Articles | Volume 5-opsr
https://doi.org/10.5194/sp-5-opsr-2-2025
© 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-2-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
02 Jun 2025
| OPSR | Chapter 2.1
| 02 Jun 2025 | OPSR | Chapter 2.1
Core services: an introduction to global ocean forecasting
Yann Drillet
CORRESPONDING AUTHOR
Mercator Ocean International, Toulouse, France
Matthew Martin
Met Office, Exeter, UK
Yosuke Fujii
Japan Meteorological Agency, Meteorological Research Institute, Tsukuba, Japan
Eric Chassignet
Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, Florida, United States
Stefania Ciliberti
Nologin Oceanic Weather Systems, Santiago de Compostela, Spain
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Gaël Many, Julien Jouanno, Marc Lucas, Audrey Hasson, Jean-Michel Lellouche, and Yann Drillet
State Planet Discuss., https://doi.org/10.5194/sp-2026-30, https://doi.org/10.5194/sp-2026-30, 2026
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Large Sargassum blooms have become a recurring feature of the Tropical Atlantic, affecting coastal areas and ecosystems. We studied satellite observations from 2002 to 2025 to understand how bloom size and severity vary through time and across regions. We developed two simple indicators to compare years and areas. The results reveal strong regional differences and show that 2025 was an exceptional basin-wide bloom, highlighting the value of consistent monitoring for tracking future events.
Pierre-Yves Le Traon, Gérald Dibarboure, Jean-Michel Lellouche, Marie-Isabelle Pujol, Mounir Benkiran, Marie Drevillon, Yann Drillet, Yannice Faugère, and Elisabeth Remy
Ocean Sci., 21, 1329–1347, https://doi.org/10.5194/os-21-1329-2025, https://doi.org/10.5194/os-21-1329-2025, 2025
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By providing all weather, global, and real-time observations of sea level, a key variable to constrain ocean analysis and forecasting systems, satellite altimetry has had a profound impact on the development of operational oceanography. This paper provides an overview of the development and evolution of satellite altimetry and operational oceanography over the past 20 years from the launch of Jason-1 in 2001 to the launch of SWOT (Surface Water and Ocean Topography) in 2022.
Liying Wan, Marcos Garcia Sotillo, Mike Bell, Yann Drillet, Roland Aznar, and Stefania Ciliberti
State Planet, 5-opsr, 15, https://doi.org/10.5194/sp-5-opsr-15-2025, https://doi.org/10.5194/sp-5-opsr-15-2025, 2025
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Operating the ocean value chain requires the implementation of steps that must work systematically and automatically to generate ocean predictions and deliver this information. The paper illustrates the main challenges foreseen by operational chains in integrating complex numerical frameworks from the global to coastal scale and discusses existing tools that facilitate orchestration, including examples of existing systems and their capacity to provide high-quality and timely ocean forecasts.
Michael J. Bell, Andreas Schiller, and Stefania Ciliberti
State Planet, 5-opsr, 10, https://doi.org/10.5194/sp-5-opsr-10-2025, https://doi.org/10.5194/sp-5-opsr-10-2025, 2025
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We provide an introduction to physical ocean models, at elementary and intermediate levels, describing the properties they represent, the principles and equations they use to evolve these properties, the physical phenomena they simulate, and the wider context and prospects for their further development. We also outline, at a more technical level, the methods and approximations that they use and the difficulties that limit their accuracy or reliability.
Mounir Benkiran, Pierre-Yves Le Traon, Elisabeth Rémy, and Yann Drillet
EGUsphere, https://doi.org/10.5194/egusphere-2024-420, https://doi.org/10.5194/egusphere-2024-420, 2024
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The assimilation of altimetry data corrects and improves the forecast of a global ocean forecasting system. Until now, the use of altimetry observations from nadir altimeters has had a major impact on the quality of ocean forecasts. Our study shows that the use of observations from swath altimeters will have a greater impact than the quality of these forecasts and will better constrain mesoscale structures.
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
Davi Mignac and Matthew J. Martin
EGUsphere, https://doi.org/10.5194/egusphere-2026-5409, https://doi.org/10.5194/egusphere-2026-5409, 2026
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Satellites track Arctic sea ice daily, but the widely used microwave sensors blur the ice edge. We used machine learning to sharpen the satellite observations by teaching them from more detailed radar images, then fed the improved observations into a global ocean and sea-ice forecasting model. The corrected observations produced a clearer, better-placed ice edge and more accurate short-range forecasts. This could help make Arctic shipping and weather forecasts more reliable.
