Articles | Volume 13, issue 9
https://doi.org/10.5194/gmd-13-4503-2020
© Author(s) 2020. 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-13-4503-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
25 Sep 2020
Model description paper |
| 25 Sep 2020
| 25 Sep 2020
CSIRO Environmental Modelling Suite (EMS): scientific description of the optical and biogeochemical models (vB3p0)
CSIRO, Oceans and Atmosphere, Hobart, Australia
Karen A. Wild-Allen
CSIRO, Oceans and Atmosphere, Hobart, Australia
John Parslow
CSIRO, Oceans and Atmosphere, Hobart, Australia
Mathieu Mongin
CSIRO, Oceans and Atmosphere, Hobart, Australia
Barbara Robson
Australian Institute of Marine Science, Townsville, Australia
Jennifer Skerratt
CSIRO, Oceans and Atmosphere, Hobart, Australia
Farhan Rizwi
CSIRO, Oceans and Atmosphere, Hobart, Australia
Monika Soja-Woźniak
CSIRO, Oceans and Atmosphere, Hobart, Australia
Emlyn Jones
CSIRO, Oceans and Atmosphere, Hobart, Australia
Mike Herzfeld
CSIRO, Oceans and Atmosphere, Hobart, Australia
Nugzar Margvelashvili
CSIRO, Oceans and Atmosphere, Hobart, Australia
John Andrewartha
CSIRO, Oceans and Atmosphere, Hobart, Australia
Clothilde Langlais
CSIRO, Oceans and Atmosphere, Hobart, Australia
Matthew P. Adams
School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
Nagur Cherukuru
CSIRO, Oceans and Atmosphere, Canberra, Australia
Malin Gustafsson
Plant Functional Biology and Climate Change Cluster, Faculty of Science, University of Technology Sydney, Sydney, Australia
Scott Hadley
CSIRO, Oceans and Atmosphere, Hobart, Australia
Peter J. Ralph
Plant Functional Biology and Climate Change Cluster, Faculty of Science, University of Technology Sydney, Sydney, Australia
Uwe Rosebrock
CSIRO, Oceans and Atmosphere, Hobart, Australia
Thomas Schroeder
CSIRO, Oceans and Atmosphere, Hobart, Australia
Leonardo Laiolo
CSIRO, Oceans and Atmosphere, Hobart, Australia
Daniel Harrison
Southern Cross University, Coffs Harbour, Australia
Andrew D. L. Steven
CSIRO, Oceans and Atmosphere, Hobart, Australia
Related authors
Jodie Anne Schlaefer, Clothilde Langlais, Severine Marie Choukroun, Mathieu Mongin, and Mark E. Baird
EGUsphere, https://doi.org/10.22541/essoar.173282297.70109457/v1, https://doi.org/10.22541/essoar.173282297.70109457/v1, 2025
Short summary
Short summary
We studied how the Coral Sea and South Equatorial Current may change with climate change using high resolution models. At 1.5 °C and 2 °C global warming, the Coral Sea surface was projected to warm by 0.78 °C and 1.12 °C, respectfully. Temperature increases were simulated down to 400 m. The extra heat could further stress ecosystems. Two of the South Equatorial Current jets were projected to decrease in strength and one increased, which could affect the circulation features they feed.
Emlyn M. Jones, Mark E. Baird, Mathieu Mongin, John Parslow, Jenny Skerratt, Jenny Lovell, Nugzar Margvelashvili, Richard J. Matear, Karen Wild-Allen, Barbara Robson, Farhan Rizwi, Peter Oke, Edward King, Thomas Schroeder, Andy Steven, and John Taylor
Biogeosciences, 13, 6441–6469, https://doi.org/10.5194/bg-13-6441-2016, https://doi.org/10.5194/bg-13-6441-2016, 2016
Short summary
Short summary
Marine biogeochemical models are often used to understand water quality, nutrient and blue-carbon dynamics at scales that range from estuaries and bays, through to the global ocean. We introduce a new methodology allowing for the assimilation of observed remote sensing reflectances, avoiding the need to use empirically derived chlorophyll-a concentrations. This method opens up the possibility to assimilate of reflectances from a variety of missions and potentially non-satellite platforms.
Jodie Anne Schlaefer, Clothilde Langlais, Severine Marie Choukroun, Mathieu Mongin, and Mark E. Baird
EGUsphere, https://doi.org/10.22541/essoar.173282297.70109457/v1, https://doi.org/10.22541/essoar.173282297.70109457/v1, 2025
Short summary
Short summary
We studied how the Coral Sea and South Equatorial Current may change with climate change using high resolution models. At 1.5 °C and 2 °C global warming, the Coral Sea surface was projected to warm by 0.78 °C and 1.12 °C, respectfully. Temperature increases were simulated down to 400 m. The extra heat could further stress ecosystems. Two of the South Equatorial Current jets were projected to decrease in strength and one increased, which could affect the circulation features they feed.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Thomas Jackson, Andrei Chuprin, Malcolm Taberner, Ruth Airs, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Robert J. W. Brewin, Elisabetta Canuti, Francisco P. Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Afonso Ferreira, Scott Freeman, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Ralf Goericke, Richard Gould, Nathalie Guillocheau, Stanford B. Hooker, Chuamin Hu, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Steven Lohrenz, Hubert Loisel, Antonio Mannino, Victor Martinez-Vicente, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Enrique Montes, Frank Muller-Karger, Aimee Neeley, Michael Novak, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Rüdiger Röttgers, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Crystal Thomas, Rob Thomas, Gavin Tilstone, Andreia Tracana, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Bozena Wojtasiewicz, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 14, 5737–5770, https://doi.org/10.5194/essd-14-5737-2022, https://doi.org/10.5194/essd-14-5737-2022, 2022
Short summary
Short summary
A compiled set of in situ data is vital to evaluate the quality of ocean-colour satellite data records. Here we describe the global compilation of bio-optical in situ data (spanning from 1997 to 2021) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Jenny Choo, Nagur Cherukuru, Eric Lehmann, Matt Paget, Aazani Mujahid, Patrick Martin, and Moritz Müller
Biogeosciences, 19, 5837–5857, https://doi.org/10.5194/bg-19-5837-2022, https://doi.org/10.5194/bg-19-5837-2022, 2022
Short summary
Short summary
This study presents the first observation of water quality changes over space and time in the coastal systems of Sarawak, Malaysian Borneo, using remote sensing technologies. While our findings demonstrate that the southwestern coast of Sarawak is within local water quality standards, historical patterns of water quality degradation that were detected can help to alert local authorities and enhance management and monitoring strategies of coastal waters in this region.
