Articles | Volume 14, issue 10
Geosci. Model Dev., 14, 6177–6195, 2021
https://doi.org/10.5194/gmd-14-6177-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 14, 6177–6195, 2021
https://doi.org/10.5194/gmd-14-6177-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper 15 Oct 2021
Model description paper | 15 Oct 2021
S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales
Paul R. Halloran et al.
Related authors
Shrivardhan Hulswar, Rafel Simo, Martí Galí, Thomas Bell, Arancha Lana, Swaleha Inamdar, Paul R. Halloran, George Manville, and Anoop Sharad Mahajan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-236, https://doi.org/10.5194/essd-2021-236, 2021
Preprint under review for ESSD
Short summary
Short summary
The third climatological estimation of sea-surface DMS concentrations based on in-situ measurements was created. The update includes a much larger input dataset and includes improvements in the data unification, filtering, and smoothing algorithm. The DMS-Rev3 climatology provides more realistic monthly estimates of DMS and shows significant regional differences compared to the past climatologies.
Matthew P. Couldrey, Kevin I. C. Oliver, Andrew Yool, Paul R. Halloran, and Eric P. Achterberg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-16, https://doi.org/10.5194/bg-2019-16, 2019
Revised manuscript not accepted
Short summary
Short summary
Determining how much carbon dioxide (CO2) the oceans absorb is key to predicting human-caused climate change. A computer model of the ocean shows how the North Atlantic will change up to the end of the century. Year-to-year variations are mostly caused by changes in ocean temperature and seawater chemistry, altering CO2 solubility. By 2100, human emissions cause the biggest changes. The near term changes are physically driven, which may be more predictable than biological changes.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
Short summary
Short summary
This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
P. R. Halloran, B. B. B. Booth, C. D. Jones, F. H. Lambert, D. J. McNeall, I. J. Totterdell, and C. Völker
Biogeosciences, 12, 4497–4508, https://doi.org/10.5194/bg-12-4497-2015, https://doi.org/10.5194/bg-12-4497-2015, 2015
Short summary
Short summary
The oceans currently take up around a quarter of the carbon dioxide (CO2) emitted by human activity. While stored in the ocean, this CO2 is not causing global warming. Here we explore high latitude North Atlantic CO2 uptake across a set of climate model simulations, and find that the models show a peak in ocean CO2 uptake around the middle of the century after which time CO2 uptake begins to decline. We identify the causes of this long-term change and interannual variability in the models.
L. Kwiatkowski, A. Yool, J. I. Allen, T. R. Anderson, R. Barciela, E. T. Buitenhuis, M. Butenschön, C. Enright, P. R. Halloran, C. Le Quéré, L. de Mora, M.-F. Racault, B. Sinha, I. J. Totterdell, and P. M. Cox
Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, https://doi.org/10.5194/bg-11-7291-2014, 2014
J. H. T. Williams, I. J. Totterdell, P. R. Halloran, and P. J. Valdes
Geosci. Model Dev., 7, 1419–1431, https://doi.org/10.5194/gmd-7-1419-2014, https://doi.org/10.5194/gmd-7-1419-2014, 2014
L. Bopp, L. Resplandy, J. C. Orr, S. C. Doney, J. P. Dunne, M. Gehlen, P. Halloran, C. Heinze, T. Ilyina, R. Séférian, J. Tjiputra, and M. Vichi
Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, https://doi.org/10.5194/bg-10-6225-2013, 2013
O. D. Andrews, N. L. Bindoff, P. R. Halloran, T. Ilyina, and C. Le Quéré
Biogeosciences, 10, 1799–1813, https://doi.org/10.5194/bg-10-1799-2013, https://doi.org/10.5194/bg-10-1799-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
Gandy Maria Rosales Quintana, Robert Marsh, and Luis Alfredo Icochea Salas
Ocean Sci., 17, 1385–1402, https://doi.org/10.5194/os-17-1385-2021, https://doi.org/10.5194/os-17-1385-2021, 2021
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The Equatorial Undercurrent (EUC) is a key influence on upwelling of nutrient-rich waters associated ecosystems off Peru. To quantify this influence, we backtrack upwelling waters in a computer model of ocean currents, annually, over 1989–2007. The EUC influence varies from year to year, dominating in warm El Niño years, when the EUC extends much closer to the Peruvian coast. In other years, more
localupwelling is associated with coastal winds, coincident with major key population shifts.
Shrivardhan Hulswar, Rafel Simo, Martí Galí, Thomas Bell, Arancha Lana, Swaleha Inamdar, Paul R. Halloran, George Manville, and Anoop Sharad Mahajan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-236, https://doi.org/10.5194/essd-2021-236, 2021
Preprint under review for ESSD
Short summary
Short summary
The third climatological estimation of sea-surface DMS concentrations based on in-situ measurements was created. The update includes a much larger input dataset and includes improvements in the data unification, filtering, and smoothing algorithm. The DMS-Rev3 climatology provides more realistic monthly estimates of DMS and shows significant regional differences compared to the past climatologies.
Matthew Clark, Robert Marsh, and James Harle
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-60, https://doi.org/10.5194/os-2021-60, 2021
Revised manuscript under review for OS
Short summary
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The European Slope Current (SC) is a northward-flowing current running parallel to the UK coastline. It is forced by changes in the density gradient of the wider North Atlantic Ocean. As the North Atlantic has warmed since the late 1990s, these gradients have changed strength and moved: reducing the volume and speed of water feeding into the SC. The SC flows into the North Sea, where changes in the species distribution of some plankton and fish has been seen due to the warming inputs.
Emma L. Worthington, Ben I. Moat, David A. Smeed, Jennifer V. Mecking, Robert Marsh, and Gerard D. McCarthy
Ocean Sci., 17, 285–299, https://doi.org/10.5194/os-17-285-2021, https://doi.org/10.5194/os-17-285-2021, 2021
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The RAPID array has observed the Atlantic meridional overturning circulation (AMOC) since 2004, but the AMOC was directly calculated only five times from 1957–2004. Here we create a statistical regression model from RAPID data, relating AMOC changes to density changes within the different water masses at 26° N, and apply it to historical hydrographic data. The resulting 1981–2016 record shows that the AMOC from 2008–2012 was its weakest since the mid-1980s, but it shows no overall decline.
