Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1445-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-14-1445-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
15 Mar 2021
Development and technical paper |
| 15 Mar 2021
| 15 Mar 2021
The Regional Ice Ocean Prediction System v2: a pan-Canadian ocean analysis system using an online tidal harmonic analysis
Gregory C. Smith
CORRESPONDING AUTHOR
Meteorological Research Division, Environment and Climate Change
Canada (ECCC), Dorval, H9P1J3, Canada
Yimin Liu
Meteorological Research Division, Environment and Climate Change
Canada (ECCC), Dorval, H9P1J3, Canada
Mounir Benkiran
Mercator Océan International, Toulouse, France
Kamel Chikhar
Meteorological Service of Canada, ECCC, Dorval, H9P1J3, Canada
Dorina Surcel Colan
Meteorological Service of Canada, ECCC, Dorval, H9P1J3, Canada
Audrey-Anne Gauthier
Meteorological Service of Canada, ECCC, Dorval, H9P1J3, Canada
Charles-Emmanuel Testut
Mercator Océan International, Toulouse, France
Frederic Dupont
Meteorological Service of Canada, ECCC, Dorval, H9P1J3, Canada
Ji Lei
Meteorological Service of Canada, ECCC, Dorval, H9P1J3, Canada
François Roy
Meteorological Research Division, Environment and Climate Change
Canada (ECCC), Dorval, H9P1J3, Canada
Jean-François Lemieux
Meteorological Research Division, Environment and Climate Change
Canada (ECCC), Dorval, H9P1J3, Canada
Fraser Davidson
Northwest Atlantic Fisheries Centre, Fisheries and Ocean Canada, St.
John's, Newfoundland, Canada
Related authors
Christopher Subich, Pierre Pellerin, Gregory Smith, and Frederic Dupont
Geosci. Model Dev., 13, 4379–4398, https://doi.org/10.5194/gmd-13-4379-2020, https://doi.org/10.5194/gmd-13-4379-2020, 2020
Short summary
Short summary
This work presents a semi-Lagrangian advection module for the NEMO (OPA) ocean model. Semi-Lagrangian advection transports fluid properties (temperature, salinity, velocity) between time steps by following fluid motion and interpolating from upstream locations of fluid parcels.
This method is commonly used in atmospheric models to extend time step size, but it has not previously been applied to operational ocean models. Overcoming this required a new approach for solid boundaries (coastlines).
Sergey Skachko, Mark Buehner, Stéphane Laroche, Ervig Lapalme, Gregory Smith, François Roy, Dorina Surcel-Colan, Jean-Marc Bélanger, and Louis Garand
Geosci. Model Dev., 12, 5097–5112, https://doi.org/10.5194/gmd-12-5097-2019, https://doi.org/10.5194/gmd-12-5097-2019, 2019
Short summary
Short summary
The study presents a weakly coupled atmosphere–ocean data assimilation system that uses coupled atmosphere–ocean–ice short-term forecasts as background states for atmospheric and ocean systems that independently compute atmospheric and ocean analyses. This system leads to better agreement between the coupled atmosphere–ocean analyses and coupled forecasts that have been used operationally for the last year.
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Adrienne Tivy, Joey Angnatok, François Roy, Gregory Smith, Frédéric Dupont, and Adrian K. Turner
The Cryosphere, 18, 1685–1708, https://doi.org/10.5194/tc-18-1685-2024, https://doi.org/10.5194/tc-18-1685-2024, 2024
Short summary
Short summary
We use a sea ice model to reproduce ice growth observations from two buoys deployed on coastal sea ice and analyze the improvements brought by new physics that represent the presence of saline liquid water in the ice interior. We find that the new physics with default parameters degrade the model performance, with overly rapid ice growth and overly early snow flooding on top of the ice. The performance is largely improved by simple modifications to the ice growth and snow-flooding algorithms.
Jean-Francois Lemieux, William Lipscomb, Anthony Craig, David A. Bailey, Elizabeth Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frederic Dupont, David Hebert, and Richard Allard
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-239, https://doi.org/10.5194/gmd-2023-239, 2024
Preprint under review for GMD
Short summary
Short summary
We present the latest version of the CICE model. CICE solves equations that describe the dynamics and the growth/melt of sea ice. To do so, the domain is divided in grid cells and the variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows a natural coupling with some oceanic and atmospheric models. It also allows the transport of ice in narrow channels.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Jean-Philippe Paquin, François Roy, Gregory C. Smith, Sarah MacDermid, Ji Lei, Frédéric Dupont, Youyu Lu, Stephanne Taylor, Simon St-Onge-Drouin, Hauke Blanken, Michael Dunphy, and Nancy Soontiens
EGUsphere, https://doi.org/10.5194/egusphere-2023-42, https://doi.org/10.5194/egusphere-2023-42, 2023
Preprint withdrawn
Short summary
Short summary
This paper present the Coastal Ice-Ocean Prediction System implemented operationally at Environment and climate change Canada. The objective is to enhance the numerical guidance in coastal areas to support electronic navigation and response to environmental emergencies in the aquatic environment. Model evaluation against observations shows improvements for most surface ocean variables in the coastal system compared to current coarser-resolution operational systems.
Frédéric Dupont, Dany Dumont, Jean-François Lemieux, Elie Dumas-Lefebvre, and Alain Caya
The Cryosphere, 16, 1963–1977, https://doi.org/10.5194/tc-16-1963-2022, https://doi.org/10.5194/tc-16-1963-2022, 2022
Short summary
Short summary
In some shallow seas, grounded ice ridges contribute to stabilizing and maintaining a landfast ice cover. A scheme has already proposed where the keel thickness varies linearly with the mean thickness. Here, we extend the approach by taking into account the ice thickness and bathymetry distributions. The probabilistic approach shows a reasonably good agreement with observations and previous grounding scheme while potentially offering more physical insights into the formation of landfast ice.
Jean-François Lemieux, L. Bruno Tremblay, and Mathieu Plante
The Cryosphere, 14, 3465–3478, https://doi.org/10.5194/tc-14-3465-2020, https://doi.org/10.5194/tc-14-3465-2020, 2020
Short summary
Short summary
Sea ice pressure poses great risk for navigation; it can lead to ship besetting and damages. Sea ice forecasting systems can predict the evolution of pressure. However, these systems have low spatial resolution (a few km) compared to the dimensions of ships. We study the downscaling of pressure from the km-scale to scales relevant for navigation. We find that the pressure applied on a ship beset in heavy ice conditions can be markedly larger than the pressure predicted by the forecasting system.
Christopher Subich, Pierre Pellerin, Gregory Smith, and Frederic Dupont
Geosci. Model Dev., 13, 4379–4398, https://doi.org/10.5194/gmd-13-4379-2020, https://doi.org/10.5194/gmd-13-4379-2020, 2020
Short summary
Short summary
This work presents a semi-Lagrangian advection module for the NEMO (OPA) ocean model. Semi-Lagrangian advection transports fluid properties (temperature, salinity, velocity) between time steps by following fluid motion and interpolating from upstream locations of fluid parcels.
