Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-157-2023
© 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-16-157-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
04 Jan 2023
Development and technical paper |
| 04 Jan 2023
| 04 Jan 2023
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
Coastal and Regional Oceanography Lab, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia
Shane R. Keating
School of Mathematics and Statistics, UNSW Sydney, Sydney, NSW, Australia
Colette Kerry
Coastal and Regional Oceanography Lab, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia
Moninya Roughan
Coastal and Regional Oceanography Lab, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia
Related authors
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.
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.
David E. Gwyther, Colette Kerry, Moninya Roughan, and Shane R. Keating
Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022, https://doi.org/10.5194/gmd-15-6541-2022, 2022
Short summary
Short summary
The ocean current flowing along the southeastern coast of Australia is called the East Australian Current (EAC). Using computer simulations, we tested how surface and subsurface observations might improve models of the EAC. Subsurface observations are particularly important for improving simulations, and if made in the correct location and time, can have impact 600 km upstream. The stability of the current affects model estimates could be capitalized upon in future observing strategies.
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022, https://doi.org/10.5194/gmd-15-5421-2022, 2022
Short summary
Short summary
We use a coupled ice–ocean model to explore an oscillation feature found in several contributing models to MISOMIP1. The oscillation is closely related to the discretized grounding line retreat and likely strengthened by the buoyancy–melt feedback and/or melt–geometry feedback near the grounding line, and frequent ice–ocean coupling. Our model choices have a non-trivial impact on mean melt and ocean circulation strength, which might be interesting for the coupled ice–ocean community.
Ole Richter, David E. Gwyther, Matt A. King, and Benjamin K. Galton-Fenzi
The Cryosphere, 16, 1409–1429, https://doi.org/10.5194/tc-16-1409-2022, https://doi.org/10.5194/tc-16-1409-2022, 2022
Short summary
Short summary
Tidal currents may play an important role in Antarctic ice sheet retreat by changing the rate at which the ocean melts glaciers. Here, using a computational ocean model, we derive the first estimate of present-day tidal melting that covers all of Antarctica. Our results suggest that large-scale ocean models aiming to accurately predict ice melt rates will need to account for the effects of tides. The inclusion of tide-induced friction at the ice–ocean interface should be prioritized.
Ole Richter, David E. Gwyther, Benjamin K. Galton-Fenzi, and Kaitlin A. Naughten
Geosci. Model Dev., 15, 617–647, https://doi.org/10.5194/gmd-15-617-2022, https://doi.org/10.5194/gmd-15-617-2022, 2022
Short summary
Short summary
Here we present an improved model of the Antarctic continental shelf ocean and demonstrate that it is capable of reproducing present-day conditions. The improvements are fundamental and regard the inclusion of tides and ocean eddies. We conclude that the model is well suited to gain new insights into processes that are important for Antarctic ice sheet retreat and global ocean changes. Hence, the model will ultimately help to improve projections of sea level rise and climate change.
Chad A. Greene, Duncan A. Young, David E. Gwyther, Benjamin K. Galton-Fenzi, and Donald D. Blankenship
The Cryosphere, 12, 2869–2882, https://doi.org/10.5194/tc-12-2869-2018, https://doi.org/10.5194/tc-12-2869-2018, 2018
Short summary
Short summary
We show that Totten Ice Shelf accelerates each spring in response to the breakup of seasonal landfast sea ice at the ice shelf calving front. The previously unreported seasonal flow variability may have aliased measurements in at least one previous study of Totten's response to ocean forcing on interannual timescales. The role of sea ice in buttressing the flow of the ice shelf implies that long-term changes in sea ice cover could have impacts on the mass balance of the East Antarctic Ice Sheet.
D. E. Gwyther, B. K. Galton-Fenzi, J. R. Hunter, and J. L. Roberts
Ocean Sci., 10, 267–279, https://doi.org/10.5194/os-10-267-2014, https://doi.org/10.5194/os-10-267-2014, 2014
Manh Cuong Tran, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-480, https://doi.org/10.5194/essd-2024-480, 2024
Preprint under review for ESSD
Short summary
Short summary
The East Australian Current (EAC) plays an important role in the marine ecosystem and climate of the region. To understand the EAC regime and the inner shelf dynamics, we implement the variational approach to produce the first multi-year coastal radar dataset (2012–2023) in this region. The validated data allows for a comprehensive investigation of the EAC dynamics. This dataset will be useful for understanding the complex EAC regime and its far-reaching impacts on the shelf environment.
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.
