwards, N. R. and Marsh, R.: Uncertainties due to transport-parameter
sensitivity in an efficient 3-D ocean-climate model, Clim. Dynam., 24,
415–433, https://doi.org/10.1007/s00382-004-0508-8, 2005.
Eppley, R. W.: Temperature and phytoplankton growth in the sea, Fish. Bull.,
70, 1063–1085, 1972.
Galbraith, E. D. and Martiny, A. C.: A simple nutrient-dependence mechanism
for predicting the stoichiometry of marine ecosystems, P. Natl. Acad.
Sci. USA, 112, 8199–8204, https://doi.org/10.1073/pnas.1423917112, 2015.
Garcia, H., Weathers, K. W., Paver, C. R., Smolyar, I., Boyer, T. P.,
Locarnini, R. A., Zweng, M. M., Mishonov, A. V., Baranova, O. K., Seidov, D.,
and Reagan, J. R.: World Ocean Atlas 2018. Volume 4: Dissolved Inorganic
Nutrients (phosphate, nitrate and nitrate+nitrite, silicate), NOAA Atlas NESDIS, 84, 35 pp., 2018.
Garcia, H. E., Weathers, K., Paver, C. R., Smolyar, I., Boyer, T. P.,
Locarnini, R. A., Zweng, M. M., Mishonov, A. V., Baranova, O. K., Seidov, D.,
and Reagan, J. R.: World Ocean Atlas 2018, Volume 3: Dissolved Oxygen,
Apparent Oxygen Utilization, and Oxygen Saturation, NOAA Atlas NESDIS,
3, 38 pp., 2019.
Gruber, N. and Sarmiento, J. L.: Global patterns of marine nitrogen fixation
and denitrification, Global Biogeochem. Cy., 11, 235–266,
https://doi.org/10.1029/97GB00077, 1997.
Hansell, D. A.: Recalcitrant Dissolved Organic Carbon Fractions, Ann. Rev.
Mar. Sci., 5, 421–445, https://doi.org/10.1146/annurev-marine-120710-100757, 2013.
Hansell, D. A. and Carlson, C. A.: Deep-ocean gradients in the concentration
of dissolved organic carbon, Nature, 395, 263–266, https://doi.org/10.1038/26200,
1998.
Hansell, D. A., Carlson, C. A., Repeta, D. J., and Schlitzer, R.: Dissolved
Organic Matter in the Ocean: A Controversy stimulates new insights,
Oceanography, 22, 202–211, https://doi.org/10.5670/oceanog.2009.109,
2009.
Henson, S. A., Sanders, R., Madsen, E., Morris, P. J., Le Moigne, F., and
Quartly, G. D.: A reduced estimate of the strength of the ocean's biological
carbon pump, Geophys. Res. Lett., 38, L04606, https://doi.org/10.1029/2011GL046735,
2011.
Hutchins, D. A. and Bruland, K. W.: Iron-limited growth and Si:N ratios in a
costal upwelling regime, Nature, 393, 561–564, 1998.
Joos, F., Roth, R., Fuglestvedt, J. S., Peters, G. P., Enting, I. G., von Bloh, W., Brovkin, V., Burke, E. J., Eby, M., Edwards, N. R., Friedrich, T., Frölicher, T. L., Halloran, P. R., Holden, P. B., Jones, C., Kleinen, T., Mackenzie, F. T., Matsumoto, K., Meinshausen, M., Plattner, G.-K., Reisinger, A., Segschneider, J., Shaffer, G., Steinacher, M., Strassmann, K., Tanaka, K., Timmermann, A., and Weaver, A. J.: Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis, Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, 2013.
Kwiatkowski, L., Aumont, O., Bopp, L., and Ciais, P.: The Impact of Variable
Phytoplankton Stoichiometry on Projections of Primary Production, Food
Quality, and Carbon Uptake in the Global Ocean, Global Biogeochem. Cy.,
516–528, https://doi.org/10.1002/2017GB005799, 2018.
Kwiatkowski, L., Aumont, O., and Bopp, L.: Consistent trophic amplification
of marine biomass declines under climate change, Glob. Chang. Biol., 25,
218–229, https://doi.org/10.1111/gcb.14468, 2019.
Landolfi, A., Kähler, P., Koeve, W., and Oschlies, A.: Global marine N2
fixation estimates: From observations to models, Front. Microbiol., 9,
1–8, https://doi.org/10.3389/fmicb.2018.02112, 2018.
Lang, S. Q., Butterfield, D. A., Lilley, M. D., Paul Johnson, H., and Hedges,
J. I.: Dissolved organic carbon in ridge-axis and ridge-flank hydrothermal
systems, Geochim. Cosmochim. Ac., 70, 3830–3842,
https://doi.org/10.1016/j.gca.2006.04.031, 2006.