David A. Griffin, Mike Herzfeld, Mark Hemer, and Darren Engwirda
Geosci. Model Dev., 14, 5561–5582, https://doi.org/10.5194/gmd-14-5561-2021, https://doi.org/10.5194/gmd-14-5561-2021, 2021
Short summary
Short summary
In support of the developing ocean renewable energy sector, and indeed all mariners, we have developed a new tidal model for Australian waters and thoroughly evaluated it using a new compilation of tide gauge and current meter data. We show that while there is certainly room for improvement, the model provides useful predictions of tidal currents for about 80 % (by area) of Australian shelf waters. So we intend to commence publishing tidal current predictions for those regions soon.
David A. Griffin, Mike Herzfeld, and Mark Hemer
Ocean Sci. Discuss., https://doi.org/10.5194/os-2020-107, https://doi.org/10.5194/os-2020-107, 2020
Preprint withdrawn
Short summary
Short summary
In support of the developing ocean renewable energy sector, and indeed all mariners, we have developed a new tidal model for Australian waters and thoroughly evaluated it using a new compilation of tide gauge and current meter data. We show that while there is certainly room for improvement, the model provides useful predictions of tidal currents for about 80 % (by area) of Australian shelf waters. So we intend to commence publishing tidal current predictions for those regions soon.
Lin Tang, Martin O. P. Ramacher, Jana Moldanová, Volker Matthias, Matthias Karl, Lasse Johansson, Jukka-Pekka Jalkanen, Katarina Yaramenka, Armin Aulinger, and Malin Gustafsson
Atmos. Chem. Phys., 20, 7509–7530, https://doi.org/10.5194/acp-20-7509-2020, https://doi.org/10.5194/acp-20-7509-2020, 2020
Short summary
Short summary
The effects of shipping emissions on air quality and health in the harbour city of Gothenburg were simulated for 2012 with coupled regional and city-scale chemistry transport models. The results show that contributions of shipping to exposure and health impacts from particulate matter and NO2 are significant and that shipping-related exposure to PM is dominated by emissions from regional shipping outside the city domain and is larger than exposure related to emissions from local road traffic.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Malcolm Taberner, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Elisabetta Canuti, Francisco Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Richard Gould, Stanford B. Hooker, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Hubert Loisel, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Frank Muller-Karger, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 11, 1037–1068, https://doi.org/10.5194/essd-11-1037-2019, https://doi.org/10.5194/essd-11-1037-2019, 2019
Short summary
Short summary
A compiled set of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the compilation of global bio-optical in situ data (spanning from 1997 to 2018) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Luke C. Jeffrey, Damien T. Maher, Scott G. Johnston, Kylie Maguire, Andrew D. L. Steven, and Douglas R. Tait
Biogeosciences, 16, 1799–1815, https://doi.org/10.5194/bg-16-1799-2019, https://doi.org/10.5194/bg-16-1799-2019, 2019
Short summary
Short summary
Wetlands represent the largest natural source of methane (CH4), so understanding CH4 drivers is important for management and climate models. We compared several CH4 pathways of a remediated subtropical Australian wetland. We found permanently inundated sites emitted more CH4 than seasonally inundated sites and that the soil properties of each site corresponded to CH4 emissions. This suggests that selective wetland remediation of favourable soil types may help to mitigate unwanted CH4 emissions.
Patrick Martin, Nagur Cherukuru, Ashleen S. Y. Tan, Nivedita Sanwlani, Aazani Mujahid, and Moritz Müller
Biogeosciences, 15, 6847–6865, https://doi.org/10.5194/bg-15-6847-2018, https://doi.org/10.5194/bg-15-6847-2018, 2018
Short summary
Short summary
The carbon cycle is a key control for the Earth's climate. Every year rivers deliver a lot of organic carbon to coastal seas, but we do not know what happens to this carbon, particularly in the tropics. We show that rivers in Borneo deliver carbon from peat swamps to the sea with at most minimal biological or chemical alteration in estuaries, but sunlight can rapidly oxidise this carbon to CO2. This means that south-east Asian seas are likely hotspots of terrestrial carbon decomposition.
Paula Conde Pardo, Bronte Tilbrook, Clothilde Langlais, Thomas William Trull, and Stephen Rich Rintoul
Biogeosciences, 14, 5217–5237, https://doi.org/10.5194/bg-14-5217-2017, https://doi.org/10.5194/bg-14-5217-2017, 2017
Short summary
Short summary
The carbon content of the water masses of the Southern Ocean south of Tasmania has increased over the period 1995–2011, leading to a general decrease in pH. An enhancement in the upwelling of DIC-rich deep waters is the main plausible cause of the increase in carbon in surface waters south of the Polar Front. North of the Polar Front, strong winds favor the ventilation of surface to intermediate layers, where the DIC increase is explained by the uptake of atmospheric CO2.
Jeffrey J. Kelleway, Neil Saintilan, Peter I. Macreadie, Jeffrey A. Baldock, and Peter J. Ralph
Biogeosciences, 14, 3763–3779, https://doi.org/10.5194/bg-14-3763-2017, https://doi.org/10.5194/bg-14-3763-2017, 2017
Short summary
Short summary
In this study, we compare rates of accretion, C content, source and stability between different salt marsh vegetation assemblages, using a range of analytical techniques. We find substantial differences in surface and carbon dynamics among assemblages, driven by both biological and physical processes. These findings have important implications for the fate of tidal wetlands and their capacity for accumulating carbon during a time of environmental change.
Emlyn M. Jones, Mark E. Baird, Mathieu Mongin, John Parslow, Jenny Skerratt, Jenny Lovell, Nugzar Margvelashvili, Richard J. Matear, Karen Wild-Allen, Barbara Robson, Farhan Rizwi, Peter Oke, Edward King, Thomas Schroeder, Andy Steven, and John Taylor
Biogeosciences, 13, 6441–6469, https://doi.org/10.5194/bg-13-6441-2016, https://doi.org/10.5194/bg-13-6441-2016, 2016
Short summary
Short summary
Marine biogeochemical models are often used to understand water quality, nutrient and blue-carbon dynamics at scales that range from estuaries and bays, through to the global ocean. We introduce a new methodology allowing for the assimilation of observed remote sensing reflectances, avoiding the need to use empirically derived chlorophyll-a concentrations. This method opens up the possibility to assimilate of reflectances from a variety of missions and potentially non-satellite platforms.