Matthew P. Couldrey, Kevin I. C. Oliver, Andrew Yool, Paul R. Halloran, and Eric P. Achterberg
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-16, https://doi.org/10.5194/bg-2019-16, 2019
Revised manuscript not accepted
Short summary
Short summary
Determining how much carbon dioxide (CO2) the oceans absorb is key to predicting human-caused climate change. A computer model of the ocean shows how the North Atlantic will change up to the end of the century. Year-to-year variations are mostly caused by changes in ocean temperature and seawater chemistry, altering CO2 solubility. By 2100, human emissions cause the biggest changes. The near term changes are physically driven, which may be more predictable than biological changes.
Roland Séférian, Marion Gehlen, Laurent Bopp, Laure Resplandy, James C. Orr, Olivier Marti, John P. Dunne, James R. Christian, Scott C. Doney, Tatiana Ilyina, Keith Lindsay, Paul R. Halloran, Christoph Heinze, Joachim Segschneider, Jerry Tjiputra, Olivier Aumont, and Anastasia Romanou
Geosci. Model Dev., 9, 1827–1851, https://doi.org/10.5194/gmd-9-1827-2016, https://doi.org/10.5194/gmd-9-1827-2016, 2016
Short summary
Short summary
This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR's results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.
P. R. Halloran, B. B. B. Booth, C. D. Jones, F. H. Lambert, D. J. McNeall, I. J. Totterdell, and C. Völker
Biogeosciences, 12, 4497–4508, https://doi.org/10.5194/bg-12-4497-2015, https://doi.org/10.5194/bg-12-4497-2015, 2015
Short summary
Short summary
The oceans currently take up around a quarter of the carbon dioxide (CO2) emitted by human activity. While stored in the ocean, this CO2 is not causing global warming. Here we explore high latitude North Atlantic CO2 uptake across a set of climate model simulations, and find that the models show a peak in ocean CO2 uptake around the middle of the century after which time CO2 uptake begins to decline. We identify the causes of this long-term change and interannual variability in the models.
L. Kwiatkowski, A. Yool, J. I. Allen, T. R. Anderson, R. Barciela, E. T. Buitenhuis, M. Butenschön, C. Enright, P. R. Halloran, C. Le Quéré, L. de Mora, M.-F. Racault, B. Sinha, I. J. Totterdell, and P. M. Cox
Biogeosciences, 11, 7291–7304, https://doi.org/10.5194/bg-11-7291-2014, https://doi.org/10.5194/bg-11-7291-2014, 2014
J. H. T. Williams, I. J. Totterdell, P. R. Halloran, and P. J. Valdes
Geosci. Model Dev., 7, 1419–1431, https://doi.org/10.5194/gmd-7-1419-2014, https://doi.org/10.5194/gmd-7-1419-2014, 2014
L. Bopp, L. Resplandy, J. C. Orr, S. C. Doney, J. P. Dunne, M. Gehlen, P. Halloran, C. Heinze, T. Ilyina, R. Séférian, J. Tjiputra, and M. Vichi
Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, https://doi.org/10.5194/bg-10-6225-2013, 2013
O. D. Andrews, N. L. Bindoff, P. R. Halloran, T. Ilyina, and C. Le Quéré
Biogeosciences, 10, 1799–1813, https://doi.org/10.5194/bg-10-1799-2013, https://doi.org/10.5194/bg-10-1799-2013, 2013
F. Joos, R. Roth, J. S. Fuglestvedt, G. P. Peters, I. G. Enting, W. von Bloh, V. Brovkin, E. J. Burke, M. Eby, N. R. Edwards, T. Friedrich, T. L. Frölicher, P. R. Halloran, P. B. Holden, C. Jones, T. Kleinen, F. T. Mackenzie, K. Matsumoto, M. Meinshausen, G.-K. Plattner, A. Reisinger, J. Segschneider, G. Shaffer, M. Steinacher, K. Strassmann, K. Tanaka, A. Timmermann, and A. J. Weaver
Atmos. Chem. Phys., 13, 2793–2825, https://doi.org/10.5194/acp-13-2793-2013, https://doi.org/10.5194/acp-13-2793-2013, 2013
Related subject area
Oceanography
ISWFoam: a numerical model for internal solitary wave simulation in continuously stratified fluids
PyCO2SYS v1.8: marine carbonate system calculations in Python
Plume spreading test case for coastal ocean models
The interpretation of temperature and salinity variables in numerical ocean model output and the calculation of heat fluxes and heat content
Improve Ocean Modelling Software NEMO 4.0 benchmarking and communication efficiency
The Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application to the Yellow Sea green tide
Reconsideration of winds, wind waves, and turbulence in simulating wind-driven currents of shallow lakes in the Wave-current Coupled Model (WCCM) version 1.0
Nemo-Nordic 2.0: operational marine forecast model for the Baltic Sea
Australian tidal currents – assessment of a barotropic model (COMPAS v1.3.0 rev6631) with an unstructured grid
The improvements to the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv1)
Sedapp v2021: a nonlinear diffusion-based forward stratigraphic model for shallow marine environments
A discrete interaction numerical model for coagulation and fragmentation of marine detritic particulate matter (Coagfrag v.1)
Parallel computing efficiency of SWAN 40.91
Integrating CVMix into GOTM (v6.0): a consistent framework for testing, comparing, and applying ocean mixing schemes
A NEMO-based model of Sargassum distribution in the tropical Atlantic: description of the model and sensitivity analysis (NEMO-Sarg1.0)
Evaluating the physical and biogeochemical state of the global ocean component of UKESM1 in CMIP6 historical simulations
Iron and sulfur cycling in the cGENIE.muffin Earth system model (v0.9.21)
BFM17 v1.0: a reduced biogeochemical flux model for upper-ocean biophysical simulations
A mechanistic analysis of tropical Pacific dynamic sea level in GFDL-OM4 under OMIP-I and OMIP-II forcings
Comparison of ocean vertical mixing schemes in the Max Planck Institute Earth System Model (MPI-ESM1.2)
MESMO 3: Flexible phytoplankton stoichiometry and refractory dissolved organic matter
HIDRA 1.0: deep-learning-based ensemble sea level forecasting in the northern Adriatic
Towards multiscale modeling of ocean surface turbulent mixing using coupled MPAS-Ocean v6.3 and PALM v5.0
Improved representation of river runoff in Estimating the Circulation and Climate of the Ocean Version 4 (ECCOv4) simulations: implementation, evaluation, and impacts to coastal plume regions
The Regional Ice Ocean Prediction System v2: a pan-Canadian ocean analysis system using an online tidal harmonic analysis
Global storm tide modeling with ADCIRC v55: unstructured mesh design and performance