Michael Hemming, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 16, 887–901, https://doi.org/10.5194/essd-16-887-2024, https://doi.org/10.5194/essd-16-887-2024, 2024
Short summary
Short summary
We present new datasets that are useful for exploring extreme ocean temperature events in Australian coastal waters. These datasets span multiple decades, starting from the 1940s and 1950s, and include observations from the surface to the bottom at four coastal sites. The datasets provide valuable insights into the intensity, frequency and timing of extreme warm and cold temperature events and include event characteristics such as duration, onset and decline rates and their categorisation.
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.
Michael P. Hemming, Moninya Roughan, Neil Malan, and Amandine Schaeffer
Ocean Sci., 19, 1145–1162, https://doi.org/10.5194/os-19-1145-2023, https://doi.org/10.5194/os-19-1145-2023, 2023
Short summary
Short summary
We estimate subsurface linear and non-linear temperature trends at five coastal sites adjacent to the East Australian Current (EAC). We see accelerating trends at both 34.1 and 42.6 °S and place our results in the context of previously reported trends, highlighting that magnitudes are depth-dependent and vary across latitude. Our results indicate the important role of regional dynamics and show the necessity of subsurface data for the improved understanding of regional climate change impacts.
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
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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.
David E. Gwyther, Colette Kerry, Moninya Roughan, and Shane R. Keating
Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022, https://doi.org/10.5194/gmd-15-6541-2022, 2022
Short summary
Short summary
The ocean current flowing along the southeastern coast of Australia is called the East Australian Current (EAC). Using computer simulations, we tested how surface and subsurface observations might improve models of the EAC. Subsurface observations are particularly important for improving simulations, and if made in the correct location and time, can have impact 600 km upstream. The stability of the current affects model estimates could be capitalized upon in future observing strategies.
Chen Zhao, Rupert Gladstone, Benjamin Keith Galton-Fenzi, David Gwyther, and Tore Hattermann
Geosci. Model Dev., 15, 5421–5439, https://doi.org/10.5194/gmd-15-5421-2022, https://doi.org/10.5194/gmd-15-5421-2022, 2022
Short summary
Short summary
We use a coupled ice–ocean model to explore an oscillation feature found in several contributing models to MISOMIP1. The oscillation is closely related to the discretized grounding line retreat and likely strengthened by the buoyancy–melt feedback and/or melt–geometry feedback near the grounding line, and frequent ice–ocean coupling. Our model choices have a non-trivial impact on mean melt and ocean circulation strength, which might be interesting for the coupled ice–ocean community.
Ole Richter, David E. Gwyther, Matt A. King, and Benjamin K. Galton-Fenzi
The Cryosphere, 16, 1409–1429, https://doi.org/10.5194/tc-16-1409-2022, https://doi.org/10.5194/tc-16-1409-2022, 2022
Short summary
Short summary
Tidal currents may play an important role in Antarctic ice sheet retreat by changing the rate at which the ocean melts glaciers. Here, using a computational ocean model, we derive the first estimate of present-day tidal melting that covers all of Antarctica. Our results suggest that large-scale ocean models aiming to accurately predict ice melt rates will need to account for the effects of tides. The inclusion of tide-induced friction at the ice–ocean interface should be prioritized.
Ole Richter, David E. Gwyther, Benjamin K. Galton-Fenzi, and Kaitlin A. Naughten
Geosci. Model Dev., 15, 617–647, https://doi.org/10.5194/gmd-15-617-2022, https://doi.org/10.5194/gmd-15-617-2022, 2022
Short summary
Short summary
Here we present an improved model of the Antarctic continental shelf ocean and demonstrate that it is capable of reproducing present-day conditions. The improvements are fundamental and regard the inclusion of tides and ocean eddies. We conclude that the model is well suited to gain new insights into processes that are important for Antarctic ice sheet retreat and global ocean changes. Hence, the model will ultimately help to improve projections of sea level rise and climate change.
Carlos Rocha, Christopher A. Edwards, Moninya Roughan, Paulina Cetina-Heredia, and Colette Kerry
Geosci. Model Dev., 12, 441–456, https://doi.org/10.5194/gmd-12-441-2019, https://doi.org/10.5194/gmd-12-441-2019, 2019
Short summary
Short summary
Off southeast Australia, the East Australian Current (EAC) moves warm nutrient-poor waters towards the pole. In this region, the EAC and a large number of vortices pinching off it strongly affect phytoplankton’s access to nutrients and light. To study these dynamics, we created a numerical model that is able to solve the ocean conditions and how they modulate the foundation of the region’s ecosystem. We validated model results against available data and this showed that the model performs well.