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
Short summary
Short summary
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.
Related subject area
Oceanography
A new global high-resolution wave model for the tropical ocean using WAVEWATCH III version 7.14
sedInterFoam 1.0: a three-phase numerical model for sediment transport applications with free surfaces
The Ross Sea and Amundsen Sea Ice–Sea Model (RAISE v1.0): a high-resolution ocean–sea ice–ice shelf coupling model for simulating the Dense Shelf Water and Antarctic Bottom Water in the Ross Sea, Antarctica
Sensitivity of the tropical Atlantic to vertical mixing in two ocean models (ICON-O v2.6.6 and FESOM v2.5)
HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures
A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0
HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development
DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
An optimal transformation method for inferring ocean tracer sources and sinks
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
Updates to the Met Office’s global ocean-sea ice forecasting system including model and data assimilation changes
Using automatic calibration to improve the physics behind complex numerical models: An example from a 3D lake model using Delft3d (v6.02.10) and DYNO-PODS (v1.0)
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
GREAT v1.0: Global Real-time Early Assessment of Tsunamis
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
Resolution dependence of interlinked Southern Ocean biases in global coupled HadGEM3 models
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)
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
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Axelle Gaffet, Xavier Bertin, Damien Sous, Héloïse Michaud, Aron Roland, and Emmanuel Cordier
Geosci. Model Dev., 18, 1929–1946, https://doi.org/10.5194/gmd-18-1929-2025, https://doi.org/10.5194/gmd-18-1929-2025, 2025
Short summary
Short summary
This study presents a new global wave model that improves predictions of sea states in tropical areas by using a high-resolution grid and corrected wind fields. The model is validated globally with satellite data and nearshore using in situ data. The model allows for the first time direct comparisons with in situ data collected at 10–30 m water depth, which is very close to shore due to the steep slope usually surrounding volcanic islands.
Antoine Mathieu, Yeulwoo Kim, Tian-Jian Hsu, Cyrille Bonamy, and Julien Chauchat
Geosci. Model Dev., 18, 1561–1573, https://doi.org/10.5194/gmd-18-1561-2025, https://doi.org/10.5194/gmd-18-1561-2025, 2025
Short summary
Short summary
Most of the tools available to model sediment transport do not account for complex physical mechanisms such as surface-wave-driven processes. In this study, a new model, sedInterFoam, allows us to reproduce numerically complex configurations in order to investigate coastal sediment transport applications dominated by surface waves and to gain insight into the complex physical processes associated with breaking waves and morphodynamics.
Zhaoru Zhang, Chuan Xie, Chuning Wang, Yuanjie Chen, Heng Hu, and Xiaoqiao Wang
Geosci. Model Dev., 18, 1375–1393, https://doi.org/10.5194/gmd-18-1375-2025, https://doi.org/10.5194/gmd-18-1375-2025, 2025
Short summary
Short summary
A coupled fine-resolution ocean–ice model is developed for the Ross Sea and adjacent regions in Antarctica, a key area for the formation of global ocean bottom water, the Antarctic Bottom Water (AABW), which affects global ocean circulation. The model has a high skill level in simulating sea ice production driving the AABW source water formation and AABW properties when assessed against observations. A model experiment shows a significant impact of ice shelf melting on the AABW characteristics.
Swantje Bastin, Aleksei Koldunov, Florian Schütte, Oliver Gutjahr, Marta Agnieszka Mrozowska, Tim Fischer, Radomyra Shevchenko, Arjun Kumar, Nikolay Koldunov, Helmuth Haak, Nils Brüggemann, Rebecca Hummels, Mia Sophie Specht, Johann Jungclaus, Sergey Danilov, Marcus Dengler, and Markus Jochum
Geosci. Model Dev., 18, 1189–1220, https://doi.org/10.5194/gmd-18-1189-2025, https://doi.org/10.5194/gmd-18-1189-2025, 2025
Short summary
Short summary
Vertical mixing is an important process, for example, for tropical sea surface temperature, but cannot be resolved by ocean models. Comparisons of mixing schemes and settings have usually been done with a single model, sometimes yielding conflicting results. We systematically compare two widely used schemes with different parameter settings in two different ocean models and show that most effects from mixing scheme parameter changes are model-dependent.
Marko Rus, Hrvoje Mihanović, Matjaž Ličer, and Matej Kristan
Geosci. Model Dev., 18, 605–620, https://doi.org/10.5194/gmd-18-605-2025, https://doi.org/10.5194/gmd-18-605-2025, 2025
Short summary
Short summary
HIDRA3 is a deep-learning model for predicting sea levels and storm surges, offering significant improvements over previous models and numerical simulations. It utilizes data from multiple tide gauges, enhancing predictions even with limited historical data and during sensor outages. With its advanced architecture, HIDRA3 outperforms current state-of-the-art models by achieving a mean absolute error of up to 15 % lower, proving effective for coastal flood forecasting under diverse conditions.
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev., 18, 319–336, https://doi.org/10.5194/gmd-18-319-2025, https://doi.org/10.5194/gmd-18-319-2025, 2025
Short summary
Short summary
This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev., 18, 211–237, https://doi.org/10.5194/gmd-18-211-2025, https://doi.org/10.5194/gmd-18-211-2025, 2025
Short summary
Short summary
We developed a 3D ocean model called the Hindcast of the Salish Sea (HOTSSea v1) that recreates physical conditions throughout the Salish Sea from 1980 to 2018. It was not clear that acceptable accuracy could be achieved because of computational and data limitations, but the model's predictions agreed well with observations. When we used the model to examine ocean temperature trends in areas that lack observations, it indicated that some seasons and areas are warming faster than others.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 2024
Short summary
Short summary
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 ocean 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.
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., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
Short summary
Short summary
Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
Short summary
Short summary
We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
Short summary
Short summary
We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. 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.
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
Short summary
Short summary
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.