Development of a MetUM (v 11.1) and NEMO (v 3.6) coupled operational forecast model for the Maritime Continent – Part 1: Evaluation of ocean forecasts
Advanced parallel implementation of the coupled ocean–ice model FEMAO (version 2.0) with load balancing
The Meridionally Averaged Model of Eastern Boundary Upwelling Systems (MAMEBUSv1.0)
Model-driven optimization of coastal sea observatories through data assimilation in a finite element hydrodynamic model (SHYFEM v. 7_5_65)
A simplified atmospheric boundary layer model for an improved representation of air–sea interactions in eddying oceanic models: implementation and first evaluation in NEMO (4.0)
Performance of offline passive tracer advection in the Regional Ocean Modeling System (ROMS; v3.6, revision 904)
Implementation and assessment of a carbonate system model (Eco3M-CarbOx v1.1) in a highly dynamic Mediterranean coastal site (Bay of Marseille, France)
Numerical integrators for Lagrangian oceanography
Multi-grid algorithm for passive tracer transport in the NEMO ocean circulation model: a case study with the NEMO OGCM (version 3.6)
Introducing LAB60: A 1∕60° NEMO 3.6 numerical simulation of the Labrador Sea
Impact of horizontal resolution on global ocean–sea ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)
CSIRO Environmental Modelling Suite (EMS): scientific description of the optical and biogeochemical models (vB3p0)
Constraining the response of phytoplankton to zooplankton grazing and photo-acclimation in a temperate shelf sea with a 1-D model – towards S2P3 v8.0
Doppio – a ROMS (v3.6)-based circulation model for the Mid-Atlantic Bight and Gulf of Maine: configuration and comparison to integrated coastal observing network observations
Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)
Representation of the Denmark Strait overflow in a z-coordinate eddying configuration of the NEMO (v3.6) ocean model: resolution and parameter impacts
A global eddying hindcast ocean simulation with OFES2
Tracking water masses using passive-tracer transport in NEMO v3.4 with NEMOTAM: application to North Atlantic Deep Water and North Atlantic Subtropical Mode Water
Sensitivity study on the main tidal constituents of the Gulf of Tonkin by using the frequency-domain tidal solver in T-UGOm
DINCAE 1.0: a convolutional neural network with error estimates to reconstruct sea surface temperature satellite observations
Mitigation of model bias influences on wave data assimilation with multiple assimilation systems using WaveWatch III v5.16 and SWAN v41.20
MOMSO 1.0 – an eddying Southern Ocean model configuration with fairly equilibrated natural carbon
Simulating barrier island response to sea level rise with the barrier island and inlet environment (BRIE) model v1.0
Dealing with discontinuous meteorological forcing in operational ocean modelling: a case study using ECMWF-IFS and GETM (v2.5)
Jingyuan Li, Qinghe Zhang, and Tongqing Chen
Geosci. Model Dev., 15, 105–127, https://doi.org/10.5194/gmd-15-105-2022, https://doi.org/10.5194/gmd-15-105-2022, 2022
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A numerical model, ISWFoam with a modified k–ω SST model, is developed to simulate internal solitary waves (ISWs) in continuously stratified, incompressible, viscous fluids based on a fully three-dimensional (3D) Navier–Stokes equation with the finite-volume method. ISWFoam can accurately simulate the generation and evolution of ISWs, the ISW breaking phenomenon, waveform inversion of ISWs, and the interaction between ISWs and complex topography.
Matthew P. Humphreys, Ernie R. Lewis, Jonathan D. Sharp, and Denis Pierrot
Geosci. Model Dev., 15, 15–43, https://doi.org/10.5194/gmd-15-15-2022, https://doi.org/10.5194/gmd-15-15-2022, 2022
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The ocean helps to mitigate our impact on Earth's climate by absorbing about a quarter of the carbon dioxide (CO2) released by human activities each year. However, once absorbed, chemical reactions between CO2 and water reduce seawater pH (
ocean acidification), which may have adverse effects on marine ecosystems. Our Python package, PyCO2SYS, models the chemical reactions of CO2 in seawater, allowing us to quantify the corresponding changes in pH and related chemical properties.
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
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We present a test case of river plume spreading to evaluate coastal ocean models. Our test case reveals the level of numerical mixing (due to parameterizations used and numerical treatment of processes in the model) and the ability of models to reproduce complex dynamics. The major result of our comparative study is that accuracy in reproducing the analytical solution depends less on the type of applied model architecture or numerical grid than it does on the type of advection scheme.
Trevor J. McDougall, Paul M. Barker, Ryan M. Holmes, Rich Pawlowicz, Stephen M. Griffies, and Paul J. Durack
Geosci. Model Dev., 14, 6445–6466, https://doi.org/10.5194/gmd-14-6445-2021, https://doi.org/10.5194/gmd-14-6445-2021, 2021
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We show that the way that the air–sea heat flux is treated in ocean models means that the model's temperature variable should be interpreted as being Conservative Temperature, irrespective of whether the equation of state used in an ocean model is EOS-80 or TEOS-10.
Gaston Irrmann, Sébastien Masson, Éric Maisonnave, David Guibert, and Erwan Raffin
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-320, https://doi.org/10.5194/gmd-2021-320, 2021
Revised manuscript accepted for GMD
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To be efficient on supercomputers, softwares must be high-performance at computing many concurrent tasks. Communications between tasks is often necessary but time consuming, ocean modelling software NEMO 4.0 is no exception. In this work we describe approaches enabling fewer communications, an optimization to share the workload more equally between tasks and a new flexible configuration to assess NEMO's performance easily.