This method is commonly used in atmospheric models to extend time step size, but it has not previously been applied to operational ocean models. Overcoming this required a new approach for solid boundaries (coastlines).
Mathieu Plante, Bruno Tremblay, Martin Losch, and Jean-François Lemieux
The Cryosphere, 14, 2137–2157, https://doi.org/10.5194/tc-14-2137-2020, https://doi.org/10.5194/tc-14-2137-2020, 2020
Short summary
Short summary
We study the formation of ice arches between two islands using a model that resolves crack initiation and propagation. This model uses a damage parameter to parameterize the presence or absence of cracks in the ice. We find that the damage parameter allows for cracks to propagate in the ice but in a different orientation than predicted by theory. The results call for improvement in how stress relaxation associated with this damage is parameterized.
Angela Cheng, Barbara Casati, Adrienne Tivy, Tom Zagon, Jean-François Lemieux, and L. Bruno Tremblay
The Cryosphere, 14, 1289–1310, https://doi.org/10.5194/tc-14-1289-2020, https://doi.org/10.5194/tc-14-1289-2020, 2020
Short summary
Short summary
Sea ice charts by the Canadian Ice Service (CIS) contain visually estimated ice concentration produced by analysts. The accuracy of manually derived ice concentrations is not well understood. The subsequent uncertainty of ice charts results in downstream uncertainties for ice charts users, such as models and climatology studies, and when used as a verification source for automated sea ice classifiers. This study quantifies the level of accuracy and inter-analyst agreement for ice charts by CIS.
Jean-François Lemieux and Frédéric Dupont
Geosci. Model Dev., 13, 1763–1769, https://doi.org/10.5194/gmd-13-1763-2020, https://doi.org/10.5194/gmd-13-1763-2020, 2020
Short summary
Short summary
Sea ice dynamics plays an important role in shaping the sea cover in polar regions. Winds and ocean currents exert large stresses on the sea ice cover. This can lead to the formation of long cracks and ridges, which strongly impact the exchange of heat, momentum and moisture between the atmosphere and the ocean. It is therefore crucial for a sea ice model to be able to represent these features. This article describes how internal sea ice stresses should be diagnosed from model simulations.
Sergey Skachko, Mark Buehner, Stéphane Laroche, Ervig Lapalme, Gregory Smith, François Roy, Dorina Surcel-Colan, Jean-Marc Bélanger, and Louis Garand
Geosci. Model Dev., 12, 5097–5112, https://doi.org/10.5194/gmd-12-5097-2019, https://doi.org/10.5194/gmd-12-5097-2019, 2019
Short summary
Short summary
The study presents a weakly coupled atmosphere–ocean data assimilation system that uses coupled atmosphere–ocean–ice short-term forecasts as background states for atmospheric and ocean systems that independently compute atmospheric and ocean analyses. This system leads to better agreement between the coupled atmosphere–ocean analyses and coupled forecasts that have been used operationally for the last year.
Frédéric Laliberté, Stephen E. L. Howell, Jean-François Lemieux, Frédéric Dupont, and Ji Lei
The Cryosphere, 12, 3577–3588, https://doi.org/10.5194/tc-12-3577-2018, https://doi.org/10.5194/tc-12-3577-2018, 2018
Short summary
Short summary
Ice that forms over marginal seas often gets anchored and becomes landfast. Landfast ice is fundamental to the local ecosystems, is of economic importance as it leads to hazardous seafaring conditions and is also a choice hunting ground for both the local population and large predators. Using observations and climate simulations, this study shows that, especially in the Canadian Arctic, landfast ice might be more resilient to climate change than is generally thought.
Antonio Bonaduce, Mounir Benkiran, Elisabeth Remy, Pierre Yves Le Traon, and Gilles Garric
Ocean Sci., 14, 1405–1421, https://doi.org/10.5194/os-14-1405-2018, https://doi.org/10.5194/os-14-1405-2018, 2018
F. Dupont, S. Higginson, R. Bourdallé-Badie, Y. Lu, F. Roy, G. C. Smith, J.-F. Lemieux, G. Garric, and F. Davidson
Geosci. Model Dev., 8, 1577–1594, https://doi.org/10.5194/gmd-8-1577-2015, https://doi.org/10.5194/gmd-8-1577-2015, 2015
Short summary
Short summary
1/12th degree resolution runs of Arctic--Atlantic were compared for the period 2003-2009. We found good representation of sea surface height and of its statistics; model temperature and salinity in general agreement with in situ measurements, but upper ocean properties in Beaufort Sea are challenging; distribution of concentration and volume of sea ice is improved when slowing down the ice and further improvements require better initial conditions and modifications to mixing.
Related subject area
Oceanography
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)
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean Archipelago
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Comparison of the Coastal and Regional Ocean Community Model (CROCO) and NCAR-LES in Non-hydrostatic Simulations
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Implementation of additional spectral wave field exchanges in a 3D wave-current coupled WAVEWATCH-III (version 6.07) – CROCO (version 1.2) configuration and assessment of their implications for macro-tidal coastal hydrodynamics
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
Intercomparisons of five ocean particle tracking software packages
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Arctic Ocean simulations in the CMIP6 Ocean Model Intercomparison Project (OMIP)
ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants
The Met Office operational wave forecasting system: the evolution of the regional and global models
4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry
Development and validation of a global 1∕32° surface-wave–tide–circulation coupled ocean model: FIO-COM32
Reproducible and relocatable regional ocean modelling: fundamentals and practices
Barotropic tides in MPAS-Ocean (E3SM V2): impact of ice shelf cavities
Using the two-way nesting technique AGRIF with MARS3D V11.2 to improve hydrodynamics and estimate environmental indicators
Multidecadal and climatological surface current simulations for the southwestern Indian Ocean at 1∕50° resolution
The tidal effects in the Finite-volumE Sea ice–Ocean Model (FESOM2.1): a comparison between parameterised tidal mixing and explicit tidal forcing
HIDRA2: deep-learning ensemble sea level and storm tide forecasting in the presence of seiches – the case of the northern Adriatic
Moana Ocean Hindcast – a > 25-year simulation for New Zealand waters using the Regional Ocean Modeling System (ROMS) v3.9 model
A nonhydrostatic oceanic regional model, ORCTM v1, for internal solitary wave simulation
How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9
An ensemble Kalman filter-based ocean data assimilation system improved by adaptive observation error inflation (AOEI)
GULF18, a high-resolution NEMO-based tidal ocean model of the Arabian/Persian Gulf
The Baltic Sea Model Intercomparison Project (BMIP) – a platform for model development, evaluation, and uncertainty assessment
An ensemble Kalman filter system with the Stony Brook Parallel Ocean Model v1.0
Wind work at the air-sea interface: a modeling study in anticipation of future space missions
Improved upper-ocean thermodynamical structure modeling with combined effects of surface waves and M2 internal tides on vertical mixing: a case study for the Indian Ocean
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.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-183, https://doi.org/10.5194/gmd-2023-183, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
In order to improve the Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher resolution ocean currents. To this goal a 3-km resolution regional ocean model has been developed. its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation were found to be quite realistic.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
