Articles | Volume 5-opsr
https://doi.org/10.5194/sp-5-opsr-5-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/sp-5-opsr-5-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A description of existing operational ocean forecasting services around the globe
Departmento de Meteorologia, Instituto de Geociências, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
Enrique Alvarez-Fanjul
Mercator Ocean International, Toulouse, France
Arthur Capet
ECOMOD, Royal Belgian Institutes of Natural Sciences, Brussels, Belgium
Stefania Ciliberti
Nologin Oceanic Weather Systems, Santiago de Compostela, Spain
Emanuela Clementi
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Bologna, Italy
Boris Dewitte
Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Coquimbo, Chile
Departamento de Biología, Facultad de Ciencias del Mar, Universidad Católica del Norte, Coquimbo, Chile
CECI, Université de Toulouse, CERFACS/CNRS, Toulouse, France
Matias Dinápoli
Centro de Investigaciones del Mar y la Atmosfera (CIMA/CONICET-UBA), Buenos Aires, Argentina
Ghada El Serafy
Data Science and Water Quality, Deltares, Delft, the Netherlands
Patrick Hogan
NOAA, National Centers for Environment Information, Stennis Space Center, Hancock County, Mississippi, United States
Sudheer Joseph
Indian National Centre for Ocean Information Services (INCOIS), Pragathi Nagar, Nizampet, Hyderabad, Telangana 500090, India
Yasumasa Miyazawa
Application Laboratory, Research Institute for Value Added Information Generation, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
Ivonne Montes
Instituto Geofisico del Perú (IGP), Lima, Peru
Diego A. Narvaez
COPAS Coastal and Departamento de Oceanografía, Universidad de Concepción, Concepción, Chile
Heather Regan
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Claudia G. Simionato
Centro de Investigaciones del Mar y la Atmosfera (CIMA/CONICET-UBA), Buenos Aires, Argentina
Gregory C. Smith
Meteorological Research Division, Environment and Climate Change Canada, Montreal, Canada
Joanna Staneva
Helmholtz-Zentrum Hereon GmbH, Geesthacht, Germany
Clemente A. S. Tanajura
Department of Earth and Environmental Physics, Physics Institute, Federal University of Bahia (UFBA), Salvador, Brazil
Pramod Thupaki
Hakai Institute, Victoria, Canada
currently at: Institute of Ocean Sciences, Fisheries and Oceans, Sidney, Canada
Claudia Urbano-Latorre
Centro de Investigaciones Oceanográficas e Hidrográficas del Caribe DIMAR, Bolivar, Colombia
Jennifer Veitch
Egagasini Node, South African Environmental Observation Network (SAEON), Cape Town, South Africa
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Jennifer Veitch, Enrique Alvarez-Fanjul, Arthur Capet, Stefania Ciliberti, Mauro Cirano, Emanuela Clementi, Fraser Davidson, Ghada el Serafy, Guilherme Franz, Patrick Hogan, Sudheer Joseph, Svitlana Liubartseva, Yasumasa Miyazawa, Heather Regan, and Katerina Spanoudaki
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This preprint is open for discussion and under review for Ocean Science (OS).
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Salvatore Causio, Seimur Shirinov, Ivan Federico, Giovanni De Cillis, Emanuela Clementi, Lorenzo Mentaschi, and Giovanni Coppini
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Roderik van de Wal, Angélique Melet, Debora Bellafiore, Paula Camus, Christian Ferrarin, Gualbert Oude Essink, Ivan D. Haigh, Piero Lionello, Arjen Luijendijk, Alexandra Toimil, Joanna Staneva, and Michalis Vousdoukas
State Planet, 3-slre1, 5, https://doi.org/10.5194/sp-3-slre1-5-2024, https://doi.org/10.5194/sp-3-slre1-5-2024, 2024
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Sea level rise has major impacts in Europe, which vary from place to place and in time, depending on the source of the impacts. Flooding, erosion, and saltwater intrusion lead, via different pathways, to various consequences for coastal regions across Europe. This causes damage to assets, the environment, and people for all three categories of impacts discussed in this paper. The paper provides an overview of the various impacts in Europe.
Lianne C. Harrison, Jennifer A. Graham, Piyali Chowdhury, Tiago A. M. Silva, Danja P. Hoehn, Alakes Samanta, Kunal Chakraborty, Sudheer Joseph, T. M. Balakrishnan Nair, and T. Srinivasa Kumar
EGUsphere, https://doi.org/10.5194/egusphere-2024-3096, https://doi.org/10.5194/egusphere-2024-3096, 2024
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Particle tracking models allow us to explore pathways of floating marine litter, source-to-sink, between countries. This study showed the influence of seasonality for dispersal in Bay of Bengal and how ocean current forcing impacts model performance. Most litter beached on the country of origin, but there was a greater spread shown between countries during the post-monsoon period (Oct–Jan). Results will inform future model developments as well as management of marine litter in the region.
Ronan McAdam, Giulia Bonino, Emanuela Clementi, and Simona Masina
State Planet, 4-osr8, 13, https://doi.org/10.5194/sp-4-osr8-13-2024, https://doi.org/10.5194/sp-4-osr8-13-2024, 2024
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In the summer of 2022, a regional short-term forecasting system was able to predict the onset, spread, peaks, and decay of a record-breaking marine heatwave in the Mediterranean Sea up to 10 d in advance. Satellite data show that the event was record-breaking in terms of basin-wide intensity and duration. This study demonstrates the potential of state-of-the-art forecasting systems to provide early warning of marine heatwaves for marine activities (e.g. conservation and aquaculture).
Anna Teruzzi, Ali Aydogdu, Carolina Amadio, Emanuela Clementi, Simone Colella, Valeria Di Biagio, Massimiliano Drudi, Claudia Fanelli, Laura Feudale, Alessandro Grandi, Pietro Miraglio, Andrea Pisano, Jenny Pistoia, Marco Reale, Stefano Salon, Gianluca Volpe, and Gianpiero Cossarini
State Planet, 4-osr8, 15, https://doi.org/10.5194/sp-4-osr8-15-2024, https://doi.org/10.5194/sp-4-osr8-15-2024, 2024
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A noticeable cold spell occurred in Eastern Europe at the beginning of 2022 and was the main driver of intense deep-water formation and the associated transport of nutrients to the surface. Southeast of Crete, the availability of both light and nutrients in the surface layer stimulated an anomalous phytoplankton bloom. In the area, chlorophyll concentration (a proxy for bloom intensity) and primary production were considerably higher than usual, suggesting possible impacts on fishery catches.
Wei Chen and Joanna Staneva
State Planet, 4-osr8, 7, https://doi.org/10.5194/sp-4-osr8-7-2024, https://doi.org/10.5194/sp-4-osr8-7-2024, 2024
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Marine heatwaves (MHWs), which are the unusually warm periods in the ocean, are becoming more frequent and lasting longer in the northwest European Shelf (NWES), particularly near the coast, from 1993 to 2023. However, thermal stratification is weakening, implying that the sea surface warming caused by MHWs is insufficient to counteract the overall stratification decline due to global warming. Moreover, the varying salinity has a notable impact on the trend of density stratification change.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Ali Aydogdu, Lluis Castrillo, Daniele Ciani, Andrea Cipollone, Emanuela Clementi, Gianpiero Cossarini, Alvaro de Pascual-Collar, Vincenzo De Toma, Marion Gehlen, Rianne Giesen, Marie Drevillon, Claudia Fanelli, Kevin Hodges, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Priidik Lagemaa, Vidar Lien, Leonardo Lima, Vladyslav Lyubartsev, Ilja Maljutenko, Simona Masina, Ronan McAdam, Pietro Miraglio, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Urmas Raudsepp, Roshin Raj, Ad Stoffelen, Simon Van Gennip, Pierre Veillard, and Chunxue Yang
State Planet, 4-osr8, 2, https://doi.org/10.5194/sp-4-osr8-2-2024, https://doi.org/10.5194/sp-4-osr8-2-2024, 2024
Kunal Madkaiker, Ambarukhana D. Rao, and Sudheer Joseph
Ocean Sci., 20, 1167–1185, https://doi.org/10.5194/os-20-1167-2024, https://doi.org/10.5194/os-20-1167-2024, 2024
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Using a high-resolution model, we estimated the volume, freshwater, and heat transports along Indian coasts. Affected by coastal currents, transport along the eastern coast is highly seasonal, and the western coast is impacted by intraseasonal oscillations. Coastal currents and equatorial forcing determine the relation between NHT and net heat flux in dissipating heat in coastal waters. The north Indian Ocean functions as a heat source or sink based on seasonal flow of meridional heat transport.
Bethany McDonagh, Emanuela Clementi, Anna Chiara Goglio, and Nadia Pinardi
Ocean Sci., 20, 1051–1066, https://doi.org/10.5194/os-20-1051-2024, https://doi.org/10.5194/os-20-1051-2024, 2024
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Tides in the Mediterranean Sea are typically of low amplitude, but twin experiments with and without tides demonstrate that tides affect the circulation directly at scales away from those of the tides. Analysis of the energy changes due to tides shows that they enhance existing oscillations, and internal tides interact with other internal waves. Tides also increase the mixed layer depth and enhance deep water formation in key regions. Internal tides are widespread in the Mediterranean Sea.
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
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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.
Giulia Bonino, Giuliano Galimberti, Simona Masina, Ronan McAdam, and Emanuela Clementi
Ocean Sci., 20, 417–432, https://doi.org/10.5194/os-20-417-2024, https://doi.org/10.5194/os-20-417-2024, 2024
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This study employs machine learning to predict marine heatwaves (MHWs) in the Mediterranean Sea. MHWs have far-reaching impacts on society and ecosystems. Using data from ESA and ECMWF, the research develops accurate prediction models for sea surface temperature (SST) and MHWs across the region. Notably, machine learning methods outperform existing forecasting systems, showing promise in early MHW predictions. The study also highlights the importance of solar radiation as a predictor of SST.
Mikhail Popov, Jean-Michel Brankart, Arthur Capet, Emmanuel Cosme, and Pierre Brasseur
Ocean Sci., 20, 155–180, https://doi.org/10.5194/os-20-155-2024, https://doi.org/10.5194/os-20-155-2024, 2024
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This study contributes to the development of methods to estimate targeted ocean ecosystem indicators, including their uncertainty, in the framework of the Copernicus Marine Service. A simplified approach is introduced to perform a 4D ensemble analysis and forecast, directly targeting selected biogeochemical variables and indicators (phenology, trophic efficiency, downward flux of organic matter). Care is taken to present the methods and discuss the reliability of the solution proposed.