Fucang Zhou, Jianzhong Ge, Dongyan Liu, Pingxing Ding, Changsheng Chen, and Xiaodao Wei
Geosci. Model Dev., 14, 6049–6070, https://doi.org/10.5194/gmd-14-6049-2021, https://doi.org/10.5194/gmd-14-6049-2021, 2021
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In this study, a physical–ecological model, the Floating Macroalgal Growth and Drift Model (FMGDM), was developed to determine the dynamic growth and drifting pattern of floating macroalgae. Based on Lagrangian tracking, the macroalgae bloom is jointly controlled by ocean flows, sea surface wind, temperature, irradiation, and nutrients. The FMGDM was robust in successfully reproducing the spatial and temporal dynamics of the massive green tide around the Yellow Sea.
Tingfeng Wu, Boqiang Qin, Anning Huang, Yongwei Sheng, Shunxin Feng, and Céline Casenave
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-229, https://doi.org/10.5194/gmd-2021-229, 2021
Revised manuscript accepted for GMD
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Most hydrodynamic models were initially developed based in marine environments. They can not be directly applied to large lakes. Based on field observations and numerical experiments of a large shallow lake, we developed a hydrodynamic model by adopting the new schemes of wind stress, wind waves and turbulence for large lakes. Our model can greatly improve the simulation of lake currents. This study will be a reminder to limnologist to prudently use ocean models to study lake hydrodynamics.
Tuomas Kärnä, Patrik Ljungemyr, Saeed Falahat, Ida Ringgaard, Lars Axell, Vasily Korabel, Jens Murawski, Ilja Maljutenko, Anja Lindenthal, Simon Jandt-Scheelke, Svetlana Verjovkina, Ina Lorkowski, Priidik Lagemaa, Jun She, Laura Tuomi, Adam Nord, and Vibeke Huess
Geosci. Model Dev., 14, 5731–5749, https://doi.org/10.5194/gmd-14-5731-2021, https://doi.org/10.5194/gmd-14-5731-2021, 2021
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We present Nemo-Nordic 2.0, a novel operational marine model for the Baltic Sea. The model covers the Baltic Sea and the North Sea with approximately 1 nmi resolution. We validate the model's performance against sea level, water temperature, and salinity observations, as well as sea ice charts. The skill analysis demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features of the Baltic Sea.
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
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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.
Xueming Zhu, Ziqing Zu, Shihe Ren, Miaoyin Zhang, Yunfei Zhang, Hui Wang, and Ang Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-235, https://doi.org/10.5194/gmd-2021-235, 2021
Revised manuscript accepted for GMD
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SCSOFS operated in NMEFC of China can provide daily updated marine forecasting in SCS for the future 5 days since 2013. Comprehensive updates have been conducted to the configurations of SCSOFS’s physical model and data assimilation scheme in order to improve forecasting skills. Three most sensitive updates are highlighted. Scientific comparison and accuracy assessment results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version SCSOFSv1.
Jingzhe Li, Piyang Liu, Shuyu Sun, Zhifeng Sun, Yongzhang Zhou, Liang Gong, Jinliang Zhang, and Dongxing Du
Geosci. Model Dev., 14, 4925–4937, https://doi.org/10.5194/gmd-14-4925-2021, https://doi.org/10.5194/gmd-14-4925-2021, 2021
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This paper introduces Sedapp, a basin fill simulation tool. Sedapp is an open-source computer code written in R language. Using this program, one can simulate the formation of sedimentary strata, especially in shallow marine environments injected by rivers. With proper parameter settings, the simulation results are very similar to the real geological bodies. Sedapp can also be used in continental fault basin environments, which may serve as a tool for oil exploration.
Gwenaëlle Gremion, Louis-Philippe Nadeau, Christiane Dufresne, Irene R. Schloss, Philippe Archambault, and Dany Dumont
Geosci. Model Dev., 14, 4535–4554, https://doi.org/10.5194/gmd-14-4535-2021, https://doi.org/10.5194/gmd-14-4535-2021, 2021
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An accurate description of detritic organic particles is key to improving estimations of carbon export into the ocean abyss in ocean general circulation models. Yet, most parametrization are numerically impractical due to the required number of tracers needed to resolve the particle size spectrum. Here, a new parametrization that aims to minimize the tracers number while accurately describing the particles dynamics is developed and tested in a series of idealized numerical experiments.
Christo Rautenbach, Julia C. Mullarney, and Karin R. Bryan
Geosci. Model Dev., 14, 4241–4247, https://doi.org/10.5194/gmd-14-4241-2021, https://doi.org/10.5194/gmd-14-4241-2021, 2021
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The simulation of ocean waves is important for various reasons, e.g. ship route safety and coastal vulnerability assessments. SWAN is a popular tool with which ocean waves may be predicted. Simulations using this tool can be computationally expensive. The present study thus aimed to understand which typical parallel-computing SWAN model set-up will be most effective. There thus do exist configurations where these simulations are most time-saving and effective.
Qing Li, Jorn Bruggeman, Hans Burchard, Knut Klingbeil, Lars Umlauf, and Karsten Bolding
Geosci. Model Dev., 14, 4261–4282, https://doi.org/10.5194/gmd-14-4261-2021, https://doi.org/10.5194/gmd-14-4261-2021, 2021
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Different ocean vertical mixing schemes are usually developed in different modeling framework, making the comparison across such schemes difficult. Here, we develop a consistent framework for testing, comparing, and applying different ocean mixing schemes by integrating CVMix into GOTM, which also extends the capability of GOTM towards including the effects of ocean surface waves. A suite of test cases and toolsets for developing and evaluating ocean mixing schemes is also described.
Julien Jouanno, Rachid Benshila, Léo Berline, Antonin Soulié, Marie-Hélène Radenac, Guillaume Morvan, Frédéric Diaz, Julio Sheinbaum, Cristele Chevalier, Thierry Thibaut, Thomas Changeux, Frédéric Menard, Sarah Berthet, Olivier Aumont, Christian Ethé, Pierre Nabat, and Marc Mallet
Geosci. Model Dev., 14, 4069–4086, https://doi.org/10.5194/gmd-14-4069-2021, https://doi.org/10.5194/gmd-14-4069-2021, 2021
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The tropical Atlantic has been facing a massive proliferation of Sargassum since 2011, with severe environmental and socioeconomic impacts. We developed a modeling framework based on the NEMO ocean model, which integrates transport by currents and waves, and physiology of Sargassum with varying internal nutrient quota, and considers stranding at the coast. Results demonstrate the ability of the model to reproduce and forecast the seasonal cycle and large-scale distribution of Sargassum biomass.