Laufkötter, C., John, J. G., Stock, C. A., and Dunne, J. P.: Temperature
and oxygen dependence of the remineralization of organic matter, Global
Biogeochem. Cy., 31, 1038–1050, https://doi.org/10.1002/2017GB005643, 2017.
Laws, E. A., Falkowski, P. G., Smith, W. O., Ducklow, H. W., and McCarthy, J.
J.: Temperature effects on export production in the open ocean, Global
Biogeochem. Cy., 14, 1231–1246, https://doi.org/10.1029/1999GB001229, 2000.
Lee, S. Y., Chiang, J. C. H., Matsumoto, K. and Tokos, K. S.: Southern Ocean
wind response to North Atlantic cooling and the rise in atmospheric CO2:
Modeling perspective and paleoceanographic implications, Paleoceanography,
26, 1–16, https://doi.org/10.1029/2010PA002004, 2011.
Lenton, T. M., Williamson, M. S., Edwards, N. R., Marsh, R., Price, A. R.,
Ridgwell, A. J., Shepherd, J. G., and Cox, S. J.: Millennial timescale carbon
cycle and climate change in an efficient Earth system model, Clim. Dynam.,
26, 687–711, https://doi.org/10.1007/s00382-006-0109-9, 2006.
Letscher, R. T. and Moore, J. K.: Preferential remineralization of dissolved
organic phosphorus and non-Redfield DOM dynamics in the global ocean:
Impacts on marine productivity, nitrogen fixation, and carbon export, Global
Biogeochem. Cy., 29, 325–340, https://doi.org/10.1002/2014GB004904, 2015.
Levitus, S.: Climatological Atlas of the World Ocean, NOAA Professional Paper 13, 173 pp., 1982.
Mahowald, N. M., Muhs, D. R., Levis, S., Rasch, P. J., Yoshioka, M., Zender,
C. S., and Luo, C.: Change in atmospheric mineral aerosols in response to
climate: Last glacial period, preindustrial, modern, and doubled carbon
dioxide climates, J. Geophys. Res.-Atmos., 111,
https://doi.org/10.1029/2005JD006653, 2006.
Marchal, O., Stocker, T. F. and Joos, F.: A latitude-depth,
circulation-biogeochemical ocean model for palaeoclimate studies.
Development and sensitivities, Tellus B, 50B,
290–316, https://doi.org/10.1034/j.1600-0889.1998.t01-2-00006.x, 1998.
Martiny, A. C., Pham, C. T. A. A., Primeau, F. W., Vrugt, J. A., Moore, J.
K., Levin, S. A., and Lomas, M. W.: Strong latitudinal patterns in the
elemental ratios of marine plankton and organic matter, Nat. Geosci., 6,
279–283, https://doi.org/10.1038/ngeo1757, 2013.
Mather, R. L., Reynolds, S. E., Wolff, G. A., Williams, R. G.,
Torres-Valdes, S., Woodward, E. M. S., Landolfi, A., Pan, X., Sanders, R.,
and Achterberg, E. P.: Phosphorus cycling in the North and South Atlantic
Ocean subtropical gyres, Nat. Geosci., 1, 439–443, https://doi.org/10.1038/ngeo232,
2008.
Matsumoto, K.: gaia3intc/mesmo: Release of MESMO v3.0 (Version v3.0), Zenodo, https://doi.org/10.5281/zenodo.4403605, 2020.
Matsumoto, K. and Key, R. M.: Natural radiocarbon distribution in the deep
ocean, in Global Environmental Change in the Ocean and on Land, edited by:
Shiyomi, M., Kawahata, H., Koizumi, H., Tsuda, A., and Awaya, Y., 45–58,
Terrapub, Tokyo, available at:
http://svr4.terrapub.co.jp/e-library/kawahata/pdf/045.pdf (last access: 23 April 2021), 2004.
Matsumoto, K. and McNeil, B.: Decoupled response of ocean acidification to
variations in climate sensitivity, J. Climate, 26, 1764–1771,
https://doi.org/10.1175/JCLI-D-12-00290.1, 2012.
Matsumoto, K. and Tanioka, T.: Shifts in regional production as a driver of
future global ocean production stoichiometry, Environ. Res. Lett.,
15, 124027, https://doi.org/10.1088/1748-9326/abc4b0, 2020.
Matsumoto, K. and Yokoyama, Y.: Atmospheric Δ 14 C reduction in
simulations of Atlantic overturning circulation shutdown, Global Biogeochem.
Cy., 27, 296–304, https://doi.org/10.1002/gbc.20035, 2013.
Matsumoto, K., Tokos, K. S., Price, A. R., and Cox, S. J.: First description of the Minnesota Earth System Model for Ocean biogeochemistry (MESMO 1.0), Geosci. Model Dev., 1, 1–15, https://doi.org/10.5194/gmd-1-1-2008, 2008.