Giovanni Coppini, Emanuela Clementi, Gianpiero Cossarini, Stefano Salon, Gerasimos Korres, Michalis Ravdas, Rita Lecci, Jenny Pistoia, Anna Chiara Goglio, Massimiliano Drudi, Alessandro Grandi, Ali Aydogdu, Romain Escudier, Andrea Cipollone, Vladyslav Lyubartsev, Antonio Mariani, Sergio Cretì, Francesco Palermo, Matteo Scuro, Simona Masina, Nadia Pinardi, Antonio Navarra, Damiano Delrosso, Anna Teruzzi, Valeria Di Biagio, Giorgio Bolzon, Laura Feudale, Gianluca Coidessa, Carolina Amadio, Alberto Brosich, Arnau Miró, Eva Alvarez, Paolo Lazzari, Cosimo Solidoro, Charikleia Oikonomou, and Anna Zacharioudaki
Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, https://doi.org/10.5194/os-19-1483-2023, 2023
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The paper presents the Mediterranean Forecasting System evolution and performance developed in the framework of the Copernicus Marine Service.
Reynier Bada-Diaz, Martín Jacques-Coper, Laura Farías, Diego Narváez, and Italo Masotti
EGUsphere, https://doi.org/10.5194/egusphere-2023-2272, https://doi.org/10.5194/egusphere-2023-2272, 2023
Preprint archived
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In this research we perform an analysis of the phenomena that induce favourable conditions for the occurrence of algal bloom events in a fjord in Chilean Patagonia. We propose an atmospheric-oceanographic mechanism: the passage of a low-pressure system modifies conditions in the water column and establishes optimal conditions for the occurrence of an extreme bloom event. Establishing such an atmosphere-ocean mechanism is important, given the predictive capabilities of these atmospheric systems.
Pablo Lorente, Anna Rubio, Emma Reyes, Lohitzune Solabarrieta, Silvia Piedracoba, Joaquín Tintoré, and Julien Mader
State Planet, 1-osr7, 8, https://doi.org/10.5194/sp-1-osr7-8-2023, https://doi.org/10.5194/sp-1-osr7-8-2023, 2023
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Upwelling is an important process that impacts water quality and aquaculture production in coastal areas. In this work we present a new methodology to monitor this phenomenon in two different regions by using surface current estimations provided by remote sensing technology called high-frequency radar.
Carolina B. Gramcianinov, Joanna Staneva, Celia R. G. Souza, Priscila Linhares, Ricardo de Camargo, and Pedro L. da Silva Dias
State Planet, 1-osr7, 12, https://doi.org/10.5194/sp-1-osr7-12-2023, https://doi.org/10.5194/sp-1-osr7-12-2023, 2023
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We analyse extreme wave event trends in the south-western South Atlantic in the last 29 years using wave products and coastal hazard records. The results show important regional changes associated with increased mean sea wave height, wave period, and wave power. We also find a rise in the number of coastal hazards related to waves affecting the state of São Paulo, Brazil, which partially agrees with the increase in extreme waves in the adjacent ocean sector but is also driven by local factors.
Ali Aydogdu, Pietro Miraglio, Romain Escudier, Emanuela Clementi, and Simona Masina
State Planet, 1-osr7, 6, https://doi.org/10.5194/sp-1-osr7-6-2023, https://doi.org/10.5194/sp-1-osr7-6-2023, 2023
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This paper investigates the salt content, salinity anomaly and trend in the Mediterranean Sea using observational and reanalysis products. The salt content increases overall, while negative salinity anomalies appear in the western basin, especially around the upwelling regions. There is a large spread in the salinity estimates that is reduced with the emergence of the Argo profilers.
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
Heather Regan, Pierre Rampal, Einar Ólason, Guillaume Boutin, and Anton Korosov
The Cryosphere, 17, 1873–1893, https://doi.org/10.5194/tc-17-1873-2023, https://doi.org/10.5194/tc-17-1873-2023, 2023
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Multiyear ice (MYI), sea ice that survives the summer, is more resistant to changes than younger ice in the Arctic, so it is a good indicator of sea ice resilience. We use a model with a new way of tracking MYI to assess the contribution of different processes affecting MYI. We find two important years for MYI decline: 2007, when dynamics are important, and 2012, when melt is important. These affect MYI volume and area in different ways, which is important for the interpretation of observations.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
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Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Kathrin Wahle, Emil V. Stanev, and Joanna Staneva
Nat. Hazards Earth Syst. Sci., 23, 415–428, https://doi.org/10.5194/nhess-23-415-2023, https://doi.org/10.5194/nhess-23-415-2023, 2023
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Knowledge of what causes maximum water levels is often key in coastal management. Processes, such as storm surge and atmospheric forcing, alter the predicted tide. Whilst most of these processes are modeled in present-day ocean forecasting, there is still a need for a better understanding of situations where modeled and observed water levels deviate from each other. Here, we will use machine learning to detect such anomalies within a network of sea-level observations in the North Sea.
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
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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.
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
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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.
Begoña Pérez Gómez, Ivica Vilibić, Jadranka Šepić, Iva Međugorac, Matjaž Ličer, Laurent Testut, Claire Fraboul, Marta Marcos, Hassen Abdellaoui, Enrique Álvarez Fanjul, Darko Barbalić, Benjamín Casas, Antonio Castaño-Tierno, Srđan Čupić, Aldo Drago, María Angeles Fraile, Daniele A. Galliano, Adam Gauci, Branislav Gloginja, Víctor Martín Guijarro, Maja Jeromel, Marcos Larrad Revuelto, Ayah Lazar, Ibrahim Haktan Keskin, Igor Medvedev, Abdelkader Menassri, Mohamed Aïssa Meslem, Hrvoje Mihanović, Sara Morucci, Dragos Niculescu, José Manuel Quijano de Benito, Josep Pascual, Atanas Palazov, Marco Picone, Fabio Raicich, Mohamed Said, Jordi Salat, Erdinc Sezen, Mehmet Simav, Georgios Sylaios, Elena Tel, Joaquín Tintoré, Klodian Zaimi, and George Zodiatis
Ocean Sci., 18, 997–1053, https://doi.org/10.5194/os-18-997-2022, https://doi.org/10.5194/os-18-997-2022, 2022
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This description and mapping of coastal sea level monitoring networks in the Mediterranean and Black seas reveals the existence of 240 presently operational tide gauges. Information is provided about the type of sensor, time sampling, data availability, and ancillary measurements. An assessment of the fit-for-purpose status of the network is also included, along with recommendations to mitigate existing bottlenecks and improve the network, in a context of sea level rise and increasing extremes.
Juan Manuel Castillo, Huw W. Lewis, Akhilesh Mishra, Ashis Mitra, Jeff Polton, Ashley Brereton, Andrew Saulter, Alex Arnold, Segolene Berthou, Douglas Clark, Julia Crook, Ananda Das, John Edwards, Xiangbo Feng, Ankur Gupta, Sudheer Joseph, Nicholas Klingaman, Imranali Momin, Christine Pequignet, Claudio Sanchez, Jennifer Saxby, and Maria Valdivieso da Costa
Geosci. Model Dev., 15, 4193–4223, https://doi.org/10.5194/gmd-15-4193-2022, https://doi.org/10.5194/gmd-15-4193-2022, 2022
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A new environmental modelling system has been developed to represent the effect of feedbacks between atmosphere, land, and ocean in the Indian region. Different approaches to simulating tropical cyclones Titli and Fani are demonstrated. It is shown that results are sensitive to the way in which the ocean response to cyclone evolution is captured in the system. Notably, we show how a more rigorous formulation for the near-surface energy budget can be included when air–sea coupling is included.
Wei Chen, Joanna Staneva, Sebastian Grayek, Johannes Schulz-Stellenfleth, and Jens Greinert
Nat. Hazards Earth Syst. Sci., 22, 1683–1698, https://doi.org/10.5194/nhess-22-1683-2022, https://doi.org/10.5194/nhess-22-1683-2022, 2022
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This study links the occurrence and persistence of density stratification in the southern North Sea to the increased number of extreme marine heat waves. The study further identified the role of the cold spells at the early stage of a year to the intensity of thermal stratification in summer. In a broader context, the research will have fundamental significance for further discussion of the secondary effects of heat wave events, such as in ecosystems, fisheries, and sediment dynamics.
Georg Umgiesser, Marco Bajo, Christian Ferrarin, Andrea Cucco, Piero Lionello, Davide Zanchettin, Alvise Papa, Alessandro Tosoni, Maurizio Ferla, Elisa Coraci, Sara Morucci, Franco Crosato, Andrea Bonometto, Andrea Valentini, Mirko Orlić, Ivan D. Haigh, Jacob Woge Nielsen, Xavier Bertin, André Bustorff Fortunato, Begoña Pérez Gómez, Enrique Alvarez Fanjul, Denis Paradis, Didier Jourdan, Audrey Pasquet, Baptiste Mourre, Joaquín Tintoré, and Robert J. Nicholls
Nat. Hazards Earth Syst. Sci., 21, 2679–2704, https://doi.org/10.5194/nhess-21-2679-2021, https://doi.org/10.5194/nhess-21-2679-2021, 2021
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The city of Venice relies crucially on a good storm surge forecast to protect its population and cultural heritage. In this paper, we provide a state-of-the-art review of storm surge forecasting, starting from examples in Europe and focusing on the Adriatic Sea and the Lagoon of Venice. We discuss the physics of storm surge, as well as the particular aspects of Venice and new techniques in storm surge modeling. We also give recommendations on what a future forecasting system should look like.
Florian Ricour, Arthur Capet, Fabrizio D'Ortenzio, Bruno Delille, and Marilaure Grégoire
Biogeosciences, 18, 755–774, https://doi.org/10.5194/bg-18-755-2021, https://doi.org/10.5194/bg-18-755-2021, 2021
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This paper addresses the phenology of the deep chlorophyll maximum (DCM) in the Black Sea (BS). We show that the DCM forms in March at a density level set by the winter mixed layer. It maintains this location until June, suggesting an influence of the DCM on light and nutrient profiles rather than mere adaptation to external factors. In summer, the DCM concentrates ~55 % of the chlorophyll in a 10 m layer at ~35 m depth and should be considered a major feature of the BS phytoplankton dynamics.
Arthur Capet, Luc Vandenbulcke, and Marilaure Grégoire
Biogeosciences, 17, 6507–6525, https://doi.org/10.5194/bg-17-6507-2020, https://doi.org/10.5194/bg-17-6507-2020, 2020
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The Black Sea is 2000 m deep, but, due to limited ventilation, only about the upper 100 m contains enough oxygen to support marine life such as fish. This oxygenation depth has been shown to be decreasing (1955–2019). Here, we evidence that atmospheric warming induced a clear shift in an important ventilation mechanism. We highlight the impact of this shift on oxygenation. There are important implications for marine life and carbon and nutrient cycling if this new ventilation regime persists.
Miho Ishizu, Yasumasa Miyazawa, Tomohiko Tsunoda, and Tsuneo Ono
Biogeosciences, 16, 4747–4763, https://doi.org/10.5194/bg-16-4747-2019, https://doi.org/10.5194/bg-16-4747-2019, 2019
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Using water quality data collected at 289 monitoring sites as part of the Water Pollution Control Program, we evaluated the long-term trends of pH in Japanese coastal seawater at ambient temperature from 1978 to 2009. We found that the annual maximum pH, which generally represents the pH of surface waters in winter, had decreased at 75 % of the sites, but had increased at the remaining sites. The annual maximum pH decreased at an average rate of −0.0024 yr−1, with relatively large deviations.