Álvaro de Pascual Collar, Axel Alonso Valle, Alex Gallardo, Marta de Alfonso Alonso-Muñoyerro, Begoña Pérez Gómez, Stefania Ciliberti, and Marcos G. Sotillo
State Planet, 7-osr10, 7, https://doi.org/10.5194/sp-7-osr10-7-2026, https://doi.org/10.5194/sp-7-osr10-7-2026, 2026
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This study improves the monitoring of extreme sea surface temperature events in the Iberia–Biscay–Ireland region. We tested new data sources and combined information from different models and satellites to provide more consistent results and characterize inter-product spread. The findings show that these methods make the indicator more reliable and useful for supporting climate and ocean management decisions.
Gaël Many, Julien Jouanno, Marc Lucas, Audrey Hasson, Jean-Michel Lellouche, and Yann Drillet
State Planet Discuss., https://doi.org/10.5194/sp-2026-30, https://doi.org/10.5194/sp-2026-30, 2026
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Large Sargassum blooms have become a recurring feature of the Tropical Atlantic, affecting coastal areas and ecosystems. We studied satellite observations from 2002 to 2025 to understand how bloom size and severity vary through time and across regions. We developed two simple indicators to compare years and areas. The results reveal strong regional differences and show that 2025 was an exceptional basin-wide bloom, highlighting the value of consistent monitoring for tracking future events.
Joseph K. Ansong, Brian K. Arbic, Romain Bourdalle-Badié, Clément Bricaud, Jérôme Chanut, Dimitris Menemenlis, Richard D. Ray, Michael Schindelegger, Alan J. Wallcraft, He Wang, Alistair J. Adcroft, Frédéric Briol, Maarten C. Buijsman, Loren Carrère, Eric P. Chassignet, Gerald Dibarboure, Robert W. Hallberg, Christopher N. Hill, Ariane Koch-Larrouy, Florent Lyard, Matthew R. Mazloff, An T. Nguyen, Nicolas Picot, Rui M. Ponte, and Jay F. Shriver
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We assess how well four high-resolution global ocean models reproduce surface and internal tides compared with satellite observations. Some models produce internal tides that are too strong, but including energy loss over rough seafloor improves their accuracy. Longer model records and higher resolution also improve agreement with observations. We further identify errors in the tidal forcing of widely used MITgcm simulations that reduce the accuracy of their simulated tides.
Rémi Laxenaire, Eric P. Chassignet, Xiaobiao Xu, Alan J. Wallcraft, Luna Hiron, Brian K. Arbic, Maarten C. Buijsman, Miguel Solano, and Shane Elipot
Geosci. Model Dev., 19, 5571–5599, https://doi.org/10.5194/gmd-19-5571-2026, https://doi.org/10.5194/gmd-19-5571-2026, 2026
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Surface kinetic energy reflects the distribution of ocean circulation across temporal and spatial scales, shaping energy transfer and mixing in the upper ocean. In a series of North and Equatorial Atlantic numerical simulations, we show that the surface kinetic energy is sensitive to the model's choices in grid and seafloor resolution and to the tides and wind variability, offering guidance for the configuration of future ocean simulations.
Gokhan Danabasoglu, Frederic S. Castruccio, Burcu Boza, Alice M. Barthel, Arne Biastoch, Adam Blaker, Alexandra Bozec, Diego Bruciaferri, Frank O. Bryan, Eric P. Chassignet, Yao Fu, Ian Grooms, Catherine Guiavarc'h, Hakase Hayashida, Andrew McC. Hogg, Ryan M. Holmes, Doroteaciro Iovino, Andrew E. Kiss, M. Susan Lozier, Gustavo Marques, Alex Megann, Franziska U. Schwarzkopf, Dave Storkey, Luke van Roekel, Jon Wolfe, Xiaobiao Xu, and Rong Zhang
Geosci. Model Dev., 19, 5071–5117, https://doi.org/10.5194/gmd-19-5071-2026, https://doi.org/10.5194/gmd-19-5071-2026, 2026
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A comparison of simulated and observed overturning transports across the Overturning in the Subpolar North Atlantic Program sections is presented. Eighteen ocean simulations participate in the study with resolutions ranging from coarse to eddy-resolving. The simulated transports are in general agreement with observations, with better agreement at high resolution. Analyzing overturning circulations in both depth and density space together provides a more complete picture.
