Articles | Volume 16, issue 12
https://doi.org/10.5194/gmd-16-3581-2023
© Author(s) 2023. 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-16-3581-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
29 Jun 2023
Model description paper |
| 29 Jun 2023
| 29 Jun 2023
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Daniele Bianchi
CORRESPONDING AUTHOR
Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, USA
Daniel McCoy
Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, USA
Simon Yang
Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, USA
Related authors
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
Short summary
Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-26, https://doi.org/10.5194/gmd-2024-26, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Numerical models that capture key features of the global dynamics of fish communities play a crucial role in addressing the impacts of climate change and industrial fishing on ecosystems and societies. Here, we detail an update of the BiOeconomic marine Trophic Size-spectrum model that corrects the model representation of the dynamic of fisheries in the High Seas. This update also allows a better representation of biodiversity to improve future global and regional fisheries studies.
De'Marcus Robinson, Anh L. D. Pham, David J. Yousavich, Felix Janssen, Frank Wenzhöfer, Eleanor C. Arrington, Kelsey M. Gosselin, Marco Sandoval-Belmar, Matthew Mar, David L. Valentine, Daniele Bianchi, and Tina Treude
Biogeosciences, 21, 773–788, https://doi.org/10.5194/bg-21-773-2024, https://doi.org/10.5194/bg-21-773-2024, 2024
Short summary
Short summary
The present study suggests that high release of ferrous iron from the seafloor of the oxygen-deficient Santa Barabara Basin (California) supports surface primary productivity, creating positive feedback on seafloor iron release by enhancing low-oxygen conditions in the basin.
Priscilla Le Mézo, Jérôme Guiet, Kim Scherrer, Daniele Bianchi, and Eric Galbraith
Biogeosciences, 19, 2537–2555, https://doi.org/10.5194/bg-19-2537-2022, https://doi.org/10.5194/bg-19-2537-2022, 2022
Short summary
Short summary
This study quantifies the role of commercially targeted fish biomass in the cycling of three important nutrients (N, P, and Fe), relative to nutrients otherwise available in water and to nutrients required by primary producers, and the impact of fishing. We use a model of commercially targeted fish biomass constrained by fish catch and stock assessment data to assess the contributions of fish at the global scale, at the time of the global peak catch and prior to industrial fishing.
Jordyn E. Moscoso, Andrew L. Stewart, Daniele Bianchi, and James C. McWilliams
Geosci. Model Dev., 14, 763–794, https://doi.org/10.5194/gmd-14-763-2021, https://doi.org/10.5194/gmd-14-763-2021, 2021
Short summary
Short summary
This project was created to understand the across-shore distribution of plankton in the California Current System. To complete this study, we used a quasi-2-D dynamical model coupled to an ecosystem model. This paper is a preliminary study to test and validate the model against data collected by the California Cooperative Oceanic Fisheries Investigations (CalCOFI). We show the solution of our model solution compares well to the data and discuss our model as a tool for further model development.
Samuel T. Wilson, Alia N. Al-Haj, Annie Bourbonnais, Claudia Frey, Robinson W. Fulweiler, John D. Kessler, Hannah K. Marchant, Jana Milucka, Nicholas E. Ray, Parvadha Suntharalingam, Brett F. Thornton, Robert C. Upstill-Goddard, Thomas S. Weber, Damian L. Arévalo-Martínez, Hermann W. Bange, Heather M. Benway, Daniele Bianchi, Alberto V. Borges, Bonnie X. Chang, Patrick M. Crill, Daniela A. del Valle, Laura Farías, Samantha B. Joye, Annette Kock, Jabrane Labidi, Cara C. Manning, John W. Pohlman, Gregor Rehder, Katy J. Sparrow, Philippe D. Tortell, Tina Treude, David L. Valentine, Bess B. Ward, Simon Yang, and Leonid N. Yurganov
Biogeosciences, 17, 5809–5828, https://doi.org/10.5194/bg-17-5809-2020, https://doi.org/10.5194/bg-17-5809-2020, 2020
Short summary
Short summary
The oceans are a net source of the major greenhouse gases; however there has been little coordination of oceanic methane and nitrous oxide measurements. The scientific community has recently embarked on a series of capacity-building exercises to improve the interoperability of dissolved methane and nitrous oxide measurements. This paper derives from a workshop which discussed the challenges and opportunities for oceanic methane and nitrous oxide research in the near future.
Olivier Cartapanis, Eric D. Galbraith, Daniele Bianchi, and Samuel L. Jaccard
Clim. Past, 14, 1819–1850, https://doi.org/10.5194/cp-14-1819-2018, https://doi.org/10.5194/cp-14-1819-2018, 2018
Short summary
Short summary
A data-based reconstruction of carbon-bearing deep-sea sediment shows significant changes in the global burial rate over the last glacial cycle. We calculate the impact of these deep-sea changes, as well as hypothetical changes in continental shelf burial and volcanic outgassing. Our results imply that these geological fluxes had a significant impact on ocean chemistry and the global carbon isotopic ratio, and that the natural carbon cycle was not in steady state during the Holocene.
David Anthony Carozza, Daniele Bianchi, and Eric Douglas Galbraith
Geosci. Model Dev., 9, 1545–1565, https://doi.org/10.5194/gmd-9-1545-2016, https://doi.org/10.5194/gmd-9-1545-2016, 2016
Short summary
Short summary
We present the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modeling upper trophic level biomass at the global scale. BOATS employs fundamental ecological principles and takes a simple approach that relies on fewer parameters compared to similar modelling efforts. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, upper trophic levels, and fisheries at the global scale.
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024, https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
Short summary
Atmospheric concentrations of nitrous oxide (N2O), a greenhouse gas 273 times more potent than carbon dioxide, have increased by 25 % since the preindustrial period, with the highest observed growth rate in 2020 and 2021. This rapid growth rate has primarily been due to a 40 % increase in anthropogenic emissions since 1980. Observed atmospheric N2O concentrations in recent years have exceeded the worst-case climate scenario, underscoring the importance of reducing anthropogenic N2O emissions.