Andrew Yool, Julien Palmiéri, Colin G. Jones, Lee de Mora, Till Kuhlbrodt, Ekatarina E. Popova, A. J. George Nurser, Joel Hirschi, Adam T. Blaker, Andrew C. Coward, Edward W. Blockley, and Alistair A. Sellar
Geosci. Model Dev., 14, 3437–3472, https://doi.org/10.5194/gmd-14-3437-2021, https://doi.org/10.5194/gmd-14-3437-2021, 2021
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The ocean plays a key role in modulating the Earth’s climate. Understanding this role is critical when using models to project future climate change. Consequently, it is necessary to evaluate their realism against the ocean's observed state. Here we validate UKESM1, a new Earth system model, focusing on the realism of its ocean physics and circulation, as well as its biological cycles and productivity. While we identify biases, generally the model performs well over a wide range of properties.
Sebastiaan J. van de Velde, Dominik Hülse, Christopher T. Reinhard, and Andy Ridgwell
Geosci. Model Dev., 14, 2713–2745, https://doi.org/10.5194/gmd-14-2713-2021, https://doi.org/10.5194/gmd-14-2713-2021, 2021
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Biogeochemical interactions between iron and sulfur are central to the long-term biogeochemical evolution of Earth’s oceans. Here, we introduce an iron–sulphur cycle in a model of Earth's oceans. Our analyses show that the results of the model are robust towards parameter choices and that simulated concentrations and reactions are comparable to those observed in ancient ocean analogues (anoxic lakes). Our model represents an important step forward in the study of iron–sulfur cycling.
Katherine M. Smith, Skyler Kern, Peter E. Hamlington, Marco Zavatarelli, Nadia Pinardi, Emily F. Klee, and Kyle E. Niemeyer
Geosci. Model Dev., 14, 2419–2442, https://doi.org/10.5194/gmd-14-2419-2021, https://doi.org/10.5194/gmd-14-2419-2021, 2021
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We present a newly developed reduced-order biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics but reduced enough to incorporate into highly resolved numerical simulations with limited additional computational cost. The model provides improved correlations between model output and field data, indicating that significant improvements in the reproduction of real-world data can be achieved with a small number of variables.
Chia-Wei Hsu, Jianjun Yin, Stephen M. Griffies, and Raphael Dussin
Geosci. Model Dev., 14, 2471–2502, https://doi.org/10.5194/gmd-14-2471-2021, https://doi.org/10.5194/gmd-14-2471-2021, 2021
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The new surface forcing from JRA55-do (OMIP II) significantly improved the underestimated sea level trend across the entire Pacific Ocean along 10° N in the simulation forced by CORE (OMIP I). We summarize and list out the reasons for the existing sea level biases across all studied timescales as a reference for improving the sea level simulation in the future. This study on the evaluation and improvement of ocean climate models should be of broad interest to a large modeling community.
Oliver Gutjahr, Nils Brüggemann, Helmuth Haak, Johann H. Jungclaus, Dian A. Putrasahan, Katja Lohmann, and Jin-Song von Storch
Geosci. Model Dev., 14, 2317–2349, https://doi.org/10.5194/gmd-14-2317-2021, https://doi.org/10.5194/gmd-14-2317-2021, 2021
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We compare four ocean vertical mixing schemes in 100-year coupled simulations with the Max Planck Institute Earth System Model (MPI-ESM1.2) and analyse their model biases. Overall, the mixing schemes modify biases in the ocean interior that vary with region and variable but produce a similar global bias pattern. We therefore cannot classify any scheme as superior but conclude that the chosen mixing scheme may be important for regional biases.
Katsumi Matsumoto, Tatsuro Tanioka, and Jacob Zahn
Geosci. Model Dev., 14, 2265–2288, https://doi.org/10.5194/gmd-14-2265-2021, https://doi.org/10.5194/gmd-14-2265-2021, 2021
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MESMO is a mathematical model that represents the essential components of the Earth, such as the global ocean, atmosphere, and sea ice. It is used to study the global climate and the global carbon cycle. We describe the third version of MESMO. A novel feature of the new version is its mathematical representations of the chemical composition of marine phytoplankton and the marine dissolved organic matter, which are both recognized as important for the global ocean carbon cycle.
Lojze Žust, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 14, 2057–2074, https://doi.org/10.5194/gmd-14-2057-2021, https://doi.org/10.5194/gmd-14-2057-2021, 2021
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Adriatic basin sea level modelling is a challenging problem due to the interplay between terrain, weather, tides and seiches. Current state-of-the-art numerical models (e.g. NEMO) require large computational resources to produce reliable forecasts. In this study we propose HIDRA, a novel deep learning approach for sea level modeling, which drastically reduces the numerical cost while demonstrating predictive capabilities comparable to that of the NEMO model, outperforming it in many instances.
Qing Li and Luke Van Roekel
Geosci. Model Dev., 14, 2011–2028, https://doi.org/10.5194/gmd-14-2011-2021, https://doi.org/10.5194/gmd-14-2011-2021, 2021
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Physical processes in the ocean span multiple spatial and temporal scales. Simultaneously resolving all these in a simulation is computationally challenging. Here we develop a more efficient technique to better study the interactions across scales, particularly focusing on the ocean surface turbulent mixing, by coupling a global ocean circulation model MPAS-Ocean and a large eddy simulation model PALM. The latter is customized and ported on a GPU to further accelerate the computation.
Yang Feng, Dimitris Menemenlis, Huijie Xue, Hong Zhang, Dustin Carroll, Yan Du, and Hui Wu
Geosci. Model Dev., 14, 1801–1819, https://doi.org/10.5194/gmd-14-1801-2021, https://doi.org/10.5194/gmd-14-1801-2021, 2021
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Simulation of coastal plume regions was improved in global ECCOv4 with a series of sensitivity tests. We find modeled SSS is closer to SMAP when using daily point-source runoff as well as increasing the resolution from coarse to intermediate. The plume characteristics, freshwater transport, and critical water properties are modified greatly. But this may not happen with a further increase to high resolution. The study will advance the seamless modeling of land–ocean–atmosphere feedback in ESMs.