Pablo Lorente, Marcos García-Sotillo, Arancha Amo-Baladrón, Roland Aznar, Bruno Levier, José C. Sánchez-Garrido, Simone Sammartino, Álvaro de Pascual-Collar, Guillaume Reffray, Cristina Toledano, and Enrique Álvarez-Fanjul
Ocean Sci., 15, 967–996, https://doi.org/10.5194/os-15-967-2019, https://doi.org/10.5194/os-15-967-2019, 2019
Johannes Pein, Annika Eisele, Richard Hofmeister, Tina Sanders, Ute Daewel, Emil V. Stanev, Justus van Beusekom, Joanna Staneva, and Corinna Schrum
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-265, https://doi.org/10.5194/bg-2019-265, 2019
Revised manuscript not accepted
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The Elbe estuary is subject to vigorous tidal forcing from the sea side and considerable biological inputs from the land side. Our 3D numerical coupled physical-biogeochemical integrates these forcing signals and provides highly realistic hindcasts of the associated dynamics. Model simulations show that the freshwater part of Elbe estuary is inhabited by plankton. According to simulations these organism play a key role in converting organic inputs into nitrate, the major inorganic nutrient.
Huw W. Lewis, Juan Manuel Castillo Sanchez, John Siddorn, Robert R. King, Marina Tonani, Andrew Saulter, Peter Sykes, Anne-Christine Pequignet, Graham P. Weedon, Tamzin Palmer, Joanna Staneva, and Lucy Bricheno
Ocean Sci., 15, 669–690, https://doi.org/10.5194/os-15-669-2019, https://doi.org/10.5194/os-15-669-2019, 2019
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Forecasts of ocean temperature, salinity, currents, and sea height can be improved by linking state-of-the-art ocean and wave models, so that they can interact to better represent the real world. We test this approach in an ocean model of north-west Europe which can simulate small-scale details of the ocean state. The intention is to implement the system described in this study for operational use so that improved information can be provided to users of ocean forecast data.
Álvaro de Pascual-Collar, Marcos G. Sotillo, Bruno Levier, Roland Aznar, Pablo Lorente, Arancha Amo-Baladrón, and Enrique Álvarez-Fanjul
Ocean Sci., 15, 565–582, https://doi.org/10.5194/os-15-565-2019, https://doi.org/10.5194/os-15-565-2019, 2019
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The Mediterranean Outflow Water (MOW) is a dense water mass originated in the Gibraltar Straight. The CMEMS IBI ocean reanalysis is used to provide a detailed view of the circulation and mixing processes of MOW near the Iberian and African Continental slopes. This work emphasizes the relevance of the complex bathymetric features defining the circulation and variability processes of MOW in this region.
Johannes Schulz-Stellenfleth and Joanna Staneva
Ocean Sci., 15, 249–268, https://doi.org/10.5194/os-15-249-2019, https://doi.org/10.5194/os-15-249-2019, 2019
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Errors of observations and numerical model data are analysed with a focus on heterogeneous coastal areas. An extension of the triple collocation method is proposed, which takes into account gradients in the collocation of datasets separated by distances which may not be acceptable for a nearest-neigbour approximation, but still be feasible for linear or higher order interpolations. The technique is applied to wave height data from in situ stations, models, and the Sentinel-3A altimeter.
Romain Rainaud, Lotfi Aouf, Alice Dalphinet, Marcos Garcia Sotillo, Enrique Alvarez-Fanjul, Guillaume Reffray, Bruno Levier, Stéphane LawChune, Pablo Lorente, and Cristina Toledano
Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-165, https://doi.org/10.5194/os-2018-165, 2019
Publication in OS not foreseen
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This paper highlight the adjustment of the wave physics in order to improve the surface stress and thus the ocean/wave coupling dedicated to Iberian Biscay and Ireland domain. The validation with altimeters wave data during the year 2014 has shown a slight improvement of the significant wave height. Statistical analysis of the results of the new and old versions of the wave model MFWAM is examined for the three main ocean regions of the IBI domain.
Romain Rainaud, Lotfi Aouf, Alice Dalphinet, Marcos Garcia Sotillo, Enrique Alvarez-Fanjul, Guillaume Reffray, Bruno Levier, Stéphane Law-Chune, Pablo Lorente, and Cristina Toledano
Ocean Sci. Discuss., https://doi.org/10.5194/os-2018-167, https://doi.org/10.5194/os-2018-167, 2019
Publication in OS not foreseen
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This work highlights the relevance of coupling wave model with ocean model in order to improve key surface ocean parameters and in general to better describe the ocean circulation at small and large scale.
The results focus on the Iberian Biscay and Ireland ocean region with fine grid resolution of 2.5 km for the ocean model. The main conclusion is the improvement of wave physics induces a better ocean mixing at the upper layer and a positive impact for sea surface height in storm events.
Anne Wiese, Joanna Staneva, Johannes Schulz-Stellenfleth, Arno Behrens, Luciana Fenoglio-Marc, and Jean-Raymond Bidlot
Ocean Sci., 14, 1503–1521, https://doi.org/10.5194/os-14-1503-2018, https://doi.org/10.5194/os-14-1503-2018, 2018
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The increase of data quality of wind and wave measurements provided by the new Sentinel-3A satellite in coastal areas is demonstrated compared to measurements of older satellites with in situ data and spectral wave model simulations. Furthermore, the sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, where an hourly temporal resolution is necessary to represent the peak of extreme events better.
Burkard Baschek, Friedhelm Schroeder, Holger Brix, Rolf Riethmüller, Thomas H. Badewien, Gisbert Breitbach, Bernd Brügge, Franciscus Colijn, Roland Doerffer, Christiane Eschenbach, Jana Friedrich, Philipp Fischer, Stefan Garthe, Jochen Horstmann, Hajo Krasemann, Katja Metfies, Lucas Merckelbach, Nino Ohle, Wilhelm Petersen, Daniel Pröfrock, Rüdiger Röttgers, Michael Schlüter, Jan Schulz, Johannes Schulz-Stellenfleth, Emil Stanev, Joanna Staneva, Christian Winter, Kai Wirtz, Jochen Wollschläger, Oliver Zielinski, and Friedwart Ziemer
Ocean Sci., 13, 379–410, https://doi.org/10.5194/os-13-379-2017, https://doi.org/10.5194/os-13-379-2017, 2017
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The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the heavily used German Bight in the North Sea. The automated observing and modelling system is designed to monitor real-time conditions, to provide short-term forecasts and data products, and to assess the impact of anthropogenically induced change.
Giovanni Coppini, Palmalisa Marra, Rita Lecci, Nadia Pinardi, Sergio Cretì, Mario Scalas, Luca Tedesco, Alessandro D'Anca, Leopoldo Fazioli, Antonio Olita, Giuseppe Turrisi, Cosimo Palazzo, Giovanni Aloisio, Sandro Fiore, Antonio Bonaduce, Yogesh Vittal Kumkar, Stefania Angela Ciliberti, Ivan Federico, Gianandrea Mannarini, Paola Agostini, Roberto Bonarelli, Sara Martinelli, Giorgia Verri, Letizia Lusito, Davide Rollo, Arturo Cavallo, Antonio Tumolo, Tony Monacizzo, Marco Spagnulo, Rorberto Sorgente, Andrea Cucco, Giovanni Quattrocchi, Marina Tonani, Massimiliano Drudi, Paola Nassisi, Laura Conte, Laura Panzera, Antonio Navarra, and Giancarlo Negro
Nat. Hazards Earth Syst. Sci., 17, 533–547, https://doi.org/10.5194/nhess-17-533-2017, https://doi.org/10.5194/nhess-17-533-2017, 2017
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SeaConditions aims to support the users by providing the environmental information in due time and with adequate accuracy in the marine and coastal environments, enforcing users' sea situational awareness. SeaConditions consists of a web and mobile application for the provision of meteorological and oceanographic observation and forecasting products. The iOS/Android apps were downloaded by more than 105 000 users and more than 100 000 users have visited the web version (www.sea-conditions.com).
Kathrin Wahle, Joanna Staneva, Wolfgang Koch, Luciana Fenoglio-Marc, Ha T. M. Ho-Hagemann, and Emil V. Stanev
Ocean Sci., 13, 289–301, https://doi.org/10.5194/os-13-289-2017, https://doi.org/10.5194/os-13-289-2017, 2017
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Reduction of wave forecasting errors is a challenge, especially in dynamically complicated coastal ocean areas such as the southern part of the North Sea area. We study the effects of coupling between an atmospheric and two nested-grid wind wave models. Comparisons with data from in situ and satellite altimeter observations indicate that two-way coupling improves the simulation of wind and wave parameters of the model and justifies its implementation for both operational and climate simulation.
Matías G. Dinapoli, Claudia G. Simionato, and Diego Moreira
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2016-393, https://doi.org/10.5194/nhess-2016-393, 2017
Preprint withdrawn
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The Río de la Plata Estuary (ubicated at South-Western South Atlantic Continental Shelf) presents extreme storm surges generated by persistent and strong southeasterly winds (Sudestadas) which has historically caused catastrophic floods. A sensitivity analysis of the many inputs parameter was made for a 2-D barotropic application of the ROMS_AGRIF ocean model. As a result, the most important input is wind speed. That suggests that should make focus in a better regional wind speed calibration.
Nadia Pinardi, Vladyslav Lyubartsev, Nicola Cardellicchio, Claudio Caporale, Stefania Ciliberti, Giovanni Coppini, Francesca De Pascalis, Lorenzo Dialti, Ivan Federico, Marco Filippone, Alessandro Grandi, Matteo Guideri, Rita Lecci, Lamberto Lamberti, Giuliano Lorenzetti, Paolo Lusiani, Cosimo Damiano Macripo, Francesco Maicu, Michele Mossa, Diego Tartarini, Francesco Trotta, Georg Umgiesser, and Luca Zaggia
Nat. Hazards Earth Syst. Sci., 16, 2623–2639, https://doi.org/10.5194/nhess-16-2623-2016, https://doi.org/10.5194/nhess-16-2623-2016, 2016
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A multiscale sampling experiment was carried out in the Gulf of Taranto (eastern Mediterranean) providing the first synoptic evidence of the large-scale circulation structure and associated mesoscale variability. The circulation is shown to be dominated by an anticyclonic gyre and upwelling areas at the gyre periphery.
Vasco M. N. C. S. Vieira, Pavel Jurus, Emanuela Clementi, Heidi Pettersson, and Marcos Mateus
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2016-273, https://doi.org/10.5194/gmd-2016-273, 2016
Revised manuscript has not been submitted
Joanna Staneva, Kathrin Wahle, Wolfgang Koch, Arno Behrens, Luciana Fenoglio-Marc, and Emil V. Stanev
Nat. Hazards Earth Syst. Sci., 16, 2373–2389, https://doi.org/10.5194/nhess-16-2373-2016, https://doi.org/10.5194/nhess-16-2373-2016, 2016
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This study addresses the impact of wind, waves, tidal forcing and baroclinicity on the sea level of the German Bight during extreme storm events. The role of wave-induced processes, tides and baroclinicity is quantified, and the results are compared with in situ measurements and satellite data. Considering a wave-dependent approach and baroclinicity, the surge is significantly enhanced in the coastal areas and the model results are closer to observations, especially during the extreme storm.