Short summary
Short summary
A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
Short summary
Short summary
The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Francis Auclair, Peter P. Sullivan, and Paul S. Hall
EGUsphere, https://doi.org/10.5194/egusphere-2023-1657, https://doi.org/10.5194/egusphere-2023-1657, 2023
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 similarly accurate, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
Short summary
Short summary
While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
Short summary
Short summary
We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
Short summary
Short summary
Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
Short summary
Short summary
Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
Short summary
Short summary
We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
EGUsphere, https://doi.org/10.5194/egusphere-2023-715, https://doi.org/10.5194/egusphere-2023-715, 2023
Short summary
Short summary
Here a new method of modeling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean circulation and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave-current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
Short summary
Short summary
In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
Short summary
Short summary
Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
Short summary
Short summary
An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
Short summary
Short summary
Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Jilian Xiong and Parker MacCready
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-45, https://doi.org/10.5194/gmd-2023-45, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
A new offline particle tracking model, Tracker, was introduced to work with the Regional Ocean Modeling System (ROMS). Its performance was compared with four other particle tracking models and passive dye, which span a representative range of tracking algorithms. All tracking models perform similarly, especially for the first day. The comparison of multiple tracking codes in the same circulation model establishes confidence in all, and allows comparison of performance and ease of use.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
Short summary
Short summary
MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
Short summary
Short summary
Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
Short summary
Short summary
Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Manuel Aghito, Loris Calgaro, Knut-Frode Dagestad, Christian Ferrarin, Antonio Marcomini, Øyvind Breivik, and Lars Robert Hole
Geosci. Model Dev., 16, 2477–2494, https://doi.org/10.5194/gmd-16-2477-2023, https://doi.org/10.5194/gmd-16-2477-2023, 2023
Short summary
Short summary
The newly developed ChemicalDrift model can simulate the transport and fate of chemicals in the ocean and in coastal regions. The model combines ocean physics, including transport due to currents, turbulence due to surface winds and the sinking of particles to the sea floor, with ocean chemistry, such as the partitioning, the degradation and the evaporation of chemicals. The model will be utilized for risk assessment of ocean and sea-floor contamination from pollutants emitted from shipping.
Nieves G. Valiente, Andrew Saulter, Breogan Gomez, Christopher Bunney, Jian-Guo Li, Tamzin Palmer, and Christine Pequignet
Geosci. Model Dev., 16, 2515–2538, https://doi.org/10.5194/gmd-16-2515-2023, https://doi.org/10.5194/gmd-16-2515-2023, 2023
Short summary
Short summary
We document the Met Office operational global and regional wave models which provide wave forecasts up to 7 d ahead. Our models present coarser resolution offshore to higher resolution near the coastline. The increased resolution led to replication of the extremes but to some overestimation during modal conditions. If currents are included, wave directions and long period swells near the coast are significantly improved. New developments focus on the optimisation of the models with resolution.
Maxime Beauchamp, Quentin Febvre, Hugo Georgenthum, and Ronan Fablet
Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023, https://doi.org/10.5194/gmd-16-2119-2023, 2023
Short summary
Short summary
4DVarNet is a learning-based method based on traditional data assimilation (DA). This new class of algorithms can be used to provide efficient reconstructions of a dynamical system based on single observations. We provide a 4DVarNet application to sea surface height reconstructions based on nadir and future Surface Water and Ocean and Topography data. It outperforms other methods, from optimal interpolation to sophisticated DA algorithms. This work is part of on-going AI Chair Oceanix projects.
Bin Xiao, Fangli Qiao, Qi Shu, Xunqiang Yin, Guansuo Wang, and Shihong Wang
Geosci. Model Dev., 16, 1755–1777, https://doi.org/10.5194/gmd-16-1755-2023, https://doi.org/10.5194/gmd-16-1755-2023, 2023
Short summary
Short summary
A new global surface-wave–tide–circulation coupled ocean model (FIO-COM32) with a resolution of 1/32° × 1/32° is developed and validated. Both the promotion of the horizontal resolution and included physical processes are shown to be important contributors to the significant improvements in FIO-COM32 simulations. It is time to merge these separated model components (surface waves, tidal currents and ocean circulation) and start a new generation of ocean model development.
Jeff Polton, James Harle, Jason Holt, Anna Katavouta, Dale Partridge, Jenny Jardine, Sarah Wakelin, Julia Rulent, Anthony Wise, Katherine Hutchinson, David Byrne, Diego Bruciaferri, Enda O'Dea, Michela De Dominicis, Pierre Mathiot, Andrew Coward, Andrew Yool, Julien Palmiéri, Gennadi Lessin, Claudia Gabriela Mayorga-Adame, Valérie Le Guennec, Alex Arnold, and Clément Rousset
Geosci. Model Dev., 16, 1481–1510, https://doi.org/10.5194/gmd-16-1481-2023, https://doi.org/10.5194/gmd-16-1481-2023, 2023
Short summary
Short summary
The aim is to increase the capacity of the modelling community to respond to societally important questions that require ocean modelling. The concept of reproducibility for regional ocean modelling is developed: advocating methods for reproducible workflows and standardised methods of assessment. Then, targeting the NEMO framework, we give practical advice and worked examples, highlighting key considerations that will the expedite development cycle and upskill the user community.
Nairita Pal, Kristin N. Barton, Mark R. Petersen, Steven R. Brus, Darren Engwirda, Brian K. Arbic, Andrew F. Roberts, Joannes J. Westerink, and Damrongsak Wirasaet
Geosci. Model Dev., 16, 1297–1314, https://doi.org/10.5194/gmd-16-1297-2023, https://doi.org/10.5194/gmd-16-1297-2023, 2023
Short summary
Short summary
Understanding tides is essential to accurately predict ocean currents. Over the next several decades coastal processes such as flooding and erosion will be severely impacted due to climate change. Tides affect currents along the coastal regions the most. In this paper we show the results of implementing tides in a global ocean model known as MPAS–Ocean. We also show how Antarctic ice shelf cavities affect global tides. Our work points towards future research with tide–ice interactions.
Sébastien Petton, Valérie Garnier, Matthieu Caillaud, Laurent Debreu, and Franck Dumas
Geosci. Model Dev., 16, 1191–1211, https://doi.org/10.5194/gmd-16-1191-2023, https://doi.org/10.5194/gmd-16-1191-2023, 2023
Short summary
Short summary
The nesting AGRIF library is implemented in the MARS3D hydrodynamic model, a semi-implicit, free-surface numerical model which uses a time scheme as an alternating-direction implicit (ADI) algorithm. Two applications at the regional and coastal scale are introduced. We compare the two-nesting approach to the classic offline one-way approach, based on an in situ dataset. This method is an efficient means to significantly improve the physical hydrodynamics and unravel ecological challenges.