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc’h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-3143, https://doi.org/10.5194/egusphere-2024-3143, 2024
Short summary
Short summary
We describe major improvements of the Met Office's global ocean-sea ice forecasting system. The models and the way observations are used to improve the forecasts were changed, which led to a significant error reduction of 1-day forecasts. The new system performance in past conditions, where sub-surface observations are scarce, was improved with more consistent ocean heat content estimates. The new system will be of better use for climate studies and will provide improved forecasts for end users.
Marina Amadori, Abolfazl Irani Rahaghi, Damien Bouffard, and Marco Toffolon
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-118, https://doi.org/10.5194/gmd-2024-118, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Models simplify reality using assumptions, which can sometimes introduce flaws and affect their accuracy. Properly calibrating model parameters is essential, and although automated tools can speed up this process, they may occasionally produce incorrect values due to inconsistencies in the model. We demonstrate that by carefully applying automated tools, we were able to identify and correct a flaw in a widely used model for lake environments.
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.
Usama Kadri, Ali Abdolali, and Maxim Filimonov
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-139, https://doi.org/10.5194/gmd-2024-139, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
The GREAT v1.0 software introduces a novel tsunami warning technology for global real-time analysis. It leverages acoustic signals generated by tsunamis, which propagate faster than the tsunami itself, enabling real-time detection and assessment. Integrating various models, the software provides reliable and rapid assessment, mapping risk areas, and estimating tsunami amplitude. This advancement reduces false alarms and enhances global tsunami warning systems' accuracy and efficiency.
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.
David Storkey, Pierre Mathiot, Michael J. Bell, Dan Copsey, Catherine Guiavarc'h, Helene T. Hewitt, Jeff Ridley, and Malcolm J. Roberts
EGUsphere, https://doi.org/10.5194/egusphere-2024-1414, https://doi.org/10.5194/egusphere-2024-1414, 2024
Short summary
Short summary
The Southern Ocean is a key region of the world ocean in the context of climate change studies. We show that the HadGEM3 coupled model with intermediate ocean resolution struggles to accurately simulate the Southern Ocean. Increasing the frictional drag that the sea floor exerts on ocean currents, and introducing a representation of unresolved ocean eddies both appear to reduce the large-scale biases in this model.
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.
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.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
Short summary
Short summary
A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
Short summary
Short summary
The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
Short summary
Short summary
While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
Short summary
Short summary
We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
Cited articles
Anthony, K. R. N., Kleypas, J. A., and Gattuso, J.-P.: Coral reefs modify their
seawater carbon chemistry - implications for impacts of ocean acidification,
Glob. Change Biol., 17, 3655–3666, 2011. a
Atkins, P. W.: Physical Chemistry, Oxford University Press, Oxford, 5th Edn.,
1994. a
Atkinson, M. J.: Productivity of Eniwetak Atoll reef predicted from
mass-transfer relationships, Cont. Shelf Res., 12, 799–807, 1992. a
Atkinson, M. J. and Bilger, B. W.: Effects of water velocity on phosphate
uptake in coral reef-flat communities, Limnol. Oceanogr., 37, 273–279, 1992. a
Atkinson, M. J. and Smith, S. V.: C:N:P ratios of benthic marine plants,
Limnol. Oceanogr., 28, 568–574, 1983. 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
Babcock, R. C., Baird, M. E., Pillans, R., Patterson, T., Clementson, L. A.,
Haywood, M. E., Rochester, W., Morello, E., Kelly, N., Oubelkheir, K., Fry,
G., Dunbabin, M., Perkins, S., Forcey, K., Cooper, S., Donovan, A., Kenyon,
R., Carlin, G., and Limpus, C.: Towards an integrated study of the Gladstone
marine system, 278 pp., ISBN: 978-1-4863-0539-1, Tech. rep., CSIRO Oceans and
Atmosphere Flagship, Brisbane, 2015. a
Baird, M. E.: Numerical approximations of the mean absorption cross-section of
a variety of randomly oriented microalgal shapes, J. Math. Biol., 47,
325–336, 2003. a
Baird, M. E. and Emsley, S. M.: Towards a mechanistic model of plankton
population dynamics, J. Plankton Res., 21, 85–126, 1999. a
Baird, M. E., Timko, P. G., Suthers, I. M., and Middleton, J. H.: Coupled
physical-biological modelling study of the East Australian Current with
idealised wind forcing: Part II: Biological dynamical analysis, J. Marine
Sys., 59, 271–291, 2006. a
Baird, M. E., Leth, O., and Middleton, J. F.: Biological response to
circulation driven by mean summertime winds off central Chile: A numerical
model study, J. Geophys. Res., 112, C07031, https://doi.org/10.1029/2006JC003655,
2007a. a
Baird, M. E., Timko, P. G., and Wu, L.: The effect of packaging of chlorophyll
within phytoplankton and light scattering in a coupled physical-biological
ocean model., Mar. Fresh. Res., 58, 966–981, 2007b. a
Baird, M. E., Adams, M. P., Babcock, R. C., Oubelkheir, K., Mongin, M.,