Emil V. Stanev, Johannes Schulz-Stellenfleth, Joanna Staneva, Sebastian Grayek, Sebastian Grashorn, Arno Behrens, Wolfgang Koch, and Johannes Pein
Ocean Sci., 12, 1105–1136, https://doi.org/10.5194/os-12-1105-2016, https://doi.org/10.5194/os-12-1105-2016, 2016
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This paper describes coastal ocean forecasting practices exemplified for the North Sea and Baltic Sea. It identifies new challenges, most of which are associated with the nonlinear behavior of coastal oceans. It describes the assimilation of remote sensing, in situ and HF radar data, prediction of wind waves and storm surges, as well as applications to search and rescue operations. Seamless applications to coastal and estuarine modeling are also presented.
Bàrbara Barceló-Llull, Evan Mason, Arthur Capet, and Ananda Pascual
Ocean Sci., 12, 1003–1011, https://doi.org/10.5194/os-12-1003-2016, https://doi.org/10.5194/os-12-1003-2016, 2016
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Vertical velocity in the ocean makes an important contribution to the modulation of marine ecosystems through its impact on fluxes of nutrients and phytoplankton. Here, we estimate full 3-D current velocity fields from an observation-based data product. The 3-D currents are used to force a set of particle-tracking (Lagrangian) experiments. The Lagrangian results show that vertical motions induce local increases in nitrate uptake reaching up to 30 %.
Oscar Vergara, Boris Dewitte, Ivonne Montes, Veronique Garçon, Marcel Ramos, Aurélien Paulmier, and Oscar Pizarro
Biogeosciences, 13, 4389–4410, https://doi.org/10.5194/bg-13-4389-2016, https://doi.org/10.5194/bg-13-4389-2016, 2016
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The Southeast Pacific hosts one of the most extensive oxygen minimum zone (OMZ), yet the dynamics behind it remain unveiled. We use a high-resolution coupled physical–biogeochemical model to document the seasonal cycle of dissolved oxygen within the OMZ in both the coastal zone and the offshore ocean. The OMZ seasonal variability is driven by the seasonal fluctuations of the dissolved oxygen eddy flux, with a peak in Austral winter (fall) at the northern (southern) boundary and near the coast.
Joanna Staneva, Kathrin Wahle, Heinz Günther, and Emil Stanev
Ocean Sci., 12, 797–806, https://doi.org/10.5194/os-12-797-2016, https://doi.org/10.5194/os-12-797-2016, 2016
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This study addresses the impact of coupling between wind wave and circulation models on the quality of coastal ocean predicting systems. This topic reflects the increased interest in operational oceanography to reduce prediction errors of state estimates at coastal scales. The improved skill of the coupled forecasts compared to the non-coupled ones, in particular during extreme events, justifies the further enhancements of coastal operational systems by including wind wave models.
Arthur Capet, Emil V. Stanev, Jean-Marie Beckers, James W. Murray, and Marilaure Grégoire
Biogeosciences, 13, 1287–1297, https://doi.org/10.5194/bg-13-1287-2016, https://doi.org/10.5194/bg-13-1287-2016, 2016
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We show that the Black Sea oxygen inventory has decreased by 44 % from 1955 to 2015, while oxygen penetration depth decreased from 140 to 90 m. A transient increase of the oxygen inventory during 1985–1995 supported the perception of a stable oxic interface and of a general recovery of the Black Sea after a strong eutrophication phase (1970–1990). Instead, we show that ongoing high oxygen consumption was masked by high ventilation rates, which are now limited by atmospheric warming.
C. Yan, J. Zhu, and C. A. S. Tanajura
Ocean Sci., 11, 829–837, https://doi.org/10.5194/os-11-829-2015, https://doi.org/10.5194/os-11-829-2015, 2015
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The altimetry data assimilation requires the addition of the mean dynamic topography to the altimetric sea level anomaly to match the model sea surface height. The mean dynamic topography is usually computed from the model long-term mean sea surface height. In this study, the impact of different mean dynamic topographies on the sea level anomaly assimilation is examined. Results show that impacts of the mean dynamic topography cannot be neglected.
V. M. N. C. S. Vieira, E. Sahlée, P. Jurus, E. Clementi, H. Pettersson, and M. Mateus
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-15901-2015, https://doi.org/10.5194/bgd-12-15901-2015, 2015
Manuscript not accepted for further review
V. M. N. C. S. Vieira, E. Sahlée, P. Jurus, E. Clementi, H. Pettersson, and M. Mateus
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-15925-2015, https://doi.org/10.5194/bgd-12-15925-2015, 2015
Manuscript not accepted for further review
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.
D. Mignac, C. A. S. Tanajura, A. N. Santana, L. N. Lima, and J. Xie
Ocean Sci., 11, 195–213, https://doi.org/10.5194/os-11-195-2015, https://doi.org/10.5194/os-11-195-2015, 2015
T. Waseda, K. In, K. Kiyomatsu, H. Tamura, Y. Miyazawa, and K. Iyama
Nat. Hazards Earth Syst. Sci., 14, 945–957, https://doi.org/10.5194/nhess-14-945-2014, https://doi.org/10.5194/nhess-14-945-2014, 2014
Y. Miyazawa, Y. Masumoto, S. M. Varlamov, T. Miyama, M. Takigawa, M. Honda, and T. Saino
Biogeosciences, 10, 2349–2363, https://doi.org/10.5194/bg-10-2349-2013, https://doi.org/10.5194/bg-10-2349-2013, 2013
Cited articles
Alonso, G., Simionato, C. G., Dinápoli, M. G., Saurral, R., and Bodnariuk, N.: Positive Storm Surges in the Río de la Plata Estuary: forcings, long-term variability, trends and linkage with Southwestern Atlantic Continental Shelf dynamics, Nat. Hazards, 120, 5007–5032, https://doi.org/10.1007/s11069-024-06402-w, 2024.
Álvarez Fanjul, E., Sotillo, M. G., Perez Gomez, B., Valdecasas, M. G., Perez Rubio, S., Lorente, P., Dapena, A. R., Martinez Marco, I., Luna, Y., Padorno, E., Santos Atienza, I., Hernandez, G. D., Lopez Lara, J., Medina, R., Grifoll, M., Espino, M., Mestres, M., Cerralbo, P., and Sanchez Arcilla, A.: Operational oceanography at the service of the ports, in: New Frontiers in Operational Oceanography, edited by: Chassignet, E., Pascual, A., Tintoré, J., and Verron, J., GODAE OceanView, 729–736, https://doi.org/10.17125/gov2018.ch27, 2018.
Alvarez Fanjul, E., Ciliberti, S., Pearlman, J., Wilmer-Becker, K., Ardhuin, F., Arnaud, A., Azizzadenesheli, K., Bahurel, P., Bell, M., Berthou, S. Bertino, L., Calewaert, J. B., Capet, A., Chassignet, E., Ciavatta, S., Cirano, M., Clementi, E., Cornacchia, L., Cossarini, G., Coro, G., Corney, S., Davidson, F., Drevillon, M., Drillet, Y., Dussurget, R., El Serafy, G., Fennel, K., Heimbach, P., Hernandez, F., Hogan, P., Hoteit, I., Joseph, S., Josey, S., Le Traon, P.-Y., Libralato, S., Mancini, M., Martin, M., Matte, P., Melet, A., Miyazawa, Y., Moore, A.M., Novellino, A., O'Donncha, F., Porter, A., Qiao, F., Regan, H., Schiller, A., Siddorn, J., Sotillo, M. G., Staneva, J., Thomas-Courcoux, C., Thupaki, P., Tonani, M., Garcia Valdecasas, J. M., Veitch, J., von Schuckmann, K., Wan, L., Wilkin, J., and Zufic, R.: The OceanPrediction DCC Architecture for Ocean Forecasting, OceanPrediction Decade Collaborative Centre, https://doi.org/10.48670/oofsarchitecture, 2024a.
Alvarez Fanjul, E., Ciliberti, S., Pearlman, J., Wilmer-Becker, K., Bahurel, P., Ardhuin, F., Arnaud, A., Azizzadenesheli, K., Aznar, R., Bell, M., Bertino, L., Behera, S., Brassington, G., Calewaert, J.B., Capet, A., Chassignet, E., Ciavatta, S., Cirano, M., Clementi, E., Cornacchia, L., Cossarini, G., Coro, G., Corney, S., Davidson, F., Drevillon, M., Drillet, Y., Dussurget, R., El Serafy, G., Fearon, G., Fennel, K., Ford, D., Le Galloudec, O., Huang, X., Lellouche, J.M., Heimbach, P., Hernandez, F., Hogan, P., Hoteit, I., Joseph, S., Josey, S., Le Traon, P.-Y., Libralato, S., Mancini, M., Martin, M., Matte, P., McConnell, T., Melet, A., Miyazawa, Y., Moore, A. M., Novellino, A., O'Donncha, F., Porter, A., Qiao, F., Regan, H., Robert-Jones, J., Sanikommu, S., Schiller, A., Siddorn, J., Sotillo, M. G., Staneva, J., Thomas-Courcoux, C., Thupaki, P., Tonani, M., Garcia Valdecasas, J.M., Veitch, J., von Schuckmann, K., Wan, L., Wilkin, J., Zhong, A., and Zufic, R.: Promoting best practices in ocean forecasting through an Operational Readiness Level, Front. Mar. Sci., 11, 1443284, https://doi.org/10.3389/fmars.2024.1443284, 2024b.
Arellano, C., Echevin, V., Merma-Mora, L., Chamorro, A., Gutierrez, D., Aguirre-Velarde, A., Tam, J., and Colas, F.: Circulation and stratification drivers during the summer season in the upwelling bay of Paracas (Peru): A modelling study, Cont. Shelf Res., 254, 104923, https://doi.org/10.1016/j.csr.2022.104923, 2023.
Astudillo, O., Dewitte, B., Mallet, M., Rutllant, J. A., Goubanova, K., Frappart, F., Ramos, M., and Bravo, L. : Sensitivity of the near-shore oceanic circulation off Central Chile to coastal wind profiles characteristics, J. Geophys. Res.-Oceans, 124, 4644–4676, https://doi.org/10.1029/2018JC014051, 2019.
Augusto Souza Tanajura, C., Novaes Santana, A., Mignac, D., Nascimento Lima, L., Belyaev, K., and Ji-Ping, X.: The REMO Ocean Data Assimilation System into HYCOM (RODAS_H): General Description and Preliminary Results, Atmospheric and Oceanic Science Letters, 7, 464–470, https://doi.org/10.3878/j.issn.1674-2834.14.0011, 2014.
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015.
Baretta, J. W., Ebenhöh, W., and Ruardij, P.: The European regional seas ecosystem model, a complex marine ecosystem model, Netherlands J. Sea Res., 33, 233–246, https://doi.org/10.1016/0077-7579(95)90047-0, 1995.