Jerome Guiet, Daniele Bianchi, Kim J. N. Scherrer, Ryan F. Heneghan, and Eric D. Galbraith
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-26, https://doi.org/10.5194/gmd-2024-26, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Numerical models that capture key features of the global dynamics of fish communities play a crucial role in addressing the impacts of climate change and industrial fishing on ecosystems and societies. Here, we detail an update of the BiOeconomic marine Trophic Size-spectrum model that corrects the model representation of the dynamic of fisheries in the High Seas. This update also allows a better representation of biodiversity to improve future global and regional fisheries studies.
De'Marcus Robinson, Anh L. D. Pham, David J. Yousavich, Felix Janssen, Frank Wenzhöfer, Eleanor C. Arrington, Kelsey M. Gosselin, Marco Sandoval-Belmar, Matthew Mar, David L. Valentine, Daniele Bianchi, and Tina Treude
Biogeosciences, 21, 773–788, https://doi.org/10.5194/bg-21-773-2024, https://doi.org/10.5194/bg-21-773-2024, 2024
Short summary
Short summary
The present study suggests that high release of ferrous iron from the seafloor of the oxygen-deficient Santa Barabara Basin (California) supports surface primary productivity, creating positive feedback on seafloor iron release by enhancing low-oxygen conditions in the basin.
Priscilla Le Mézo, Jérôme Guiet, Kim Scherrer, Daniele Bianchi, and Eric Galbraith
Biogeosciences, 19, 2537–2555, https://doi.org/10.5194/bg-19-2537-2022, https://doi.org/10.5194/bg-19-2537-2022, 2022
Short summary
Short summary
This study quantifies the role of commercially targeted fish biomass in the cycling of three important nutrients (N, P, and Fe), relative to nutrients otherwise available in water and to nutrients required by primary producers, and the impact of fishing. We use a model of commercially targeted fish biomass constrained by fish catch and stock assessment data to assess the contributions of fish at the global scale, at the time of the global peak catch and prior to industrial fishing.
Jordyn E. Moscoso, Andrew L. Stewart, Daniele Bianchi, and James C. McWilliams
Geosci. Model Dev., 14, 763–794, https://doi.org/10.5194/gmd-14-763-2021, https://doi.org/10.5194/gmd-14-763-2021, 2021
Short summary
Short summary
This project was created to understand the across-shore distribution of plankton in the California Current System. To complete this study, we used a quasi-2-D dynamical model coupled to an ecosystem model. This paper is a preliminary study to test and validate the model against data collected by the California Cooperative Oceanic Fisheries Investigations (CalCOFI). We show the solution of our model solution compares well to the data and discuss our model as a tool for further model development.
Samuel T. Wilson, Alia N. Al-Haj, Annie Bourbonnais, Claudia Frey, Robinson W. Fulweiler, John D. Kessler, Hannah K. Marchant, Jana Milucka, Nicholas E. Ray, Parvadha Suntharalingam, Brett F. Thornton, Robert C. Upstill-Goddard, Thomas S. Weber, Damian L. Arévalo-Martínez, Hermann W. Bange, Heather M. Benway, Daniele Bianchi, Alberto V. Borges, Bonnie X. Chang, Patrick M. Crill, Daniela A. del Valle, Laura Farías, Samantha B. Joye, Annette Kock, Jabrane Labidi, Cara C. Manning, John W. Pohlman, Gregor Rehder, Katy J. Sparrow, Philippe D. Tortell, Tina Treude, David L. Valentine, Bess B. Ward, Simon Yang, and Leonid N. Yurganov
Biogeosciences, 17, 5809–5828, https://doi.org/10.5194/bg-17-5809-2020, https://doi.org/10.5194/bg-17-5809-2020, 2020
Short summary
Short summary
The oceans are a net source of the major greenhouse gases; however there has been little coordination of oceanic methane and nitrous oxide measurements. The scientific community has recently embarked on a series of capacity-building exercises to improve the interoperability of dissolved methane and nitrous oxide measurements. This paper derives from a workshop which discussed the challenges and opportunities for oceanic methane and nitrous oxide research in the near future.
Olivier Cartapanis, Eric D. Galbraith, Daniele Bianchi, and Samuel L. Jaccard
Clim. Past, 14, 1819–1850, https://doi.org/10.5194/cp-14-1819-2018, https://doi.org/10.5194/cp-14-1819-2018, 2018
Short summary
Short summary
A data-based reconstruction of carbon-bearing deep-sea sediment shows significant changes in the global burial rate over the last glacial cycle. We calculate the impact of these deep-sea changes, as well as hypothetical changes in continental shelf burial and volcanic outgassing. Our results imply that these geological fluxes had a significant impact on ocean chemistry and the global carbon isotopic ratio, and that the natural carbon cycle was not in steady state during the Holocene.
David Anthony Carozza, Daniele Bianchi, and Eric Douglas Galbraith
Geosci. Model Dev., 9, 1545–1565, https://doi.org/10.5194/gmd-9-1545-2016, https://doi.org/10.5194/gmd-9-1545-2016, 2016
Short summary
Short summary
We present the ecological module of the BiOeconomic mArine Trophic Size-spectrum (BOATS) model, which takes an Earth-system approach to modeling upper trophic level biomass at the global scale. BOATS employs fundamental ecological principles and takes a simple approach that relies on fewer parameters compared to similar modelling efforts. As such, it enables the exploration of the linkages between ocean biogeochemistry, climate, upper trophic levels, and fisheries at the global scale.