Chad A. Greene, Duncan A. Young, David E. Gwyther, Benjamin K. Galton-Fenzi, and Donald D. Blankenship
The Cryosphere, 12, 2869–2882, https://doi.org/10.5194/tc-12-2869-2018, https://doi.org/10.5194/tc-12-2869-2018, 2018
Short summary
Short summary
We show that Totten Ice Shelf accelerates each spring in response to the breakup of seasonal landfast sea ice at the ice shelf calving front. The previously unreported seasonal flow variability may have aliased measurements in at least one previous study of Totten's response to ocean forcing on interannual timescales. The role of sea ice in buttressing the flow of the ice shelf implies that long-term changes in sea ice cover could have impacts on the mass balance of the East Antarctic Ice Sheet.
Colette Kerry, Brian Powell, Moninya Roughan, and Peter Oke
Geosci. Model Dev., 9, 3779–3801, https://doi.org/10.5194/gmd-9-3779-2016, https://doi.org/10.5194/gmd-9-3779-2016, 2016
Short summary
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Ocean circulation drives weather and climate and supports marine ecosystems, so providing accurate predictions is important. The ocean circulation is complex, 3-D and highly variable, and its prediction requires advanced numerical models combined with real-time measurements. Focusing on the dynamic East Austr. Current, we use novel mathematical techniques to combine an ocean model with measurements to better estimate the circulation. This is an important step towards improving ocean forecasts.
Peter R. Oke, Roger Proctor, Uwe Rosebrock, Richard Brinkman, Madeleine L. Cahill, Ian Coghlan, Prasanth Divakaran, Justin Freeman, Charitha Pattiaratchi, Moninya Roughan, Paul A. Sandery, Amandine Schaeffer, and Sarath Wijeratne
Geosci. Model Dev., 9, 3297–3307, https://doi.org/10.5194/gmd-9-3297-2016, https://doi.org/10.5194/gmd-9-3297-2016, 2016
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The Marine Virtual Laboratory (MARVL) is designed to help ocean modellers hit the ground running. Usually, setting up an ocean model involves a handful of technical steps that time and effort. MARVL provides a user-friendly interface that allows users to choose what options they want for their model, including the region, time period, and input data sets. The user then hits "go", and MARVL does the rest – delivering a "take-away bundle" that contains all the files needed to run the model.
Amandine Schaeffer, Moninya Roughan, Emlyn M. Jones, and Dana White
Biogeosciences, 13, 1967–1975, https://doi.org/10.5194/bg-13-1967-2016, https://doi.org/10.5194/bg-13-1967-2016, 2016
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The water properties of the coastal ocean such as temperature, salt, oxygen, or chlorophyll content vary spatially, and estimates need to be made regarding the scales of variability. Here, we use statistical techniques to determine the spatial variability of ocean properties from high-resolution measurements by gliders. We show that biological activity is patchy compared to the distribution of physical characteristics, and that the size and shape of this is determined by coastal ocean processes.
Paulina Cetina-Heredia, Erik van Sebille, Richard Matear, and Moninya Roughan
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-53, https://doi.org/10.5194/bg-2016-53, 2016
Revised manuscript not accepted
Short summary
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Characterizing phytoplankton growth influences fisheries and climate. We use a lagrangian approach to identify phytoplankton blooms in the Great Australian Bight (GAB), and associate them with nitrate sources. We find that 88 % of the nitrate utilized in blooms is originated between the GAB and the SubAntarctic Front. Large nitrate concentrations are supplied at depth but do not reach the euphotic zone often. As a result, 55 % of blooms utilize nitrate supplied in the top 100 m.
D. E. Gwyther, B. K. Galton-Fenzi, J. R. Hunter, and J. L. Roberts
Ocean Sci., 10, 267–279, https://doi.org/10.5194/os-10-267-2014, https://doi.org/10.5194/os-10-267-2014, 2014
A. M. Waite, V. Rossi, M. Roughan, B. Tilbrook, P. A. Thompson, M. Feng, A. S. J. Wyatt, and E. J. Raes
Biogeosciences, 10, 5691–5702, https://doi.org/10.5194/bg-10-5691-2013, https://doi.org/10.5194/bg-10-5691-2013, 2013
Related subject area
Oceanography
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
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
DALROMS-NWA12 v1.0, a coupled circulation-ice-biogeochemistry modelling system for the northwest Atlantic Ocean: Development and validation
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
A revised ocean mixed layer model for better simulating the diurnal variation of ocean skin temperature
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)
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
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
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Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
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
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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
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We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
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
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Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
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
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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
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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
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Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
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Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
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The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
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The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
EGUsphere, https://doi.org/10.5194/egusphere-2024-1372, https://doi.org/10.5194/egusphere-2024-1372, 2024
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We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the oceans’ capture of atmospheric carbon dioxide which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
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Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
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This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
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We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
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Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
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Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
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The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
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In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
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Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
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Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
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The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
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A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
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We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
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Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-23, https://doi.org/10.5194/gmd-2024-23, 2024
Revised manuscript accepted for GMD
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The recently available ERA5 hourly ocean skin temperature (Tint) data is expected to be valuable for various science studies. However, when analyzing the hourly variations of Tint, questions arise about its reliability, the deficiency of which may be related to errors in the ocean mixed layer (OML) model. To address this, we reexamined and corrected significant errors in the OML model. Validation of the simulated SST using the revised OML model against observations demonstrated good agreement.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
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This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
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
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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
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We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
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We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
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While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
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Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
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Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
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This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
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The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
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While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Jan David Zika and Sohail Taimoor
EGUsphere, https://doi.org/10.5194/egusphere-2023-1220, https://doi.org/10.5194/egusphere-2023-1220, 2023
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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
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We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
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Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
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Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
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We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
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In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
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Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
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An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
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Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
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
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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
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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.