Wild-Allen, K. A., Skerratt, J., Robson, B. J., Petrou, K., Ralph, P. J.,
O'Brien, K. R., Carter, A. B., Jarvis, J. C., and Rasheed, M. A.: A
biophysical representation of seagrass growth for application in a complex
shallow-water biogeochemical model, Ecol. Model., 325, 13–27,
2016a. a, b, c, d, e, f, g, h, i, j
Baird, M. E., Cherukuru, N., Jones, E., Margvelashvili, N., Mongin, M.,
Oubelkheir, K., Ralph, P. J., Rizwi, F., Robson, B. J., Schroeder, T.,
Skerratt, J., Steven, A. D. L., and Wild-Allen, K. A.: Remote-sensing
reflectance and true colour produced by a coupled hydrodynamic, optical,
sediment, biogeochemical model of the Great Barrier Reef, Australia:
comparison with satellite data, Environ. Modell. Softw., 78, 79–96,
2016b. a, b, c, d, e, f
Baretta-Bekker, J., Baretta, J., and Ebenhöh, W.: Microbial dynamics in the
marine ecosystem model ERSEM II with decoupled carbon assimilation and
nutrient uptake, J. Sea Res., 38, 195–211, 1997. a
Beckmann, A. and Hense, I.: Torn between extremes: the ups and downs of
phytoplankton, Ocean Dynam., 54, 581–592, 2004. a
Benthuysen, J. A., Tonin, H., Brinkman, R., Herzfeld, M., and Steinberg, C.:
Intrusive upwelling in the Central Great Barrier Reef, J. Geophys. Res.-Oceans, 121, 8395–8416, 2016. a
Blondeau-Patissier, D., Brando, V. E., Oubelkheir, K., Dekker, A. G.,
Clementson, L. A., and Daniel, P.: Bio-optical variability of the absorption
and scattering properties of the Queensland inshore and reef waters,
Australia, J. Geophys. Res.-Oceans, 114, C05003, https://doi.org/10.1029/2008JC005039, 2009. a, b, c
Bohren, C. F. and Huffman, D. R.: Absorption and scattering of light particles
by small particles, John Wiley & Sons, 1983. a
Boudreau, B. P.: A method-of-lines code for carbon and nutrient diagenesis in
aquatic sediments, Comput. Geosci., 22, 479–496, 1996. a
Bruggeman, J. and Kooijman, S. A. L. M.: A biodiversity-inspired approach to
aquatic ecosystem modeling, Limnol. Oceanogr., 52, 1533–1544, 2007. a
Butenschön, M., Clark, J., Aldridge, J. N., Allen, J. I., Artioli, Y., Blackford, J., Bruggeman, J., Cazenave, P., Ciavatta, S., Kay, S., Lessin, G., van Leeuwen, S., van der Molen, J., de Mora, L., Polimene, L., Sailley, S., Stephens, N., and Torres, R.: ERSEM 15.06: a generic model for marine biogeochemistry and the ecosystem dynamics of the lower trophic levels, Geosci. Model Dev., 9, 1293–1339, https://doi.org/10.5194/gmd-9-1293-2016, 2016. a, b, c
Cambridge, M. L. and Lambers, H.: Specific leaf area and functional leaf
anatomy in Western Australian seagrasses, in: Inherent variations in plant
growth: physiological mechanisms and ecological consequences, edited by:
Lambers, H., Poorter, H., and Vuren, M. M. I. V., Backhuys,
Leiden, 88–99, 1998. a
Carpenter, E., O’Neil, J., Dawson, R., Capone, D., Siddiqui, P., Roenneberg,
T., and Bergman, B.: The tropical diazotrophic phytoplankter
Trichodesmium: Biological characteristics of two common species,
Mar. Ecol. Prog. Ser., 95, 295–304, 1993. a
Chartrand, K. M., Ralph, P. J., Petrou, K., and Rasheed, M. A.: Development of
a Light-Based Seagrass Management Approach for the Gladstone Western Basin
Dredging Program, Tech. rep., DAFF Publication. Fisheries Queensland, Cairns
126 pp., 2012. a
Chartrand, K. M., , Bryant, C. V., Sozou, A., Ralph, P. J., and Rasheed, M. A.:
Final Report: Deepwater seagrass dynamics: Light requirements, seasonal
change and mechanisms of recruitment, Tech. rep., Centre for Tropical Water
and Aquatic Ecosystem Research (TropWATER) Publication, James Cook
University, Report No 17/16, Cairns, 67 pp., 2017. a
Cherukuru, N., Dekker, A. G., Hardman-Mountford, N. J., Clementson, L. A., and
Thompson, P. A.: Bio-optical variability in multiple water masses across a
tropical shelf: Implications for ocean colour remote sensing models, Estuar.
Coast. Shelf Sci., 219, 223–230, 2019. a
Clementson, L. A. and Wojtasiewicz, B.: Dataset on the absorption
characteristics of extracted phytoplankton pigments, Data in Brief, 24, 103875,
https://doi.org/10.1016/j.dib.2019.103875, 2019. a, b
Condie, S. A., Herzfeld, M., Margvelashvili, N., and Andrewartha, J. R.:
Modeling the physical and biogeochemical response of a marine shelf system to
a tropical cyclone, Geophys. Res. Lett., 36, L22603, https://doi.org/10.1029/2009GL039563,
2009. a, b
CSIRO: EMS Release v1.1.1. v1. CSIRO, Software Collection,
https://doi.org/10.25919/5e701c5c2d9c9, 2019. a
CSIRO Coastal Environmental Modelling Team: CSIRO Environmental Modelling Suite GitHub archive, available at: https://github.com/csiro-coasts/EMS/, last access: 22 September 2020a. a
CSIRO Coastal Environmental Modelling Team: CSIRO Environmental Modelling Suite GitHub archive v1.1.1, available at: https://github.com/csiro-coasts/EMS/releases/tag/v1.1.1, last access: 22 September 2020. a
Dietze, H., Matear, R., and Moore, T.: Nutrient supply to anticyclonic
meso-scale eddies off western Australia estimated with artificial tracers
released in a circulation model, Deep-Sea Res. Pt. I, 56, 1440–1448, 2009. a
Duarte, C. M. and Chiscano, C. L.: Seagrass biomass and production: a
reassessment, Aquat. Bot., 65, 159–174, 1999. a
Dutkiewicz, S., Hickman, A. E., Jahn, O., Gregg, W. W., Mouw, C. B., and Follows, M. J.: Capturing optically important constituents and properties in a marine biogeochemical and ecosystem model, Biogeosciences, 12, 4447–4481, https://doi.org/10.5194/bg-12-4447-2015, 2015. a, b, c
Falter, J. L., Atkinson, M. J., and Merrifield, M. A.: Mass-transfer limitation
of nutrient uptake by a wave-dominated reef flat community, Limnol.
