Articles | Volume 15, issue 11
https://doi.org/10.5194/gmd-15-4625-2022
© Author(s) 2022. 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-15-4625-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
16 Jun 2022
Model description paper |
| 16 Jun 2022
| 16 Jun 2022
GNOM v1.0: an optimized steady-state model of the modern marine neodymium cycle
Earth Sciences Department, University of Southern California, Los Angeles, CA, USA
now at: School of Mathematics and Statistics, University of New South Wales, Sydney, Australia
Sophia K. V. Hines
CORRESPONDING AUTHOR
Lamont–Doherty Earth Observatory, Columbia University, Palisades, NY, USA
Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
Hengdi Liang
Earth Sciences Department, University of Southern California, Los Angeles, CA, USA
Yingzhe Wu
Lamont–Doherty Earth Observatory, Columbia University, Palisades, NY, USA
Steven L. Goldstein
Lamont–Doherty Earth Observatory, Columbia University, Palisades, NY, USA
Department of Earth and Environmental Sciences, Columbia University, Palisades, NY, USA
Seth G. John
Earth Sciences Department, University of Southern California, Los Angeles, CA, USA
Related authors
Benoît Pasquier, Mark Holzer, and Matthew A. Chamberlain
EGUsphere, https://doi.org/10.5194/egusphere-2023-2525, https://doi.org/10.5194/egusphere-2023-2525, 2023
Short summary
Short summary
How will the future ocean sequester carbon? We find that for an ocean perpetually warmer with slower circulation, biological productivity declines despite warming-stimulated growth because of lower nutrient supply from depth. This throttles the biological carbon pump, which still sequesters more carbon because it takes longer to return to the surface. The deep ocean is isolated from the surface allowing more carbon from the atmosphere to pass through the ocean without contributing to biology.
Benoît Pasquier, Mark Holzer, Matthew A. Chamberlain, Richard J. Matear, Nathaniel L. Bindoff, and François W. Primeau
Biogeosciences, 20, 2985–3009, https://doi.org/10.5194/bg-20-2985-2023, https://doi.org/10.5194/bg-20-2985-2023, 2023
Short summary
Short summary
Modeling the ocean's carbon and oxygen cycles accurately is challenging. Parameter optimization improves the fit to observed tracers but can introduce artifacts in the biological pump. Organic-matter production and subsurface remineralization rates adjust to compensate for circulation biases, changing the pathways and timescales with which nutrients return to the surface. Circulation biases can thus strongly alter the system’s response to ecological change, even when parameters are optimized.
and its intrinsic fertilization efficiency
Benoît Pasquier and Mark Holzer
Biogeosciences, 15, 7177–7203, https://doi.org/10.5194/bg-15-7177-2018, https://doi.org/10.5194/bg-15-7177-2018, 2018
Short summary
Short summary
We analyze data-constrained state estimates of the global marine iron cycle, a key control on the ocean's biological carbon pump. We develop new techniques for counting the iron's number of passages through the biological pump and link this number to the ocean's natural iron fertilization efficiency. We find that the majority of iron is not biologically utilized before being scavenged, and we identify the central equatorial Pacific as having the highest iron fertilization efficiency.
Benoît Pasquier and Mark Holzer
Biogeosciences, 14, 4125–4159, https://doi.org/10.5194/bg-14-4125-2017, https://doi.org/10.5194/bg-14-4125-2017, 2017
Short summary
Short summary
We construct a model of the ocean's coupled phosphorus, silicon, and iron cycles and optimize its biogeochemical parameters. State estimates for widely differing iron sources are consistent with observations because of compensation between sources and sinks. Export production and the patterns of export supported by each iron source type (aeolian, sedimentary, hydrothermal) are well constrained. The fraction of export supported by each iron type varies systematically with its fractional source.
Benoît Pasquier, Mark Holzer, and Matthew A. Chamberlain
EGUsphere, https://doi.org/10.5194/egusphere-2023-2525, https://doi.org/10.5194/egusphere-2023-2525, 2023
Short summary
Short summary
How will the future ocean sequester carbon? We find that for an ocean perpetually warmer with slower circulation, biological productivity declines despite warming-stimulated growth because of lower nutrient supply from depth. This throttles the biological carbon pump, which still sequesters more carbon because it takes longer to return to the surface. The deep ocean is isolated from the surface allowing more carbon from the atmosphere to pass through the ocean without contributing to biology.
David A. Hutchins, Fei-Xue Fu, Shun-Chung Yang, Seth G. John, Stephen J. Romaniello, M. Grace Andrews, and Nathan G. Walworth
Biogeosciences, 20, 4669–4682, https://doi.org/10.5194/bg-20-4669-2023, https://doi.org/10.5194/bg-20-4669-2023, 2023
Short summary
Short summary
Applications of the mineral olivine are a promising means to capture carbon dioxide via coastal enhanced weathering, but little is known about the impacts on important marine phytoplankton. We examined the effects of olivine dissolution products on species from three major phytoplankton groups: diatoms, coccolithophores, and cyanobacteria. Growth and productivity were generally either unaffected or stimulated, suggesting the effects of olivine on key phytoplankton are negligible or positive.
Benoît Pasquier, Mark Holzer, Matthew A. Chamberlain, Richard J. Matear, Nathaniel L. Bindoff, and François W. Primeau
Biogeosciences, 20, 2985–3009, https://doi.org/10.5194/bg-20-2985-2023, https://doi.org/10.5194/bg-20-2985-2023, 2023
Short summary
Short summary
Modeling the ocean's carbon and oxygen cycles accurately is challenging. Parameter optimization improves the fit to observed tracers but can introduce artifacts in the biological pump. Organic-matter production and subsurface remineralization rates adjust to compensate for circulation biases, changing the pathways and timescales with which nutrients return to the surface. Circulation biases can thus strongly alter the system’s response to ecological change, even when parameters are optimized.
Randelle M. Bundy, Alessandro Tagliabue, Nicholas J. Hawco, Peter L. Morton, Benjamin S. Twining, Mariko Hatta, Abigail E. Noble, Mattias R. Cape, Seth G. John, Jay T. Cullen, and Mak A. Saito
Biogeosciences, 17, 4745–4767, https://doi.org/10.5194/bg-17-4745-2020, https://doi.org/10.5194/bg-17-4745-2020, 2020
Short summary
Short summary
Cobalt (Co) is an essential nutrient for ocean microbes and is scarce in most areas of the ocean. This study measured Co concentrations in the Arctic Ocean for the first time and found that Co levels are extremely high in the surface waters of the Canadian Arctic. Although the Co primarily originates from the shelf, the high concentrations persist throughout the central Arctic. Co in the Arctic appears to be increasing over time and might be a source of Co to the North Atlantic.
and its intrinsic fertilization efficiency
Benoît Pasquier and Mark Holzer
Biogeosciences, 15, 7177–7203, https://doi.org/10.5194/bg-15-7177-2018, https://doi.org/10.5194/bg-15-7177-2018, 2018
Short summary
Short summary
We analyze data-constrained state estimates of the global marine iron cycle, a key control on the ocean's biological carbon pump. We develop new techniques for counting the iron's number of passages through the biological pump and link this number to the ocean's natural iron fertilization efficiency. We find that the majority of iron is not biologically utilized before being scavenged, and we identify the central equatorial Pacific as having the highest iron fertilization efficiency.
Mak A. Saito, Abigail E. Noble, Nicholas Hawco, Benjamin S. Twining, Daniel C. Ohnemus, Seth G. John, Phoebe Lam, Tim M. Conway, Rod Johnson, Dawn Moran, and Matthew McIlvin
Biogeosciences, 14, 4637–4662, https://doi.org/10.5194/bg-14-4637-2017, https://doi.org/10.5194/bg-14-4637-2017, 2017
Short summary
Short summary
Cobalt has the smallest oceanic inventory of all known inorganic micronutrients, and hence is particularly vulnerable to influence by internal oceanic processes. The stoichiometry of cobalt was studied in the North Atlantic, and interpreted with regard to the context of Redfield theory with a focus on biological uptake, scavenging, and the coupling between dissolved and particulate phases. The stoichiometry of cobalt accelerated towards the surface due to increased biological activity and use.