Noam S. Vogt-Vincent and Helen L. Johnson
Geosci. Model Dev., 16, 1163–1178, https://doi.org/10.5194/gmd-16-1163-2023, https://doi.org/10.5194/gmd-16-1163-2023, 2023
Short summary
Short summary
Ocean currents transport things over large distances across the ocean surface. Predicting this transport is key for tackling many environmental problems, such as marine plastic pollution and coral reef resilience. However, doing this requires a good understanding ocean currents, which is currently lacking. Here, we present and validate state-of-the-art simulations for surface currents in the southwestern Indian Ocean, which will support future marine dispersal studies across this region.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
Short summary
Short summary
Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
Marko Rus, Anja Fettich, Matej Kristan, and Matjaž Ličer
Geosci. Model Dev., 16, 271–288, https://doi.org/10.5194/gmd-16-271-2023, https://doi.org/10.5194/gmd-16-271-2023, 2023
Short summary
Short summary
We propose a new fast and reliable deep-learning architecture HIDRA2 for sea level and storm surge modeling. HIDRA2 features new feature encoders and a fusion-regression block. We test HIDRA2 on Adriatic storm surges, which depend on an interaction between tides and seiches. We demonstrate that HIDRA2 learns to effectively mimic the timing and amplitude of Adriatic seiches. This is essential for reliable HIDRA2 predictions of total storm surge sea levels.
Joao Marcos Azevedo Correia de Souza, Sutara H. Suanda, Phellipe P. Couto, Robert O. Smith, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 211–231, https://doi.org/10.5194/gmd-16-211-2023, https://doi.org/10.5194/gmd-16-211-2023, 2023
Short summary
Short summary
The current paper describes the configuration and evaluation of the Moana Ocean Hindcast, a > 25-year simulation of the ocean state around New Zealand using the Regional Ocean Modeling System v3.9. This is the first open-access, long-term, continuous, realistic ocean simulation for this region and provides information for improving the understanding of the ocean processes that affect the New Zealand exclusive economic zone.
Hao Huang, Pengyang Song, Shi Qiu, Jiaqi Guo, and Xueen Chen
Geosci. Model Dev., 16, 109–133, https://doi.org/10.5194/gmd-16-109-2023, https://doi.org/10.5194/gmd-16-109-2023, 2023
Short summary
Short summary
The Oceanic Regional Circulation and Tide Model (ORCTM) is developed to reproduce internal solitary wave dynamics. The three-dimensional nonlinear momentum equations are involved with the nonhydrostatic pressure obtained via solving the Poisson equation. The validation experimental results agree with the internal wave theories and observations, demonstrating that the ORCTM can successfully describe the life cycle of nonlinear internal solitary waves under different oceanic environments.
David E. Gwyther, Shane R. Keating, Colette Kerry, and Moninya Roughan
Geosci. Model Dev., 16, 157–178, https://doi.org/10.5194/gmd-16-157-2023, https://doi.org/10.5194/gmd-16-157-2023, 2023
Short summary
Short summary
Ocean eddies are important for weather, climate, biology, navigation, and search and rescue. Since eddies change rapidly, models that incorporate or assimilate observations are required to produce accurate eddy timings and locations, yet the model accuracy is rarely assessed below the surface. We use a unique type of ocean model experiment to assess three-dimensional eddy structure in the East Australian Current and explore two pathways in which this subsurface structure is being degraded.
Shun Ohishi, Takemasa Miyoshi, and Misako Kachi
Geosci. Model Dev., 15, 9057–9073, https://doi.org/10.5194/gmd-15-9057-2022, https://doi.org/10.5194/gmd-15-9057-2022, 2022
Short summary
Short summary
An adaptive observation error inflation (AOEI) method was proposed for atmospheric data assimilation to mitigate erroneous analysis updates caused by large observation-minus-forecast differences for satellite brightness temperature around clear- and cloudy-sky boundaries. This study implemented the AOEI with an ocean data assimilation system, leading to an improvement of analysis accuracy and dynamical balance around the frontal regions with large meridional temperature differences.
Diego Bruciaferri, Marina Tonani, Isabella Ascione, Fahad Al Senafi, Enda O'Dea, Helene T. Hewitt, and Andrew Saulter
Geosci. Model Dev., 15, 8705–8730, https://doi.org/10.5194/gmd-15-8705-2022, https://doi.org/10.5194/gmd-15-8705-2022, 2022
Short summary
Short summary
More accurate predictions of the Gulf's ocean dynamics are needed. We investigate the impact on the predictive skills of a numerical shelf sea model of the Gulf after changing a few key aspects. Increasing the lateral and vertical resolution and optimising the vertical coordinate system to best represent the leading physical processes at stake significantly improve the accuracy of the simulated dynamics. Additional work may be needed to get real benefit from using a more realistic bathymetry.
Matthias Gröger, Manja Placke, H. E. Markus Meier, Florian Börgel, Sandra-Esther Brunnabend, Cyril Dutheil, Ulf Gräwe, Magnus Hieronymus, Thomas Neumann, Hagen Radtke, Semjon Schimanke, Jian Su, and Germo Väli
Geosci. Model Dev., 15, 8613–8638, https://doi.org/10.5194/gmd-15-8613-2022, https://doi.org/10.5194/gmd-15-8613-2022, 2022
Short summary
Short summary
Comparisons of oceanographic climate data from different models often suffer from different model setups, forcing fields, and output of variables. This paper provides a protocol to harmonize these elements to set up multidecadal simulations for the Baltic Sea, a marginal sea in Europe. First results are shown from six different model simulations from four different model platforms. Topical studies for upwelling, marine heat waves, and stratification are also assessed.
Shun Ohishi, Tsutomu Hihara, Hidenori Aiki, Joji Ishizaka, Yasumasa Miyazawa, Misako Kachi, and Takemasa Miyoshi
Geosci. Model Dev., 15, 8395–8410, https://doi.org/10.5194/gmd-15-8395-2022, https://doi.org/10.5194/gmd-15-8395-2022, 2022
Short summary
Short summary
We develop an ensemble-Kalman-filter-based regional ocean data assimilation system in which satellite and in situ observations are assimilated at a daily frequency. We find the best setting for dynamical balance and accuracy based on sensitivity experiments focused on how to inflate the ensemble spread and how to apply the analysis update to the model evolution. This study has a broader impact on more general data assimilation systems in which the initial shocks are a significant issue.