Oceanogr., 49, 1820–1831, 2004. 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,
1990. a
Fennel, K., Gehlen, M., Brasseur, P., Brown, C. W., Ciavatta, S., Cossarini,
G., Crise, A., Edwards, C. A., Ford, D., Friedrichs, M. A. M., Gregoire, M.,
Jones, E. M., Kim, H.-C., Lamouroux, J., Murtugudde, R., and Perruche, C.:
Advancing marine biogeochemical and ecosystem reanalyses and forecasts as
tools for monitoring and managing ecosystem health, Front. Mar. Sci., 6, 89, https://doi.org/10.3389/fmars.2019.00089,
2019. a
Ficek, D., Kaczmarek, S., Stoń-Egiert, J., Woźniak, B., Majchrowski,
R., and Dera, J.: Spectra of light absorption by phytoplankton pigments in
the Baltic; conclusions to be drawn from a Gaussian analysis of empirical
data, Oceanologia, 46, 533–555, 2004. a
Flynn, K. J. and Mitra, A.: Why plankton modelers should reconsider using
rectangular hyperbolic (Michaelis-Menten, Monod) descriptions of
predator-prey interactions, Front. Mar. Sci., 3, 165, https://doi.org/10.3389/fmars.2016.00165, 2016. a
Fulton, E. A., Smith, A. D. M., Smith, D. C., and Johnson, P.: An integrated
approach is needed for ecosystem based fisheries management: Insights from
ecosystem-level management strategy evaluation, PLoS One, 9, e84242, https://doi.org/10.1371/journal.pone.0084242, 2014. a, b
Geider, R. J., MacIntyre, H. L., and Kana, T. M.: A dynamic regulatory model of
phytoplanktonic acclimation to light, nutrients, and temperature, Limnol.
Oceanogr., 43, 679–694, 1998. a
Gentleman, W.: A chronology of plankton dynamics in silico: how
computer models have been used to study marine ecosystems, Hydrobiologica,
480, 69–85, 2002. a
Gras, A. F., Koch, M. S., and Madden, C. J.: Phosphorus uptake kinetics of a
dominant tropical seagrass Thalassia testudinum, Aquat. Bot., 76,
299–315, 2003. a
Griffies, S. M., Harrison, M. J., Pacanowski, R. C., and Rosati, A.: A
technical guide to MOM4 GFDL Ocean Group TECHNICAL REPORT NO. 5
Version prepared on 3 March 2004, Tech. rep., NOAA/Geophysical Fluid
Dynamics Laboratory, 2004. a
Gumley, L., Descloitres, J., and Shmaltz, J.: Creating reprojected true color
MODIS images: A tutorial, Tech. Rep 1.0.2, 17 pp., Tech. rep., Univ. of
Wisconsin, Madison, 2010. a
Gustafsson, M. S. M., Baird, M. E., and Ralph, P. J.: Modelling
photoinhibition and bleaching in Scleractinian coral as a function of light,
temperature and heterotrophy, Limnol. Oceanogr., 59, 603–622, 2014. a
Hadley, S., Wild-Allen, K. A., Johnson, C., and Macleod, C.: Quantification of
the impacts of finfish aquaculture and bioremediation capacity of integrated
multi-trophic aquaculture using a 3D estuary model, J. Appl. Phycol., 28, 1875–1889,
https://doi.org/10.1007/s10811-015-0714-2, 2015b. a, b
Hansen, J. W., Udy, J. W., Perry, C. J., Dennison, W. C., and Lomstein, B. A.:
Effect of the seagrass Zostera capricorni on sediment microbial
processes, Mar. Ecol. Prog. Ser., 199, 83–96, 2000. a
Hansen, P. J., Bjornsen, P. K., and Hansen, B. W.: Zooplankton grazing and
growth: Scaling within the 2–2,000 µm body size range, Limnol. Oceanogr.,
42, 687–704, 1997. a
Harris, G., Batley, G., Fox, D., Hall, D., Jernakoff, P., Molloy, R., Murray,
A., Newell, B., Parslow, J., Skyring, G., and Walker, S.: Port Phillip Bay
Environmental Study Final Report, CSIRO, Canberra, Australia, 1996. a
Herzfeld, M., Andrewartha, J., Baird, M., Brinkman, R., Furnas, M., Gillibrand,
P., Hemer, M., Joehnk, K., Jones, E., McKinnon, D., Margvelashvili, N.,
Mongin, M., Oke, P., Rizwi, F., Robson, B., Seaton, S., Skerratt, J., Tonin,
H., and Wild-Allen, K.: eReefs Marine Modelling: Final Report, CSIRO, Hobart,
497 pp.,
available at http://hdl.handle.net/102.100.100/90405?index=1 (last access: 22 September 2020),
Tech. rep., CSIRO, 2016. a
Hochberg, E. J., Apprill, A. M., Atkinson, M. J., and Bidigare, R. R.:
Bio-optical modeling of photosynthetic pigments in corals, Coral Reefs, 25,
99–109, 2006. a
Hundsdorfer, W. and Verwer, J. G.: Numerical solutions of time-dependent
advection-diffusion-reaction equations, Springer, 2003. a
Hurd, C. L.: Water motion, marine macroalgal physiology, and production, J.
Phycol., 36, 453–472, 2000. a
Jones, E. M., Baird, M. E., Mongin, M., Parslow, J., Skerratt, J., Lovell, J., Margvelashvili, N., Matear, R. J., Wild-Allen, K., Robson, B., Rizwi, F., Oke, P., King, E., Schroeder, T., Steven, A., and Taylor, J.: Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef, Biogeosciences, 13, 6441–6469, https://doi.org/10.5194/bg-13-6441-2016, 2016. a
Kaldy, J. E., Brown, C. A., and Andersen, C. P.: In situ 13C
tracer experiments elucidate carbon translocation rates and allocation
patterns in eelgrass Zostera marina, Mar. Ecol. Prog. Ser., 487,
27–39, 2013. a
Kemp, W. M., Murray, L., Borum, J., and Sand-Jensen, K.: Diel growth in
eelgrass Zostera marina, Mar. Ecol. Prog. Ser., 41, 79–86, 1987. a
Lee, J.-Y., Tett, P., Jones, K., Jones, S., Luyten, P., Smith, C., and
Wild-Allen, K.: The PROWQM physical–biological model with benthic–pelagic
coupling applied to the northern North Sea, J. Sea Res., 48, 287–331,
2002. a
Lee, K.-S. and Dunton, K. H.: Inorganic nitrogen acquisition in the seagrass
Thalassia testudinum: Development of a whole-plant nitrogen budget,
Limnol. Oceanogr., 44, 1204–1215, 1999. a
Li, Y. and Gregory, S.: Diffusion of ions in sea water and in deep-sea
sediments, Geochim. Cosmochim. Ac., 38, 703–714, 1974. a
Litchman, E. and Klausmeier, C. A.: Trait-based community ecology of
phytoplankton, Annu. Rev. Ecol. Evol. Syst., 39, 615–639, 2008. a
Longstaff, B. J.: Investigations into the light requirements of seagrasses in
northeast Australia, Ph.D. thesis, University of Queensland, 2003. a
Lønborg, C., Álvarez-Salgado, X. A., Duggan, S., and
Carreira, C.: Organic matter bioavailability in tropical coastal waters: The
Great Barrier Reef, Limnol. Oceanogr., 63, 1015–1035, 2017. a
Mann, K. H. and Lazier, J. R. N.: Dynamics of Marine Ecosystems, Blackwell
Scientific Publications Inc., Oxford, 3rd Edn., 2006. a
Monbet, P., Brunskill, G. J., Zagorskis, I., and Pfitzner, J.: Phosphorus
speciation in the sediment and mass balance for the central region of the
Great Barrier Reef continental shelf (Australia), Geochim. Cosmochim.