Benoît Pasquier and Mark Holzer
Biogeosciences, 14, 4125–4159, https://doi.org/10.5194/bg-14-4125-2017, https://doi.org/10.5194/bg-14-4125-2017, 2017
Short summary
Short summary
We construct a model of the ocean's coupled phosphorus, silicon, and iron cycles and optimize its biogeochemical parameters. State estimates for widely differing iron sources are consistent with observations because of compensation between sources and sinks. Export production and the patterns of export supported by each iron source type (aeolian, sedimentary, hydrothermal) are well constrained. The fraction of export supported by each iron type varies systematically with its fractional source.
Related subject area
Oceanography
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Great Lakes wave forecast system on high-resolution unstructured meshes
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
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)
Comparison of 4-Dimensional Variational and Ensemble Optimal Interpolation data assimilation systems using a Regional Ocean Modelling System (v3.4) configuration of the eddy-dominated East Australian Current System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean Archipelago
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
Implementation of additional spectral wave field exchanges in a 3D wave-current coupled WAVEWATCH-III (version 6.07) – CROCO (version 1.2) configuration and assessment of their implications for macro-tidal coastal hydrodynamics
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)
Intercomparisons of five ocean particle tracking software packages
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
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
Short summary
Short summary
The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
Short summary
Short summary
A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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 way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
Short summary
Short summary
Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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 wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
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.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripitana, and Joao Marcos A. C. Souza
EGUsphere, https://doi.org/10.5194/egusphere-2023-2355, https://doi.org/10.5194/egusphere-2023-2355, 2023
Short summary
Short summary
Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic Western Boundary Current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 days. This advocates the use of advanced methods for highly variable oceanic regions.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-183, https://doi.org/10.5194/gmd-2023-183, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
In order to improve the Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher resolution ocean currents. To this goal a 3-km resolution regional ocean model has been developed. its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation were found to be quite realistic.
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.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
EGUsphere, https://doi.org/10.5194/egusphere-2023-715, https://doi.org/10.5194/egusphere-2023-715, 2023
Short summary
Short summary
Here a new method of modeling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean circulation and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave-current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
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.
Jilian Xiong and Parker MacCready
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-45, https://doi.org/10.5194/gmd-2023-45, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
A new offline particle tracking model, Tracker, was introduced to work with the Regional Ocean Modeling System (ROMS). Its performance was compared with four other particle tracking models and passive dye, which span a representative range of tracking algorithms. All tracking models perform similarly, especially for the first day. The comparison of multiple tracking codes in the same circulation model establishes confidence in all, and allows comparison of performance and ease of use.
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.
Cited articles
Abbott, A. N., Haley, B. A., and McManus, J.: Bottoms up: Sedimentary control
of the deep North Pacific Ocean's εNd signature, Geology, 43, 1035–1035, https://doi.org/10.1130/g37114.1, 2015a. a
Abbott, A. N., Haley, B. A., McManus, J., and Reimers, C. E.: The sedimentary
flux of dissolved rare earth elements to the ocean, Geochim.
Cosmochim. Ac., 154, 186–200, https://doi.org/10.1016/j.gca.2015.01.010,
2015b. a, b
Adebiyi, A. A., Kok, J. F., Wang, Y., Ito, A., Ridley, D. A., Nabat, P., and Zhao, C.: Dust Constraints from joint Observational-Modelling-experiMental analysis (DustCOMM): comparison with measurements and model simulations, Atmos. Chem. Phys., 20, 829–863, https://doi.org/10.5194/acp-20-829-2020, 2020. a, b, c, d
Adkins, J. F.: The role of deep ocean circulation in setting glacial
climates, Paleoceanography, 28, 539–561, https://doi.org/10.1002/palo.20046, 2013. a
Amakawa, H., Yu, T.-L., Tazoe, H., Obata, H., Gamo, T., Sano, Y., Shen, C.-C.,
and Suzuki, K.: Neodymium concentration and isotopic composition
distributions in the southwestern Indian Ocean and the Indian sector of the
Southern Ocean, Chem. Geol., 511, 190–203,
https://doi.org/10.1016/j.chemgeo.2019.01.007, 2019. a
Anderson, S. P.: Glaciers show direct linkage between erosion rate and chemical
weathering fluxes, Geomorphology, 67, 147–157,
https://doi.org/10.1016/j.geomorph.2004.07.010,
2005. a
Arsouze, T., Dutay, J.-C., Lacan, F., and Jeandel, C.: Modeling the neodymium
isotopic composition with a global ocean circulation model, Chem. Geol.,
239, 165–177, https://doi.org/10.1016/j.chemgeo.2006.12.006, 2007. a, b
Arsouze, T., Treguier, A. M., Peronne, S., Dutay, J.-C., Lacan, F., and Jeandel, C.: Modeling the Nd isotopic composition in the North Atlantic basin using an eddy-permitting model, Ocean Sci., 6, 789–797, https://doi.org/10.5194/os-6-789-2010, 2010. a, b
Bacon, M. P. and Anderson, R. F.: Distribution of thorium isotopes between
dissolved and particulate forms in the deep sea, J. Geophys.
Res.-Oceans, 87, 2045–2056, https://doi.org/10.1029/JC087iC03p02045, 1982. a
Basak, C., Pahnke, K., Frank, M., Lamy, F., and Gersonde, R.: Neodymium
isotopic characterization of Ross Sea Bottom Water and its advection through
the southern South Pacific, Earth Planet. Sc. Lett., 419,
211–221, https://doi.org/10.1016/j.epsl.2015.03.011, 2015. a
Behrens, M. K., Pahnke, K., Paffrath, R., Schnetger, B., and Brumsack, H.-J.:
Rare earth element distributions in the West Pacific: Trace element sources
and conservative vs. non-conservative behavior, Earth Planet. Sc. Lett., 486, 166–177, https://doi.org/10.1016/j.epsl.2018.01.016, 2018a. a
Behrens, M. K., Pahnke, K., Schnetger, B., and Brumsack, H.-J.: Sources and
processes affecting the distribution of dissolved Nd isotopes and
concentrations in the West Pacific, Geochim. Cosmochim. Ac., 222,
508–534, https://doi.org/10.1016/j.gca.2017.11.008, 2018b. a
Bertram, C. and Elderfield, H.: The geochemical balance of the rare earth
elements and neodymium isotopes in the oceans, Geochim. Cosmochim. Ac., 57, 1957–1986, https://doi.org/10.1016/0016-7037(93)90087-D, 1993. a, b, c
Bezanson, J., Edelman, A., Karpinski, S., and Shah, V. B.: Julia: A Fresh
Approach to Numerical Computing, SIAM Review, 59, 65–98,
https://doi.org/10.1137/141000671, 2017. a, b
Blaser, P., Lippold, J., Gutjahr, M., Frank, N., Link, J. M., and Frank, M.:
Extracting foraminiferal seawater Nd isotope signatures from bulk deep sea
sediment by chemical leaching, Chem. Geol., 439, 189 – 204,
https://doi.org/10.1016/j.chemgeo.2016.06.024, 2016. a, b, c
Blaser, P., Gutjahr, M., Pöppelmeier, F., Frank, M., Kaboth-Bahr, S., and
Lippold, J.: Labrador Sea bottom water provenance and REE exchange during
the past 35,000 years, Earth Planet. Sc. Lett., 542, 116299,
https://doi.org/10.1016/j.epsl.2020.116299, 2020. a, b
Bouvier, A., Vervoort, J. D., and Patchett, P. J.: The Lu–Hf and Sm–Nd
isotopic composition of CHUR: Constraints from unequilibrated chondrites and
implications for the bulk composition of terrestrial planets, Earth Planet. Sc. Lett., 273, 48–57, https://doi.org/10.1016/j.epsl.2008.06.010,
2008. a
Brahney, J., Mahowald, N., Ward, D. S., Ballantyne, A. P., and Neff, J. C.: Is
atmospheric phosphorus pollution altering global alpine Lake stoichiometry?,
Global Biogeochem. Cycles, 29, 1369–1383, https://doi.org/10.1002/2015GB005137,
2015. a, b
Byrne, R. H. and Kim, K.-H.: Rare earth element scavenging in seawater,
Geochim. Cosmochim. Ac., 54, 2645–2656,
https://doi.org/10.1016/0016-7037(90)90002-3, 1990. a
Che, H. and Zhang, J.: Water Mass Analysis and End-Member Mixing Contribution
Using Coupled Radiogenic Nd Isotopes and Nd Concentrations: Interaction
Between Marginal Seas and the Northwestern Pacific, Geophys. Res.