Hector S. Torres, Patrice Klein, Jinbo Wang, Alexander Wineteer, Bo Qiu, Andrew F. Thompson, Lionel Renault, Ernesto Rodriguez, Dimitris Menemenlis, Andrea Molod, Christopher N. Hill, Ehud Strobach, Hong Zhang, Mar Flexas, and Dragana Perkovic-Martin
Geosci. Model Dev., 15, 8041–8058, https://doi.org/10.5194/gmd-15-8041-2022, https://doi.org/10.5194/gmd-15-8041-2022, 2022
Short summary
Short summary
Wind work at the air-sea interface is the scalar product of winds and currents and is the transfer of kinetic energy between the ocean and the atmosphere. Using a new global coupled ocean-atmosphere simulation performed at kilometer resolution, we show that all scales of winds and currents impact the ocean dynamics at spatial and temporal scales. The consequential interplay of surface winds and currents in the numerical simulation motivates the need for a winds and currents satellite mission.
Zhanpeng Zhuang, Quanan Zheng, Yongzeng Yang, Zhenya Song, Yeli Yuan, Chaojie Zhou, Xinhua Zhao, Ting Zhang, and Jing Xie
Geosci. Model Dev., 15, 7221–7241, https://doi.org/10.5194/gmd-15-7221-2022, https://doi.org/10.5194/gmd-15-7221-2022, 2022
Short summary
Short summary
We evaluate the impacts of surface waves and internal tides on the upper-ocean mixing in the Indian Ocean. The surface-wave-generated turbulent mixing is dominant if depth is < 30 m, while the internal-tide-induced mixing is larger than surface waves in the ocean interior from 40
to 130 m. The simulated thermal structure, mixed layer depth and surface current are all improved when the mixing schemes are jointly incorporated into the ocean model because of the strengthened vertical mixing.
Cited articles
Amante, C. and Eakins, B. W.: ETOPO1 1-Arc-Minute Global Relief Model:
Procedures, Data Sources and Analysis, Tech. rep., NOAA Technical Memorandum
NESDIS NGDC-24, National Geophysical Data Center, NOAA,
https://doi.org/10.7289/V5C8276M, 2009.
Arbic, B. K., St-Laurent, P., Sutherland, G., and Garrett, C.: On the resonance and influence of the tides in Ungava Bay and Hudson Strait,
Geophys. Res. Lett., 34, L17606, https://doi.org/10.1029/2007GL030845, 2007.
Bell, M. J., Schiller, A., Le Traon, P.-Y., Smith, N. R., Dombrowsky, E., and Wilmer-Becker, K.: An introduction to GODAE OceanView, J. Oper. Oceanogr., 8, s2–s11, https://doi.org/10.1080/1755876X.2015.1022041, 2015.
Benkiran, M. and Greiner, E.: Impact of the Incremental Analysis Updates on a Real-Time System of the North Atlantic Ocean, J. Atmos. Ocean. Tech., 25, 2055–2073, 2008.
Blanke, B. and Delecluse, P.: Variability of the Tropical Atlantic Ocean Simulated by a General Circulation Model with Two Different Mixed-Layer Physics, J. Phys. Oceanogr., 23, 1363–1388, 1993.
Bloom, S. C., Takacs, L. L., Da Silva, A. M., and Ledvina, D.: Data assimilation using incremental analysis updates, Mon. Weather Rev., 124, 1256–1271, 1996.
Boutin, G., Lique, C., Ardhuin, F., Rousset, C., Talandier, C., Accensi, M., and Girard-Ardhuin, F.: Towards a coupled model to investigate wave–sea ice interactions in the Arctic marginal ice zone, The Cryosphere, 14, 709–735, https://doi.org/10.5194/tc-14-709-2020, 2020.
Boyer, T. P., Antonov, J. I., Baranova, O. K., Coleman, C., Garcia, H. E., Grodsky, A., Johnson, D. R., Locarnini, R. A., Mishonov, A. V., O'Brien, T. D., Paver, C. R., Reagan, J. R., Seidov, D., Smolyar, I. V., and Zweng, M. M.: World Ocean Database 2013, NOAA Atlas NESDIS 72, edited by: Levitus, S. and Mishonov, A., Silver Spring, MD, 209 pp.,
https://doi.org/10.7289/V5NZ85MT, 2013.
Brasnett, B. and Colan, D. S.: Assimilating retrievals of sea surface temperature from VIIRS and AMSR2, J. Atmos. Ocean. Tech., 33, 361–375, https://doi.org/10.1175/JTECH-D-15-0093.1, 2016.
Browne, P. A., de Rosnay, P., Zuo, H., Bennett, A. and Dawson, A.: Weakly coupled ocean–atmosphere data assimilation in the ECMWF NWP system, Remote Sens., 11, 234, https://doi.org/10.3390/rs11030234, 2019.
Buehner, M., Caya, A., Pogson, L., Carrieres, T., and Pestieau, P.: A New Environment Canada Regional Ice Analysis System, Atmos. Ocean, 51, 18–34, 2013.
Buehner, M., Caya, A., Carrieres, T., and Pogson, L.: Assimilation of SSMIS and ASCAT data and the replacement of highly uncertain estimates in the
Environment Canada Regional Ice Prediction System, Q. J. Roy. Meteor. Soc.,
142, 562–573, 2016.
Carrère, L. and Lyard, F.: Modelling the barotropic response of the global ocean to atmospheric wind and pressure forcing -comparisons with observations, Geophys. Res. Lett., 30, 1275, https://doi.org/10.1029/2002GL016473, 2003.
Carrère, L., Lyard, F., Cancet, M., Roblou, L., and Guillot, A.: ES 2012: a new global tidal model taking advantage of nearly 20 years of altimetry measurements, in: Proc. 20 Years of Progress in Radar Altimetry Symp., Venice-Lido, Italy, 22–29, 2012.
Chao, Y., Farrara, J. D., Zhang, H., Armenta, K. J., Centurioni, L., Chavez, F., Girton, J. B., Rudnick, D., and Walter, R. K.: Development, implementation, and validation of a California coastal ocean modeling, data
assimilation, and forecasting system, Deep-Sea Res. Pt. II, 151, 49–63, 2018.
Chikhar, K., Lemieux, J. F., Dupont, F., Roy, F., Smith, G. C., Brady, M., Howell, S. E., and Beaini, R.: Sensitivity of Ice Drift to Form Drag and Ice Strength Parameterization in a Coupled Ice–Ocean Model, Atmos. Ocean, 57, 329–349, 2019.
Cho, K.-H., Li, Y., Wang, H., Park, K.-S., Choi, J.-Y., Shin, K.-I., and Kwon, J.-I.: Development and Validation of an Operational Searchand Rescue Modelling System for the Yellow Sea and the East and South China Seas, J. Atmos. Ocean Tech., 31, 197–215, 2014.
Desroziers, G., Berre, L., Chapnik, B., and Polli, P.: Diagnosis of observation, background and analysis-error statistics in observation space, Q. J. Roy. Meteor. Soc., 131, 3385–3396,
https://doi.org/10.1256/qj.05.108, 2005.
Dibarboure, G., Pujol, M.-I., Briol, F., Le Traon, P. Y., Larnicol, G., Picot, N., Mertz, F., and Ablain, M.: Jason-2 in DUACS: Updated system description, first tandem results and impact on processing and products, Mar. Geod., 34, 214–241, 2011.