Barnard, P. L., van Ormondt, M., Erikson, L. H., Eshleman, J., Hapke, C., Ruggiero, P., Adams, P. N., and Foxgrover, A. C.: Development of the Coastal Storm Modeling System (CoSMoS) for predicting the impact of storms on high-energy, active-margin coasts, Nat. Hazards, 74, 1095–1125, https://doi.org/10.1007/s11069-014-1236-y, 2014.
Barnes, M. A. and Rautenbach, C.: Toward operational wave-current interactions over the Agulhas Current system, J. Geophys. Res.-Oceans, 125, e2020JC016321, https://doi.org/10.1029/2020JC016321, 2020.
Blumberg, A. F. and Mellor, G. L.: A description of a three-dimensional coastal ocean circulation model. Three-Dimensional Coastal ocean Models, edited by: Heaps, N., Coastal and Estuarine Sciences, American Geophysical Union, 208 pp., 1987.
Booij, N., Ris, R. C., and Holthuijsen, L. H.: A third-generation wave model for coastal regions: 1. Model description and validation, J. Geophys. Res.-Oceans, 104, 7649–7666, https://doi.org/10.1029/98JC02622, 1999.
Brassington, G. B., Sakov, P., Divakaran, P., Aijaz, S., Sweeney-Van Kinderen, J., Huang, X., and Allen, S.: OceanMAPS v4. 0i: a global eddy resolving EnKF ocean forecasting system, in: OCEANS 2023-Limerick, Limerick, Ireland, 5–8 June 2023, IEEE, 1–8, https://doi.org/10.1109/OCEANSLimerick52467.2023.10244383, 2023.
Bruschi, A., Lisi, I., De Angelis, R., Querin, S., Cossarini, G., Di Biagio, V., Salon, S., Solidoro, C., Fassina, D., Ancona, S., and Silvestri, C.: Indexes for the assessment of bacterial pollution in bathing waters from point sources: The northern Adriatic Sea CADEAU service, J. Environ. Manage., 293, 112878, https://doi.org/10.1016/j.jenvman.2021.112878, 2021.
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, https://doi.org/10.1002/qj.2408, 2016.
Capet, A., Meysman, F., Akoumianaki, I., Soeteart, K., and Gregoire, M.: Integrating sediment biogeochemistry into 3D oceanic models: A study of benthic-pelagic coupling in the Black Sea, Ocean Model., 101, 83–100, https://doi.org/10.1016/j.ocemod.2016.03.006, 2016.
Capet, A., Fernández, V., She, J., Dabrowski, T., Umgiesser, G., Staneva, J., Mészáros, L., Campuzano, F., Ursella, L., Nolan, G., and El Serafy, G.: Operational Modeling Capacity in European Seas – An EuroGOOS Perspective and Recommendations for Improvement, Front. Mar. Sci., 7, 129, https://doi.org/10.3389/fmars.2020.00129, 2020.
Casati, B., Robinson, T., Lemay, F., Køltzow, M., Haiden, T., Mekis, E., Lespinas, F., Fortin, V., Gascon, G., Milbrandt, J., and Smith, G.: Performance of the Canadian Arctic prediction system during the YOPP special observing periods, Atmos.-Ocean, 61, 246–272, https://doi.org/10.1080/07055900.2023.2191831, 2023.
Ciliberti, S. and Coro, G.: Distributed Environments for Ocean Forecasting: the role of Cloud Computing, in: Ocean prediction: present status and state of the art (OPSR), edited by: Álvarez Fanjul, E., Ciliberti, S. A., Pearlman, J., Wilmer-Becker, K., and Behera, S., Copernicus Publications, State Planet, 5-opsr, 24, https://doi.org/10.5194/sp-5-opsr-24-2025, 2025.
Ciliberti, S. A., Grégoire, M., Staneva, J., Palazov, A., Coppini, G., Lecci, R., Peneva, E., Matreata, M., Marinova, V., Masina, S., Pinardi, N., Jansen, E., Lima, L., Aydoğdu, A., Creti’, S., Stefanizzi, L., Azevedo, D., Causio, S., Vandenbulcke, L., Capet, A., Maulders, C., Ivanov, E., Behrens, A., Ricker, M., Gayer, G., Palermo, F., Ilicak, M., Gunduz, M., Valcheva, N., and Agostini, P.: Monitoring and Forecasting the Ocean State and Biogeochemical Processes in the Black Sea: Recent Developments in the Copernicus Marine Service, J. Mar. Sci. Eng., 9, 1146, https://doi.org/10.3390/jmse9101146, 2022.
Coppini, G., Clementi, E., Cossarini, G., Salon, S., Korres, G., Ravdas, M., Lecci, R., Pistoia, J., Goglio, A. C., Drudi, M., Grandi, A., Aydogdu, A., Escudier, R., Cipollone, A., Lyubartsev, V., Mariani, A., Cretì, S., Palermo, F., Scuro, M., Masina, S., Pinardi, N., Navarra, A., Delrosso, D., Teruzzi, A., Di Biagio, V., Bolzon, G., Feudale, L., Coidessa, G., Amadio, C., Brosich, A., Miró, A., Alvarez, E., Lazzari, P., Solidoro, C., Oikonomou, C., and Zacharioudaki, A.: The Mediterranean Forecasting System – Part 1: Evolution and performance, Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, 2023.
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017.
Davidson, F., Robertson, A., Vitart, F., Rea, A., Jean, M., Schiller, A., Cuff, T. J., Grimes, S., Lim, E., de Coning, E., and Shi, P.: Ocean Prediction – modelling for the future, WMO Magazine, https://wmo.int/media/magazine-article/ocean-prediction-modelling-future (last access: 28 February 2025), 2021.
Debreu, L., Marchesiello, P., Penven, P., and Cambon, G.: Two-way nesting in split-explicit ocean models: Algorithms, implementation and validation, Ocean Model., 49–50, 1–21, https://doi.org/10.1016/j.ocemod.2012.03.003, 2012.
de Vos, M., Barnes, M., Biddle, L. C., Swart, S., Ramjukadh, C. L., and Vichi, M.: Evaluating numerical and free-drift forecasts of sea ice drift during a Southern Ocean research expedition: An operational perspective, J. Oper. Oceanogr., 15, 187–203, https://doi.org/10.1080/1755876X.2021.1883293, 2021.
DFO: Application of high-resolution hydrodynamic prediction systems for forecasting of ocean conditions in Canadian ports and approaches, National Peer Review – National Capital Region, 14–16 and 21–23 March 2023, Virtual Meeting, https://www.dfo-mpo.gc.ca/csas-sccs/Schedule-Horraire/2023/03_14-23-eng.html (last access: 26 May 2025), 2023.
Di Maio, A., Martin, M. V., and Sorgente, R.: Evaluation of the search and rescue LEEWAY model in the Tyrrhenian Sea: a new point of view, Nat. Hazards Earth Syst. Sci., 16, 1979–1997, https://doi.org/10.5194/nhess-16-1979-2016, 2016.
Dinápoli, M. G. and Simionato, C. G.: An integrated methodology for post-processing ensemble prediction systems to produce more representative extreme water level forecasts: the case of the Río de la Plata estuary, Nat. Hazards, 114, 2927–2940, https://doi.org/10.1007/s11069-022-05499-1, 2022.
Dinápoli, M. G. and Simionato, C. G.: Study of the tidal dynamics in the Southwestern Atlantic Continental Shelf based on data assimilation, Ocean Model., 188, 102332, https://doi.org/10.1016/j.ocemod.2024.102332, 2024.
Dinapoli, M. G. and Simionato, C. G.: On the impact of Southeastern Pacific‐generated storm surges on the Southwestern Atlantic Continental Shelf: Interoceanic connections through coastally trapped waves, J. Geophys. Res.-Oceans, 130, e2024JC021685, https://doi.org/10.1029/2024JC021685, 2025.
Dinápoli, M. G., Simionato, C. G., and Moreira D.: Model Sensitivity during Extreme Positive and Negative Surges in the Río de la Plata Estuary: Highlighting the Need for an Appropriate Hindcast/Forecast System, Weather Forecast., 35, 1097–1112, https://doi.org/10.1175/WAF-D-19-0171.1, 2020a.
Dinápoli, M. G., Simionato, C. G., and Moreira D.: Nonlinear tide-surge interactions in the Río de la Plata Estuary, Estuar. Coast. Shelf Sci., 241, 106834, https://doi.org/10.1016/j.ecss.2020.106834, 2020b.
Dinápoli, M. G., Simionato, C. G., and Moreira D.: Development and evaluation of an ensemble forecast/hindcast system for storm surges in the Río de la Plata Estuary, Q. J. Roy. Meteor. Soc., 147, 557–572, https://doi.org/10.1002/qj.3933, 2021.
Dinápoli, M. G., Ruiz, J. J., Simionato, C. G., and Berden, G.: Improving the short-range forecast of storm surges in the southwestern Atlantic continental shelf using 4DEnSRF data assimilation, Q. J. Roy. Meteor. Soc., 149, 2333–2347, https://doi.org/10.1002/qj.4509, 2023.
Dinápoli, M. G., Simionato, C. G., Alonso, G., Bodnariuk, N., and Saurral, R.: Negative storm surges in the Río de la Plata Estuary: mechanisms, variability, trends and linkage with the Continental Shelf dynamics,Estuarine, Coast. Shelf Sci., 305, 108844, https://doi.org/10.1016/j.ecss.2024.108844, 2024.
Dobricic, S. and Pinardi N.: An oceanographic three-dimensional variational data assimilation scheme, Ocean Model., 22, 89–105, 2008.
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.
Durnford, D., Fortin, V., Smith, G.C., Archambault, B., Deacu, D., Dupont, F., Dyck, S., Martinez, Y., Klyszejko, E., MacKay, M., and Liu, L.: Toward an operational water cycle prediction system for the Great Lakes and St. Lawrence River, B. Am. Meteorol. Soc., 99, 521–546, https://doi.org/10.1175/BAMS-D-16-0155.1, 2018.
Federico, I., Pinardi, N., Coppini, G., Oddo, P., Lecci, R., and Mossa, M.: Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas, Nat. Hazards Earth Syst. Sci., 17, 45–59, https://doi.org/10.5194/nhess-17-45-2017, 2017.
Feng, B., Wang, Z., Zhang, Y., and Wan, L.: Numerical Simulation of the Northwest Pacific Based on the MaCOM, J. Phys. Conf. Ser., 2718, 012029, https://doi.org/10.1088/1742-6596/2718/1/012029, 2024.
Ferrarin, C., Roland, A., Bajo, M., Umgiesser, G., Cucco, A., Davolio, S., Buzzi, A., Malguzzi, P., and Drofa, O.: Tide-surge-wave modelling and forecasting in the Mediterranean Sea with focus on the Italian coast, Ocean Model. 61, 38–48, https://doi.org/10.1016/j.ocemod.2012.10.003, 2013.