Simona Masina, Andrea Cipollone, Doroteaciro Iovino, Stefania Ciliberti, Rita Lecci, Sergio Cretí, Vladyslav Lyubartsev, Giovanni Coppini, and Emanuela Clementi
EGUsphere, https://doi.org/10.5194/egusphere-2026-887, https://doi.org/10.5194/egusphere-2026-887, 2026
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The paper presents GOFS16, an eddy-resolving global operational ocean and sea ice forecasting system which provides 6-day forecasts of three-dimensional temperature, salinity, currents, sea level, and sea ice properties. The system assimilates satellite and in situ observations using a 3D variational data assimilation scheme. Validation is conducted routinely using global and regional metrics. Results indicate that GOFS16 performs within the expected range of skill for current global systems.
Marco Larrañaga, Julien Jouanno, Eric P. Chassignet, Giovanni Durante, Ilkyeong Ma, Julio Sheinbaum, and Lionel Renault
Ocean Sci., 22, 821–841, https://doi.org/10.5194/os-22-821-2026, https://doi.org/10.5194/os-22-821-2026, 2026
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We analyze 29 years of satellite altimetry to investigate the detachment of Loop Current Eddies in the Gulf of Mexico. Over half of the Loop Current eddies reattach within a month, while 42 % separate and drift westward. Detachment requires the Loop Current to reach the Mississippi Fan and is strongly influenced by cyclonic eddies, whose configuration determines whether an eddy separates or reattaches to the Loop Current.
Manuel García-León, José María García-Valdecasas, Lotfi Aouf, Alice Dalphinet, Juan Asensio, Stefania Angela Ciliberti, Breogán Gómez, Víctor Aquino, Roland Aznar, and Marcos Sotillo
Ocean Sci., 21, 3265–3290, https://doi.org/10.5194/os-21-3265-2025, https://doi.org/10.5194/os-21-3265-2025, 2025
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Accurate short-term wave forecasts are key for coastal activities. These forecasts rely on wind and currents as forcing, which in this work were both enhanced using neural networks (NNs) trained with satellite and radar data. Tested at three European sites, the NN-corrected winds were 35 % more accurate, and currents also improved. This led to improved IBI (Iberian–Biscay–Ireland) wave model predictions of wave height and period by 10 % and 17 %, respectively; even correcting under extreme events.
Jozef Skákala, David Ford, Keith Haines, Amos Lawless, Matthew J. Martin, Philip Browne, Marcin Chrust, Stefano Ciavatta, Alison Fowler, Daniel Lea, Matthew Palmer, Andrea Rochner, Jennifer Waters, Hao Zuo, Deep S. Banerjee, Mike Bell, Davi M. Carneiro, Yumeng Chen, Susan Kay, Dale Partridge, Martin Price, Richard Renshaw, Georgy Shapiro, and James While
Ocean Sci., 21, 1709–1734, https://doi.org/10.5194/os-21-1709-2025, https://doi.org/10.5194/os-21-1709-2025, 2025
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UK marine data assimilation (MDA) involves a closely collaborating research community. In this paper, we offer both an overview of the state of the art and a vision for the future across all of the main areas of UK MDA, ranging from physics to biogeochemistry to coupled DA. We discuss the current UK MDA stakeholder applications, highlight theoretical developments needed to advance our systems, and reflect upon upcoming opportunities with respect to hardware and observational missions.
Pierre-Yves Le Traon, Gérald Dibarboure, Jean-Michel Lellouche, Marie-Isabelle Pujol, Mounir Benkiran, Marie Drevillon, Yann Drillet, Yannice Faugère, and Elisabeth Remy
Ocean Sci., 21, 1329–1347, https://doi.org/10.5194/os-21-1329-2025, https://doi.org/10.5194/os-21-1329-2025, 2025
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By providing all weather, global, and real-time observations of sea level, a key variable to constrain ocean analysis and forecasting systems, satellite altimetry has had a profound impact on the development of operational oceanography. This paper provides an overview of the development and evolution of satellite altimetry and operational oceanography over the past 20 years from the launch of Jason-1 in 2001 to the launch of SWOT (Surface Water and Ocean Topography) in 2022.
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc'h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
Geosci. Model Dev., 18, 3405–3425, https://doi.org/10.5194/gmd-18-3405-2025, https://doi.org/10.5194/gmd-18-3405-2025, 2025
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We describe major improvements of the Met Office's global ocean–sea ice forecasting system. The models and the way observations are used to improve the forecasts were changed, which led to a significant error reduction of 1 d forecasts. The new system performance in past conditions, where subsurface observations are scarce, was improved with more consistent ocean heat content estimates. The new system will be of better use for climate studies and will provide improved forecasts for end users.