Cited articles
Abernathey, R. and Haller, G.: Transport by Lagrangian Vortices in the Eastern
Pacific, J. Phys. Oceanogr., 48, 667–685,
https://doi.org/10.1175/jpo-d-17-0102.1, 2018. a
Ballabrera-Poy, J., Hackert, E., Murtugudde, R., and Busalacchi, A. J.: An
Observing System Simulation Experiment for an Optimal Moored Instrument Array
in the Tropical Indian Ocean, J. Climate, 20, 3284–3299,
https://doi.org/10.1175/jcli4149.1, 2007. a
Bannister, R. N.: A review of forecast error covariance statistics in
atmospheric variational data assimilation. I: Characteristics and
measurements of forecast error covariances, Q. J. Roy.
Meteor. Soc., 134, 1951–1970, https://doi.org/10.1002/qj.339,
2008a. a, b
Bannister, R. N.: A review of forecast error covariance statistics in
atmospheric variational data assimilation. II: Modelling the forecast error
covariance statistics, Q. J. Roy. Meteor. Soc.,
134, 1971–1996, https://doi.org/10.1002/qj.340, 2008b. a
Bonavita, M., Raynaud, L., and Isaksen, L.: Estimating background-error
variances with the ECMWF Ensemble of Data Assimilations system: some
effects of ensemble size and day-to-day variability, Q. J.
Roy. Meteor. Soc., 137, 423–434, https://doi.org/10.1002/qj.756, 2011. a, b
Brassington, G., Pugh, T., Spillman, C., Schulz, E., Beggs, H., Schiller, A.,
and Oke, P.: BLUElink> Development of Operational Oceanography and Servicing
in Australia, J. Res. Pract. Inf. Tech., 39, 151–164,
2007. a
Brink, K.: Cross-Shelf Exchange, Annu. Rev. Mar. Sci., 8, 59–78,
https://doi.org/10.1146/annurev-marine-010814-015717, 2016. a
Chamberlain, M. A., Oke, P. R., Fiedler, R. A. S., Beggs, H. M., Brassington, G. B., and Divakaran, P.: Next generation of Bluelink ocean reanalysis with multiscale data assimilation: BRAN2020, Earth Syst. Sci. Data, 13, 5663–5688, https://doi.org/10.5194/essd-13-5663-2021, 2021. a
Chelton, D. B., Schlax, M. G., and Samelson, R. M.: Global observations of
nonlinear mesoscale eddies, Progr. Oceanogr., 91, 167–216,
https://doi.org/10.1016/j.pocean.2011.01.002, 2011. a
Copernicus Marine Service (CMEMS): Global ocean along-track L3 sea surface heights reprocessed (1993–ongoing) tailored for data assimilation (SEALEVEL_GLO_PHY_L3_MY_008_062), https://doi.org/10.48670/moi-00146,
2022. a
Denes, M. C., Froyland, G., and Keating, S. R.: Persistence and material
coherence of a mesoscale ocean eddy, Phys. Rev. Fl., 7, 034501,
https://doi.org/10.1103/physrevfluids.7.034501, 2022. a
de Paula, T. P., Lima, J. A. M., Tanajura, C. A. S., Andrioni, M., Martins,
R. P., and Arruda, W. Z.: The impact of ocean data assimilation on the
simulation of mesoscale eddies at São Paulo plateau (Brazil) using the
regional ocean modeling system, Ocean Model., 167, 101889,
https://doi.org/10.1016/j.ocemod.2021.101889, 2021. a
Dong, C., McWilliams, J. C., Liu, Y., and Chen, D.: Global heat and salt
transports by eddy movement, Nat. Commun., 5, 3294,
https://doi.org/10.1038/ncomms4294, 2014. a
Elzahaby, Y., Schaeffer, A., Roughan, M., and Delaux, S.: Oceanic Circulation
Drives the Deepest and Longest Marine Heatwaves in the East Australian
Current System, Geophys. Res. Lett., 48, e2021GL094785,
https://doi.org/10.1029/2021gl094785, 2021. a
Fairall, C. W., Bradley, E. F., Rogers, D. P., Edson, J. B., and Young, G. S.:
Bulk parameterization of air-sea fluxes for Tropical Ocean-Global Atmosphere
Coupled-Ocean Atmosphere Response Experiment, J. Geophys.