Gregory C. Smith, Yimin Liu, Mounir Benkiran, Kamel Chikhar, Dorina Surcel Colan, Audrey-Anne Gauthier, Charles-Emmanuel Testut, Frederic Dupont, Ji Lei, François Roy, Jean-François Lemieux, and Fraser Davidson
Geosci. Model Dev., 14, 1445–1467, https://doi.org/10.5194/gmd-14-1445-2021, https://doi.org/10.5194/gmd-14-1445-2021, 2021
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Canada's coastlines include diverse ocean environments. In response to the strong need to support marine activities and security, we present the first pan-Canadian operational regional ocean analysis system. A novel online tidal harmonic analysis method is introduced that uses a sliding-window approach. Innovations are compared to those from the Canadian global analysis system. Particular improvements are found near the Gulf Stream due to the higher model grid resolution.
William J. Pringle, Damrongsak Wirasaet, Keith J. Roberts, and Joannes J. Westerink
Geosci. Model Dev., 14, 1125–1145, https://doi.org/10.5194/gmd-14-1125-2021, https://doi.org/10.5194/gmd-14-1125-2021, 2021
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We improve and test a computer model that simulates tides and storm surge over all of Earth's oceans and seas. The model varies mesh resolution (triangular element sizes) freely so that coastal areas, especially storm landfall locations, are well-described. We develop systematic tests of the resolution in order to suggest good mesh design criteria that balance computational efficiency with accuracy for both global astronomical tides and coastal storm tides under extreme weather forcing.
Bijoy Thompson, Claudio Sanchez, Boon Chong Peter Heng, Rajesh Kumar, Jianyu Liu, Xiang-Yu Huang, and Pavel Tkalich
Geosci. Model Dev., 14, 1081–1100, https://doi.org/10.5194/gmd-14-1081-2021, https://doi.org/10.5194/gmd-14-1081-2021, 2021
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This article describes the development and ocean forecast evaluation of an atmosphere–ocean coupled prediction system for the Maritime Continent domain, which includes the eastern Indian and western Pacific oceans. The coupled system comprises regional configurations of the atmospheric model MetUM and ocean model NEMO, coupled using the OASIS3-MCT libraries. The model forecast deviation of selected fields relative to observations is within acceptable error limits of operational forecast models.
Pavel Perezhogin, Ilya Chernov, and Nikolay Iakovlev
Geosci. Model Dev., 14, 843–857, https://doi.org/10.5194/gmd-14-843-2021, https://doi.org/10.5194/gmd-14-843-2021, 2021
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We describe the parallel implementation of the FEMAO model for an ice-covered sea with 2D Hilbert-curve domain decomposition. Load balancing is crucial because performance depends on the local depth. We propose, compare, and discuss four approaches to load balancing. The parallel library allowed us to modify the original sequential algorithm as little as possible. The performance increases almost linearly (tested with up to 996 CPU cores) for the model of the shallow White Sea.
Jordyn E. Moscoso, Andrew L. Stewart, Daniele Bianchi, and James C. McWilliams
Geosci. Model Dev., 14, 763–794, https://doi.org/10.5194/gmd-14-763-2021, https://doi.org/10.5194/gmd-14-763-2021, 2021
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This project was created to understand the across-shore distribution of plankton in the California Current System. To complete this study, we used a quasi-2-D dynamical model coupled to an ecosystem model. This paper is a preliminary study to test and validate the model against data collected by the California Cooperative Oceanic Fisheries Investigations (CalCOFI). We show the solution of our model solution compares well to the data and discuss our model as a tool for further model development.
Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 14, 645–659, https://doi.org/10.5194/gmd-14-645-2021, https://doi.org/10.5194/gmd-14-645-2021, 2021
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The problem of the optimization of ocean monitoring networks is tackled through the implementation of data assimilation techniques in a numerical model. The methodology has been applied to the tide gauge network in the Lagoon of Venice (Italy). The data assimilation methods allow identifying the minimum number of stations and their distribution that correctly represent the lagoon's dynamics. The methodology is easily exportable to other environments and can be extended to other variables.
Florian Lemarié, Guillaume Samson, Jean-Luc Redelsperger, Hervé Giordani, Théo Brivoal, and Gurvan Madec
Geosci. Model Dev., 14, 543–572, https://doi.org/10.5194/gmd-14-543-2021, https://doi.org/10.5194/gmd-14-543-2021, 2021
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A simplified model of the atmospheric boundary layer (ABL) of intermediate complexity between a bulk parameterization and a full three-dimensional atmospheric model has been developed and integrated to the NEMO ocean model.
An objective in the derivation of such a simplified model is to reach an apt representation of ocean-only numerical simulations of some of the key processes associated with air–sea interactions at the characteristic scales of the oceanic mesoscale.
Kristen M. Thyng, Daijiro Kobashi, Veronica Ruiz-Xomchuk, Lixin Qu, Xu Chen, and Robert D. Hetland
Geosci. Model Dev., 14, 391–407, https://doi.org/10.5194/gmd-14-391-2021, https://doi.org/10.5194/gmd-14-391-2021, 2021
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We modified the ROMS model to run in offline mode so that previously run fields of sea surface height and velocity fields are input to calculate tracer advection without running the full model with a larger time step; thus, it is faster. The code was tested with two advection schemes, and both are robust with over 99 % accuracy of the offline to online run after 14 simulation days. This allows for ROMS users to maximize use of new or existing output to quickly run additional tracer simulations.
Katixa Lajaunie-Salla, Frédéric Diaz, Cathy Wimart-Rousseau, Thibaut Wagener, Dominique Lefèvre, Christophe Yohia, Irène Xueref-Remy, Brian Nathan, Alexandre Armengaud, and Christel Pinazo
Geosci. Model Dev., 14, 295–321, https://doi.org/10.5194/gmd-14-295-2021, https://doi.org/10.5194/gmd-14-295-2021, 2021
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A biogeochemical model of planktonic food webs including a carbonate balance module is applied in the Bay of Marseille (France) to represent the carbon marine cycle expected to change in the future owing to significant increases in anthropogenic emissions of CO2. The model correctly simulates the ranges and seasonal dynamics of most variables of the carbonate system (pH). This study shows that external physical forcings have an important impact on the carbonate equilibrium in this coastal area.