Related subject area
Oceanography
Experimental design for the Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2)
Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids
Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)
Modelling the water isotope distribution in the Mediterranean Sea using a high-resolution oceanic model (NEMO-MED12-watiso v1.0): evaluation of model results against in situ observations
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0
A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study of Quatsino Sound, British Columbia
An optimal transformation method applied to diagnose the ocean carbon budget
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 2: Towards a better representation of total alkalinity when modeling the carbonate system and air–sea CO2 fluxes
Development of a novel storm surge inundation model framework for efficient prediction
Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth
DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
StraitFlux – precise computations of water strait fluxes on various modeling grids
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
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)
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet-ocean modelling
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)
PPCon 1.0: Biogeochemical Argo Profile Prediction with 1D Convolutional Networks
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
An optimal transformation method for inferring ocean tracer sources and sinks
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
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
The Met Office operational wave forecasting system: the evolution of the regional and global models
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
Development and validation of a global 1∕32° surface-wave–tide–circulation coupled ocean model: FIO-COM32
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
Short summary
Short summary
Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
Short summary
Short summary
We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
Short summary
Short summary
Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
Short summary
Short summary
Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
Short summary
Short summary
Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
Short summary
Short summary
Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
Short summary
Short summary
Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
Short summary
Short summary
The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
Short summary
Short summary
The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
Short summary
Short summary
Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
Short summary
Short summary
This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
Short summary
Short summary
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
Short summary
Short summary
Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
Short summary
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
Short summary
Short summary
The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
Short summary
Short summary
In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
Short summary
Short summary
Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-244, https://doi.org/10.5194/gmd-2023-244, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We have introduced an "accelerated forcing" approach to address the discrepancy in timescales between ice sheet and ocean models in coupled modelling, by reducing the ocean model simulation duration. We evaluate the approach's applicability and limitations based on idealized coupled models. Our results suggest that, when used carefully, the approach can be a useful tool in coupled ice sheet-ocean modelling, especially relevant to studies on sea level rise projections.
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.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
EGUsphere, https://doi.org/10.5194/egusphere-2023-1876, https://doi.org/10.5194/egusphere-2023-1876, 2023
Short summary
Short summary
Harness AI for better ocean insights. BGC-Argo floats collect deep ocean data, yet forecasting vital nutrient levels is a challenge. Our novel AI approach, PPCon, learns from Argo float measurements and provides improved nutrient predictions. This enhances our understanding of ocean dynamics and nutrient distribution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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.
Jan David Zika and Sohail Taimoor
EGUsphere, https://doi.org/10.5194/egusphere-2023-1220, https://doi.org/10.5194/egusphere-2023-1220, 2023
Short summary
Short summary
We describe a method to relate the fluxes of heat and fresh water at the sea surface, to the resulting distribution of sea water among categories such as warm and salty, cold and salty, etc. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
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.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
Short summary
Short summary
In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
Short summary
Short summary
Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
Short summary
Short summary
An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
Short summary
Short summary
Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
Short summary
Short summary
MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
Short summary
Short summary
Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
Short summary
Short summary
The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
Short summary
Short summary
We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
Short summary
Short summary
4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
Short summary
Short summary
A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Cited articles
Anderson, L. A. and Sarmiento, J. L.: Redfield ratios of remineralization
determined by nutrient data analysis, Global Biogeochem. Cy., 8,
65–80, https://doi.org/10.1029/93GB03318, 1994. a, b, c
Arévalo-Martínez, D. L., Kock, A., Löscher, C. R., Schmitz, R. A., Stramma, L., and Bange, H. W.: Influence of mesoscale eddies on the distribution of nitrous oxide in the eastern tropical South Pacific, Biogeosciences, 13, 1105–1118, https://doi.org/10.5194/bg-13-1105-2016, 2016. a
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. a, b
Azhar, M. A., Canfield, D. E., Fennel, K., Thamdrup, B., and Bjerrum, C. J.: A
model-based insight into the coupling of nitrogen and sulfur cycles in a
coastal upwelling system, J. Geophys. Res.-Biogeo.,
119, 264–285, 2014. a
Babbin, A. R., Keil, R. G., Devol, A. H., and Ward, B. B.: Organic matter
stoichiometry, flux, and oxygen control nitrogen loss in the ocean, Science,
344, 406–408, https://doi.org/10.1126/science.1248364, 2014. a, b, c
Babbin, A. R., Peters, B. D., Mordy, C. W., Widner, B., Casciotti, K. L., and
Ward, B. B.: Multiple metabolisms constrain the anaerobic nitrite budget in
the Eastern Tropical South Pacific, Global Biogeochem. Cy., 31,
258–271, https://doi.org/10.1002/2016GB005407, 2017. a, b
Babbin, A. R., Buchwald, C., Morel, F. M., Wankel, S. D., and Ward, B. B.:
Nitrite oxidation exceeds reduction and fixed nitrogen loss in anoxic
Pacific waters, Mar. Chem., 224, 103814, https://doi.org/10.1016/j.marchem.2020.103814,
2020. a, b, c, d
Battaglia, G. and Joos, F.: Marine N2O Emissions From Nitrification and
Denitrification Constrained by Modern Observations and Projected in
Multimillennial Global Warming Simulations, Global Biogeochem. Cy.,
32, 92–121, https://doi.org/10.1002/2017GB005671, 2018. a
Berelson, W.: The Flux of Particulate Organic Carbon Into the Ocean Interior:
A Comparison of Four U.S. JGOFS Regional Studies, Oceanography, 14, 59–67,
https://doi.org/10.5670/oceanog.2001.07, 2001. a
Bettencourt, J. H., Lopez, C., Hernandez-Garcia, E., Montes, I., Sudre, J.,
Dewitte, B., Paulmier, A., and Garçon, V.: Boundaries of the Peruvian
oxygen minimum zone shaped by coherent mesoscale dynamics, Nat.
Geosci., 8, 937–940, https://doi.org/10.1038/ngeo2570, 2015. a
Bianchi, D., Dunne, J. P., Sarmiento, J. L., and Galbraith, E. D.: Data-based
estimates of suboxia, denitrification, and N2O production in the ocean and
their sensitivities to dissolved O2, Global Biogeochem. Cy., 26,
GB2009, https://doi.org/10.1029/2011GB004209, 2012. a
Bianchi, D., Babbin, A. R., and Galbraith, E. D.: Enhancement of anammox by the
excretion of diel vertical migrators, P. Natl. Acad.
Sci. USA, 111, 15653–15658, 2014. a
Bianchi, D., Weber, T. S., Kiko, R., and Deutsch, C.: Global niche of marine
anaerobic metabolisms expanded by particle microenvironments, Nat.