Matsumoto, K., Tokos, K., Chikamoto, M., and Ridgwell, A.: Characterizing
post-industrial changes in the ocean carbon cycle in an Earth system model,
Tellus B, 62, 296–313,
https://doi.org/10.1111/j.1600-0889.2010.00461.x, 2010.
Matsumoto, K., Tokos, K., Huston, A., and Joy-Warren, H.: MESMO 2: a mechanistic marine silica cycle and coupling to a simple terrestrial scheme, Geosci. Model Dev., 6, 477–494, https://doi.org/10.5194/gmd-6-477-2013, 2013.
Matsumoto, K., Rickaby, R. and Tanioka, T.: Carbon Export Buffering and CO2
Drawdown by Flexible Phytoplankton
Moore, J. K., Doney, S. C., and Lindsay, K.: Upper ocean ecosystem dynamics
and iron cycling in a global three-dimensional model, Global Biogeochem.
Cy., 18, 1–21, https://doi.org/10.1029/2004GB002220, 2004.
Mopper, K., Zhou, X., Kieber, R. J., Kieber, D. J., Sikorski, R. J., and
Jones, R. D.: Photochemical degradation of dissolved organic carbon and its
impact on the oceanic carbon cycle, Nature, 353, 60–62,
https://doi.org/10.1038/353060a0, 1991.
Najjar, R. G., Sarmiento, J. L., and Toggweiler, J. R.: Downward transport
and fate of organic matter in the ocean: Simulations with a general
circulation model, Global Biogeochem. Cy., 6, 45–76,
https://doi.org/10.1029/91GB02718, 1992.
Pahlow, M. and Oschlies, A.: Chain model of phytoplankton P, N and light
colimitation, Mar. Ecol. Prog. Ser., 376, 69–83, https://doi.org/10.3354/meps07748,
2009.
Pahlow, M. and Oschlies, A.: Optimal allocation backs droop's cell-quota
model, Mar. Ecol. Prog. Ser., 473, 1–5, https://doi.org/10.3354/meps10181, 2013.
Pahlow, M., Dietze, H. and Oschlies, A.: Optimality-based model of
phytoplankton growth and diazotrophy, Mar. Ecol. Prog. Ser., 489, 1–16,
https://doi.org/10.3354/meps10449, 2013.
Pahlow, M., Chien, C.-T., Arteaga, L. A., and Oschlies, A.: Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 1: Implementation and model behaviour, Geosci. Model Dev., 13, 4663–4690, https://doi.org/10.5194/gmd-13-4663-2020, 2020.
Paulsen, H., Ilyina, T., Six, K. D., and Stemmler, I.: Incorporating a
prognostic representation of marine nitrogen fixers into the global ocean
biogeochemical model HAMOCC, J. Adv. Model. Earth Sy., 9, 438–464,
https://doi.org/10.1002/2016MS000737, 2017.
Ragueneau, O., Tréguer, P., Leynaert, A., Anderson, R., Brzezinski, M., DeMaster, D., Dugdale, R., Dymond, J., Fischer, G., François, R.,
Heinze, C., Maier-Reimer, E., Martin-Jézéquel, V., Nelson, D., and
Quéguiner, B.: A review of the Si cycle in the modern ocean: recent
progress and missing gaps in the application of biogenic opal as a
paleoproductivity proxy, Global Planet. Change, 26, 317–365,
https://doi.org/10.1016/S0921-8181(00)00052-7, 2000.
Ridgwell, A.: Glacial-interglacial perturbations in the global carbon cycle,
PhD thesis, Univ. East Anglia, Norwich, U. K. Ridgwell, A. J.,
U. Edwards, 134 pp., 2001.
Ridgwell, A., Hargreaves, J. C., Edwards, N. R., Annan, J. D., Lenton, T. M., Marsh, R., Yool, A., and Watson, A.: Marine geochemical data assimilation in an efficient Earth System Model of global biogeochemical cycling, Biogeosciences, 4, 87–104, https://doi.org/10.5194/bg-4-87-2007, 2007.
Ridgwell, A. J., Watson, A. J., and Archer, D. E.: Modeling the response of
the oceanic Si inventory to perturbation, and consequences for atmospheric
CO 2, Global Biogeochem. Cy., 16, 19-1–19-25,
https://doi.org/10.1029/2002GB001877, 2002.
Roshan, S. and DeVries, T.: Efficient dissolved organic carbon production
and export in the oligotrophic ocean, Nat. Commun., 8, 2036,
https://doi.org/10.1038/s41467-017-02227-3, 2017.
Sarmiento, J. L., Gruber, N., Brzezinski, M. A., and Dunne, J. P.:
High-latitude controls of thermocline nutrients and low latitude biological
productivity, Nature, 427, 56–60, https://doi.org/10.1038/nature02127, 2004.