Ferrarin, C., Davolio, S., Bellafiore, D., Ghezzo, M., Maicu, F., McKiver, W., Drofa, O., Umgiesser, G., Bajo, M., De Pascalis, F., Malguzzi, P., Zaggia, L., Lorenzetti, G., and Manfé, G.: Cross-scale operational oceanography in the Adriatic Sea, J. Oper. Oceanogr., 12, 86–103, https://doi.org/10.1080/1755876X.2019.1576275, 2019.
Franz, G., Garcia, C. A. E., Pereira, J., de Freitas Assad, L. P., Rollnic, M., Garbossa, L. H. P., da Cunha, L. C., Lentini, C. A. D., Nobre, P., Turra, A., Trotte-Duhá, J. R., Cirano, M., Estefen, S. F., Lima, J. A. M., Paiva, A. M., Noernberg, M. A., Tanajura, C. A. S., Moutinho, J. L., Campuzano, F., Pereira, E. S., Lima, A. C., Mendonça, L. F. F., Nocko, H., Machado, L., Alvarenga, J. B. R., Martins, R. P., Böck, C. S., Toste, R., Landau, L., Miranda, T., dos Santos, F., Pellegrini, J., Juliano, M., Neves, R., and Polejack, A.: Coastal Ocean Observing and Modeling Systems in Brazil: Initiatives and Future Perspectives, Front. Mar. Sci., 8, 681619, https://doi.org/10.3389/fmars.2021.681619, 2021.
García-León, M., Sotillo, M. G., Mestres, M., Espino, M., Fanjul, and E. A.: Improving Operational Ocean Models for the Spanish Port Authorities: Assessment of the SAMOA Coastal Forecasting Service Upgrades, J. Mar. Sci. Eng., 10, 149, https://doi.org/10.3390/jmse10020149, 2022.
Goddard, L., González Romero, C., Muñoz, Á. G., Acharya, N., Ahmed, S., Baethgen, W., Blumenthal, B., Braun, M., Campos, D., Chourio, X., Cousin, R., Cortés, C., Curtis, A., del Corral, J., Dinh, D., Dinku, T., Fiondella, F., Furlow, J., García-López, A., Giraldo Mendez, D., Gómez, R., Grossi, A., Hailemariam, K., Hansen, J., Hassan, Q., Hoang, L., Jordan, P., List, G., Mannan, M. A., Mason, S. J., Melo, J., Navarro-Racines, C., Ndiaye, O., Nguyen-Quang, T., Nguyen-Van, T., Oliva, J. P., Osgood, D., Pons, D., Prager, S. D., Hernandez Quevedo, M., Robertson, A. W., Ramírez Villegas, J., Ruiz, J. F., Rojas, O., Schubmann, L., Teshome, F., Thomson, M., Turner, J. Trzaska, S., Van Mai, K., Vadillo, A., Vicencio, J. M., and Vu-Van, T.: Climate Services Ecosystems in times of COVID-19, WMO at 70 – Responding to a Global Pandemic, WMO Bulletin, 69, 39–46, https://wmo.int/media/magazine-article/climate-services-ecosystems-times-of-covid-19 (last access: 14 May 2025), 2020.
Goessling, H. F., Jung, T., Klebe, S., Baeseman, J., Bauer, P., Chen, P., Chevallier, M., Dole, R., Gordon, N., Ruti, P., and Bradley, A.: Paving the way for the year of polar prediction, B. Am. Meteorol. Soc., 97, ES85–ES88, https://doi.org/10.1175/BAMS-D-15-00270.1, 2016.
Grégoire, M., Raick, C., and Soetaert, K.: Numerical modeling of the deep Black Sea ecosystem functioning during the late 80's (eutrophication phase), Prog. Oceanogr., 76, 286–333, https://doi.org/10.1016/j.pocean.2008.01.002, 2008.
Gurvan, M., Bourdalle'-Badie, R., Chanut, J., Clementi, E., Coward, A., Ethe', C., Iovino, D., Lea, D., Levy, C., Lovato, T., Martin, N., Masson, S., Movavero, S., Rousset, C., Storkey, D., Mueller, S., Nurser, G., Bell, M., Samson, G., Mathiot, P., Mele, F., Moulin, A.: NEMO ocean engine, Zenodo, https://doi.org/10.5281/zenodo.6334656, 2022.
Heimbach, P., O'Donncha, F., Smith, T., Garcia-Valdecasas, J. M., Arnaud, A., and Wan, L.: Crafting the Future: Machine Learning for Ocean Forecasting, in: Ocean prediction: present status and state of the art (OPSR), edited by: Álvarez Fanjul, E., Ciliberti, S. A., Pearlman, J., Wilmer-Becker, K., and Behera, S., Copernicus Publications, State Planet, 5-opsr, 22, https://doi.org/10.5194/sp-5-opsr-22-2025, 2025.
Hoteit, I., Abualnaja, Y., Afzal, S., Ait-El-Fquih, B., Akylas, T., Antony, C., Dawson, C., Asfahani, K., Brewin, R. J., Cavaleri, L., Cerovecki, I., Cornuelle, B., Desamsetti, S., Attada, R., Dasari, H., Sanchez-Garrido, J., Genevier, L., El Gharamti, M., Gittings, J. A., Gokul, E., Gopalakrishnan, G., Guo, D., Hadri, B., Hadwiger, M., Abed Hammoud, M., Hendershott, M., Hittawe, M., Karumuri, A., Knio, O., Köhl, S., Kortas, S., Krokos, G., Kunchala, R., Issa, L., Lakkis, I., Langodan, S., Lermusiaux, P., Luong, T., Ma, J., Le Maitre, O., Mazloff, M., El Mohtar, S., Papadopoulos, V. P., Platt, T., Pratt, L., Raboudi, N., Racault, M.-F., Raitsos, D. E., Razak, S., Sanikommu, S., Sathyendranath, S., Sofianos, S., Subramanian, A., Sun, R., Titi, E., Toye, H., Triantafyllou, G., Tsiaras, K., Vasou, P., Viswanadhapalli, Y., Wang, Y., Yao, F., Zhan, P., and Zodiatis, G.: Towards an End-to-End Analysis and Prediction System for Weather, Climate, and Marine Applications in the Red Sea, B. Am. Meteorol. Soc., 102, E99–E122, https://doi.org/10.1175/BAMS-D-19-0005.1, 2021.
Jayson-Quashigah, P. N., Staneva, J., Chen, W., and Djath, B.: Exploring the Role of Mangroves as Nature-Based Solutions in Coastal Erosion Management: A What-If Analysis, Nature Based Solutions, in review, 2025.
Jin, H., Kim, Y. H., Park, Y.-G., Chang, I., Chang, Y.-S., Park, H., and Pak, G.: Simulation Characteristics of Ocean Predictability Experiment for Marine environment (OPEM): A Western North Pacific Regional Ocean Prediction System, Ocean Sci. J., 59, 71, https://doi.org/10.1007/s12601-024-00195-6, 2024.
Juza, M., Mourre, B., Renault, L., Gómara, S., Sebastián, K., Lora, S., Beltran, J. P., Frontera, B., Garau, B., Troupin, C., Torner, M., Heslop, E., Casas, B., Escudier, R., Vizoso, G., and Tintoré, J.: SOCIB operational ocean forecasting system and multi-platform validation in the Western Mediterranean Sea, J. Oper. Oceanogr., 9, s155–s166, https://doi.org/10.1080/1755876X.2015.1117764, 2016.
Kalaroni, S., Tsiaras, K., Petihakis, Economou-Amilli, A., and Triantafyllou, G.: Modelling the Mediterranean Pelagic Ecosystem using the POSEIDON ecological model. Part I: Nutrients and Chlorophyll-a dynamics, Deep-Sea Res. Pt. II, 171, 104647, https://doi.org/10.1016/j.dsr2.2019.104647, 2020a.
Kalaroni, S., Tsiaras, K., Petihakis, G., Economou-Amilli, A., and Triantafyllou, G.: Modelling the Mediterranean Pelagic Ecosystem using the POSEIDON ecological model. Part II: Biological dynamics, Deep-Sea Res. Pt. II, 171, 104711, https://doi.org/10.1016/j.dsr2.2019.104711, 2020b.
Kido, S., Nonaka, M., and Miyazawa, Y.: JCOPE-FGO: an eddy-resolving quasi-global ocean reanalysis product, Ocean Dynam. 72, 599–619, https://doi.org/10.1007/s10236-022-01521-z, 2022.
Korres, G. and Lascaratos, A.: A one-way nested eddy resolving model of the Aegean and Levantine basins: implementation and climatological runs, Ann. Geophys., 21, 205–220, https://doi.org/10.5194/angeo-21-205-2003, 2003.
Korres, G., Hoteit, I., and Triantafyllou, G.: Data assimilation into a Princeton Ocean Model of the Mediterranean Sea using advanced Kalman filters, J. Mar. Syst., 65, 84–104, https://doi.org/10.1016/j.jmarsys.2006.09.005, 2007.
Kourafalou, V. H., Peng, G., Kang, H., Hogan, P. J., Smedstad, O.-M., and Weisberg, R. H.: Evaluation of Global Ocean Data Assimilation Experiment products on South Florida nested simulations with the Hybrid Coordinate Ocean Model, Ocean Dynam. 59, 47–66, https://doi.org/10.1007/s10236-008-0160-7, 2009.
Kurapov, A. L., Erofeeva, S. Y., and Myers, E.: Coastal sea level variability in the US West Coast Ocean forecast system (WCOFS), Ocean Dynam., 67, 23–36, https://doi.org/10.1007/s10236-016-1013-4, 2017.
Lavoie, D., Bourgault-Brunelle, C., Brickman, D., Gibb, O., Guyondet, T., Niemi, A., Peña, A., Shen, H., and Soontiens, N.: Biogeochemical modelling at DFO: overview and recommendations of the biogeochemical modelling working group, Canadian Technical Report of Hydrography and Ocean Sciences 388, 1488–5417, https://publications.gc.ca/collections/collection_2025/mpo-dfo/Fs97-18-388-eng.pdf (last access: 14 May 2025), 2025.
Lemieux, J. F., Beaudoin, C., Dupont, F., Roy, F., Smith, G. C., Shlyaeva, A., Buehner, M., Caya, A., Chen, J., Carrieres, T., and Pogson, L.: 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, 2016.