Lett., 45, 2388–2395, https://doi.org/10.1002/2017GL076978, 2018. a
Chien, C.-T., Mackey, K. R. M., Dutkiewicz, S., Mahowald, N. M., Prospero,
J. M., and Paytan, A.: Effects of African dust deposition on phytoplankton
in the western tropical Atlantic Ocean off Barbados, Global
Biogeochem. Cycles, 30, 716–734, https://doi.org/10.1002/2015GB005334, 2016. a, b, c
Dai, A.: Historical and Future Changes in Streamflow and Continental Runoff,
chap. 2, 17–37, American Geophysical Union (AGU),
https://doi.org/10.1002/9781118971772.ch2, 2016. a
Dai, A.: Dai and Trenberth Global River Flow and Continental Discharge
Dataset, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, https://doi.org/10.5065/D6V69H1T, 2017. a, b, c
Dai, A. and Trenberth, K. E.: Estimates of Freshwater Discharge from
Continents: Latitudinal and Seasonal Variations, J.
Hydrometeorol., 3, 660–687,
https://doi.org/10.1175/1525-7541(2002)003<0660:EOFDFC>2.0.CO;2, 2002. a, b
Dai, A., Qian, T., Trenberth, K. E., and Milliman, J. D.: Changes in
Continental Freshwater Discharge from 1948 to 2004, J. Climate, 22,
2773–2792, https://doi.org/10.1175/2008JCLI2592.1, 2009. a
Danisch, S. and Krumbiegel, J.: Makie.jl: Flexible high-performance data
visualization for Julia, J. Open Source Softw., 6, 3349,
https://doi.org/10.21105/joss.03349, 2021. a
Danisch, S., Krumbiegel, J., Singhvi, A., Freyer, F., Wang, A., Vertechi, P., Holy, T., Widmann, D., Krabbe Borregaard, M., Datseris, G., M. M., Greimel, F., Butterworth, I., Foster, C., Dehaybe, H., Schauer, M., Kilpatrick, L., Byrne, S., kragol, Weidner, J., Hatherly, M., Sharma, A., Micluța-Câmpeanu, S., t-bltg, Herikstad, R., Goretkin, G., TagBot, J., Štih, V., and smldis: JuliaPlots/Makie.jl, Zenodo,
https://doi.org/10.5281/zenodo.3735092, 2021. a
Dausmann, V., Frank, M., and Zieringer, M.: Dissolved Hafnium and
Neodymium data measured on water samples during METEOR cruise M84/5 in the
Bay of Biscay, PANGAEA, https://doi.org/10.1594/PANGAEA.902808, 2019. a
Dausmann, V., Frank, M., and Zieringer, M.: Water mass mixing versus local
weathering inputs along the Bay of Biscay: Evidence from dissolved hafnium
and neodymium isotopes, Marine Chemistry, 224, 103844,
https://doi.org/10.1016/j.marchem.2020.103844, 2020. a
de Baar, H. J. W., Bacon, M. P., and Brewer, P. G.: Rare-earth distributions
with a positive Ce anomaly in the Western North Atlantic Ocean, Nature, 310,
324–327, https://doi.org/10.1038/301324a0, 1983. a
de Baar, H. J. W., Bacon, M. P., Brewer, P. G., and Bruland, K. W.: Rare earth
elements in the Pacific and Atlantic Oceans, Geochim. Cosmochim. Ac., 49, 1943–1959, https://doi.org/10.1016/0016-7037(85)90089-4, 1985. a
DePaolo, D. J. and Wasserburg, G. J.: Nd isotopic variations and petrogenetic
models, Geophys. Res. Lett., 3, 249–252,
https://doi.org/10.1029/GL003i005p00249, 1976. a, b, c
Dessert, C., Dupré, B., Gaillardet, J., François, L. M., and Allègre, C. J.:
Basalt weathering laws and the impact of basalt weathering on the global
carbon cycle, Chem. Geol., 202, 257–273,
https://doi.org/10.1016/j.chemgeo.2002.10.001, 2003. a
DeVries, T.: The oceanic anthropogenic CO2 sink: Storage,
air–sea fluxes, and transports over the industrial era, Global
Biogeochem. Cycles, 28, 631–647, https://doi.org/10.1002/2013GB004739, 2014. a, b
DeVries, T. and Primeau, F.: Dynamically and Observationally Constrained
Estimates of Water-Mass Distributions and Ages in the Global Ocean, J. Phys. Oceanogr., 41, 2381–2401, https://doi.org/10.1175/JPO-D-10-05011.1,
2011. a, b
Du, J., Haley, B. A., and Mix, A. C.: Evolution of the Global Overturning
Circulation since the Last Glacial Maximum based on marine authigenic
neodymium isotopes, Quaternary Sci. Rev., 241, 106396,
https://doi.org/10.1016/j.quascirev.2020.106396, 2020. a, b, c, d
Elderfield, H.: The oceanic chemistry of the rare-earth elements,
Philos. T. Roy. Soc. Lond. A, 325, 105–126,
https://doi.org/10.1098/rsta.1988.0046, 1988. a, b
Elderfield, H. and Greaves, M. J.: The rare earth elements in seawater,
Nature, 296, 214–219, https://doi.org/10.1038/296214a0, 1982. a
Elderfield, H. and Sholkovitz, E. R.: Rare earth elements in the pore waters
of reducing nearshore sediments, Earth Planet. Sc. Lett., 82,
280–288, https://doi.org/10.1016/0012-821x(87)90202-0, 1987. a, b, c
Elderfield, H., Hawkesworth, C. J., Greaves, M. J., and Calvert, S. E.: Rare
earth element geochemistry of oceanic ferromanganese nodules and associated
sediments, Geochim. Cosmochim. Ac., 45, 513–528,
https://doi.org/10.1016/0016-7037(81)90184-8, 1981. a, b
Frank, M.: Radiogenic isotopes: Tracers of past ocean circulation and
erosional input, Rev. Geophys., 40, 1-1–1-38, https://doi.org/10.1029/2000RG000094, 2002. a, b, c
Fröllje, H., Pahnke, K., Schnetger, B., Brumsack, H.-J., Dulai, H., and
Fitzsimmons, J. N.: Hawaiian imprint on dissolved Nd and Ra isotopes and rare
earth elements in the central North Pacific: Local survey and seasonal
variability, Geochim. Cosmochim. Ac., 189, 110–131,
https://doi.org/10.1016/j.gca.2016.06.001, 2016. a
Gaillardet, J., Dupré, B., Louvat, P., and Allègre, C.: Global silicate
weathering and CO2 consumption rates deduced from the
chemistry of large rivers, Chem. Geol., 159, 3–30,
https://doi.org/10.1016/S0009-2541(99)00031-5, 1999. a
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, NOAA Atlas NESDIS 84, vol. 4:
Dissolved Inorganic Nutrients (phosphate, nitrate and nitrate+nitrite,
silicate), edited by: Mishonov, A., NOAA Atlas NESDIS 84, 35 pp., 2019. a, b
Garcia-Solsona, E., Jeandel, C., Labatut, M., Lacan, F., Vance, D., Chavagnac,
V., and Pradoux, C.: Rare earth elements and Nd isotopes tracing water mass
mixing and particle-seawater interactions in the SE Atlantic, Geochim.
Cosmochim. Ac., 125, 351–372, https://doi.org/10.1016/j.gca.2013.10.009, 2014. a, b
Gardner, W. D., Richardson, M. J., and Mishonov, A. V.: Global assessment of
benthic nepheloid layers and linkage with upper ocean dynamics, Earth Planet. Sc. Lett., 482, 126–134, https://doi.org/10.1016/j.epsl.2017.11.008,
2018. a
Gebbie, G. and Huybers, P. J.: Total Matrix Intercomparison: A Method for
Determining the Geometry of Water-Mass Pathways, J. Phys.