Geosci., 11, 263–268, https://doi.org/10.1038/s41561-018-0081-0, 2018. a
Bianchi, D., Yang, S., and McCoy, D.: NitrOMZv1.0 Model Code,
Zenodo [code, data set], https://doi.org/10.5281/zenodo.7106213, 2022. a
Bopp, L., Resplandy, L., Orr, J. C., Doney, S. C., Dunne, J. P., Gehlen, M., Halloran, P., Heinze, C., Ilyina, T., Séférian, R., Tjiputra, J., and Vichi, M.: Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models, Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, 2013. a
Boyd, P. W., Claustre, H., Levy, M., Siegel, D. A., and Weber, T.:
Multi-faceted particle pumps drive carbon sequestration in the ocean, Nature,
568, 327–335, 2019. a
Bristow, L. A., Dalsgaard, T., Tiano, L., Mills, D. B., Bertagnolli, A. D.,
Wright, J. J., Hallam, S. J., Ulloa, O., Canfield, D. E., Revsbech, N. P.,
and Thamdrup, B.: Ammonium and nitrite oxidation at nanomolar oxygen
concentrations in oxygen minimum zone waters, P. Natl.
Acad. Sci. USA, 113, 10601–10606,
https://doi.org/10.1073/pnas.1600359113, 2016. a, b, c, d, e, f, g
Buchanan, P. J., Sun, X., Weissman, J. L., and Zakem, E.: Oxygen intrusions
sustain aerobic nitrite oxidation in anoxic marine zones, bioRxiv,
https://doi.org/10.1101/2023.02.22.529547, 2023. a
Buchwald, C., Santoro, A. E., Stanley, R. H. R., and Casciotti, K. L.: Global Biogeochem. Cy., 29, 2061–2081, https://doi.org/10.1002/2015GB005187,
2015b. a
Buitenhuis, E. T., Suntharalingam, P., and Le Quéré, C.: Constraints on global oceanic emissions of N2O from observations and models, Biogeosciences, 15, 2161–2175, https://doi.org/10.5194/bg-15-2161-2018, 2018. a
Busecke, J. J. M., Resplandy, L., Ditkovsky, S. J., and John, J. G.: Diverging
Fates of the Pacific Ocean Oxygen Minimum Zone and Its Core in a Warming
World, AGU Advances, 3, e2021AV000470, https://doi.org/10.1029/2021AV000470, 2022. a
Callbeck, C. M., Canfield, D. E., Kuypers, M. M. M., Yilmaz, P., Lavik, G.,
Thamdrup, B., Schubert, C. J., and Bristow, L. A.: Sulfur cycling in oceanic
oxygen minimum zones, Limnol. Oceanogr., 66, 2360–2392,
https://doi.org/10.1002/lno.11759, 2021. a, b
Capone, D., Bronk, D., Mulholland, M. R., and Carpenter, E.: Nitrogen in the
Marine Environment, Elsevier, https://doi.org/10.1016/B978-0-12-372522-6.X0001-1,
2008. a, b
Casciotti, K., Forbes, M., Vedamati, J., Peters, B., Martin, T., and Mordy, C.:
Nitrous oxide cycling in the Eastern Tropical South Pacific as inferred from
isotopic and isotopomeric data, Deep-Sea Res. Pt. II, 156, 155–167, https://doi.org/10.1016/j.dsr2.2018.07.014, 2018. a
Cinay, T., Dumit, D., Woosley, R. J., Boles, E. L., Kwiecinski, J. V., Mullen,
S., Tamasi, T. J., Wolf, M. J., Kelly, C. L., Travis, N. M., Casciotti, K. L., and Babbin, A. R.:
Coincident biogenic nitrite and pH maxima arise in the upper anoxic layer in
the Eastern Tropical North Pacific, Global Biogeochem. Cy.,
36,
e2022GB007470, https://doi.org/10.1029/2022GB007470, 2022. a, b
Dalsgaard, T., Stewart, F. J., Thamdrup, B., De Brabandere, L., Revsbech,
N. P., Ulloa, O., Canfield, D. E., and Delong, E. F.: Oxygen at nanomolar
levels reversibly suppresses process rates and gene expression in anammox and
denitrification in the oxygen minimum zone off Northern Chile, mBio, 5,
1–14, https://doi.org/10.1128/mBio.01966-14, 2014. a, b, c, d, e, f, g, h, i, j, k
De Brabandere, L., Canfield, D. E., Dalsgaard, T., Friederich, G. E., Revsbech,
N. P., Ulloa, O., and Thamdrup, B.: Vertical partitioning of nitrogen-loss
processes across the oxic-anoxic interface of an oceanic oxygen minimum
zone, Environ. Microbiol., 16, 3041–3054,
https://doi.org/10.1111/1462-2920.12255, 2014. a
Deutsch, C., Brix, H., Ito, T., Frenzel, H., and Thompson, L.: Climate-forced
variability of ocean hypoxia, Science, 333, 336–339, 2011. a
DeVries, T., Deutsch, C., Primeau, F., Chang, B., and Devol, A.: Global rates
of water-column denitrification derived from nitrogen gas measurements,
Nat. Geosci., 5, 547–550, 2012. a
DeVries, T., Deutsch, C., Rafter, P. A., and Primeau, F.: Marine denitrification rates determined from a global 3-D inverse model, Biogeosciences, 10, 2481–2496, https://doi.org/10.5194/bg-10-2481-2013, 2013. a
Fasham, M. J. R., Ducklow, H. W., and McKelvie, S. M.: A nitrogen-based model
of plankton dynamics in the oceanic mixed layer, J. Mar. Res.,
48, 591–639, https://doi.org/10.1357/002224090784984678, 1990. a
Fischer, T., Banyte, D., Brandt, P., Dengler, M., Krahmann, G., Tanhua, T., and Visbeck, M.: Diapycnal oxygen supply to the tropical North Atlantic oxygen minimum zone, Biogeosciences, 10, 5079–5093, https://doi.org/10.5194/bg-10-5079-2013, 2013. a
Frey, C., Bange, H. W., Achterberg, E. P., Jayakumar, A., Löscher, C. R., Arévalo-Martínez, D. L., León-Palmero, E., Sun, M., Sun, X., Xie, R. C., Oleynik, S., and Ward, B. B.: Regulation of nitrous oxide production in low-oxygen waters off the coast of Peru, Biogeosciences, 17, 2263–2287, https://doi.org/10.5194/bg-17-2263-2020, 2020. a, b, c, d, e, f
Galbraith, E. D., Dunne, J. P., Gnanadesikan, A., Slater, R. D., Sarmiento,
J. L., Dufour, C. O., De Souza, G. F., Bianchi, D., Claret, M., Rodgers,
K. B., and Marvasti, S. S.: Complex functionality with minimal computation: Promise and
pitfalls of reduced-tracer ocean biogeochemistry models,
J. Adv. Model. Earth Sy., 7, 2012–2028, 2015. a
Ganesh, S., Bristow, L. A., Larsen, M., Sarode, N., Thamdrup, B., and Stewart,
F. J.: Size-fraction partitioning of community gene transcription and
nitrogen metabolism in a marine oxygen minimum zone, ISME J., 9,
2682–2696, https://doi.org/10.1038/ismej.2015.44, 2015. a
Giovannoni, S. J., Cameron Thrash, J., and Temperton, B.: Implications of
streamlining theory for microbial ecology, ISME J., 8, 1553–1565,
https://doi.org/10.1038/ismej.2014.60, 2014. a
Gnanadesikan, A., Bianchi, D., and Pradal, M. A.: Critical role for mesoscale
eddy diffusion in supplying oxygen to hypoxic ocean waters, Geophys.