Le Traon, P. Y., Reppucci, A., Alvarez Fanjul, E., Aouf, L., Behrens, A., Belmonte, M., Bentamy, A., Bertino, L., Brando, V. E., Kreiner, M. B., Benkiran, M., Carval, T., Ciliberti, S. A., Claustre, H., Clementi, E., Coppini, G., Cossarini, G., De Alfonso Alonso-Muñoyerro, M., Delamarche, A., Dibarboure, G., Dinessen, F., Drevillon, M., Drillet, Y., Faugere, Y., Fernández, V., Fleming, A., Garcia-Hermosa, M. I., Sotillo, M. G., Garric, G., Gasparin, F., Giordan, C., Gehlen, M., Gregoire, M. L., Guinehut, S., Hamon, M., Harris, C., Hernandez, F., Hinkler, J. B., Hoyer, J., Karvonen, J., Kay, S., King, R., Lavergne, T., Lemieux-Dudon, B., Lima, L., Mao, C., Martin, M. J., Masina, S., Melet, A., Buongiorno Nardelli, B., Nolan, G., Pascual, A., Pistoia, J., Palazov, A., Piolle, J. F., Pujol, M. I., Pequignet, A. C., Peneva, E., Pérez Gómez, B., Petit de la Villeon, L., Pinardi, N., Pisano, A., Pouliquen, S., Reid, R., Remy, E., Santoleri, R., Siddorn, J., She, J., Staneva, J., Stoffelen, A., Tonani, M., Vandenbulcke, L., von Schuckmann, K., Volpe, G., Wettre, C., and Zacharioudaki, A.: From Observation to Information and Users: The Copernicus Marine Service Perspective, Front. Mar. Sci., 6, 23, https://doi.org/10.3389/fmars.2019.00234, 2019.
Liang, X., Fu, Z., Li, C., Lin, Z., and Li, B.: Evaluation of ArcIOPS sea ice forecasting products during the ninth CHINARE-Arctic in Summer 2018, Advances in Polar Science, 31, 14–25, https://doi.org/10.13679/j.advps.2019.0019, 2019.
Lima, J. A. M., Parkinson Martins, R., Tanajura, C. A. S., de Moraes Paiva, A., Cirano, M., Dias Campos, E. J., Dias Soares, I., Borges França, G., de Souza Obino, R., and Bosco Rodrigues Alvarenga, J.: Design and implementation of the Oceanographic Modeling and Observation Network (REMO) for operational oceanography and ocean forecasting, Brazilian Journal of Geophysics, 31, 209–228, https://doi.org/10.22564/rbgf.v31i2.290, 2013.
Liu, T. and Hirose, N.: Comparison of surface and lateral boundary conditions controlled by pseudo-altimeter data assimilation for a regional Kuroshio model, J. Oceanogr., 78, 73–88, https://doi.org/10.1007/s10872-021-00629-y, 2022.
Lyard, F. H., Allain, D. J., Cancet, M., Carrère, L., and Picot, N.: FES2014 global ocean tide atlas: design and performance, Ocean Sci., 17, 615–649, https://doi.org/10.5194/os-17-615-2021, 2021.
Marshall, J., Adcroft, A., Hill, C., Perelman, L., and Heisey, C.: A finite-volume, incompressible Navier Stokes model for studies of the ocean on parallel computers. J. Geophys. Res.-Oceans, 102, 5753–5766, https://doi.org/10.1029/96JC02775, 1997.
Mehra, A. and Rivin, I.: A Real Time Ocean Forecast System for the North Atlantic Ocean, Terr. Atmos. Ocean. Sci., 21, 211–228, https://doi.org/10.3319/TAO.2009.04.16.01(IWNOP), 2010.
Miyazawa, Y., Zhang, R., Guo, X., Tamura, H., Ambe, D., Lee, J.-S., Okuno, A., Yoshinari, H., Setou, T., and Komatsu, K.: Water mass variability in the western North Pacific detected in a 15-year eddy resolving ocean reanalysis, J. Oceanogr., 65, 737–756, https://doi.org/10.1007/s10872-009-0063-3, 2009.
Miyazawa, Y., Varlamov, S. M., Miyama, T., Kurihara, Y., Murakami, H., and Kachi, M.: A nowcast/forecast system for Japan's coasts using daily assimilation of remote sensing and in situ data, Remote Sens., 13, 2431, https://doi.org/10.3390/rs13132431, 2021.
Montes, I., Dewitte, B., Gutknecht, E., Paulmier, A., Dadou, I., Oschlies, A., and Garçon, V.: High-resolution modeling of the Oxygen Minimum Zone of the Eastern Tropical Pacific: Sensitivity to the tropical oceanic circulation, J. Geophys. Res.-Oceans, 119, 5515–5532, https://doi.org/10.1002/2014JC009858, 2014.
Montes, I., Segura, B., Castillón, F., Manay, R., Mosquera, K., and Takahashi, K.: Pronósticos experimentales del posible FEN para la Comisión ENFEN con un modelo de Sistema Tierra de alta resolución para el territorio nacional y el Pacífico oriental, Informe Técnico, https://www.gob.pe/institucion/igp/informes-publicaciones/5119632-pronosticos-experimentales-del-posible-fen-para-la-comision-enfen-con-un-modelo-de-sistema-tierra-de-alta-resolucion-para-el-territorio-nacional-y-el-pacifico-oriental (last access: 26 July 2024), 2023.
Mosquera-Vasquez, K., Dewitte, B., and Illig, S.: The Central Pacific El Nino intraseasonal Kelvin wave, J. Geophys. Res.-Oceans, 119, 6605–6621, https://doi.org/10.1002/2014JC010044, 2014
Mourre, B., Aguiar, E., Juza, M., Hernandez-Lasheras, J., Reyes, E., Heslop, E., Escudier, R., Cutolo, E., Ruiz, S., Mason, E., Pascual, A., Tintoré, J.: Assessment of high-resolution regional ocean prediction systems using muli-platform ob-servations: illustrations in the Western Mediterranean Sea, in: New Frontiers in Operational Oceanography, edited by: Chassignet, E., Pascual, A., Tintoré, J., and Verron, J., GODAE OceanView, 663–694, https://doi.org/10.17125/gov2018.ch24, 2018.
Napolitano, E., Iacono, R., Palma, M., Sannino, G., Carillo, A., Lombardi, E., Pisacane, G., and Struglia, M. V.: MITO: A new operational model for the forecasting of the Mediterranean Sea circulation, Front. Energy Res., 10, 1296, https://doi.org/10.3389/fenrg.2022.941606, 2022.
Palma, M., Iacono, R., Sannino, G., Bargagli, A., Carillo, A., Fekete, B. M., Lombardi, E., Napolitano, E., Pisacane, G., and Struglia, M. V.: Short-term, linear, and non-linear local effects of the tides on the surface dynamics in a new, high-resolution model of the Mediterranean Sea circulation, Ocean Dynam., 70, 935–963, https://doi.org/10.1007/s10236-020-01364-6, 2020.
Paquin, J. P., Lu, Y., Taylor, S., Blanken, H., Marcotte, G., Hu, X., Zhai, L., Higginson, S., Nudds, S., Chanut, J., and Smith, G. C.: High-resolution modelling of a coastal harbour in the presence of strong tides and significant river runoff, Ocean Dynam., 70, 365–385, https://doi.org/10.1007/s10236-019-01334-7, 2020.
Paquin, J. P., Roy, F., Smith, G. C., MacDermid, S., Lei, J., Dupont, F., Lu, Y., Taylor, S., St-Onge-Drouin, S., Blanken, H., and Dunphy, M.: A new high-resolution Coastal Ice-Ocean Prediction System for the east coast of Canada, Ocean Dynam., 74, 799–826, https://doi.org/10.1007/s10236-024-01634-7, 2024.
Pellerin, P., Ritchie, H., Saucier, F. 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, https://doi.org/10.1175/MWR-D-17-0157.1, 2004.
Peterson, K. A., Smith, G. C., Lemieux, J. F., Roy, F., Buehner, M., Caya, A., Houtekamer, P. L., Lin, H., Muncaster, R., Deng, X., and Dupont, F.: Understanding sources of Northern Hemisphere uncertainty and forecast error in a medium-range coupled ensemble sea-ice prediction system, Q. J. Roy. Meteor. Soc., 148, 2877–2902, https://doi.org/10.1002/qj.4340, 2022.
Pinardi, N., Allen, I., Demirov, E., De Mey, P., Korres, G., Lascaratos, A., Le Traon, P.-Y., Maillard, C., Manzella, G., and Tziavos, C.: The Mediterranean ocean forecasting system: first phase of implementation (1998–2001), Ann. Geophys., 21, 3–20, https://doi.org/10.5194/angeo-21-3-2003, 2003.
Pizarro-Koch, M., Pizarro, O., Dewitte, B., Montes, I., Ramos, M., Paulmier, A., and Garcon, V.: Seasonal variability of the southern tip of the Oxygen Minimum Zone in the Eastern South Pacific (30°–38° S): A modeling study, J. Geophys. Res.-Oceans, 124, 8574–8604, https://doi.org/10.1029/2019JC015201, 2019.
Ponsoni, L., Ribergaard, M. H., Nielsen-Englyst, P., Wulf, T., Buus-Hinkler, J., Kreiner, M. B., and Rasmussen, T. A. S.: Greenlandic sea ice products with a focus on an updated operational forecast system, Front. Mar. Sci., 10, 979792, https://doi.org/10.3389/fmars.2023.979782, 2023.
Porter, A. R. and Heimbach, P.: Unlocking the Power of Parallel Computing: GPU technologies for Ocean Forecasting, in: Ocean prediction: present status and state of the art (OPSR), edited by: Álvarez Fanjul, E., Ciliberti, S. A., Pearlman, J., Wilmer-Becker, K., and Behera, S., Copernicus Publications, State Planet, 5-opsr, 23, https://doi.org/10.5194/sp-5-opsr-23-2025, 2025.
Qiao, F., Wang, G., Khokiattiwong, S., Akhir, M. F., Zhu, W., and Xiao, B.: China published ocean forecasting system for the 21st-Century Maritime Silk Road on December 10, 2018, Acta Oceanol. Sin., 38, 1–3, https://doi.org/10.1007/s13131-019-1365-y, 2019.
Reche, P., Artal, O., Pinilla, E., Ruiz, C., Venegas, O., Arriagada, A., and Falvey, M.: CHONOS: oceanographic information website for Chilean Patagonia, Ocean Coast. Manage., 208, 105634, https://doi.org/10.1016/j.ocecoaman.2021.105634, 2021.
Röhrs, J., Gusdal, Y., Rikardsen, E. S. U., Durán Moro, M., Brændshøi, J., Kristensen, N. M., Fritzner, S., Wang, K., Sperrevik, A. K., Idžanović, M., Lavergne, T., Debernard, J. B., and Christensen, K. H.: Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard, Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, 2023.
Sakov, P., Evensen, G., and Bertino, L.: Asynchronous data assimilation with the EnKF, Tellus A, 62, 24–29, https://doi.org/10.1111/j.1600-0870.2009.00417.x, 2010.
Sannino, G., Carillo, A., Iacono, R., Napolitano, E., Palma, M., Pisacane, G., and Struglia, M. V.: Modelling present and future climate in the Mediterranean Sea: a focus on sea-level change, Clim. Dynam., 59, 357–391, https://doi.org/10.1007/s00382-021-06132-w, 2022.
Saucier, F. J., Roy, F., Gilbert, D., Pellerin, P., and Ritchie, H.:. Modeling the formation and circulation processes of water masses and sea ice in the Gulf of St. Lawrence, Canada, J. Geophys. Res.-Oceans, 108, 3269, https://doi.org/10.1029/2000JC000686, 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. Dynam., 23, 303–326, https://doi.org/10.1007/s00382-004-0445-6, 2004.