Tor Nordam and Rodrigo Duran
Geosci. Model Dev., 13, 5935–5957, https://doi.org/10.5194/gmd-13-5935-2020, https://doi.org/10.5194/gmd-13-5935-2020, 2020
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In applied oceanography, a common task is to calculate the trajectory of objects floating at the sea surface or submerged in the water. We have investigated different numerical methods for doing such calculations and discuss the benefits and challenges of some common methods. We then propose a small change to some common methods that make them more efficient for this particular application. This will allow researchers to obtain more accurate answers with fewer computer resources.
Clément Bricaud, Julien Le Sommer, Gurvan Madec, Christophe Calone, Julie Deshayes, Christian Ethe, Jérôme Chanut, and Marina Levy
Geosci. Model Dev., 13, 5465–5483, https://doi.org/10.5194/gmd-13-5465-2020, https://doi.org/10.5194/gmd-13-5465-2020, 2020
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In order to reduce the cost of ocean biogeochemical models, a multi-grid approach where ocean dynamics and tracer transport are computed with different spatial resolution has been developed in the NEMO v3.6 OGCM. Different experiments confirm that the spatial resolution of hydrodynamical fields can be coarsened without significantly affecting the resolved passive tracer fields. This approach leads to a factor of 7 reduction of the overhead associated with running a full biogeochemical model.
Clark Pennelly and Paul G. Myers
Geosci. Model Dev., 13, 4959–4975, https://doi.org/10.5194/gmd-13-4959-2020, https://doi.org/10.5194/gmd-13-4959-2020, 2020
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A high-resolution ocean simulation was carried out within the Labrador Sea, a region that low-resolution climate simulations may misrepresent. We show that small-scale eddies and their associated transport are better resolved at higher resolution than at lower resolution. These eddies transport important properties to the interior of the Labrador Sea, impacting the stratification and reducing the convection extent so that it is far more accurate when compared to what observations suggest.
Eric P. Chassignet, Stephen G. Yeager, Baylor Fox-Kemper, Alexandra Bozec, Frederic Castruccio, Gokhan Danabasoglu, Christopher Horvat, Who M. Kim, Nikolay Koldunov, Yiwen Li, Pengfei Lin, Hailong Liu, Dmitry V. Sein, Dmitry Sidorenko, Qiang Wang, and Xiaobiao Xu
Geosci. Model Dev., 13, 4595–4637, https://doi.org/10.5194/gmd-13-4595-2020, https://doi.org/10.5194/gmd-13-4595-2020, 2020
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This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations to assess the robustness of climate-relevant improvements in ocean simulations associated with moving from coarse (∼1°) to eddy-resolving (∼0.1°) horizontal resolutions. Despite significant improvements, greatly enhanced horizontal resolution does not deliver unambiguous bias reduction in all regions for all models.
Mark E. Baird, Karen A. Wild-Allen, John Parslow, Mathieu Mongin, Barbara Robson, Jennifer Skerratt, Farhan Rizwi, Monika Soja-Woźniak, Emlyn Jones, Mike Herzfeld, Nugzar Margvelashvili, John Andrewartha, Clothilde Langlais, Matthew P. Adams, Nagur Cherukuru, Malin Gustafsson, Scott Hadley, Peter J. Ralph, Uwe Rosebrock, Thomas Schroeder, Leonardo Laiolo, Daniel Harrison, and Andrew D. L. Steven
Geosci. Model Dev., 13, 4503–4553, https://doi.org/10.5194/gmd-13-4503-2020, https://doi.org/10.5194/gmd-13-4503-2020, 2020
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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.
Angela A. Bahamondes Dominguez, Anna E. Hickman, Robert Marsh, and C. Mark Moore
Geosci. Model Dev., 13, 4019–4040, https://doi.org/10.5194/gmd-13-4019-2020, https://doi.org/10.5194/gmd-13-4019-2020, 2020
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The central Celtic Sea has previously been studied with a 1-D model called S2P3, showing discrepancies between observations and the model results due to poor representation of some processes. Therefore, the S2P3 model was developed to include zooplankton and phytoplankton cells' adaptation to changes in irradiance. Results demonstrate that better agreement with biological observations can be achieved when the model includes these processes and is adequately constrained.
Alexander G. López, John L. Wilkin, and Julia C. Levin
Geosci. Model Dev., 13, 3709–3729, https://doi.org/10.5194/gmd-13-3709-2020, https://doi.org/10.5194/gmd-13-3709-2020, 2020
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This article describes a regional circulation model, Doppio, for the Mid-Atlantic Bight and the Gulf of Maine. The model demonstrates useful skill in comparison to a comprehensive suite of observations. Development focused on achieving a model configuration that allows decadal-scale simulations of physical ocean circulation that can underpin studies of ecosystems and biogeochemistry. Doppio captures the temperature and salinity stratification well, along with the large-scale mean circulation.
Hiroyuki Tsujino, L. Shogo Urakawa, Stephen M. Griffies, Gokhan Danabasoglu, Alistair J. Adcroft, Arthur E. Amaral, Thomas Arsouze, Mats Bentsen, Raffaele Bernardello, Claus W. Böning, Alexandra Bozec, Eric P. Chassignet, Sergey Danilov, Raphael Dussin, Eleftheria Exarchou, Pier Giuseppe Fogli, Baylor Fox-Kemper, Chuncheng Guo, Mehmet Ilicak, Doroteaciro Iovino, Who M. Kim, Nikolay Koldunov, Vladimir Lapin, Yiwen Li, Pengfei Lin, Keith Lindsay, Hailong Liu, Matthew C. Long, Yoshiki Komuro, Simon J. Marsland, Simona Masina, Aleksi Nummelin, Jan Klaus Rieck, Yohan Ruprich-Robert, Markus Scheinert, Valentina Sicardi, Dmitry Sidorenko, Tatsuo Suzuki, Hiroaki Tatebe, Qiang Wang, Stephen G. Yeager, and Zipeng Yu
Geosci. Model Dev., 13, 3643–3708, https://doi.org/10.5194/gmd-13-3643-2020, https://doi.org/10.5194/gmd-13-3643-2020, 2020
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The OMIP-2 framework for global ocean–sea-ice model simulations is assessed by comparing multi-model means from 11 CMIP6-class global ocean–sea-ice models calculated separately for the OMIP-1 and OMIP-2 simulations. Many features are very similar between OMIP-1 and OMIP-2 simulations, and yet key improvements in transitioning from OMIP-1 to OMIP-2 are also identified. Thus, the present assessment justifies that future ocean–sea-ice model development and analysis studies use the OMIP-2 framework.