Divakaran, P., Brassington, G. B., Ryan, A. G., Regnier, C., Spindler, T., Mehra, A., Hernandez, F., Smith, G., Liu, Y., and Davidson, F.: GODAE OceanView Class-4 Inter-comparison for the Australian Region, J. Oper. Oceanogr., 8, s112–s126, https://doi.org/10.1080/1755876X.2015.1022333, 2015.
Dupont, F., Higginson, S., Bourdallé-Badie, R., Lu, Y., Roy, F., Smith, G. C., Lemieux, J.-F., Garric, G., and Davidson, F.: A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans, Geosci. Model Dev., 8, 1577–1594, https://doi.org/10.5194/gmd-8-1577-2015, 2015.
Dupont F., Smith, G., Liu, Y., Chikhar, K., Surcel Colan, D., Lei, J., Roy, F., Pellerin, P.: Changes from version 1.3.0 to version 2.0.0 of the Regional Ice Ocean Prediction System (RIOPS), CMC Tech Doc., 39 pp., available at:
https://collaboration.cmc.ec.gc.ca/cmc/cmoi/product_guide/docs/tech_notes/technote_riops-200_e.pdf (lats access: 25 February 2021), 2019.
Egbert, G. D. and Erofeeva, S. Y.: Efficient inverse modeling of barotropic ocean tides, J. Atmos. Ocean. Tech., 19, 183–204, 2002.
Gaspar, P., Grégoris, Y., and Lefevre, J. M.: A simple eddy kinetic energy model for simulations of the oceanic vertical mixing: Tests at station Papa and Long-Term Upper Ocean Study site, J. Geophys. Res.-Oceans, 95, 16179–16193, 1990.
Hirose, N., Usui, N., Sakamoto, K., Tsujino, H., Yamanaka, G., Nakano, H., Urakawa, S., Toyoda, T., Fujii, Y., and Kohno, N.: Development of a new operational system for monitoring and forecasting coastal and open-ocean states around Japan, Ocean Dynam., 69, 1333–1357, 2019.
Hunke, E. C.: Viscous-plastic sea ice dynamics with the EVP model:
linearization issues, J. Comput. Phys., 170, 18–38, 2001.
Hunke, E. C. and Lipscomb, W. H.: CICE: The Los Alamos sea ice model, Documentation and software user's manual version 4.0 (Tech. Rep.
LA-CC-06-012), Los Alamos National Laboratory, Los Alamos, NM, 2008.
Jacobs, G. A., D'Addezio, J. M., Bartels, B., and Spence, P. L.: Constrained scales in ocean forecasting, Adv. Space Res., https://doi.org/10.1016/j.asr.2019.09.018, online first, 2019.
Jung, T., Gordon, N. D., Bauer, P., Bromwich, D. H., Chevallier, M., Day, J.
J., Dawson, J., Doblas-Reyes, F., Fairall, C., Goessling, H. F., Holland,
M., Inoue, J., Iversen, T., Klebe, S., Lemke, P., Losch, M., Makshtas. A.,
Mills, B., Nurmi, P., Perovich, D., Reid, P., Renfrew, I. A., Smith, G.,
Svensson, G., Tolstykh, M., and Yang, Q.: Advancing Polar Prediction
Capabilities on Daily to Seasonal Time Scales, B. Am. Meteorol. Soc.,
https://doi.org/10.1175/BAMS-D-14-00246.1, 2016.
King, R. R., While, J., Martin, M. J., Lea, D. J., Lemieux-Dudon, B., Waters, J., and O'Dea, E.: Improving the initialisation of the Met Office operational shelf-seas model, Ocean Model., 130, 1–14, 2018.
Kleptsova, O. and Pietrzak, J. D.: High resolution tidal model of Canadian Arctic Archipelago, Baffin and Hudson Bay, Ocean Model., 128, 15–47, 2018.
Kourafalou, V. H., De Mey, P., Staneva, J., Ayoub, N., Barth, A., Chao, Y., Cirano M., Fiechter, J., Herzfeld, M., Kurapov, A., and Moore, A. M.: Coastal Ocean Forecasting: science foundation and user benefits, J Oper. Oceanogr., 8, s147–s167, 2015.
Large, W. G. and Yeager, S. G.: Diurnal to decadal global forcing for ocean and seaice models, NCAR Technical Note, 1–22, 2004.
Lellouche, J.-M., Le Galloudec, O., Drévillon, M., Régnier, C., Greiner, E., Garric, G., Ferry, N., Desportes, C., Testut, C.-E., Bricaud, C., Bourdallé-Badie, R., Tranchant, B., Benkiran, M., Drillet, Y., Daudin, A., and De Nicola, C.: Evaluation of global monitoring and forecasting systems at Mercator Océan, Ocean Sci., 9, 57–81, https://doi.org/10.5194/os-9-57-2013, 2013.
Lellouche, J.-M., Greiner, E., Le Galloudec, O., Garric, G., Regnier, C., Drevillon, M., Benkiran, M., Testut, C.-E., Bourdalle-Badie, R., Gasparin, F., Hernandez, O., Levier, B., Drillet, Y., Remy, E., and Le Traon, P.-Y.: Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time 1∕12° high-resolution system, Ocean Sci., 14, 1093–1126, https://doi.org/10.5194/os-14-1093-2018, 2018.
Lemieux, J.-F., Tremblay, L. B., Dupont, F., Plante, M., Smith, G. C., and Dumont, D.: A basal stress parameterization for modeling landfast ice, J. Geophys. Res., 120, 3157–3173, https://doi.org/10.1002/2014JC010678, 2015.
Lemieux, J.-F., Beaudoin, C., Dupont, F., Roy, F., Smith, G. C., Shlyaeva, A., Buehner, M., Caya, A., Chen, J., Carrieres, T., Pogson, L.,
DeRepentigny, P., Plante, A., Pestieau, P., Pellerin, P., Ritchie, H.,
Garric, G., and Ferry, N.: The Regional Ice Prediction System (RIPS):
verification of forecast sea ice concentration, Q. J.
Roy. Meteor. Soc., 142, 632–643, https://doi.org/10.1002/qj.2526, 2016a.
Lemieux, J.-F., Dupont, F., Blain, P., Roy, F., Smith, G. C., and Flato, G. M.: Improving the simulation of landfast ice by combining tensile strength and a parameterization for grounded ridges, J. Geophys. Res., 121, 7354–7368, 2016b.
Lemieux, J.-F., Lei, J., Dupont, F., Roy, F., Losch, M., Lique, C. and Laliberté, F.: The Impact of Tides on Simulated Landfast Ice in a
Pan-Arctic Ice-Ocean Model, J. Geophys. Res.-Oceans, 123, 7747–7762,
2018.
Lin, H., Merryfield, W. J., Muncaster, R., Smith, G. C., Markovic, M., Dupont, F., Roy, F., Lemieux, J.-F., Dirkson, A., Kharin, V. V., and Lee, W. S.: The Canadian Seasonal to Interannual Prediction System Version 2 (CanSIPSv2), Weather Forecast., 35, 1317–1343, 2020.