Sun, X. and Matsumoto, K.: Effects of sea ice on atmospheric pCO2: A
revised view and implications for glacial and future climates, J. Geophys.
Res., 115, G02015, https://doi.org/10.1029/2009JG001023, 2010.
Sunda, W. G. and Huntsman, S. A.: Iron uptake and growth limitation in
oceanic and coastal phytoplankton, Mar. Chem., 50, 189–206,
https://doi.org/10.1016/0304-4203(95)00035-P, 1995.
Sverdrup, H. U.: On the conditions for the vernal blooming of phytoplankton,
J. Cons. Perm. Int. Pour l'Exploration La Mer, 18, 287–195, 1953.
Takeda, S.: Influence of iron availability on nutrient consumption ratio,
Nature, 393, 774–777, 1998.
Tanioka, T. and Matsumoto, K.: Buffering of Ocean Export Production by
Flexible Elemental Stoichiometry of Particulate Organic Matter, Global
Biogeochem. Cy., 31, 1528–1542, https://doi.org/10.1002/2017GB005670, 2017.
Tanioka, T. and Matsumoto, K.: A meta-analysis on environmental drivers of marine phytoplankton C : N : P, Biogeosciences, 17, 2939–2954, https://doi.org/10.5194/bg-17-2939-2020, 2020a.
Tanioka, T. and Matsumoto, K.: Stability of Marine Organic Matter
Respiration Stoichiometry, Geophys. Res. Lett., 47, 1–10,
https://doi.org/10.1029/2019GL085564, 2020b.
Ushie, H. and Matsumoto, K.: The role of shelf nutrients on
glacial-interglacial CO2: A negative feedback, Global Biogeochem. Cy.,
26, 1–10, https://doi.org/10.1029/2011GB004147, 2012.
Wang, W.-L., Moore, J. K., Martiny, A. C., and Primeau, F. W.: Convergent
estimates of marine nitrogen fixation, Nature, 566, 205–211,
https://doi.org/10.1038/s41586-019-0911-2, 2019.
Wanninkhof, R.: Relationship between wind speed and gas exchange over the
ocean, J. Geophys. Res., 97, 7373–7382, https://doi.org/10.1029/92JC00188, 1992.
Weaver, A. J., Sedlá, J., Eby, M., Alexander, K., Crespin, E., Fichefet,
T., Philippon-berthier, G., Joos, F., Kawamiya, M., Matsumoto, K.,
Steinacher, M., Tachiiri, K., Tokos, K., Yoshimori, M., and Zickfeld, K.:
Stability of the Atlantic meridional overturning circulation: A model
intercomparison, Geophys. Res. Lett., 39, 1–7, https://doi.org/10.1029/2012GL053763,
2012.
Yamanaka, Y. and Tajika, E.: Role of dissolved organic matter in the marine
biogeochemical cycle: Studies using an ocean biogeochemical general
circulation model, Global Biogeochem. Cy., 11, 599–612,
https://doi.org/10.1029/97GB02301, 1997.
Yamanaka, Y., Yoshie, N., Fujii, M., Aita, M. N., and Kishi, M. J.: An
Ecosystem Model Coupled with Nitrogen-Silicon-Carbon Cycles Applied to
Station A7 in the Northwestern Pacific, J. Oceanogr., 60, 227–241,
https://doi.org/10.1023/B:JOCE.0000038329.91976.7d, 2004.
Zickfeld, K., Eby, M., Weaver, A. J., Alexander, K., Crespin, E., Edwards,
N. R., Eliseev, A. V., Feulner, G., Fichefet, T., Forest, C. E.,
Friedlingstein, P., Goosse, H., Holden, P. B., Joos, F., Kawamiya, M.,
Kicklighter, D., Kienert, H., Matsumoto, K., Mokhov, I. I., Monier, E.,
Olsen, S. M., Pedersen, J. O. P., Perrette, M., Philippon-Berthier, G.,
Ridgwell, A., Schlosser, A., Von Deimling, T. S., Shaffer, G., Sokolov, A.,
Spahni, R., Steinacher, M., Tachiiri, K., Tokos, K. S., Yoshimori, M., Zeng,
N., and Zhao, F.: Long-Term climate change commitment and reversibility: An
EMIC intercomparison, J. Climate, 26, 5782–5809,
https://doi.org/10.1175/JCLI-D-12-00584.1, 2013.
Short summary
MESMO is a mathematical model that represents the essential components of the Earth, such as the global ocean, atmosphere, and sea ice. It is used to study the global climate and the global carbon cycle. We describe the third version of MESMO. A novel feature of the new version is its mathematical representations of the chemical composition of marine phytoplankton and the marine dissolved organic matter, which are both recognized as important for the global ocean carbon cycle.
MESMO is a mathematical model that represents the essential components of the Earth, such as the...