Oceanogr., 40, 1710–1728, https://doi.org/10.1175/2010JPO4272.1, 2010. a
GEOTRACES Planning Group: GEOTRACES Science Plan, Baltimore, Maryland, Scientific Committee on Oceanic Research, https://geotracesold.sedoo.fr/libraries/documents/Science_plan.pdf (last access: 7 June 2022), 2006. a
German, C. R., Masuzawa, T., Greaves, M. J., Elderfield, H., and Edmond, J. M.:
Dissolved Rare Earth Elements in the Southern Ocean: golCerium Oxidation and
the Influence of Hydrography, Geochim. Cosmochim. Ac., 59,
1551–1558, https://doi.org/10.1016/0016-7037(95)00061-4, 1995. a
Goldberg, E. D., Koide, M., Schmitt, R. A., and Smith, R. H.: Rare-Earth
Distributions in the Marine Environment, J. Geophys. Res.,
68, 4209–4217, https://doi.org/10.1029/JZ068i014p04209, 1963. a
Goldstein, S. and Hemming, S. R.: Long-lived isotopic tracers in oceanography,
paleoceanography, and ice-sheet dynamics, in: Treatise on Geochemistry,
edited by: Holland, H. D. and Turekian, K. K., 453–489, Pergamon, Oxford,
https://doi.org/10.1016/B0-08-043751-6/06179-X, 2003. a, b, c, d
Goldstein, S. and O'Nions, R. K.: Nd and Sr Isotopic Relationships in Pelagic
Clays and Ferromanganese Deposits, Nature, 292, 324–327,
https://doi.org/10.1038/292324a0, 1981. a, b
Goldstein, S. L. and Jacobsen, S. B.: The Nd and Sr Isotopic Systematics of
River-Water Dissolved Material: Implications for the Sources of Nd and Sr in
Seawater, Chem. Geol., 66, 245–272, 1987. a
Goldstein, S. L., O'Nions, R. K., and Hamilton, P. J.: A Sm–Nd isotopic study
of atomospheric dusts and particulates from major river system, Earth Planet. Sc. Lett., 70, 221–236, https://doi.org/10.1016/0012-821X(84)90007-4,
1984. a, b, c, d
Greaves, M., Statham, P., and Elderfield, H.: Rare earth element mobilization
from marine atmospheric dust into seawater, Marine Chemistry, 46, 255–260,
https://doi.org/10.1016/0304-4203(94)90081-7, 1994. a, b
Grenier, M., Garcia-Solsona, E., Lemaitre, N., Trull, T. W., Bouvier, V.,
Nonnotte, P., van Beek, P., Souhaut, M., Lacan, F., and Jeandel, C.:
Differentiating Lithogenic Supplies, Water Mass Transport, and Biological
Processes On and Off the Kerguelen Plateau Using Rare Earth Element
Concentrations and Neodymium Isotopic Compositions, Front. Marine Sci., 5, 426, https://doi.org/10.3389/fmars.2018.00426, 2018. a
Gu, S., Liu, Z., Oppo, D. W., Lynch-Stieglitz, J., Jahn, A., Zhang, J., and Wu,
L.: Assessing the potential capability of reconstructing glacial Atlantic
water masses and AMOC using multiple proxies in CESM, Earth Planet. Sc. Lett., 541, 116294, https://doi.org/10.1016/j.epsl.2020.116294, 2020. a, b, c
Haley, B., Klinkhammer, G., and McManus, J.: Rare earth elements in pore
waters of marine sediments, Geochim. Cosmochim. Ac., 68, 1265–1279, https://doi.org/10.1016/j.gca.2003.09.012, 2004. a, b, c
Haley, B. A., Frank, M., Hathorne, E., and Pisias, N.: Biogeochemical
implications from dissolved rare earth element and Nd isotope distributions
in the Gulf of Alaska, Geochim. Cosmochim. Ac., 126, 455–474,
https://doi.org/10.1016/j.gca.2013.11.012, 2014. a
Haley, B. A., Du, J., Abbott, A. N., and McManus, J.: The Impact of Benthic Processes on Rare Earth Element and Neodymium Isotope Distributions in the Oceans, Front. Marine Sci., 4,
https://doi.org/10.3389/fmars.2017.00426, 2017. a
Hartman, A. E.: The neodymium composition of Atlantic Ocean water masses:
implications for the past and present, Academic Commons, Columbia University Libraries, https://doi.org/10.7916/D8DZ077F, 2015. a
Hines, S. K. V., Bolge, L., Goldstein, S. L., Charles, C. D., Hall, I. R., and Hemming, S.: Little Change in Ice Age Water Mass Structure From Cape Basin Benthic Neodymium and Carbon Isotopes, Paleoceanogr.
Paleocl., 36, e2021PA004281, https://doi.org/10.1029/2021PA004281, 2022. a
Høgdahl, O. T., Melsom, S., and Bowen, V. T.: Neutron Activation Analysis of
Lanthanide Elements in Sea Water, in: Trace Inorganics in Water, chap. 19, edited by:
Baker, R. A., American Chemical Society, ACS, Washington, D.C., 73, 308–325, https://doi.org/10.1021/ba-1968-0073.ch019, 1968. a
Holzer, M. and Hall, T. M.: Tropospheric transport climate partitioned by
surface origin and transit time, J. Geophys. Res., 113, D08104,
https://doi.org/10.1029/2007JD009115, 2008. a
Holzer, M. and Primeau, F. W.: The path-density distribution of oceanic
surface-to-surface transport, J. Geophys. Res.-Oceans, 113, C01018,
https://doi.org/10.1029/2006JC003976, 2008. a
Holzer, M., Frants, M., and Pasquier, B.: The age of iron and iron source
attribution in the ocean, Global Biogeochem. Cycles, 30, 1454–1474,
https://doi.org/10.1002/2016GB005418, 2016. a, b
Holzer, M., Kwon, E. Y., and Pasquier, B.: A new metric of the biological
carbon pump: number of pump passages and its control on atmospheric
pCO2, Global Biogeochem. Cycles, 35, e2020GB006863,
https://doi.org/10.1029/2020GB006863, 2021. a
Huang, K. F., Oppo, D. W., and Curry, W. B.: Decreased influence of Antarctic
intermediate water in the tropical Atlantic during North Atlantic cold
events, Earth Planet. Sc. Lett., 389, 200–208,
https://doi.org/10.1016/j.epsl.2013.12.037, 2014. a
Irving, D.: A Minimum Standard for Publishing Computational Results in the
Weather and Climate Sciences, B. Am. Meteorol.
Soc., 97, 1149–1158, https://doi.org/10.1175/BAMS-D-15-00010.1, 2016. a
Jacobsen, S. B. and Wasserburg, G. J.: Sm-Nd isotopic evolution of
chondrites, Earth Planet. Sc. Lett., 50, 139–155,
https://doi.org/10.1016/0012-821X(80)90125-9, 1980. a
Jeandel, C., Arsouze, T., Lacan, F., Téchiné, P., and Dutay, J. C.:
Isotopic Nd compositions and concentrations of the lithogenic inputs into
the ocean: A compilation, with an emphasis on the margins, Chem. Geol.,
239, 156–164, https://doi.org/10.1016/j.chemgeo.2006.11.013, 2007. a, b, c
Johannesson, K. H. and Burdige, D. J.: Balancing the global oceanic neodymium
budget: Evaluating the role of groundwater, Earth Planet. Sc. Lett., 253, 129–142, https://doi.org/10.1016/j.epsl.2006.10.021, 2007. a, b
John, S. G., Liang, H., Weber, T., DeVries, T., Primeau, F., Moore, K., Holzer,
M., Mahowald, N., Gardner, W., Mishonov, A., Richardson, M. J., Faugere, Y.,
and Taburet, G.: AWESOME OCIM: A simple, flexible, and powerful tool for
modeling elemental cycling in the oceans, Chem. Geol., 533, 119403,
https://doi.org/10.1016/j.chemgeo.2019.119403, 2020. a, b, c, d, e, f
Jones, K. M., Khatiwala, S. P., Goldstein, S. L., Hemming, S. R., and van de
Flierdt, T.: Modeling the distribution of Nd isotopes in the oceans using an
ocean general circulation model, Earth Planet. Sc. Lett., 272,
610–619, https://doi.org/10.1016/j.epsl.2008.05.027, 2008. a, b, c
Khatiwala, S.: A computational framework for simulation of biogeochemical
tracers in the ocean, Global Biogeochem. Cycles, 21, GB3001,
https://doi.org/10.1029/2007GB002923, 2007. a
Khatiwala, S., Visbeck, M., and Cane, M. A.: Accelerated simulation of passive
tracers in ocean circulation models, Ocean Model., 9, 51–69,
https://doi.org/10.1016/j.ocemod.2004.04.002, 2005. a
Kim, J., Goldstein, S. L., Pena, L. D., Jaume-Seguí, M., Knudson, K. P.,
Yehudai, M., and Bolge, L.: North Atlantic Deep Water during Pleistocene
interglacials and glacials, Quaternary Sci. Rev., 269, 107146,
https://doi.org/10.1016/j.quascirev.2021.107146, 2021. a
Kok, J. F., Adebiyi, A. A., Albani, S., Balkanski, Y., Checa-Garcia, R., Chin, M., Colarco, P. R., Hamilton, D. S., Huang, Y., Ito, A., Klose, M., Leung, D. M., Li, L., Mahowald, N. M., Miller, R. L., Obiso, V., Pérez García-Pando, C., Rocha-Lima, A., Wan, J. S., and Whicker, C. A.: Improved representation of the global dust cycle using observational constraints on dust properties and abundance, Atmos. Chem. Phys., 21, 8127–8167, https://doi.org/10.5194/acp-21-8127-2021, 2021a. a, b, c
Kok, J. F., Adebiyi, A. A., Albani, S., Balkanski, Y., Checa-Garcia, R., Chin, M., Colarco, P. R., Hamilton, D. S., Huang, Y., Ito, A., Klose, M., Li, L., Mahowald, N. M., Miller, R. L., Obiso, V., Pérez García-Pando, C., Rocha-Lima, A., and Wan, J. S.: Contribution of the world's main dust source regions to the global cycle of desert dust, Atmos. Chem. Phys., 21, 8169–8193, https://doi.org/10.5194/acp-21-8169-2021, 2021b. a, b, c, d
Lacan, F. and Jeandel, C.: Tracing Papua New Guinea imprint on the central
Equatorial Pacific Ocean using neodymium isotopic compositions and Rare Earth
Element patterns, Earth Planet. Sc. Lett., 186, 497–512,
https://doi.org/10.1016/S0012-821X(01)00263-1, 2001. a
Lacan, F. and Jeandel, C.: Neodymium isotopic composition and rare earth
element concentrations in the deep and intermediate Nordic Seas: Constraints
on the Iceland Scotland Overflow Water signature, Geochem. Geophys.