Res. Lett., 40, 5194–5198, https://doi.org/10.1002/GRL.50998, 2013. a
Goreau, T. J., Kaplan, W. A., Wofsy, S. C., McElroy, M. B., Valois, F. W., and
Watson, S. W.: Production of NO(2) and N(2)O by Nitrifying Bacteria at
Reduced Concentrations of Oxygen., Appl. Environ. Microb.,
40, 526–32, https://doi.org/10.1128/aem.40.3.526-532.1980, 1980. a, b
Graf, D. R., Jones, C. M., and Hallin, S.: Intergenomic comparisons highlight
modularity of the denitrification pathway and underpin the importance of
community structure for N2O emissions, PloS one, 9, e114118, https://doi.org/10.1371/journal.pone.0114118, 2014. a
Gruber, N. and Galloway, J. N.: An Earth-system perspective of the global
nitrogen cycle, Nature, 451, 293–296, 2008. a
Hansen, N.: The CMA Evolution Strategy: A Comparing Review, in: Towards a New
Evolutionary Computation, edited by: Lozano, J. A., Larrañaga, P., Iñaki,
I., and Endika, B., Springer Berlin Heidelberg, Berlin,
Heidelberg, 75–102, https://doi.org/10.1007/3-540-32494-1_4, 2006. a
Hansen, N.: The CMA Evolution Strategy: A Tutorial, arXiv [preprint], https://doi.org/10.48550/arXiv.1604.00772, 10 March 2023. a, b
Hansen, N., Niederberger, A., Guzzella, L., and Koumoutsakos, P.: A Method for
Handling Uncertainty in Evolutionary Optimization With an Application to
Feedback Control of Combustion, IEEE T. Evolut.
Comput., 13, 180–197, https://doi.org/10.1109/TEVC.2008.924423, 2009. a, b
Hooper, A. B. and Terry, K.: Hydroxylamine oxidoreductase of Nitrosomonas,
Biochim. Biophys. Acta, 571, 12–20,
https://doi.org/10.1016/0005-2744(79)90220-1, 1979. a, b
Jensen, M. M., Lam, P., Revsbech, N. P., Nagel, B., Gaye, B., Jetten, M. S.,
and Kuypers, M. M.: Intensive nitrogen loss over the Omani Shelf due to
anammox coupled with dissimilatory nitrite reduction to ammonium, ISME
J., 5, 1660–1670, https://doi.org/10.1038/ismej.2011.44, 2011. a
Ji, Q., Babbin, A. R., Peng, X., Bowen, J. L., and Ward, B. B.: Nitrogen
substrate–dependent nitrous oxide cycling in salt marsh sediments, J. Mar. Res., 73, 71–92, https://doi.org/10.1357/002224015815848820,
2015b. a, b
Ji, Q., Buitenhuis, E., Suntharalingam, P., Sarmiento, J. L., and Ward, B. B.:
Global Nitrous Oxide Production Determined by Oxygen Sensitivity of
Nitrification and Denitrification, Global Biogeochem. Cy., 32,
1790–1802, https://doi.org/10.1029/2018GB005887, 2018b. a, b
Jin, X. and Gruber, N.: Offsetting the radiative benefit of ocean iron
fertilization by enhancing N2O emissions, Geophys. Res. Lett., 30,
1–4, https://doi.org/10.1029/2003GL018458, 2003. a
Johnson, K. A. and Goody, R. S.: The Original Michaelis Constant: Translation
of the 1913 Michaelis–Menten Paper, Biochemistry, 50, 8264–8269,
https://doi.org/10.1021/bi201284u, 2011. a
Johnston, D. T., Gill, B. C., Masterson, A., Beirne, E., Casciotti, K. L.,
Knapp, A. N., and Berelson, W.: Placing an upper limit on cryptic marine
sulphur cycling, Nature, 513, 530–533, https://doi.org/10.1038/nature13698, 2014. a
Kalvelage, T., Jensen, M. M., Contreras, S., Revsbech, N. P., Lam, P.,
Günter, M., LaRoche, J., Lavik, G., and Kuypers, M. M.: Oxygen
sensitivity of anammox and coupled N-cycle processes in oxygen minimum
zones, PLoS ONE, 6, e29299, https://doi.org/10.1371/journal.pone.0029299, 2011. a, b, c
Kalvelage, T., Lavik, G., Lam, P., Contreras, S., Arteaga, L., Löscher,
C. R., Oschlies, A., Paulmier, A., Stramma, L., and Kuypers, M. M.: Nitrogen
cycling driven by organic matter export in the South Pacific oxygen minimum
zone, Nat. Geosci., 6, 228–234, https://doi.org/10.1038/ngeo1739, 2013. a, b, c, d
Karstensen, J., Stramma, L., and Visbeck, M.: Oxygen minimum zones in the
eastern tropical Atlantic and Pacific oceans, Prog. Oceanogr., 77,
331–350, https://doi.org/10.1016/j.pocean.2007.05.009, 2008. a