Ac., 71, 2762–2779, 2007. a
Mongin, M., Baird, M. E., Lenton, A., and Hadley, S.: Optimising reef-scale
CO2 removal by seaweed to buffer ocean acidification, Environ.
Res. Lett., 11, 034023, https://doi.org/10.1088/1748-9326/11/3/034023, 2016a. a
Mongin, M., Baird, M. E., Tilbrook, B., Matear, R. J., Lenton, A., Herzfeld,
M., Wild-Allen, K. A., Skerratt, J., Margvelashvili, N., Robson, B. J.,
Duarte, C. M., Gustafsson, M. S. M., Ralph, P. J., and Steven, A. D. L.: The
exposure of the Great Barrier Reef to ocean acidification, Nat.
Commun., 7, 10732, https://doi.org/10.1038/ncomms10732, 2016b. a, b, c, d, e
Munhoven, G.: Mathematics of the total alkalinity–pH equation – pathway to robust and universal solution algorithms: the SolveSAPHE package v1.0.1, Geosci. Model Dev., 6, 1367–1388, https://doi.org/10.5194/gmd-6-1367-2013, 2013. a
Munk, W. H. and Riley, G. A.: Absorption of nutrients by aquatic plants, J.
Mar. Res., 11, 215–240, 1952. a
Murray, A. and Parlsow, J. S.: Modelling the nutrient impacts in Port
Phillip Bay – a semi enclosed marine Australian ecosystem, Mar.
Freshwater Res., 50, 469–81, 1999. a
Murray, A. and Parslow, J.: Port Phillip Bay Integrated Model: Final
Report, Tech. rep., CSIRO, GPO Box 1666, Canberra, ACT 2601, 201 pp., 1997. a
Nielsen, M. V. and Sakshaug, E.: Photobiological studies of Skeletonema
costatum adapted to spectrally different light regimes, Limnol.
Oceanogr., 38, 1576–1581, 1993. a
Orr, J. C., Fabry, V. J., Aumont, O., Bopp, L., Doney, S. C., Feely, R. A.,
Gnanadesikan, A., Gruber, N., Ishida, A., Joos, F., Key, R. M., Lindsay, K.,
Maier-Reimer, E., Matear, R., Monfray, P., Mouchet, A., Najjar, R. G.,
Plattner, G.-K., Rodgers, K. B., Sabine, C. L., Sarmiento, J. L., Schlitzer,
R., Slater, R. D., Totterdell, I. J., Weirig, M.-F., Yamanaka, Y., and Yool,
A.: Anthropogenic ocean acidification over the twenty-first century and its
impact on calcifying organisms, Nature, 437, 681–686, 2005. a
Pailles, C. and Moody, P. W.: Phosphorus sorption-desorption by some sediments
of the Johnstone Rivers catchments, northern Queensland, Aust. J. Mar.
Fresh. Res., 43, 1535–1545, 1992. a
Pasciak, W. J. and Gavis, J.: Transport limited nutrient uptake rates in
Dictylum brightwellii, Limnol. Oceanogr., 20, 604–617, 1975. a
Reynolds, C. S.: The ecology of freshwater phytoplankton, Cambridge University
Press, 1984. a
Ribes, M. and Atkinson, M. J.: Effects of water velocity on picoplankton uptake
by coral reef communities, Coral Reefs, 26, 413–421, 2007. a
Roberts, D. G.: Root-hair structure and development in the seagrass
Halophila ovalis (R. Br.) Hook. f., Aust. J. Mar. Freshw. Res., 44,
85–100, 1993. a
Robson, B., Webster, I., Margvelashvili, N. Y., and Herzfeld, M.: Scenario
modelling: simulating the downstream effects of changes in catchment land
use., Tech. rep., CRC for Coastal Zone, Estuary and Waterway Management
Technical Report 41, 26 pp., 2006. a
Robson, B. J., Baird, M. E., and Wild-Allen, K. A.: A physiological model for
the marine cyanobacteria, Trichodesmium, in: MODSIM2013, 20th
International Congress on Modelling and Simulation, edited by: Piantadosi, J.
R. S. A. and Boland, J., Modelling and Simulation Society of
Australia and New Zealand, 1652–1658, available at:
https://www.mssanz.org.au/modsim2013/H3/robson.pdf (last access: 22 September 2020), 2013. a, b, c
Sarmiento, J. L., Slater, R. D., Fasham, M. J. R., Ducklow, H. W., Toggweiler,
J. R., and Evans, G. T.: A seasonal three-dimensional ecosystem model of
nitrogen cycling in the North Atlantic euphotic zone, Global Biogeochem.
Cy., 7, 417–450, 1993. a
Schiller, A., Herzfeld, M., Brinkman, R., and Stuart, G.: Monitoring,
predicting and managing one of the seven natural wonders of the world, B.