Geosyst., 5, Q11006, https://doi.org/10.1029/2004GC000742, 2004. a
Lagarde, M., Lemaitre, N., Planquette, H., Grenier, M., Belhadj, M., Lherminier, P., and Jeandel, C.: Particulate rare earth element behavior in the North Atlantic (GEOVIDE cruise), Biogeosciences, 17, 5539–5561, https://doi.org/10.5194/bg-17-5539-2020, 2020. a
Lambelet, M., van de Flierdt, T., Crocket, K., Rehkämper, M., Kreissig, K.,
Coles, B., Rijkenberg, M. J. A., Gerringa, L. J. A., de Baar, H. J. W., and
Steinfeldt, R.: Neodymium isotopic composition and concentration in the
western North Atlantic Ocean: Results from the GEOTRACES GA02 section,
Geochim. Cosmochim. Ac., 177, 1–29, https://doi.org/10.1016/j.gca.2015.12.019,
2016. a, b
Lambelet, M., van de Flierdt, T., Butler, E. C. V., Bowie, A. R., Rintoul,
S. R., Watson, R. J., Remenyi, T., Lannuzel, D., Warner, M., Robinson, L. F.,
Bostock, H. C., and Bradtmiller, L. I.: The Neodymium Isotope Fingerprint of
Adélie Coast Bottom Water, Geophys. Res. Lett., 45, 11247–11256,
https://doi.org/10.1029/2018GL080074, 2018. a
Laukert, G., Frank, M., Bauch, D., Hathorne, E. C., Rabe, B., von Appen,
W.-J., Wegner, C., Zieringer, M., and Kassens, H.: Ocean circulation and
freshwater pathways in the Arctic Mediterranean based on a combined Nd
isotope, REE and oxygen isotope section across Fram Strait, Geochim. Cosmochim. Ac., 202, 285–309, https://doi.org/10.1016/j.gca.2016.12.028, 2017. a, b
Laukert, G., Frank, M., Bauch, D., Hathorne, E. C., Rabe, B., von
Appen, W.-J., Wegner, C., Zieringer, M., and Kassens, H.: Neodymium
isotopes and rare earth elements measured on water bottle samples during
POLARSTERN cruise ARK-XXVII/1, PANGAEA, https://doi.org/10.1594/PANGAEA.871516, 2017a. a
Laukert, G., Frank, M., Bauch, D., Hathorne, E. C., Rabe, B., von
Appen, W.-J., Wegner, C., Zieringer, M., and Kassens, H.: Rare earth
elements measured on water bottle samples at BATS, PANGAEA,
https://doi.org/10.1594/PANGAEA.871518, 2017b. a
Laukert, G., Frank, M., Bauch, D., Hathorne, E. C., Rabe, B., von
Appen, W.-J., Wegner, C., Zieringer, M., and Kassens, H.: Rare earth
elements measured on water bottle samples at BATS, PANGAEA,
https://doi.org/10.1594/PANGAEA.871519, 2017c. a
Laukert, G., Frank, M., Bauch, D., Hathorne, E. C., Rabe, B., von
Appen, W.-J., Wegner, C., Zieringer, M., and Kassens, H.: Neodymium
isotopes and rare earth elements measured on water bottle samples during
cruise TDXXI and TDXXII, PANGAEA, https://doi.org/10.1594/PANGAEA.871517, 2017d. a
Laukert, G., Makhotin, M., Petrova, M. V., Vesman, A., Frank, M.,
Hathorne, E. C., Bauch, D., Böning, P., Kassens, H., and
Ivanov, V.: Dissolved neodymium (Nd) isotope compositions and rare earth
element (REE) concentrations along with stable oxygen isotope compositions
measured on water bottle samples collected during PU2014 to the Barents Sea
in 2014, PANGAEA, https://doi.org/10.1594/PANGAEA.895123, 2018. a
Laukert, G., Makhotin, M., Petrova, M. V., Frank, M., Hathorne, E. C., Bauch,
D., Böning, P., and Kassens, H.: Water mass transformation in the Barents
Sea inferred from radiogenic neodymium isotopes, rare earth elements and
stable oxygen isotopes, Chem. Geol., 511, 416–430,
https://doi.org/10.1016/j.chemgeo.2018.10.002, 2019. a
Luijendijk, E., Gleeson, T., and Moosdorf, N.: Geospatial data and model
results for a global model study of coastal groundwater discharge, PANGAEA,
https://doi.org/10.1594/PANGAEA.907641, 2019. a, b
Luijendijk, E., Gleeson, T., and Moosdorf, N.: Fresh groundwater discharge
insignificant for the world's oceans but important for coastal ecosystems,
Nat. Commun., 11, 1260, https://doi.org/10.1038/s41467-020-15064-8, 2020. a, b, c
McCulloch, M. T. and Wasserburg, G. J.: Sm-Nd and Rb-Sr Chronology of
Continental Crust Formation, Science, 200, 1003–1011,
https://doi.org/10.1126/science.200.4345.1003, 1978. a, b
Mogensen, P. K. and Riseth, A. N.: Optim: A mathematical optimization package
for Julia, J. Open Source Softw., 3, 615,
https://doi.org/10.21105/joss.00615, 2018. a
Morrison, R., Waldner, A., Hathorne, E., Rahlf, P., Zieringer, M., Montagna,
P., Colin, C., Frank, N., and Frank, M.: Limited influence of basalt
weathering inputs on the seawater neodymium isotope composition of the
northern Iceland Basin, Chem. Geol., 511, 358–370,
https://doi.org/10.1016/j.chemgeo.2018.10.019, 2019. a
Morse, P. M., Feshbach, H., et al.: Methods of theoretical physics, McGraw-Hill
New York, 1953. a
Najjar, R. G., Jin, X., Louanchi, F., Aumont, O., Caldeira, K., Doney, S. C.,
Dutay, J.-C., Follows, M., Gruber, N., Joos, F., Lindsay, K., Maier-Reimer,
E., Matear, R. J., Matsumoto, K., Monfray, P., Mouchet, A., Orr, J. C.,
Plattner, G.-K., Sarmiento, J. L., Schlitzer, R., Slater, R. D., Weirig,
M.-F., Yamanaka, Y., and Yool, A.: Impact of circulation on export
production, dissolved organic matter, and dissolved oxygen in the ocean:
Results from Phase II of the Ocean Carbon-cycle Model Intercomparison Project
(OCMIP-2), Global Biogeochem. Cycles, 21, GB3007, https://doi.org/10.1029/2006GB002857,
2007. a
Nocedal, J. and Wright, S. J. (Eds.): Numerical optimization, Springer Verlag, 35,
7, https://doi.org/10.1007/b98874, 1999. a
O'Nions, R. K., Carter, S. R., Cohen, R. S., Evensen, N. M., and Hamilton,
P. J.: Pb, Nd and Sr isotopes in oceanic ferromanganese deposits and ocean
floor basalts, Nature, 273, 435–438, https://doi.org/10.1038/273435a0, 1978. a
Palmer, M. R. and Elderfield, H.: Variations in the Nd isotopic composition of
foraminifera from Atlantic Ocean sediments, Earth Planet. Sc. Lett., 73, 299–305, https://doi.org/10.1016/0012-821X(85)90078-0, 1985. a
Pasquier, B.: F-1 Method: A julia package for autodiff through a steady-state
solver, Zenodo, https://doi.org/10.5281/zenodo.2667835, 2020b. a, b
Pasquier, B.: Post-IDP17 Nd data, Figshare [data set], https://doi.org/10.6084/m9.figshare.15058329.v1, 2021. a
Pasquier, B. and Holzer, M.: Inverse-model estimates of the ocean's coupled phosphorus, silicon, and iron cycles, Biogeosciences, 14, 4125–4159, https://doi.org/10.5194/bg-14-4125-2017, 2017. a
Pasquier, B. and Holzer, M.: The number of past and future regenerations of iron in the ocean
and its intrinsic fertilization efficiency, Biogeosciences, 15, 7177–7203, https://doi.org/10.5194/bg-15-7177-2018, 2018. a
Pasquier, B., Hines, S. K. V., Liang, H., Wu, Y., Goldstein, S. L., and John, S. G.: GNOM: An optimized steady-state model of the modern global marine neodymium cycle (v1.0.2), Zenodo [data set], https://doi.org/10.5281/zenodo.6118414, 2022a. a, b
Pearce, C. R., Jones, M. T., Oelkers, E. H., Pradoux, C., and Jeandel, C.: The
effect of particulate dissolution on the neodymium (Nd) isotope and Rare
Earth Element (REE) composition of seawater, Earth Planet. Sc. Lett., 369, 138–147, https://doi.org/10.1016/j.epsl.2013.03.023, 2013. a, b
Pena, L., Goldstein, S., Hemming, S., Jones, K., Calvo, E., Pelejero, C., and
Cacho, I.: Rapid changes in meridional advection of Southern Ocean
intermediate waters to the tropical Pacific during the last 30 kyr, Earth Planet. Sc. Lett., 368, 20–32, https://doi.org/10.1016/j.epsl.2013.02.028,
2013. a
Pena, L. D. and Goldstein, S. L.: Thermohaline circulation crisis and impacts
during the mid-Pleistocene transition, Science, 345, 318–322,
https://doi.org/10.1126/science.1249770, 2014. a
Peng, R. D.: Reproducible Research in Computational Science, Science, 334,
1226–1227, https://doi.org/10.1126/science.1213847, 2011. a
Piepgras, D. and Wasserburg, G.: Strontium and neodymium isotopes in hot
springs on the East Pacific Rise and Guaymas Basin, Earth Planet. Sc. Lett., 72, 341–356, https://doi.org/10.1016/0012-821X(85)90057-3, 1985. a
Piepgras, D., Wasserburg, G., and Dasch, E.: The isotopic composition of Nd in
different ocean masses, Earth Planet. Sc. Lett., 45, 223–236,
https://doi.org/10.1016/0012-821X(79)90125-0, 1979. a
Piepgras, D. J. and Jacobsen, S. B.: The behavior of rare earth elements in
seawater: Precise determination of variations in the North Pacific water
column, Geochim. Cosmochim. Ac., 56, 1851–1862,
https://doi.org/10.1016/0016-7037(92)90315-A, 1992. a
Piepgras, D. J. and Wasserburg, G.: Neodymium Isotopic Variations in
Seawater, Earth Planet. Sc. Lett., 50, 128–138,
https://doi.org/10.1016/0012-821X(80)90124-7, 1980. a, b, c
Piotrowski, A. M., Goldstein, S. L., Hemming, S. R., and Fairbanks, R. G.:
Intensification and variability of ocean thermohaline circulation through the
last deglaciation, Earth Planet. Sc. Lett., 225, 205–220,
https://doi.org/10.1016/j.epsl.2004.06.002, 2004. a
Piotrowski, A. M., Goldstein, S. L., Hemming, S. R., and Fairbanks, R. G.:
Temporal Relationships of Carbon Cycling and Ocean Circulation at Glacial
Boundaries, Science, 307, 1933–1938, https://doi.org/10.1126/science.1104883, 2005. a
Piotrowski, A. M., Goldstein, S. L., Sidney, R. H., Fairbanks, R. G., and
Zylberberg, D. R.: Oscillating glacial northern and southern deep water
formation from combined neodymium and carbon isotopes, Earth Planet. Sc. Lett., 272, 394–405, https://doi.org/10.1016/j.epsl.2008.05.011, 2008. a
Piper, D. Z.: Rare earth elements in the sedimentary cycle: a summary,
Chem. Geol., 14, 285–304, https://doi.org/10.1016/0009-2541(74)90066-7, 1974. a
Pöppelmeier, F., Blaser, P., Gutjahr, M., Süfke, F., Thornalley, D.
J. R., Grützner, J., Jakob, K. A., Link, J. M., Szidat, S., and Lippold,
J.: Influence of Ocean Circulation and Benthic Exchange on Deep Northwest
Atlantic Nd Isotope Records During the Past 30,000 Years, Geochem.
Geophys. Geosyst., 20, 4457–4469, https://doi.org/10.1029/2019gc008271, 2019. a
Pöppelmeier, F., Scheen, J., Blaser, P., Lippold, J., Gutjahr, M., and
Stocker, T. F.: Influence of Elevated Nd Fluxes on the Northern Nd Isotope
End Member of the Atlantic During the Early Holocene, Paleoceanogr.