Res.-Oceans, 101, 3747–3764, https://doi.org/10.1029/95jc03205, 1996. a
Fiedler, P. C.: Comparison of objective descriptions of the thermocline,
Limnol. Oceanogr.-Meth., 8, 313–325,
https://doi.org/10.4319/lom.2010.8.313, 2010. a, b, c
Gasparin, F., Guinehut, S., Mao, C., Mirouze, I., Rémy, E., King, R. R.,
Hamon, M., Reid, R., Storto, A., Traon, P.-Y. L., Martin, M. J., and Masina,
S.: Requirements for an Integrated in situ Atlantic Ocean Observing System
From Coordinated Observing System Simulation Experiments, Front.
Mar. Sci., 6, https://doi.org/10.3389/fmars.2019.00083, 2019. a
Gill, A., Green, J., and Simmons, A.: Energy partition in the large-scale ocean
circulation and the production of mid-ocean eddies, Deep-Sea Res., 21, 499–528, https://doi.org/10.1016/0011-7471(74)90010-2,
1974. a
Gwyther, D. E., Kerry, C., Roughan, M., and Keating, S. R.: Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current, Geosci. Model Dev., 15, 6541–6565, https://doi.org/10.5194/gmd-15-6541-2022, 2022a. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o
Gwyther, D. E., Kerry, C., Roughan, M., and Keating, S.: A high-resolution, 1-year, suite of 4D-Var Observing System Simulation Experiments of the East Australian Current System using the Regional Ocean Modeling System (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.6804480, 2022b. a
Gwyther, D. E., Kerry, C., Roughan, M., and Keating, S.: A high-resolution, 1-year, suite of 4D-Var Observing System Simulation Experiments of the East Australian Current System using the Regional Ocean Modeling System, UNSW Sydney [data set], https://doi.org/10.26190/unsworks/24146, 2022c. a
Halliwell, G. R., Srinivasan, A., Kourafalou, V., Yang, H., Willey, D.,
Hénaff, M. L., and Atlas, R.: Rigorous Evaluation of a Fraternal Twin
Ocean OSSE System for the Open Gulf of Mexico, J. Atmos.
Ocean. Tech., 31, 105–130, https://doi.org/10.1175/jtech-d-13-00011.1, 2014. a, b
Halliwell, G. R., Kourafalou, V., Hénaff, M. L., Shay, L. K., and Atlas,
R.: OSSE impact analysis of airborne ocean surveys for improving
upper-ocean dynamical and thermodynamical forecasts in the Gulf of Mexico,
Prog. Oceanogr., 130, 32–46, https://doi.org/10.1016/j.pocean.2014.09.004,
2015. a
Halliwell, G. R., Mehari, M. F., Hénaff, M. L., Kourafalou, V. H.,
Androulidakis, I. S., Kang, H. S., and Atlas, R.: North Atlantic Ocean
OSSE system: Evaluation of operational ocean observing system components
and supplemental seasonal observations for potentially improving tropical
cyclone prediction in coupled systems, J. Oper. Oceanogr.,
10, 154–175, https://doi.org/10.1080/1755876x.2017.1322770, 2017. a
Kang, D. and Curchitser, E. N.: Energetics of Eddy–Mean Flow
Interactions in the Gulf Stream Region, J. Phys. Oceanogr., 45,
1103–1120, https://doi.org/10.1175/jpo-d-14-0200.1, 2015. a
Keating, S.: shane-keating/normal-modes: Initial release (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.6999169, 2022. a
Kelly, S. M.: The Vertical Mode Decomposition of Surface and Internal Tides in
the Presence of a Free Surface and Arbitrary Topography, J. Phys.
Oceanogr., 46, 3777–3788, https://doi.org/10.1175/jpo-d-16-0131.1, 2016. a
Kerry, C. and Roughan, M.: Downstream Evolution of the East Australian Current
System: Mean Flow, Seasonal, and Intra-annual Variability, J.