Segura, B., Montes, I., Castillón, F., Manay R., and Takahashi, K.: Implementación del componente acoplado océano-atmósfera del Modelo Regional del Sistema Tierra (RESM, por sus siglas en inglés) para el territorio peruano y el océano Pacífico oriental: periodo enero-julio 2023. Boletín científico El Niño, Instituto Geofísico del Perú, 10, 10–13, https://repositorio.igp.gob.pe/server/api/core/bitstreams/77707dc7-eb95-45a2-ab47-b2974ca77bfa/content (last access: 26 July 2024), 2023.
Simionato, C. G., Meccia, V. L., Dragani, W. C., and Nuñez, M. N.: On the use of the NCEP/NCAR surface winds for modelling barotropic circulation in the Río de la Plata Estuary, Estuar. Coast. Shelf Sci., 70, 195–206, https://doi.org/10.1016/j.ecss.2006.05.047, 2006.
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, https://www.thejot.net/article-preview/?show_article_preview=510 (last access: 26 May 2025), 2013a.
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, 2013b.
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., Colan, D. S., 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., Liu, Y., Benkiran, M., Chikhar, K., Surcel Colan, D., Gauthier, A.-A., Testut, C.-E., Dupont, F., Lei, J., Roy, F., Lemieux, J.-F., and Davidson, F.: The Regional Ice Ocean Prediction System v2: a pan-Canadian ocean analysis system using an online tidal harmonic analysis, Geosci. Model Dev., 14, 1445–1467, https://doi.org/10.5194/gmd-14-1445-2021, 2021.
Sorgente, R., Tedesco, C., Pessini, F., De Dominicis, M., Gerin, R., Olita, A., Fazioli, L., Di Maio A., and Ribotti, A.: Forecast of drifter trajectories using a Rapid Environmental Assessment based on CTD observations, Deep-Sea Res. Pt. II, 133, 39–53, https://doi.org/10.1016/j.dsr2.2016.06.020, 2016.
Sotillo, M. G., Cerralbo, P., Lorente, P., Grifoll, M., Espino, M., Sanchez-Arcilla, A., and Alvarez-Fanjul, E.: Coastal ocean forecasting in Spanish ports: the Samoa operational service, J. Oper. Oceanogr., 13, 37–54, https://doi.org/10.1080/1755876X.2019.1606765, 2019.
Srinivasan, A., Chin, T. M., Chassignet, E. P., Iskandarani, M., and Groves, N.: A Statistical Interpolation Code for Ocean Analysis and Forecasting, J. Atmos. Ocean. Tech., 39, 367–386, https://doi.org/10.1175/JTECH-D-21-0033.1, 2022.
Tanajura, C. A. S., Mignac, D., de Santana, A. N., Costa, F. B., Lima, L. N., Belyaev, K. P., and Zhu, J.: Observing system experiments over the Atlantic Ocean with the REMO ocean data assimilation system (RODAS) into HYCOM, Ocean Dynam., 70, 115–138, https://doi.org/10.1007/s10236-019-01309-8, 2020.
The Wamdi Group: The WAM model – a third generation ocean wave prediction model, J. Phys. Oceanogr., 18, 1775–1810, https://doi.org/10.1175/1520-0485(1988)018<1775:TWMTGO>2.0.CO;2, 1988.
Tintoré, J., Pinardi, N., Álvarez-Fanjul, E., Aguiar, E., Álvarez-Berastegui, D., Bajo, M., Balbin, R., Rozzano, R., Buongiorno Nardelli, B., Casas, B., Charcos-Llorens, M., Chiggiato, J., Clementi, E., Coppini, G., Coppola, L., Cossarini, G., Deidun, A., Deudero, S., D’Ortenzio, F., Drago, A., Drudi, M., El Serafi, G., Escudier, R., Farcy, P., Federico, I., Fernandez, J. G., Ferrarin, C., Fossi, C. Frangoulis, C., Galgani, F., Gana, S., Lafuente, J. G., Sotillo, M. G., Garreau, P., Gertman, I., Gómez-Pujol, L., Grandi, A., Hayes, D., Hernández-Lasheras, J., Herut, B., Heslop, E., Hilmi, K., Juza, M., Kallos, G., Korres, G., Lecci, R., Lazzari, P., Lorente, P., Liubartseva, S., Luoanchi, F., Malacic, V., Mannarini, G., March, D., Marullo, S., Mauri, E., Meszaros, L., Mourre, B., Mortier, L., Muñoz-Mas, C., Novellino, A., Obaton, D., Orfila, A., Pascual, A., Pensieri, S., Pérez Gómez, B., Pérez Rubio, S., Perivoliotis, L., Petihakis, G., Petit de la Villéon, L. Pistoia, J., Poulain, P.-M., Pouliquen, S., Prieto, L., Raimbault, P., Reglero, P., Reyes, E., Rotllan, P., Ruiz, S., Ruiz, J., Ruiz, I., Ruiz-Orejón, L. F., Salihoglu, B., Salon, S., Sammartino, S., Sánchez Arcilla, A., Sánchez-Román, A., Sannino, G., Santoleri, R., Sarda’, R., Schroeder, K., Simoncelli, S., Sofianos, S., Sylaios, G., Tanhua, T., Teruzzo, A., Testor, P., Tezcam, D., Torner, M., Trotta, F., Umgiesser, G., von Schuckmann, K., Verri, G., Vilibic, I., Yucel, M., Zavatarelli, M., and Zodiatis, G.: Challenges for sustained observing and Forecasting systems in the Mediterranean Sea, Front. Mar. Sci., 6, 568, https://doi.org/10.3389/fmars.2019.00568, 2019.
Toledano, C., Ghantous, M., Lorente, P., Dalphinet, A., Aouf, L., and Sotillo, M. G.: Impacts of an Altimetric Wave Data Assimilation Scheme and Currents-Wave Coupling in an Operational Wave System: The New Copernicus Marine IBI Wave Forecast Service, J. Mar. Sci. Eng., 10, 457, https://doi.org/10.3390/jmse10040457, 2022.
Tolman, H. L.: User manual and system documentation of WAVEWATCH III version 3.14, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, National Centers for Environmental Prediction, https://polar.ncep.noaa.gov/mmab/papers/tn276/MMAB_276.pdf (last access: 16 March 2025), 2009.
Tolman, H. L., Balasubramaniyan, B., Burroughs, L. D., Chalikov, D. V., Chao, Y. Y., Chen H. S., and Gerald, V. M.: Development and implementation of wind generated ocean surface wave models at NCEP, Weather Forecast., 17, 311–333, https://doi.org/10.1175/1520-0434(2002)017<0311:DAIOWG>2.0.CO;2, 2002.
Umgiesser, G., Canu, D.M., Cucco A., and Solidoro, C.: A finite element model for the Venice Lagoon. Development, set up, calibration and validation, J. Marine Syst., 51, 123–145, https://doi.org/10.1016/j.jmarsys.2004.05.009, 2004.
Urbano-Latorre, C. P., Dagua Paz, C. J., and Camilo Martiìnez, A. F.: Análisis del clima marítimo de aguas intermedias y su potencial energético en la zona de influencia de los principales puertos del Caribe colombiano, Bol. Cien. CIOH, 42, 27–46, https://doi.org/10.26640/22159045.2023.620, 2023.
Vichi, M., Lovato, T., Butenschön, M., Tedesco, L., Lazzari, P., Cossarini, G., Masina, S., Pinardi, N., Solidoro, C., and Zavatarelli, M.: The Biogeochemical Flux Model (BFM): Equation Description and User Manual, BFM version 5.2. BFM Report series N. 1, Release 1.2, June 2020, Bologna, Italy, 104 pp., http://bfm-community.eu (last access: 14 May 2025), 2020.
Whitaker, J. S. and Hamill, T. M.: Ensemble data assimilation without perturbed observations, Mon. Weather Rev., 130, 1913–1924, https://doi.org/10.1175/1520-0493(2002)130<1913:EDAWPO>2.0.CO;2, 2002.
Williams, T., Korosov, A., Rampal, P., and Ólason, E.: Presentation and evaluation of the Arctic sea ice forecasting system neXtSIM-F, The Cryosphere, 15, 3207–3227, https://doi.org/10.5194/tc-15-3207-2021, 2021.
Wu, Y., Tang, C., and Dunlap, E.: Assimilation of sea surface temperature into CECOM by flux correction, Ocean Dynam., 60, 403–412, 2010.
Yamaguchi, H.: Sea ice prediction and construction of an ice navigation support system for the Arctic sea routes. Proceedings of the 22nd International Conference on Port and Ocean Engineering under Arctic Conditions, 9–13 June 2013, Espoo, Finland, http://worldcat.org/issn/03766756 (last access: 26 May 2025), 2013.
Yiwen, L., Liu, J., Lin, P., Liu, H., Yu, Z., and Zheng, W.: An assessment of marine heat waves in a global eddy-resolving ocean forecast system: A case study around the China Sea, J. Mar. Sci. Eng., 5, 965, https://doi.org/10.3390/jmse11050965, 2023.
Zheng, L. and Weisberg, R. H.: Modeling the west Florida coastal ocean by downscaling from the deep ocean, across the continental shelf and into the estuaries, Ocean Model., 48, 10–29, https://doi.org/10.1016/j.ocemod.2012.02.002, 2012.
Zodiatis, G., Lardner, R., Lascaratos, A., Georgiou, G., Korres, G., and Syrimis, M.: High resolution nested model for the Cyprus, NE Levantine Basin, eastern Mediterranean Sea: implementation and climatological runs, Ann. Geophys., 21, 221–236, https://doi.org/10.5194/angeo-21-221-2003, 2003.
Zodiatis, G., Lardner, R., Hayes, D. R., Georgiou, G., Sofianos, S., Skliris, N., and Lascaratos, A.: Operational ocean forecasting in the Eastern Mediterranean: implementation and evaluation, Ocean Sci., 4, 31–47, https://doi.org/10.5194/os-4-31-2008, 2008.
Zodiatis, G., Radhakrishnan, H., Galanis, G., Nikolaidis, A., Emmanouil, G., Nikolaidis, G., Lardner, R., Stylianou, S., Nikolaidis, M., Sofianos, S. S., Vervatis, V., Kallos, G. B., Kozyrakis, G., and Kampis, N.: Downscaling the Copernicus Marine Service in the Eastern Mediterranean. OM14A: Advances in Coastal Ocean Modeling, Prediction, and Ocean Observing System Evaluation. AGU, Ocean Science meeting, 11–16 February 2018, Portland, Oregon, https://agu.confex.com/agu/os18/meetingapp.cgi/Paper/304719 (last access: 26 May 2025), 2018.
Short summary
Operational ocean forecasting systems (OOFSs) are crucial for human activities, environmental monitoring, and policymaking. An assessment across eight key regions highlights strengths and gaps, particularly in coastal and biogeochemical forecasting. AI offers improvements, but collaboration, knowledge sharing, and initiatives like the OceanPrediction Decade Collaborative Centre (DCC) are key to enhancing accuracy, accessibility, and global forecasting capabilities.
Operational ocean forecasting systems (OOFSs) are crucial for human activities, environmental...
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