Koeve, W. and Kähler, P.: Heterotrophic denitrification vs. autotrophic anammox – quantifying collateral effects on the oceanic carbon cycle, Biogeosciences, 7, 2327–2337, https://doi.org/10.5194/bg-7-2327-2010, 2010. a
Kraft, B., Strous, M., and Tegetmeyer, H. E.: Microbial nitrate respiration
– Genes, enzymes and environmental distribution, J. Biotechnol.,
155, 104–117, https://doi.org/10.1016/j.jbiotec.2010.12.025, 2011. a
Kriest, I. and Oschlies, A.: On the treatment of particulate organic matter sinking in large-scale models of marine biogeochemical cycles, Biogeosciences, 5, 55–72, https://doi.org/10.5194/bg-5-55-2008, 2008. a
Kriest, I., Sauerland, V., Khatiwala, S., Srivastav, A., and Oschlies, A.: Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0), Geosci. Model Dev., 10, 127–154, https://doi.org/10.5194/gmd-10-127-2017, 2017. a, b, c, d
Lam, P., Lavik, G., Jensen, M. M., van de Vossenberg, J., Schmid, M., Woebken,
D., Gutiérrez, D., Amann, R., Jetten, M. S. M., and Kuypers, M. M. M.:
Revising the nitrogen cycle in the Peruvian oxygen minimum zone,
P. Natl. Acad. Sci. USA, 106, 4752–4757,
https://doi.org/10.1073/pnas.0812444106, 2009. a, b
Long, A. M., Jurgensen, S. K., Petchel, A. R., Savoie, E. R., and Brum, J. R.:
Microbial Ecology of Oxygen Minimum Zones Amidst Ocean Deoxygenation,
Front. Microbiol., 12, 748961, https://doi.org/10.3389/fmicb.2021.748961,
2021a. a
Long, M. C., Moore, J. K., Lindsay, K., Levy, M., Doney, S. C., Luo, J. Y.,
Krumhardt, K. M., Letscher, R. T., Grover, M., and Sylvester, Z. T.:
Simulations with the marine biogeochemistry library (marbl), J. Adv. Model. Earth Sy., 13, e2021MS002647, https://doi.org/10.1029/2021MS002647 2021b. a, b
Löscher, C. R., Kock, A., Könneke, M., LaRoche, J., Bange, H. W., and Schmitz, R. A.: Production of oceanic nitrous oxide by ammonia-oxidizing archaea, Biogeosciences, 9, 2419–2429, https://doi.org/10.5194/bg-9-2419-2012, 2012. a
Louca, S., Hawley, A. K., Katsev, S., Torres-Beltran, M., Bhatia, M. P.,
Kheirandish, S., Michiels, C. C., Capelle, D., Lavik, G., Doebeli, M., Crowe,
S. A., and Hallam, S. J.: Integrating biogeochemistry with multiomic
sequence information in a model oxygen minimum zone, P.
Natl. Acad. Sci. USA, 113, E5925–E5933, https://doi.org/10.1073/pnas.1602897113, 2016. a, b, c, d, e, f
Lutterbeck, H. E., Arévalo-Martínez, D. L., Löscher, C. R.,
and Bange, H. W.: Nitric oxide (NO) in the oxygen minimum zone off Peru,
Deep-Sea Res. Pt. II, 156, 148–154,
https://doi.org/10.1016/j.dsr2.2017.12.023, 2018. a, b
Manizza, M., Keeling, R. F., and Nevison, C. D.: On the processes controlling
the seasonal cycles of the air–sea fluxes of O2 and N2O: A modelling study,
Tellus B, 64, 18429, https://doi.org/10.3402/tellusb.v64i0.18429, 2012. a
Martens-Habbena, W., Berube, P. M., Urakawa, H., De La Torre, J. R., and Stahl,
D. A.: Ammonia oxidation kinetics determine niche separation of nitrifying
Archaea and Bacteria, Nature, 461, 976–979, https://doi.org/10.1038/nature08465,
2009. a
Martin, J. H., Knauer, G. A., Karl, D. M., and Broenkow, W. W.: VERTEX: carbon
cycling in the northeast Pacific, Deep-Sea Res. Pt. I., 34, 267–285, https://doi.org/10.1016/0198-0149(87)90086-0, 1987. a
Martinez-Rey, J., Bopp, L., Gehlen, M., Tagliabue, A., and Gruber, N.: Projections of oceanic N2O emissions in the 21st century using the IPSL Earth system model, Biogeosciences, 12, 4133–4148, https://doi.org/10.5194/bg-12-4133-2015, 2015. a
McCoy, D., Damien, P., Clements, D. J., Yang, S., and Bianchi, D.: Pathways of
Nitrous Oxide Production in the Eastern Tropical South Pacific Oxygen Minimum
Zone, Authorea Preprints, https://doi.org/10.22541/essoar.167058932.27589471/v1, 2022. a, b
Moore, J. K., Doney, S. C., and Lindsay, K.: Upper ocean ecosystem dynamics
and iron cycling in a global three-dimensional model, Global Biogeochem.