Am. Meteorol. Soc., 95, 23–30, https://doi.org/10.1175/BAMS-D-12-00202.1, 2014. a
Schroeder, T., Devlin, M. J., Brando, V. E., Dekker, A. G., Brodie, J. E.,
Clementson, L. A., and McKinna, L.: Inter-annual variability of wet season
freshwater plume extent into the Great Barrier Reef lagoon based on satellite
coastal ocean colour observations, Mar. Pollut. Bull., 65, 210–223, 2012. a
Skerratt, J., Wild-Allen, K. A., Rizwi, F., Whitehead, J., and Coughanowr, C.:
Use of a high resolution 3D fully coupled hydrodynamic, sediment and
biogeochemical model to understand estuarine nutrient dynamics under various
water quality scenarios, Ocean Coast. Manage., 83, 52–66, 2013. a
Skerratt, J., Mongin, M., Wild-Allen, K. A., Baird, M. E., Robson, B. J.,
Schaffelke, B., Soja-Woźniak, M., Margvelashvili, N., Davies, C. H.,
Richardson, A. J., and Steven, A. D. L.: Simulated nutrient and plankton
dynamics in the Great Barrier Reef (2011–2016), J. Marine Syst., 192, 51–74,
2019. a, b, c
Smith, R. C. and Baker, K. S.: Optical properties of the clearest natural
waters, Appl. Optics, 20, 177–184, 1981. a
Soja-Woźniak, M., Baird, M. E., Schroeder, T., Qin, Y., Clementson, L.,
Baker, B., Boadle, D., Brando, V., and Steven, A.: Particulate
backscattering ratio as an indicator of changing particle composition in
coastal waters: observations from Great Barrier Reef waters, J. Geophys.
Res.-Oceans, 124, 5485–5502, https://doi.org/10.1029/2019JC014998, 2019. a
Spillman, C., Imberger, J., Hamilton, D., Hipsey, M., and Romero, J.: Modelling
the effects of Po River discharge, internal nutrient cycling and
hydrodynamics on biogeochemistry of the Northern Adriatic Sea, J. Marine Syst.,
68, 167–200, 2007. a
Steven, A. D. L., Aryal, S., Bernal, P., Bravo, F., Bustamante, R. H., Condie,
S., Dambacher, J. M., Dowideit, S., Fulton, E. A., Gorton, R., Herzfeld, M.,
Hodge, J., Hoshino, E., Kenna, E., Ocampo, D., van Putten, C. I., Rizwi, F.,
Skerratt, J., Steven, A., Thomas, L., Tickell, S., Vaquero, P., Wild, D., and
Wild-Allen, K.: SIMA Austral: An operational information system for managing
the Chilean aquaculture industry with international application, J.
Oper. Oceanogr., 12, S29–S46, 2019a. a
Steven, A. D. L., Baird, M. E., Brinkman, R., Car, N. J., Cox, S. J., Herzfeld,
M., Hodge, J., Jones, E., King, E., Margvelashvili, N., Robillot, C., Robson,
B., Schroeder, T., Skerratt, J., Tuteja, N., Wild-Allen, K., and Yu, J.: An
operational information system for managing the Great Barrier Reef: eReefs,
J. Oper. Oceanogr., 12, S12–S28, https://doi.org/10.1080/1755876X.2019.1650589,
2019b. a
Stock, C. A., Powell, T. M., and Levin, S. A.: Bottom-up and top-down forcing
in a simple size-structured plankton dynamics model, J. Marine Syst., 74,
134–152, 2008. a
Suggett, D. J., Warner, M. E., Smith, D. J., Davey, P., Hennige, S., and Baker,
N. R.: Photosynthesis and production of hydrogen peroxide by
Symbiodinium (Pyrrhophyta) phylotypes with different thermal
tolerances, J. Phycol., 44, 948–956, 2008. a
Thompson, P. A., Baird, M. E., Ingleton, T., and Doblin, M. A.: Long-term
changes in temperate Australian coastal waters and implications for
phytoplankton, Mar. Ecol. Prog. Ser., 394, 1–19, 2009. a
Vermaat, J. E., Agawin, N. S. R., Duarte, C. M., Fortes, M. D., Marba, N., and
Uri, J. S.: Meadow maintenance, growth and productivity of a mixed
Philippine seagrass bed, Mar. Ecol. Prog. Ser., 124, 215–225, 1995. a
von Liebig, J.: Chemistry in its Application to Agriculture and Physiology,
Taylor and Walton, London, 1840. a
Weiss, R.: The solubility of nitrogen, oxygen and argon in water and seawater,
Deep Sea Res., 17, 721–735, 1970. a
Wild-Allen, K. A., Thompson, P. A., Volkman, J., and Parslow, J.: Use of a
coastal biogeochemical model to select environmental monitoring sites, J.
Marine Syst., 88, 120–127, 2011. a
Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M.,
Legates, D. R., O'Donnell, J., and Rowe, C. M.: Statistics for the evaluation
and comparison of models, J. Geophys. Res., 90, 8995–9005, 1985. a
Wojtasiewicz, B. and Stoń-Egiert, J.: Bio-optical characterization of
selected cyanobacteria strains present in marine and freshwater ecosystems,
J. Appl. Phycol., 28, 2299–2314, 2016. a
Wright, S., Thomas, D., Marchant, H., Higgins, H., Mackey, M., and Mackey, D.:
Analysis of phytoplankton of the Australian sector of the Southern
Ocean:comparisons of microscopy and size frequency data with interpretations
of pigment HPLC data using the “CHEMTAX” matrix factorisation program,
Mar. Ecol. Prog. Ser., 144, 285–98, 1996. a
Wyatt, A. S. J., Lowe, R. J., Humphries, S., and Waite, A. M.: Particulate
nutrient fluxes over a fringing coral reef: relevant scales of phytoplankton
production and mechanisms of supply, Mar. Ecol. Prog. Ser., 405, 113–130,
2010. a
Yonge, C. M.: A Year on the Great Barrier Reef: The Story of Corals and of the
Greatest of their Creations, Putham, London, 1930. a
Yool, A.: The Dynamics of Open-Ocean Plankton Ecosystem Models, PhD thesis,
Dept. of Biological Sciences, University of Warwick, 1997. a
Yool, A. and Fasham, M. J. R.: An examination of the “continental shelf pump”
in an open ocean general circulation model, Global Biogeochem. Cy., 15,
831–844, 2001. a
Short summary
For 20+ years, the Commonwealth Science Industry and Research Organisation (CSIRO) has been developing a biogeochemical (BGC) model for coupling with a hydrodynamic and sediment model for application in estuaries, coastal waters and shelf seas. This paper provides a full mathematical description (equations, parameters), model evaluation and access to the numerical code. The model is particularly suited to applications in shallow waters where benthic processes are critical to ecosystem function.
For 20+ years, the Commonwealth Science Industry and Research Organisation (CSIRO) has been...