Geophys. Res.-Oceans, 125, e2019JC015227, https://doi.org/10.1029/2019jc015227, 2020. a, b
Kerry, C., Powell, B., Roughan, M., and Oke, P.: Development and evaluation of a high-resolution reanalysis of the East Australian Current region using the Regional Ocean Modelling System (ROMS 3.4) and Incremental Strong-Constraint 4-Dimensional Variational (IS4D-Var) data assimilation, Geosci. Model Dev., 9, 3779–3801, https://doi.org/10.5194/gmd-9-3779-2016, 2016. a, b, c, d, e, f, g, h, i
Kerry, C., Roughan, M., Powell, B., and Oke, P: A high-resolution reanalysis of the East Australian Current System assimilating an unprecedented observational data set using 4D-Var data assimilation over a two-year period (2012–2013), Version 2017, UNSW Sydney [code and data set], https://doi.org/10.26190/5ebe1f389dd87, 2020. a
Kerry, C., Roughan, M., and Powell, B.: Observation Impact in a Regional
Reanalysis of the East Australian Current System, J. Geophys.
Res.-Oceans, 123, 7511–7528, https://doi.org/10.1029/2017jc013685, 2018. a, b
Klocker, A. and Abernathey, R.: Global Patterns of Mesoscale Eddy Properties
and Diffusivities, J. Phys. Oceanogr., 44, 1030–1046,
https://doi.org/10.1175/jpo-d-13-0159.1, 2014. a
Lee, J. C. K. and Huang, X.-Y.: Background error statistics in the Tropics:
Structures and impact in a convective-scale numerical weather prediction
system, Q. J. Roy. Meteor. Soc., 146,
2154–2173, https://doi.org/10.1002/qj.3785, 2020. a, b
Li, B., de Queiroz, A. R., DeCarolis, J. F., Bane, J., He, R., Keeler, A. G.,
and Neary, V. S.: The economics of electricity generation from Gulf Stream
currents, Energy, 134, 649–658, https://doi.org/10.1016/j.energy.2017.06.048, 2017. a
Li, J., Kerry, C., and Roughan, M.: A high-resolution, 22-year, free-running, hydrodynamic simulation of the East Australia Current System using the Regional Ocean Modeling System (Version 2.0), UNSW Sydney [code and data set], https://doi.org/10.26190/TT1Q-NP46, 2021. a
Li, J., Roughan, M., and Kerry, C.: Variability and Drivers of Ocean
Temperature Extremes in a Warming Western Boundary Current, J.
Climate, 35, 1097–1111, https://doi.org/10.1175/JCLI-D-21-0622.1,
2022a. a, b
Li, J., Roughan, M., Kerry, C., and Rao, S.: Impact of Mesoscale Circulation on
the Structure of River Plumes During Large Rainfall Events Inshore of the
East Australian Current, Front. Mar. Sci., 9,
https://doi.org/10.3389/fmars.2022.815348, 2022b. a
Li, Z., McWilliams, J. C., Ide, K., and Farrara, J. D.: A Multiscale
Variational Data Assimilation Scheme: Formulation and Illustration, Mon.
Weather Rev., 143, 3804–3822, https://doi.org/10.1175/mwr-d-14-00384.1, 2015. a, b
Lorenc, A. C. and Jardak, M.: A comparison of hybrid variational data
assimilation methods for global NWP, Q. J. Roy.
Meteor. Soc., 144, 2748–2760, https://doi.org/10.1002/qj.3401, 2018. a
Malan, N., Archer, M., Roughan, M., Cetina-Heredia, P., Hemming, M., Rocha, C.,
Schaeffer, A., Suthers, I., and Queiroz, E.: Eddy-Driven Cross-Shelf
Transport in the East Australian Current Separation Zone, J.
Geophys. Res.-Oceans, 125, e2019JC015613, https://doi.org/10.1029/2019jc015613, 2020. a
Mata, M. M., Wijffels, S. E., Church, J. A., and Tomczak, M.: Eddy shedding
and energy conversions in the East Australian Current, J.