Cy., 18, GB4028, https://doi.org/10.1029/2004GB002220, 2004. a, b
Moore, J. K., Lindsay, K., Doney, S. C., Long, M. C., and Misumi, K.: Marine
Ecosystem Dynamics and Biogeochemical Cycling in the Community Earth System
Model [CESM1(BGC)]: Comparison of the 1990s with the 2090s under the RCP4.5
and RCP8.5 Scenarios, J. Climate, 26, 9291–9312,
https://doi.org/10.1175/JCLI-D-12-00566.1, 2013. a
Moreno, A. R., Garcia, C. A., Larkin, A. A., Lee, J. A., Wang, W.-L., Moore,
J. K., Primeau, F. W., and Martiny, A. C.: Latitudinal gradient in the
respiration quotient and the implications for ocean oxygen availability,
P. Natl. Acad. Sci. USA, 117, 22866–22872,
https://doi.org/10.1073/pnas.2004986117, 2020. a
Moreno, A. R., Larkin, A. A., Lee, J. A., Gerace, S. D., Tarran, G. A., and
Martiny, A. C.: Regulation of the Respiration Quotient Across Ocean Basins,
AGU Advances, 3, e2022AV000679, https://doi.org/10.1029/2022AV000679, 2022. a
Naqvi, S. W. A., Bange, H. W., Farías, L., Monteiro, P. M. S., Scranton, M. I., and Zhang, J.: Marine hypoxia/anoxia as a source of CH4 and N2O, Biogeosciences, 7, 2159–2190, https://doi.org/10.5194/bg-7-2159-2010, 2010. a
Nguyen, T. T., Zakem, E. J., Ebrahimi, A., Schwartzman, J., Caglar, T.,
Amarnath, K., Alcolombri, U., Peaudecerf, F. J., Hwa, T., Stocker, R.,
Cordero, O. X., and Levine, N. M.: Microbes contribute to setting the ocean carbon flux by altering the
fate of sinking particulates, Nat. Commun., 13, 1–9, 2022. a
Paulmier, A., Kriest, I., and Oschlies, A.: Stoichiometries of remineralisation and denitrification in global biogeochemical ocean models, Biogeosciences, 6, 923–935, https://doi.org/10.5194/bg-6-923-2009, 2009. a
Paulot, F., Stock, C., John, J. G., Zadeh, N., and Horowitz, L. W.: Ocean
ammonia outgassing: modulation by CO2and anthropogenic nitrogen deposition,
J. Adv. Model. Earth Sy., 12, e2019MS002026, https://doi.org/10.1029/2019MS002026, 2020. a
Peng, X., Fuchsman, C. A., Jayakumar, A., Warner, M. J., Devol, A. H., and
Ward, B. B.: Revisiting
nitrification in the Eastern Tropical South Pacific: A focus on controls,
J. Geophys. Res.-Oceans, 121, 1667–1684,
https://doi.org/10.1002/2015JC011455, 2016. a, b, c
Penn, J., Weber, T., and Deutsch, C.: Microbial functional diversity alters
the structure and sensitivity of oxygen deficient zones, Geophys.
Res. Lett., 43, 9773–9780, https://doi.org/10.1002/2016GL070438, 2016. a, b, c, d
Santoro, A. E., Buchwald, C., McIlvin, M. R., and Casciotti, K. L.: Isotopic
Signature of N2O Produced by Marine Ammonia-Oxidizing Archaea,
Science, 333, 1282–1285, https://doi.org/10.1126/science.1208239, 2011. a
Sarmiento, J. L., Slater, R., Fasham, M., Ducklow, H., Toggweiler, J., and
Evans, G.: A seasonal three-dimensional ecosystem model of nitrogen cycling
in the North Atlantic euphotic zone, Global Biogeochem. Cy., 7,
417–450, 1993. a
Sarmiento, J. L., Slater, R. D., Dunne, J., Gnanadesikan, A., and Hiscock, M. R.: Efficiency of small scale carbon mitigation by patch iron fertilization, Biogeosciences, 7, 3593–3624, https://doi.org/10.5194/bg-7-3593-2010, 2010. a
Schartau, M. and Oschlies, A.: Simultaneous data-based optimization of a
1D-ecosystem model at three locations in the North Atlantic: Part I–Method
and parameter estimates, J. Mar. Res., 61, 765–793,
https://doi.org/10.1357/002224003322981147, 2003. a, b
Scholz, F., Löscher, C. R., Fiskal, A., Sommer, S., Hensen, C., Lomnitz,
U., Wuttig, K., Göttlicher, J., Kossel, E., Steininger, R., and
Canfield, D. E.: Nitrate-dependent iron oxidation limits iron transport in
anoxic ocean regions, Earth Planet. Sc. Lett., 454, 272–281,
https://doi.org/10.1016/j.epsl.2016.09.025, 2016. a
Schreiber, F., Wunderlin, P., Udert, K. M., and Wells, G. F.: Nitric oxide and
nitrous oxide turnover in natural and engineered microbial communities:
biological pathways, chemical reactions, and novel technologies, Front. Microbiol., 3, 372, https://doi.org/10.3389/fmicb.2012.00372, 2012. a
Séférian, R., Berthet, S., Yool, A., Palmieri, J., Bopp, L., Tagliabue,
A., Kwiatkowski, L., Aumont, O., Christian, J., Dunne, J., Gehlen, M., Ilyina, T., John, J. G., Li, H., Long, M. C., Luo, J. Y., Nakano, H., Romanou, A., Schwinger, J., Stock, C., Santana-Falcón, Y., Takano, Y., Tjiputra, J., Tsujino, H., Watanabe, M., Wu, T., Wu, F., and Yamamoto, A.: Tracking
improvement in simulated marine biogeochemistry between CMIP5 and CMIP6,
Current Climate Change Reports, 6, 95–119, 2020. a
Smriga, S., Ciccarese, D., and Babbin, A. R.: Denitrifying bacteria respond to
and shape microscale gradients within particulate matrices,
Communications Biology, 4, 1–9, 2021. a
Stein, L. Y. and Yung, Y. L.: Production, Isotopic Composition, and
Atmospheric Fate of Biologically Produced Nitrous Oxide, Annu. Rev.
Earth Planet. Sc., 31, 329–356,
https://doi.org/10.1146/annurev.earth.31.110502.080901, 2003. a, b
Stieglmeier, M., Mooshammer, M., Kitzler, B., Wanek, W.,
Zechmeister-Boltenstern, S., Richter, A., and Schleper, C.: Aerobic nitrous
oxide production through N-nitrosating hybrid formation in ammonia-oxidizing
archaea, ISME J., 8, 1135–1146, https://doi.org/10.1038/ismej.2013.220, 2014. a, b
Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P.,
Laufkötter, C., Paulot, F., and Zadeh, N.: Ocean biogeochemistry in
GFDL's Earth System Model 4.1 and its response to increasing atmospheric CO2,
J. Adv. Model. Earth Sy., 12, e2019MS002043, https://doi.org/10.1029/2019MS002043, 2020. a, b
Sun, X., Ji, Q., Jayakumar, A., and Ward, B. B.: Dependence of nitrite
oxidation on nitrite and oxygen in low-oxygen seawater, Geophys. Rese.