Lipscomb, W. H., Hunke, E. C., Maslowski, W., and Jakacki, J.: Ridging, strength, and stability in high-resolution sea ice models, J. Geophys. Res., 112, C03S91, https://doi.org/10.1029/2005JC003355, 2007.
Madec, G.: NEMO reference manual, ocean dynamics component: NEMO-OPA. Preliminary version, Note du Pole de modélisation, Institut Pierre-Simon Laplace (IPSL), France, 27, 1288–1619, 2008.
Madec, G. and Imbard, M.: A global ocean mesh to overcome the North Pole singularity, Clim. Dynam., 12, 381–388, 1996.
Madec, G., Delecluse, P., Imbard, M., and Levy, C.: OPA 8.1 general
circulation model reference manual, Notes de l'IPSL, University P. et M.
Curie, B102 T15-E5, Paris, No. 11, 91 pp., 1998.
Masson, D. and Cummins, P. F.: Temperature trends and interannual
variability in the Strait of Georgia, British Columbia, Continental Shelf
Res., 27, 634–649, 2007.
McTaggart-Cowan, R., Vaillancourt, P. A., Zadra, A., Chamberland, S., Charron, M., Corvec, S., Milbrandt, J. A., Paquin-Ricard, D., Patoine, A., Roch, M., Separovic, L., and Yang J.: Modernization of atmospheric physics parameterization in Canadian NWP, J. Adv. Model. Earth Sy., 11, 3593–3635, https://doi.org/10.1029/2019MS001781, 2019.
Mehra, A. and Rivin, I.: A real time ocean forecast system for the North Atlantic Ocean, Terr. Atmos. Ocean. Sci., 21, 211–228, 2010.
Moore, A. M., Arango, H. G., Broquet, G., Powell, B. S., Zavala-Garay, J., and Weaver, A. T.: The Regional Ocean Modelling System (ROMS) 4-dimensional variational data assimilation systems, Part I: System overview and formulation, Prog. Oceanogr., 91, 34–49, 2011.
Nudds, S., Lu, Y., Higginson, S., Haigh, S., Paquin, J.-P.,
O'Flaherty-Sproul, M., Taylor, S., Blanken, H., Marcotte, G., Smith, G. C.,
Bernier, N., MacAulay, P., Wu, Y., Zhai, L., Hu, X., Chanut, J., Dunphy, M.,
Dupont, F., Greenberg, D., Davidson, F., and Page, F.: Evaluation of Structured and Unstructured Models for Application in Operational Ocean Forecasting in Nearshore Waters, J. Mar. Sci. Eng., 8, 484, https://doi.org/10.3390/jmse8070484, 2020.
O'Reilly, C. T., Solvason, R., and Solomon, C.: Where are the world's largest tides?, in: BIO Annual Report “2004 in Review,”, edited by: Ryan, J., Biotechnol. Ind. Org., Washington D. C., 44–46, 2005.
Park, K. S., Heo, K. Y., Jun, K., Kwon, J. I., Kim, J., Choi, J. Y., Cho, K. H., Choi, B. J., Seo, S. N., Kim, Y. H., and Kim, S. D.: Development of the operational oceanographic system of Korea, Ocean Sci. J., 50, 353–369, https://doi.org/10.1007/s12601-015-0033-1, 2015.
Pawlowicz, R., Beardsley, B., and Lentz, S.: Classical tidal harmonic analysis including error estimates in MATLAB using T_TIDE,
Comput. Geosci., 28, 929–937, 2002.
Pellerin, P., Ritchie, H., Saucier, S. J., Roy, F., Desjardins, S., Valin, M., and Lee, V.: Impact of a Two-Way Coupling between an Atmospheric and an Ocean-ice Model over the Gulf of St. Lawrence, Mon. Weather Rev., 132, 1379–1398, 2004.
Pham, D., Verron, J., and Roubaud, M.: A Singular Evolutive Extended Kalman filter for data assimilation in oceanography, J. Marine Syst., 16, 323–340, 1998.
Rigor, I. and Ortmeyer, M.: The International Arctic Buoy
Programme–monitoring the Arctic Ocean for forecasting and research, Arctic
Research of the United States, 18, 1–21, 2004.
Rio, M.-H., Mulet, S., and Picot, N.: Beyond GOCE for the ocean circulation estimate: Synergetic use of altimetry, gravimetry, and in situ data provides new insight into geostrophic and Ekman currents, Geophys. Res. Lett., 41, 8918–8925, https://doi.org/10.1002/2014GL061773, 2014.
Roy, F., Chevallier, M., Smith, G. C., Dupont, F., Garric, G., Lemieux, J.-F., Lu, Y., and Davidson, F.: Arctic sea ice and freshwater sensitivity to the treatment of the atmosphere-ice-ocean surface layer. J. Geophys. Res.-Oceans, 120, 4392–4417, 2015.
Ryan, A. G., Regnier, C., Divakaran, P., Spindler, T., Mehra, A., Hernandez, F., Smith, G. C., Liu, Y., and Davidson, F.: GODAE OceanView Class 4 forecast verification framework: Global ocean inter-comparison, J. Oper. Oceanogr., 8, s98–s111, https://doi.org/10.1080/1755876X.2015.1022330, 2015.
Sakov, P., Counillon, F., Bertino, L., Lisæter, K. A., Oke, P. R., and Korablev, A.: TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic, Ocean Sci., 8, 633–656, https://doi.org/10.5194/os-8-633-2012, 2012.
Saucier, F. J. and Chassé, J.: Tidal circulation and buoyancy effects in the St. Lawrence Estuary, Atmos. Ocean, 38, 505–556, 2000.
Saucier, F. J., Roy, F., Gilbert, D., Pellerin, P., and Ritchie, H.: The formation of water masses and sea ice in the Gulf of St. Lawrence, J. Geophys. Res., 108, 3269–3289, 2003.
Saucier, F. J., Senneville, S., Prinsenberg, S., Roy, F., Smith, G., Gachon, P., Caya, D., and Laprise, R.: Modelling the Sea Ice-Ocean Seasonal Cycle in Hudson Bay, Foxe Basin and Hudson Strait, Canada. Clim. Dyn., 23, 303–326, 2004.
Smith, G. C., Roy, F., and Brasnett, B.: Evaluation of an Operational Ice-Ocean Analysis and Forecasting System for the Gulf of St. Lawrence, Q. J. Roy. Meteor. Soc., 139, 419–433, https://doi.org/10.1002/qj.1982, 2012.
Smith, G. C., Davidson, F., and Lu, Y.: The CONCEPTS Initiative: Canadian Operational Network of Coupled Environmental Prediction Systems, J. Ocean Technol., 8, 80–81, 2013.