Geophys. Res., 111, C09034, https://doi.org/10.1029/2006jc003592, 2006. a
McGillicuddy, D. J., Robinson, A. R., Siegel, D. A., Jannasch, H. W., Johnson,
R., Dickey, T. D., McNeil, J., Michaels, A. F., and Knap, A. H.: Influence of
mesoscale eddies on new production in the Sargasso Sea, Nature, 394,
263–266, https://doi.org/10.1038/28367, 1998. a
Melet, A., Verron, J., and Brankart, J.-M.: Potential outcomes of glider data
assimilation in the Solomon Sea: Control of the water mass properties and
parameter estimation, J. Marine Syst., 94, 232–246,
https://doi.org/10.1016/j.jmarsys.2011.12.003, 2012. a
Michel, Y. and Auligné, T.: Inhomogeneous Background Error Modeling and
Estimation over Antarctica, Mon. Weather Rev., 138, 2229–2252,
https://doi.org/10.1175/2009mwr3139.1, 2010. a
Moore, A. M., Arango, H. G., Broquet, G., Powell, B. S., Weaver, A. T., and
Zavala-Garay, J.: The Regional Ocean Modeling System (ROMS) 4-dimensional
variational data assimilation systems: Part I – System overview and
formulation, Prog. Oceanogr., 91, 34–49,
https://doi.org/10.1016/j.pocean.2011.05.004, 2011. a
Moore, A. M., Martin, M. J., Akella, S., Arango, H. G., Balmaseda, M., Bertino,
L., Ciavatta, S., Cornuelle, B., Cummings, J., Frolov, S., Lermusiaux, P.,
Oddo, P., Oke, P. R., Storto, A., Teruzzi, A., Vidard, A., and Weaver, A. T.:
Synthesis of Ocean Observations Using Data Assimilation for Operational,
Real-Time and Reanalysis Systems: A More Complete Picture of the State of the
Ocean, Front. Mar. Sci., 6, https://doi.org/10.3389/fmars.2019.00090, 2019. a
Oke, P. R. and Griffin, D. A.: The cold-core eddy and strong upwelling off the
coast of New South Wales in early 2007, Deep-Sea Res. Pt. II, 58, 574–591, https://doi.org/10.1016/j.dsr2.2010.06.006,
2011. a
Oke, P. R. and Schiller, A.: A Model-Based Assessment and Design of a Tropical
Indian Ocean Mooring Array, J. Climate, 20, 3269–3283,
https://doi.org/10.1175/jcli4170.1, 2007. a
Oke, P. R., Brassington, G. B., Griffin, D. A., and Schiller, A.: The Bluelink
ocean data assimilation system (BODAS), Ocean Model., 21, 46–70,
https://doi.org/10.1016/j.ocemod.2007.11.002, 2008. a
Penny, S. G., Behringer, D. W., Carton, J. A., and Kalnay, E.: A Hybrid Global
Ocean Data Assimilation System at NCEP, Mon. Weather Rev., 143,
4660–4677, https://doi.org/10.1175/mwr-d-14-00376.1, 2015. a
Pilo, G. S., Oke, P. R., Coleman, R., Rykova, T., and Ridgway, K.: Impact of
data assimilation on vertical velocities in an eddy resolving ocean model,
Ocean Model., 131, 71–85, https://doi.org/10.1016/j.ocemod.2018.09.003, 2018. a
Puri, K., Dietachmayer, G., Steinle, P., Dix, M., Rikus, L., Logan, L.,
Naughton, M., Tingwell, C., Xiao, Y., Barras, V., Bermous, I., Bowen, R., Deschamps, L., Franklin, C., Fraser, J., Glowacki, T., Harris, B., Lee, J., Le, T., Roff, G., Sulaiman, A., Sims, H., Sun, X., Sun, Z., Zhu, H., Chattopadhyay, M., and Engel, C.: Implementation of
the initial ACCESS numerical weather prediction system, Austr.