Marina Tonani, Eric Chassignet, Mauro Cirano, Yasumasa Miyazawa, and Begoña Pérez Gómez
State Planet, 5-opsr, 3, https://doi.org/10.5194/sp-5-opsr-3-2025, https://doi.org/10.5194/sp-5-opsr-3-2025, 2025
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This article provides an overview of the main characteristics of ocean forecast systems covering a limited region of the ocean. Their main components are described, as well as the spatial and temporal scales they resolve. The oceanic variables that these systems are able to predict are also explained. An overview of the main forecasting systems currently in operation is also provided.
Michael J. Bell, Andreas Schiller, and Stefania Ciliberti
State Planet, 5-opsr, 10, https://doi.org/10.5194/sp-5-opsr-10-2025, https://doi.org/10.5194/sp-5-opsr-10-2025, 2025
Short summary
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We provide an introduction to physical ocean models, at elementary and intermediate levels, describing the properties they represent, the principles and equations they use to evolve these properties, the physical phenomena they simulate, and the wider context and prospects for their further development. We also outline, at a more technical level, the methods and approximations that they use and the difficulties that limit their accuracy or reliability.
Stefania Ciliberti and Gianpaolo Coro
State Planet, 5-opsr, 24, https://doi.org/10.5194/sp-5-opsr-24-2025, https://doi.org/10.5194/sp-5-opsr-24-2025, 2025
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This review explores how cloud computing technology and its foundational concepts can enhance operational forecasting with scalable, flexible, and measurable resources. It highlights its benefits for the ocean value chain in support of ocean data management, forecasting system infrastructure, data analysis, visualization of ocean forecasts, dissemination, and outreach, showcasing real-world initiatives from the weather and ocean community.
Mauro Cirano, Enrique Alvarez-Fanjul, Arthur Capet, Stefania Ciliberti, Emanuela Clementi, Boris Dewitte, Matias Dinápoli, Ghada El Serafy, Patrick Hogan, Sudheer Joseph, Yasumasa Miyazawa, Ivonne Montes, Diego A. Narvaez, Heather Regan, Claudia G. Simionato, Gregory C. Smith, Joanna Staneva, Clemente A. S. Tanajura, Pramod Thupaki, Claudia Urbano-Latorre, Jennifer Veitch, and Jorge Zavala Hidalgo
State Planet, 5-opsr, 5, https://doi.org/10.5194/sp-5-opsr-5-2025, https://doi.org/10.5194/sp-5-opsr-5-2025, 2025
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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.
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
State Planet, 5-opsr, 6, https://doi.org/10.5194/sp-5-opsr-6-2025, https://doi.org/10.5194/sp-5-opsr-6-2025, 2025
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Ocean forecast systems provide information about a future state of the ocean. This information is provided in the form of decision support tools, or downstream applications, that can be accessed by various stakeholders to support livelihoods, coastal resilience and the good governance of the marine environment. This paper provides an overview of the various downstream applications of ocean forecast systems that are utilized around the world.
Liying Wan, Marcos Garcia Sotillo, Mike Bell, Yann Drillet, Roland Aznar, and Stefania Ciliberti
State Planet, 5-opsr, 15, https://doi.org/10.5194/sp-5-opsr-15-2025, https://doi.org/10.5194/sp-5-opsr-15-2025, 2025
Short summary
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Operating the ocean value chain requires the implementation of steps that must work systematically and automatically to generate ocean predictions and deliver this information. The paper illustrates the main challenges foreseen by operational chains in integrating complex numerical frameworks from the global to coastal scale and discusses existing tools that facilitate orchestration, including examples of existing systems and their capacity to provide high-quality and timely ocean forecasts.
Matthew J. Martin, Ibrahim Hoteit, Laurent Bertino, and Andrew M. Moore
State Planet, 5-opsr, 9, https://doi.org/10.5194/sp-5-opsr-9-2025, https://doi.org/10.5194/sp-5-opsr-9-2025, 2025
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Observations of the ocean from satellites and platforms in the ocean are combined with information from computer models to produce predictions of how the ocean temperature, salinity, and currents will evolve over the coming days and weeks and to describe how the ocean has evolved in the past. This paper summarises the methods used to produce these ocean forecasts at various centres around the world and outlines the practical considerations for implementing such forecasting systems.