Smith, G. C., Roy, F., Reszka, M., Surcel Colan, D., He, Z., Deacu, D., Belanger, J. M., Skachko, S., Liu, Y., Dupont, F., and Lemieux, J.-F.: Sea ice forecast verification in the Canadian global ice ocean prediction system, Q. J. Roy. Meteor. Soc., 142, 659–671, https://doi.org/10.1002/qj.2555, 2016.
Smith, G. C., Bélanger, J. M., Roy, F., Pellerin, P., Ritchie, H., Onu, K., Roch, M., Zadra, A., Surcel Colan, D., Winter, B., and Fontecilla, J. S.: Impact of Coupling with an Ice-Ocean Model on Global Medium-Range NWP Forecast Skill, Mon. Weather Rev., 146, 1157–1180, https://doi.org/10.1175/MWR-D-17-0157.1, 2018.
Smith, G. C., Surcel Colan, D., Chikhar, K., and Liu, Y.: Global Ice Ocean Prediction System (GIOPS): Update from version 2.3.1 to version 3.0.0. Technical Documentation for GIOPSv3.0, CMC Tech Doc., 49 pp., available at: https://collaboration.cmc.ec.gc.ca/cmc/cmoi/product_guide/docs/tech_notes/technote_giops-300_e.pdf (last access: 25 February 2021), 2019a.
Smith, G. C., Allard, R., Babin, M., Bertino, L., Chevallier, M., Corlett, G., Crout, J., Davidson, F., Delille, B., Gille, S. T., Hebert, D., Hyder, P., Intrieri, J., Lagunas, J., Larnicol, G., Kaminski, T., Kater, B., Kauker, F., Marec, C., Mazloff, M., Metzger, E. J., Mordy, C., O'Carroll, A., Olsen, S. M., Phelps, M., Posey, P., Prandi, P., Rehm, E., Reid, P., Rigor, I., Sandven, S., Shupe, M., Swart, S., Smedstad, O. M., Solomon, A., Storto, A., Thibaut, P., Toole, J., Wood, K., Xie, J., Yang, Q., and the WWRP PPP Steering Group: Polar Ocean Observations: A Critical Gap in the Observing System and its effect on Environmental Predictions from Hours to a Season, Front. Mar. Sci., 6, 429, doi.org/10.3389/fmars.2019.00429, 2019b.
Soontiens, N., Allen, S. E., Latornell, D., Le Souëf, K., Machuca, I., Paquin, J.-P., Lu, Y., Thompson, K., and Korabel, V.: Storm surges in the Strait of Georgia simulated with a regional model, Atmos.-Ocean, 54, 1–21, 2016.
Sotillo, M. G., Cailleau, S., Lorente, P., Levier, B., Reffray, G., Amo-Baladrón, A., Benkiran, M., and Alvarez Fanjul, E.: The MyOcean IBI Ocean Forecast and Reanalysis Systems: operational
products and roadmap to the future Copernicus Service, J. Oper. Oceanogr.,
8, 63–79, https://doi.org/10.1080/1755876X.2015.1014663, 2015.
Sutherland, G., Soontiens, N., Davidson, F., Smith, G. C., Bernier, N., Blanken, H., Shillinger, D., Marcotte, G., Röhrs, J., Dagestad, K.-F., Christensen, K. H., and Breivik, Ø.: Evaluating the leeway coefficient of ocean drifters using operational marine environmental prediction systems, J. Atmos. Ocean. Tech., 37, 1943–1954, https://doi.org/10.1175/JTECH-D-20-0013.1, 2020.
Talagrand, O.: A posteriori evaluation and verification of analysis and assimilation algorithms, in: Proc. of ECMWF Workshop on Diagnosis of Data Assimilation System, 2–4 November, 1998, Reading, UK, 17–28, 1998.
Tang, C. L., Yao, T., Perrie, W., Detracey, B.M., Toulany, B., Dunlap E., and Wu, Y.: BIO ice-ocean and wave forecasting models and systems for eastern Canadian waters, Canadian Technical Report of Hydrography and Ocean Sciences, 261, 61 pp., 2008.
Tonani, M., Pinardi, N., Dobricic, S., Pujol, I., and Fratianni, C.: A high-resolution free-surface model of the Mediterranean Sea, Ocean Sci., 4, 1–14, https://doi.org/10.5194/os-4-1-2008, 2008.
Tonani, M., Balmaseda, M., Bertino, L., Blockley, E., Brassington, G. B., Davidson, F., Drillet, Y., Hogan, P. J., Kuragano, T., Lee, T., Mehra, A., Paranathara, F., Tanajura, C. A. S., and Wang, H.:
Status and future of global and regional ocean prediction systems, J. Oper. Oceanogr., 8, 201–220, https://doi.org/10.1080/1755876X.2015.1049892, 2015.
Toole, J. M., Krishfield, R. A., Timmermans, M.-L., and Proshutinsky, A.: The Ice-Tethered Profiler: Argo of the Arctic, Oceanography, 24, 126–135, https://doi.org/10.5670/oceanog.2011.64, 2011.
Tschudi, M., Meier, W. N., Stewart, J. S., Fowler, C., and Maslanik, J.: Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 4, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center https://doi.org/10.5067/INAWUWO7QH7B, 2019.
Umlauf, L. and Burchard, H.: A generic length-scale equation for geophysical turbulence models, J. Mar. Res., 61, 235–265, 2003.
Ungermann, M., Tremblay, L. B., Martin, T., and Losch, M.: Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the A rctic, J. Geophys. Res.-Oceans, 122, 2090–2107, 2017.
Wood, K. R., Jayne, S. R., Mordy, C. W., Bond, N., Overland, J. E., Ladd, C., Stabeno, P. J., Ekholm, A. K., Robbins, P. E., Schreck, M. B., and Heim, R.: Results of the First Arctic Heat Open Science Experiment, B. Am. Meteorol. Soc., 99, 513–520, 2018.
Xie, J., Counillon, F., Zhu, J., and Bertino, L.: An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI, Ocean Sci., 7, 609–627, https://doi.org/10.5194/os-7-609-2011, 2011.
Xue, H., Shi, L., Cousins, S., and Pettigrew, N. R.: The GoMOOS
nowcast/forecast system, Continental Shelf Res., 25, 2122–2146,
2005.
Zhang, W. G., Wilkin, J. L., and Arango, H. G.: Towards an integrated observation and modeling system in the New York Bight using variational methods. Part I: 4DVAR data assimilation, Ocean Model., 35, 119–133, 2010.
Zedel, L., Wang, Y., Davidson, F., and Xu, J.: Comparing ADCP data collected during a seismic survey off the coast of Newfoundland with analysis data from the CONCEPTS operational ocean model, J. Oper. Oceanogr., 11, 100–111, 2018.
Zhuang, S. Y., Fu, W. W., and She, J.: A pre-operational three Dimensional variational data assimilation system in the North/Baltic Sea, Ocean Sci., 7, 771–781, https://doi.org/10.5194/os-7-771-2011, 2011.
Short summary
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.
Canada's coastlines include diverse ocean environments. In response to the strong need to...
Special issue