Paleoclimatol., 35, e2020PA003973, https://doi.org/10.1029/2020pa003973, 2020. a, b, c, d
Pöppelmeier, F., Gutjahr, M., Blaser, P., Schulz, H., Süfke, F., and
Lippold, J.: Stable Atlantic Deep Water Mass Sourcing on Glacial-Interglacial
Timescales, Geophys. Res. Lett., 48, e2021GL092722,
https://doi.org/10.1029/2021GL092722, 2021. a
Primeau, F. W.: Characterizing Transport between the Surface Mixed Layer and
the Ocean Interior with a Forward and Adjoint Global Ocean Transport Model,
J. Phys. Oceanogr., 35, 545–564, https://doi.org/10.1175/JPO2699.1, 2005. a
Rahlf, P., Frank, M., and Hathorne, E. C.: Neodymium isotopes from water
bottle samples measured during METEOR cruise M121 (GEOTRACES cruise GA08),PANGAEA,
https://doi.org/10.1594/PANGAEA.907825, 2019. a
Rahlf, P., Hathorne, E., Laukert, G., Gutjahr, M., Weldeab, S., Frank, M.,
Rahlf, P., Hathorne, E., Laukert, G., Gutjahr, M., Weldeab, S., and Frank,
M.: Tracing water mass mixing and continental inputs in the southeastern
Atlantic Ocean with dissolved neodymium isotopes, Earth Planet. Sc. Lett., 530, 115944, https://doi.org/10.1016/j.epsl.2019.115944, 2020. a
Rahlf, P., Laukert, G., Hathorne, E. C., Vieira, L. H., and Frank,
M.: Neodymium and hafnium isotopes and rare earth element concentrations
from water bottle samples measured during METEOR cruise M121 along the Congo
River plume (GEOTRACES cruise GA08), PANGAEA, https://doi.org/10.1594/PANGAEA.925602, 2020. a
Rahlf, P., Laukert, G., Hathorne, E. C., Vieira, L. H., and Frank, M.:
Dissolved neodymium and hafnium isotopes and rare earth elements in the Congo
River Plume: Tracing and quantifying continental inputs into the southeast
Atlantic, Geochim. Cosmochim. Ac., 294, 192–214,
https://doi.org/10.1016/j.gca.2020.11.017, 2021. a
Rempfer, J., Stocker, T. F., Joos, F., Dutay, J.-C., and Siddall, M.:
Modelling Nd-isotopes with a coarse resolution ocean circulation model:
Sensitivities to model parameters and source/sink distributions, Geochim. Cosmochim. Ac., 75, 5927–5950, https://doi.org/10.1016/j.gca.2011.07.044, 2011. a, b, c, d
Robinson, S., Ivanovic, R., van de Flierdt, T., Blanchet, C. L., Tachikawa,
K., Martin, E. E., Cook, C. P., Williams, T., Gregoire, L., Plancherel, Y.,
Jeandel, C., and Arsouze, T.: Global continental and marine detrital εNd: An
updated compilation for use in understanding marine Nd cycling, Chem. Geol., 567, 120119, https://doi.org/10.1016/j.chemgeo.2021.120119, 2021. a, b, c, d, e, f, g, h, i
Rutberg, R. L., Hemming, S. R., and Goldstein, S. L.: Reduced North Atlantic
Deep Water flux to the glacial Southern Ocean inferred from neodymium isotope
ratios, Nature, 405, 935–938, https://doi.org/10.1038/35016049, 2000. a
Scanza, R. A., Hamilton, D. S., Perez Garcia-Pando, C., Buck, C., Baker, A., and Mahowald, N. M.: Atmospheric processing of iron in mineral and combustion aerosols: development of an intermediate-complexity mechanism suitable for Earth system models, Atmos. Chem. Phys., 18, 14175–14196, https://doi.org/10.5194/acp-18-14175-2018, 2018. a, b
Schijf, J., Christenson, E. A., and Byrne, R. H.: YREE scavenging in
seawater: A new look at an old model, Marine Chemistry, 177, 460–471,
https://doi.org/10.1016/j.marchem.2015.06.010, 2015. a
Schlitzer, R., Anderson, R. F., Dodas, E. M., Lohan, M., Geibert, W.,
Tagliabue, A., Bowie, A., Jeandel, C., Maldonado, M. T., Landing, W. M.,
Cockwell, D., Abadie, C., Abouchami, W., Achterberg, E. P., Agather, A.,
Aguliar-Islas, A., van Aken, H. M., Andersen, M., Archer, C., Auro, M., de
Baar, H. J., Baars, O., Baker, A. R., Bakker, K., Basak, C., Baskaran, M.,
Bates, N. R., Bauch, D., van Beek, P., Behrens, M. K., Black, E., Bluhm,
K., Bopp, L., Bouman, H., Bowman, K., Bown, J., Boyd, P., Boye, M., Boyle,
E. A., Branellec, P., Bridgestock, L., Brissebrat, G., Browning, T., Bruland,
K. W., Brumsack, H.-J., Brzezinski, M., Buck, C. S., Buck, K. N., Buesseler,
K., Bull, A., Butler, E., Cai, P., Mor, P. C., Cardinal, D., Carlson, C.,
Carrasco, G., Casacuberta, N., Casciotti, K. L., Castrillejo, M., Chamizo,
E., Chance, R., Charette, M. A., Chaves, J. E., Cheng, H., Chever, F.,
Christl, M., Church, T. M., Closset, I., Colman, A., Conway, T. M., Cossa,
D., Croot, P., Cullen, J. T., Cutter, G. A., Daniels, C., Dehairs, F., Deng,
F., Dieu, H. T., Duggan, B., Dulaquais, G., Dumousseaud, C., Echegoyen-Sanz,
Y., Edwards, R. L., Ellwood, M., Fahrbach, E., Fitzsimmons, J. N., Russell
Flegal, A., Fleisher, M. Q., van de Flierdt, T., Frank, M., Friedrich, J.,
Fripiat, F., Fröllje, H., Galer, S. J., Gamo, T., Ganeshram, R. S.,
Garcia-Orellana, J., Garcia-Solsona, E., Gault-Ringold, M., George, E.,
Gerringa, L. J., Gilbert, M., Godoy, J. M., Goldstein, S. L., Gonzalez,
S. R., Grissom, K., Hammerschmidt, C., Hartman, A., Hassler, C. S., Hathorne,
E. C., Hatta, M., Hawco, N., Hayes, C. T., Heimbürger, L.-E., Helgoe, J.,
Heller, M., Henderson, G. M., Henderson, P. B., van Heuven, S., Ho, P.,
Horner, T. J., Hsieh, Y.-T., Huang, K.-F., Humphreys, M. P., Isshiki, K.,
Jacquot, J. E., Janssen, D. J., Jenkins, W. J., John, S., Jones, E. M.,
Jones, J. L., Kadko, D. C., Kayser, R., Kenna, T. C., Khondoker, R., Kim, T.,
Kipp, L., Klar, J. K., Klunder, M., Kretschmer, S., Kumamoto, Y., Laan, P.,
Labatut, M., Lacan, F., Lam, P. J., Lambelet, M., Lamborg, C. H., Le
Moigne, F. A., Le Roy, E., Lechtenfeld, O. J., Lee, J.-M., Lherminier, P.,
Little, S., López-Lora, M., Lu, Y., Masque, P., Mawji, E., Mcclain, C. R.,
Measures, C., Mehic, S., Barraqueta, J.-L. M., van der Merwe, P., Middag,
R., Mieruch, S., Milne, A., Minami, T., Moffett, J. W., Moncoiffe, G., Moore,
W. S., Morris, P. J., Morton, P. L., Nakaguchi, Y., Nakayama, N.,
Niedermiller, J., Nishioka, J., Nishiuchi, A., Noble, A., Obata, H., Ober,
S., Ohnemus, D. C., van Ooijen, J., O'Sullivan, J., Owens, S., Pahnke, K.,
Paul, M., Pavia, F., Pena, L. D., Peters, B., Planchon, F., Planquette, H.,
Pradoux, C., Puigcorbé, V., Quay, P., Queroue, F., Radic, A., Rauschenberg,
S., Rehkämper, M., Rember, R., Remenyi, T., Resing, J. A., Rickli, J.,
Rigaud, S., Rijkenberg, M. J., Rintoul, S., Robinson, L. F., Roca-Martí, M.,
Rodellas, V., Roeske, T., Rolison, J. M., Rosenberg, M., Roshan, S., Rutgers
van der Loeff, M. M., Ryabenko, E., Saito, M. A., Salt, L. A., Sanial, V.,
Sarthou, G., Schallenberg, C., Schauer, U., Scher, H., Schlosser, C.,
Schnetger, B., Scott, P., Sedwick, P. N., Semiletov, I., Shelley, R.,
Sherrell, R. M., Shiller, A. M., Sigman, D. M., Singh, S. K., Slagter, H. A.,
Slater, E., Smethie, W. M., Snaith, H., Sohrin, Y., Sohst, B., Sonke, J. E.,
Speich, S., Steinfeldt, R., Stewart, G., Stichel, T., Stirling, C. H.,
Stutsman, J., Swarr, G. J., Swift, J. H., Thomas, A., Thorne, K., Till,
C. P., Till, R., Townsend, A. T., Townsend, E., Tuerena, R., Twining, B. S.,
Vance, D., Velazquez, S., Venchiarutti, C., Villa-Alfageme, M., Vivancos,
S. M., Voelker, A. H., Wake, B., Warner, M. J., Watson, R., van Weerlee,
E., Alexandra Weigand, M., Weinstein, Y., Weiss, D., Wisotzki, A.,
Woodward, E. M. S., Wu, J., Wu, Y., Wuttig, K., Wyatt, N., Xiang, Y., Xie,
R. C., Xue, Z., Yoshikawa, H., Zhang, J., Zhang, P., Zhao, Y., Zheng, L.,