Meteorol. Ocean. J., 63, 265–284, 2013. a
Research Technology Services, UNSW Sydney:
Katana computational cluster, https://doi.org/10.26190/669x-a286, 2022. a
Rocha, C., Edwards, C. A., Roughan, M., Cetina-Heredia, P., and Kerry, C.: A high-resolution biogeochemical model (ROMS 3.4 + bio_Fennel) of the East Australian Current system, Geosci. Model Dev., 12, 441–456, https://doi.org/10.5194/gmd-12-441-2019, 2019. a
Roughan, M., Keating, S. R., Schaeffer, A., Heredia, P. C., Rocha, C., Griffin,
D., Robertson, R., and Suthers, I. M.: A tale of two eddies: The biophysical
characteristics of two contrasting cyclonic eddies in the East Australian
Current System, J. Geophys. Res.-Oceans, 122, 2494–2518,
https://doi.org/10.1002/2016jc012241, 2017. a
Schiller, A., Wijffels, S. E., and Meyers, G. A.: Design Requirements for an
Argo Float Array in the Indian Ocean Inferred from Observing System
Simulation Experiments, J. Atmos. Ocean. Tech., 21,
1598–1620, https://doi.org/10.1175/1520-0426(2004)021<1598:drfaaf>2.0.co;2, 2004. a
Shchepetkin, A. F. and McWilliams, J. C.: The regional oceanic modeling system
(ROMS): a split-explicit, free-surface, topography-following-coordinate
oceanic model, Ocean Model., 9, 347–404,
https://doi.org/10.1016/j.ocemod.2004.08.002, 2005. a
Siripatana, A., Kerry, C., Roughan, M., Souza, J. M. A. C., and Keating, S.:
Assessing the Impact of Nontraditional Ocean Observations for Prediction of
the East Australian Current, J. Geophys. Res.-Oceans, 125, e2020JC016580,
https://doi.org/10.1029/2020jc016580, 2020. a, b, c, d
Smith, K. S.: The geography of linear baroclinic instability in
Earth′s oceans, J. Mar. Res., 65, 655–683,
https://doi.org/10.1357/002224007783649484, 2007. a, b
Smith, K. S. and Vallis, G. K.: The Scales and Equilibration of Midocean
Eddies: Freely Evolving Flow, J. Phys. Oceanogr., 31, 554–571,
https://doi.org/10.1175/1520-0485(2001)031<0554:tsaeom>2.0.co;2, 2001. a
Su, C.-H., Eizenberg, N., Steinle, P., Jakob, D., Fox-Hughes, P., White, C. J., Rennie, S., Franklin, C., Dharssi, I., and Zhu, H.: BARRA v1.0: the Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia, Geosci. Model Dev., 12, 2049–2068, https://doi.org/10.5194/gmd-12-2049-2019, 2019. a
Wang, Y., Beron-Vera, F. J., and Olascoaga, M. J.: The life cycle of a coherent
Lagrangian Agulhas ring, J. Geophys. Res.-Oceans, 121,
3944–3954, https://doi.org/10.1002/2015jc011620, 2016. a
Weaver, A. and Courtier, P.: Correlation modelling on the sphere using a
generalized diffusion equation, Q. J. Roy. Meteor.
Soc., 127, 1815–1846, https://doi.org/10.1002/qj.49712757518, 2001. a, b
Whiteway, T.: Australian bathymetry and topography grid, June 2009, Record 2009/021, Geoscience Australia [data set], Canberra,
https://doi.org/10.4225/25/53D99B6581B9A, 2009. a
Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S.,
Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J.,
Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval,
T., Maze, G., Cabanes, C., André, X., Poffa, N., Yashayaev, I., Barker,
P. M., Guinehut, S., Belbéoch, M., Ignaszewski, M., Baringer, M. O.,
Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N.,
Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P.,
West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouët, R.,
Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N.,
Bernard, V., Bourlès, B., Claustre, H., D'Ortenzio,
F., Reste, S. L., Traon, P.-Y. L., Rannou, J.-P., Saout-Grit, C., Speich, S.,
Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano,
G., Poulain, P.-M., Vélez-Belchí, P., Suga, T., Ando, K.,
Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T.,
Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R.,
van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King,
B. A., Loch, S. G., Mowat, M., Turton, J., Rao, E. P. R., Ravichandran, M.,
Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M.,
Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S.-D.,
and Park, H.-M.: Argo Data 1999–2019: Two Million
Temperature-Salinity Profiles and Subsurface Velocity Observations From a
Global Array of Profiling Floats, Front. Mar. Sci., 7,
https://doi.org/10.3389/fmars.2020.00700, 2020. a
Wunsch, C.: The Vertical Partition of Oceanic Horizontal Kinetic Energy,
J. Phys. Oceanogr., 27, 1770–1794,
https://doi.org/10.1175/1520-0485(1997)027<1770:tvpooh>2.0.co;2, 1997. a
Zavala-Garay, J., Wilkin, J. L., and Arango, H. G.: Predictability of
Mesoscale Variability in the East Australian Current Given Strong-Constraint
Data Assimilation, J. Phys. Oceanogr., 42, 1402–1420,
https://doi.org/10.1175/jpo-d-11-0168.1, 2012. a, b
Zhang, W. G., Wilkin, J. L., and Arango, H. G.: Towards an integrated
observation and modeling system in the New York Bight using variational
methods. Part I: 4DVAR data assimilation, Ocean Model., 35, 119–133,
https://doi.org/10.1016/j.ocemod.2010.08.003, 2010.
a, b
Zhang, Z., Wang, W., and Qiu, B.: Oceanic mass transport by mesoscale eddies,
Science, 345, 322–324, https://doi.org/10.1126/science.1252418, 2014. a
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.
Ocean eddies are important for weather, climate, biology, navigation, and search and rescue....