Ibrahim Hoteit, Eric Chassignet, and Mike Bell
State Planet, 5-opsr, 21, https://doi.org/10.5194/sp-5-opsr-21-2025, https://doi.org/10.5194/sp-5-opsr-21-2025, 2025
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This paper explores how using multiple predictions instead of just one can improve ocean forecasts and help prepare for changes in ocean conditions. By combining different forecasts, scientists can better understand the uncertainty in predictions, leading to more reliable forecasts and better decision-making. This method is useful for responding to hazards like oil spills, improving climate forecasts, and supporting decision-making in fields like marine safety and resource management.
Olmo Zavala-Romero, Alexandra Bozec, Eric P. Chassignet, and Jose R. Miranda
Ocean Sci., 21, 113–132, https://doi.org/10.5194/os-21-113-2025, https://doi.org/10.5194/os-21-113-2025, 2025
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This study shows AI can speed up data assimilation in ocean models. Researchers used convolutional neural networks (CNNs) to assimilate sea surface temperature and height observations in the Gulf of Mexico, learning to replicate corrections made by traditional, computationally expensive methods. CNN design and training window size significantly impacted accuracy, but the percentage of ocean pixels did not. These findings suggest CNNs may accelerate data assimilation in realistic settings.
Robert R. King, Matthew J. Martin, Lucile Gaultier, Jennifer Waters, Clément Ubelmann, and Craig Donlon
Ocean Sci., 20, 1657–1676, https://doi.org/10.5194/os-20-1657-2024, https://doi.org/10.5194/os-20-1657-2024, 2024
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We use simulations of our ocean forecasting system to compare the impact of additional altimeter observations from two proposed future satellite constellations. We found that, in our system, an altimeter constellation of 12 nadir altimeters produces improved predictions of sea surface height, surface currents, temperature, and salinity compared to a constellation of 2 wide-swath altimeters.
Mounir Benkiran, Pierre-Yves Le Traon, Elisabeth Rémy, and Yann Drillet
EGUsphere, https://doi.org/10.5194/egusphere-2024-420, https://doi.org/10.5194/egusphere-2024-420, 2024
Preprint archived
Short summary
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The assimilation of altimetry data corrects and improves the forecast of a global ocean forecasting system. Until now, the use of altimetry observations from nadir altimeters has had a major impact on the quality of ocean forecasts. Our study shows that the use of observations from swath altimeters will have a greater impact than the quality of these forecasts and will better constrain mesoscale structures.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
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Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
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
Emma K. Fiedler, Matthew J. Martin, Ed Blockley, Davi Mignac, Nicolas Fournier, Andy Ridout, Andrew Shepherd, and Rachel Tilling
The Cryosphere, 16, 61–85, https://doi.org/10.5194/tc-16-61-2022, https://doi.org/10.5194/tc-16-61-2022, 2022
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Sea ice thickness (SIT) observations derived from CryoSat-2 satellite measurements have been successfully used to initialise an ocean and sea ice forecasting model (FOAM). Other centres have previously used gridded and averaged SIT observations for this purpose, but we demonstrate here for the first time that SIT measurements along the satellite orbit track can be used. Validation of the resulting modelled SIT demonstrates improvements in the model performance compared to a control.
Robert R. King and Matthew J. Martin
Ocean Sci., 17, 1791–1813, https://doi.org/10.5194/os-17-1791-2021, https://doi.org/10.5194/os-17-1791-2021, 2021
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The SWOT satellite will provide a step change in our ability to measure the sea surface height over large areas, and so improve operational ocean forecasts, but will be affected by large correlated errors. We found that while SWOT observations without these errors significantly improved our system, including correlated errors degraded most variables. To realise the full benefits offered by the SWOT mission, we must develop methods to account for correlated errors in ocean forecasting systems.
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Dalphinet, A., Aouf, L., Law-Chune, S., and Tressol, M.: Product User Manual for Global Ocean Wave Analysis and Forecasting Product, Copernicus Marine Service, https://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-GLO-PUM-001-027.pdf (last access: 20 March 2024), 2023.
Drevillon, M., Fernandez, E., and Lellouche, J. M.: Product User Manual for the Global Ocean Physical Multi Year product, Copernicus Marine Service, https://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-GLO-PUM-001-030.pdf (last access: 20 March 2024), 2023a.
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Short summary
This article describes the various stages of research and development that have been carried out over the last few decades to produce an operational reference service for global ocean monitoring and forecasting.
This article describes the various stages of research and development that have been carried out...
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