Lett., 44, 7883–7891, https://doi.org/10.1002/2017GL074355, 2017. a, b, c
Sun, X., Frey, C., Garcia-Robledo, E., Jayakumar, A., and Ward, B. B.:
Microbial niche differentiation explains nitrite oxidation in marine oxygen
minimum zones, ISME J., 15, 1317–1329,
https://doi.org/10.1038/s41396-020-00852-3, 2021a. a, b
Sun, X., Jayakumar, A., Tracey, J. C., Wallace, E., Kelly, C. L., Casciotti,
K. L., and Ward, B. B.: Microbial N2O consumption in and above marine N2O
production hotspots, ISME J., 15, 1434–1444, 2021b. a
Suntharalingam, P. and Sarmiento, J. L.: Factors governing the oceanic nitrous
oxide distribution: Simulations with an ocean general circulation model,
Global Biogeochem. Cy., 14, 429–454, 2000. a
Suntharalingam, P., Buitenhuis, E., Le Quéré, C., Dentener, F.,
Nevison, C., Butler, J. H., Bange, H. W., and Forster, G.: Quantifying the
impact of anthropogenic nitrogen deposition on oceanic nitrous oxide,
Geophys. Res. Lett., 39, L07605, https://doi.org/10.1029/2011GL050778, 2012. a
Swan, B. K., Martinez-Garcia, M., Preston, C. M., Sczyrba, A., Woyke, T., Lamy,
D., Reinthaler, T., Poulton, N. J., Masland, E. D. P., Gomez, M. L.,
Sieracki, M. E., DeLong, E. F., Herndl, G. J., and Stepanauskas, R.:
Potential for Chemolithoautotrophy Among Ubiquitous Bacteria Lineages in the
Dark Ocean, Science, 333, 1296–1300, https://doi.org/10.1126/science.1203690, 2011. a
Teng, Y.-C., Primeau, F. W., Moore, J. K., Lomas, M. W., and Martiny, A. C.:
Global-scale variations of the ratios of carbon to phosphorus in exported
marine organic matter, Nat. Geosci., 7, 895–898,
https://doi.org/10.1038/ngeo2303, 2014. a
Thamdrup, B., Steinsdóttir, H. G. R., Bertagnolli, A. D., Padilla, C. C.,
Patin, N. V., Garcia‐Robledo, E., Bristow, L. A., and Stewart, F. J.:
Anaerobic methane oxidation is an important sink for methane in the ocean's
largest oxygen minimum zone, Limnol. Oceanogr., 64, 2569–2585,
https://doi.org/10.1002/lno.11235, 2019. a, b
Trimmer, M., Chronopoulou, P.-M., Maanoja, S. T., Upstill-Goddard, R. C.,
Kitidis, V., and Purdy, K. J.: Nitrous oxide as a function of oxygen and
archaeal gene abundance in the North Pacific, Nat. Commun., 7,
13451, https://doi.org/10.1038/ncomms13451, 2016. a
Van Mooy, B. A., Keil, R. G., and Devol, A. H.: Impact of suboxia on sinking
particulate organic carbon: Enhanced carbon flux and preferential degradation
of amino acids via denitrification, Geochim. Cosmochim. Ac., 66,
457–465, https://doi.org/10.1016/S0016-7037(01)00787-6, 2002. a
Wang, W.-L., Moore, J. K., Martiny, A. C., and Primeau, F. W.: Convergent
estimates of marine nitrogen fixation, Nature, 566, 205–211,
https://doi.org/10.1038/s41586-019-0911-2, 2019. a
Ward, B. and Zafiriou, O.: Nitrification and nitric oxide in the oxygen
minimum of the eastern tropical North Pacific, Deep-Sea Res. Pt. I, 35, 1127–1142,
https://doi.org/10.1016/0198-0149(88)90005-2, 1988. a, b, c
Ward, B. A., Friedrichs, M. A., Anderson, T. R., and Oschlies, A.: Parameter
optimisation techniques and the problem of underdetermination in marine
biogeochemical models, J. Marine Syst., 81, 34–43,
https://doi.org/10.1016/j.jmarsys.2009.12.005, 2010. a
Ward, B. B.: Nitrification in Marine Systems, in: Nitrogen in the Marine
Environment, 199–261, Elsevier,
https://doi.org/10.1016/B978-0-12-372522-6.00005-0, 2008. a
Weber, T. and Bianchi, D.: Efficient particle transfer to depth in oxygen
minimum zones of the Pacific and Indian Oceans, Front. Earth Sci.,
8, 376, https://doi.org/10.3389/feart.2020.00376, 2020. a
Wrage, N., Velthof, G. L., Van Beusichem, M. L., and Oenema, O.: Role of
nitrifier denitrification in the production of nitrous oxide,
Soil Biol. Biochem., 33, 1723–1732, https://doi.org/10.1016/S0038-0717(01)00096-7, 2001. a, b
Wyrtki, K.: The oxygen minima in relation to ocean circulation, Deep-Sea
Res., 9, 11–23,
https://doi.org/10.1016/0011-7471(62)90243-7, 1962. a
Yang, S., Chang, B. X., Warner, M. J., Weber, T. S., Bourbonnais, A. M.,
Santoro, A. E., Kock, A., Sonnerup, R. E., Bullister, J. L., Wilson, S. T.,
and Bianchi, D.: Global reconstruction reduces the uncertainty of oceanic
nitrous oxide emissions and reveals a vigorous seasonal cycle, P. Natl. Acad. Sci. USA, 117, 11954–11960,
https://doi.org/10.1073/pnas.1921914117, 2020. a
Zakem, E. J., Polz, M. F., and Follows, M. J.: Redox-informed models of global
biogeochemical cycles, Nat. Commun., 11, 5680, https://doi.org/10.1038/s41467-020-19454-w, 2020. a
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.
We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical...