Zheng, X.-Y., Zieringer, M., Zimmer, L. A., Ziveri, P., Zunino, P., and
Zurbrick, C.: The GEOTRACES Intermediate Data Product 2017, Chem. Geol., 493, 210–223, https://doi.org/10.1016/j.chemgeo.2018.05.040, 2018. a, b, c
Sholkovitz, E., Shaw, T., and Schneider, D.: The geochemistry of rare earth
elements in the seasonally anoxic water column and porewaters of Chesapeake
Bay, Geochim. Cosmochim. Ac., 56, 3389–3402,
https://doi.org/10.1016/0016-7037(92)90386-w, 1992. a, b
Sholkovitz, E. R. and Schneider, D. L.: Cerium redox cycles and rare earth
elements in the Sargasso Sea, Geochim. Cosmochim. Ac., 55,
2737–2743, https://doi.org/10.1016/0016-7037(91)90440-G, 1991. a
Sholkovitz, E. R., Piepgras, D. J., and Jacobsen, S. B.: The pore water
chemistry of rare earth elements in Buzzards Bay sediments, Geochim. Cosmochim. Ac., 53, 2847–2856, https://doi.org/10.1016/0016-7037(89)90162-2, 1989. a, b, c
Sholkovitz, E. R., Landing, W. M., and Lewis, B. L.: Ocean particle chemistry:
The fractionation of rare earth elements between suspended particles and
seawater, Geochim. Cosmochim. Ac., 58, 1567–1579,
https://doi.org/10.1016/0016-7037(94)90559-2, 1994. a, b
Siddall, M., Khatiwala, S., van de Flierdt, T., Jones, K., Goldstein, S. L.,
Hemming, S., and Anderson, R. F.: Towards explaining the Nd paradox using
reversible scavenging in an ocean general circulation model, Earth Planet. Sc. Lett., 274, 448–461, https://doi.org/10.1016/j.epsl.2008.07.044,
2008. a, b, c, d
Sigman, D. M., Hain, M. P., and Haug, G. H.: The polar ocean and glacial
cycles in atmospheric CO2 concentration, Nature, 466, 47–55,
https://doi.org/10.1038/nature09149, 2010. a
Stichel, T., Frank, M., Rickli, J., and Haley, B. A.: The hafnium and
neodymium isotope composition of seawater in the Atlantic sector of the
Southern Ocean, Earth Planet. Sc. Lett., 317–318, 282–294,
https://doi.org/10.1016/j.epsl.2011.11.025, 2012a. a, b
Stichel, T., Frank, M., Rickli, J., Hathorne, E. C., Haley, B. A., Jeandel, C.,
and Pradoux, C.: Sources and input mechanisms of hafnium and neodymium in
surface waters of the Atlantic sector of the Southern Ocean, Geochim. Cosmochim. Ac., 94, 1–50, https://doi.org/10.1016/j.gca.2012.07.005,
2012b. a
Stichel, T., Hartman, A. E., Duggan, B., Goldstein, S. L., Scher, H., and
Pahnke, K.: Separating biogeochemical cycling of neodymium from water mass
mixing in the Eastern North Atlantic, Earth Planet. Sc. Lett.,
412, 245–260, https://doi.org/10.1016/j.epsl.2014.12.008, 2015. a
Stichel, T., Pahnke, K., Duggan, B., Goldstein, S. L., Hartman, A. E.,
Paffrath, R., and Scher, H. D.: TAG Plume: Revisiting the Hydrothermal
Neodymium Contribution to Seawater, Front. Marine Sci., 5, 96,
https://doi.org/10.3389/fmars.2018.00096, 2018. a, b, c
Stichel, T., Kretschmer, S., Geibert, W., Lambelet, M., Plancherel, Y., Rutgers
van der Loeff, M. M., and van de Flierdt, T.: Particle–Seawater Interaction
of Neodymium in the North Atlantic, ACS Earth and Space Chemistry, 4,
1700–1717, https://doi.org/10.1021/acsearthspacechem.0c00034, 2020. a
Stichel, T., Kretschmer, S., Geibert, W., Lambelet, M., Plancherel,
Y., Rutgers van der Loeff, M. M., and van de Flierdt, T.: Particulate
Neodymium Isotopes and Concentrations in the Western North Atlantic, PANGAEA,
https://doi.org/10.1594/PANGAEA.922598, 2020. a
Tachikawa, K., Athias, V., and Jeandel, C.: Neodymium budget in the modern
ocean and paleo-oceanographic implications, J. Geophys. Res.-Oceans, 108, 3254, https://doi.org/10.1029/1999JC000285, 2003. a, b
Tachikawa, K., Arsouze, T., Bayon, G., Bory, A., Colin, C., Dutay, J.-C.,
Frank, N., Giraud, X., Gourlan, A. T., Jeandel, C., Lacan, F., Meynadier, L.,
Montagna, P., Piotrowski, A. M., Plancherel, Y., Pucéat, E., Roy-Barman,
M., and Waelbroeck, C.: The large-scale evolution of neodymium isotopic
composition in the global modern and Holocene ocean revealed from seawater
and archive data, Chem. Geol., 457, 131–148,
https://doi.org/10.1016/j.chemgeo.2017.03.018, 2017.
a
Tantau, T., Wibrow, M., Feuersänger, C., et al.: The TikZ and PGF Packages, Manual for version 3.1.9a,
https://github.com/pgf-tikz/pgf, last access: 26 May 2022. a
van de Flierdt, T., Robinson, L. F., Adkins, J. F., Hemming, S. R., and
Goldstein, S. L.: Temporal stability of the neodymium isotope signature of
the Holocene to glacial North Atlantic, Paleoceanography, 21, PA4102,
https://doi.org/10.1029/2006PA001294, 2006. a
van de Flierdt, T., Griffiths, A. M., Lambelet, M., Little, S. H., Stichel, T.,
and Wilson, D. J.: Neodymium in the oceans: a global database, a regional
comparison and implications for palaeoceanographic research, Philosophical
Transactions of the Royal Society A: Mathematical, Phys. Eng.
Sci., 374, 20150293, https://doi.org/10.1098/rsta.2015.0293, 2016a. a, b, c, d, e
van de Flierdt, T., Griffiths, A. M., Lambelet, M., Little, S. H., Stichel, T., and Wilson, D. J.: Global Database from Neodymium in the oceans: a global database, a regional comparison and implications for palaeoceanographic research, The Royal Society [data set], https://doi.org/10.6084/m9.figshare.3980064.v1, 2016b. a
van Hulten, M., Dutay, J.-C., and Roy-Barman, M.: A global scavenging and circulation ocean model of thorium-230 and protactinium-231 with improved particle dynamics (NEMO–ProThorP 0.1), Geosci. Model Dev., 11, 3537–3556, https://doi.org/10.5194/gmd-11-3537-2018, 2018. a
von Blanckenburg, F. and Nägler, T. F.: Weathering versus
circulation-controlled changes in radiogenic isotope tracer composition of
the Labrador Sea and North Atlantic Deep Water, Paleoceanography, 16,
424–434, https://doi.org/10.1029/2000PA000550, 2001. a, b, c
Weber, T., John, S., Tagliabue, A., and DeVries, T.: Biological uptake and
reversible scavenging of zinc in the global ocean, Science, 361, 72–76,
https://doi.org/10.1126/science.aap8532, 2018. a, b
Wilson, D. J., Piotrowski, A. M., Galy, A., and Clegg, J. A.: Reactivity of
neodymium carriers in deep sea sediments: Implications for boundary exchange
and paleoceanography, Geochim. Cosmochim. Ac., 109, 197–221,
https://doi.org/10.1016/j.gca.2013.01.042, 2013. a, b, c, d
Wu, Y.: Investigating the Applications of Neodymium Isotopic Compositions and
Rare Earth Elements as Water Mass Tracers in the South Atlantic and North
Pacific, Academic Commons, Columbia University Libraries, https://doi.org/10.7916/D8-KSTX-XG38, 2019. a
Wu, Y., Pena, L. D., Goldstein, S. L., Anderson, R. F., Hartman, A. E., Bolge,
L. L., Basak, C., Rijkenberg, M. J. A., and de Baar, H. J. W.: Assessing
neodymium isotopes as an ocean circulation tracer in the Southwest Atlantic,
Earth Planet. Sc. Lett., in review, 2022. a
Zheng, X.-Y., Plancherel, Y., Saito, M. A., Scott, P. M., and Henderson, G. M.:
Rare earth elements (REEs) in the tropical South Atlantic and quantitative
deconvolution of their non-conservative behavior, Geochim. Cosmochim.
Ac., 177, 217–237, https://doi.org/10.1016/j.gca.2016.01.018, 2016. a
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.
Neodymium isotopes in seawater have the potential to provide key information about ocean...