Pedro Colombo, Bernard Barnier, Thierry Penduff, Jérôme Chanut, Julie Deshayes, Jean-Marc Molines, Julien Le Sommer, Polina Verezemskaya, Sergey Gulev, and Anne-Marie Treguier
Geosci. Model Dev., 13, 3347–3371, https://doi.org/10.5194/gmd-13-3347-2020, https://doi.org/10.5194/gmd-13-3347-2020, 2020
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In the ocean circulation model NEMO, the representation of the overflow of dense Arctic waters through the Denmark Strait is investigated. In this
z-coordinate context, sensitivity tests show that the mixing parameterizations preferably act along the model grid slope. Thus, the representation of the overflow is more sensitive to resolution than to parameterization and is best when the numerical grid matches the local topographic slope.
Hideharu Sasaki, Shinichiro Kida, Ryo Furue, Hidenori Aiki, Nobumasa Komori, Yukio Masumoto, Toru Miyama, Masami Nonaka, Yoshikazu Sasai, and Bunmei Taguchi
Geosci. Model Dev., 13, 3319–3336, https://doi.org/10.5194/gmd-13-3319-2020, https://doi.org/10.5194/gmd-13-3319-2020, 2020
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A quasi-global eddying ocean hindcast simulation using a new version of our model, called OFES2, was conducted to overcome several issues in its previous version. OFES2 simulated oceanic fields from 1958 to 2016 with improved global sea surface temperature and salinity, water mass properties in the Indonesian and Arabian seas, and Niño3.4 and Indian Ocean Dipole indexes. The output from OFES2 will be useful in studying various oceanic phenomena with broad spatiotemporal scales.
Dafydd Stephenson, Simon A. Müller, and Florian Sévellec
Geosci. Model Dev., 13, 2031–2050, https://doi.org/10.5194/gmd-13-2031-2020, https://doi.org/10.5194/gmd-13-2031-2020, 2020
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Different water types are created at the sea surface with a signature based on the local conditions of the atmosphere. They then take these conditions with them into the deeper ocean, and so their journey is an important climate process to understand. In this study, we modify and repurpose a specialised model which simulates the ocean forward and backward in time to determine where new ocean water goes, where at the surface existing water comes from, and how old it is, by tracking it as a dye.
Violaine Piton, Marine Herrmann, Florent Lyard, Patrick Marsaleix, Thomas Duhaut, Damien Allain, and Sylvain Ouillon
Geosci. Model Dev., 13, 1583–1607, https://doi.org/10.5194/gmd-13-1583-2020, https://doi.org/10.5194/gmd-13-1583-2020, 2020
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Consequences of tidal dynamics on hydro-sedimentary processes are a recurrent issue in estuarine and coastal processes studies, and accurate tidal solutions are a prerequisite for modeling sediment transport. This study presents the implementation and optimization of a model configuration in terms of bathymetry and bottom friction and assess the influence of these parameters on tidal solutions, in a macro-tidal environment: the Gulf of Tonkin (Vietnam).
Alexander Barth, Aida Alvera-Azcárate, Matjaz Licer, and Jean-Marie Beckers
Geosci. Model Dev., 13, 1609–1622, https://doi.org/10.5194/gmd-13-1609-2020, https://doi.org/10.5194/gmd-13-1609-2020, 2020
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DINCAE is a method for reconstructing missing data in satellite datasets using a neural network. Satellite observations working in the optical and infrared bands are affected by clouds, which obscure part of the ocean underneath. In this paper, a neural network with the structure of a convolutional auto-encoder is developed to reconstruct the missing data based on the available cloud-free pixels in satellite images.
Jiangyu Li and Shaoqing Zhang
Geosci. Model Dev., 13, 1035–1054, https://doi.org/10.5194/gmd-13-1035-2020, https://doi.org/10.5194/gmd-13-1035-2020, 2020
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Two assimilation systems developed using two nearly independent wave models are used to study the influences of various error sources including mode bias on wave data assimilation; a statistical method is explored to make full use of the merits of individual assimilation systems for bias correction, thus improving wave analysis greatly. This study opens a door to further our understanding of physical processes in waves and associated air–sea interactions for improving wave modeling.
Heiner Dietze, Ulrike Löptien, and Julia Getzlaff
Geosci. Model Dev., 13, 71–97, https://doi.org/10.5194/gmd-13-71-2020, https://doi.org/10.5194/gmd-13-71-2020, 2020
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We present a new near-global coupled biogeochemical ocean-circulation model configuration of the Southern Ocean. The configuration features both a relatively equilibrated oceanic carbon inventory and an explicit representation of mesoscale eddies. In this paper, we document the model configuration and showcase its potential to tackle research questions such as the Southern Ocean carbon uptake dynamics on decadal timescales.
Jaap H. Nienhuis and Jorge Lorenzo-Trueba
Geosci. Model Dev., 12, 4013–4030, https://doi.org/10.5194/gmd-12-4013-2019, https://doi.org/10.5194/gmd-12-4013-2019, 2019
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The response of barrier islands to sea level rise depends on their ability to move landward through the transport of sediment from the beach to the back barrier. The BRIE model simulates these processes and the resulting landward movement of barrier islands. The novelty of the BRIE model is the incorporation of tidal inlets (gaps between barrier islands) that can transport sediment landward and therefore help keep barrier islands above sea level.
Bjarne Büchmann
Geosci. Model Dev., 12, 3915–3922, https://doi.org/10.5194/gmd-12-3915-2019, https://doi.org/10.5194/gmd-12-3915-2019, 2019
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Operational forecasting of the ocean state – e.g. used for ship route planning, sea rescue, and oil spill drift models – relies on data (forcing) obtained from weather forecasting. Unfortunately, the so-called meteorological analysis step introduces a discontinuity, which affects the ocean models adversely. In the present paper, a straightforward method to deal with the issue is introduced. Practical examples are given to illuminate the scale of the problem.
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Short summary
This paper describes the latest version of a simple model for simulating coastal oceanography in response to changes in weather and climate. The latest revision of this model makes scientific improvements but focuses on improvements that allow the model to be run simply at large scales and for long periods of time to explore the implications of (for example) future climate change along large areas of coastline.
This paper describes the latest version of a simple model for simulating coastal oceanography in...
