DO001
Advances in Ocean Data Assimilation and Prediction Science
Session ID#: 259709
Session Description:
Accurate ocean prediction is essential for climate resilience, maritime safety, and environmental planning. This session brings together advances in ocean data assimilation (DA), forecasting, and reanalysis to improve predictive skill across spatial and temporal scales. We welcome contributions on innovative DA algorithms -- including ensemble methods, non-Gaussian filters, and multiscale approaches -- as well as AI/ML integrations, hybrid frameworks, and data-driven error representations. Topics include coupled DA systems (e.g., ocean–atmosphere, biogeochemical, sea-ice), uncertainty quantification, and model-error handling. We also invite research on high-resolution physical and ecosystem modeling, forecast validation, and the use of diverse observations (satellite, in situ) to characterize ocean state and variability. Submissions on operational systems, observing-system design, OSE/OSSE experiments, and stakeholder-oriented tools are encouraged. Organized in collaboration with the OceanPredict programme and the UN Decade ForeSea Project, this session aims to foster interdisciplinary dialogue and showcase real-world applications that advance the science and impact of ocean prediction.
Co-Sponsor(s):
Index Terms:
1910 Data assimilation, integration and fusion [INFORMATICS]
1990 Uncertainty [INFORMATICS]
3238 Prediction [MATHEMATICAL GEOPHYSICS]
3245 Probabilistic forecasting [MATHEMATICAL GEOPHYSICS]
Primary Chair: Ibrahim Hoteit, King Abdullah University of Science and Technology (KAUST), Earth Sciences and Engineering, Thuwal, Saudi Arabia
Co-chairs: Marie Drevillon, Mercator Océan, Toulouse, France, Matthew Martin, Met Office Hadley center for Climate Change, Exeter, United Kingdom and Gregory C Smith, Environment Canada, Dorval, QC, Canada
Hybrid Ensemble-Variational Data Assimilation in a High-Resolution Global Ocean Model (2008876)
Daniel Lea, Met Office, Exeter, UNITED KINGDOM, Matthew Martin, Met Office Hadley center for Climate Change, Exeter, United Kingdom, Jennifer Waters, Met Office, Exter, United Kingdom, Davi Mignac, UK Met Office, Exeter, United Kingdom and Martin Price, Met Office, Exeter, United Kingdom
Nested 4D-Var Data Assimilation at the Ocean Submesoscale and Implications for Predictability (2011534)
Andrew M Moore1, Hernan Arango2, Julia Levin2 and John Wilkin2, (1)University of California Santa Cruz, Santa Cruz, CA, United States, (2)Rutgers University, New Brunswick, NJ, United States
What can satellite surface velocity observations bring in the Mercator system that altimetry observations cannot? (2012575)
Isabelle Mirouze1, Elisabeth Rémy2, Giovanni Ruggiero3, Mathieu Hamon2, Jean-Michel Lellouche2, Gérald Dibarboure4 and Yannice Faugere4, (1)Freelance consultant for Mercator Ocean International, Toulouse, France, (2)Mercator Ocean International, Toulouse, France, (3)Mercator Océan International, Toulouse, France, (4)CNES French National Center for Space Studies, Toulouse, France
Improving Hindcast Skills in Regions with Sparse Observations Through Transfer Learning Initialization (2013896)
Simon Lentz1, Johannes Meuer2, Felix Oertel2, Goratz Beobide-Asuaga1, Christopher Kadow2, Sebastian Brune3 and Johanna Baehr4, (1)University of Hamburg, Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Hamburg, Germany, (2)DKRZ German Climate Computing Centre, Hamburg, Germany, (3)Universität Hamburg, Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Hamburg, Germany, (4)Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany
How Does an Unconstrained Deep Ocean Impact an Ensemble Forecast? A Call for Deep Observation Assimilation (2015630)
Justin Cooke1, Kathleen A Donohue2, Clark David Rowley3, Prasad G Thoppil3 and D Randolph Watts2, (1)University of Rhode Island, Graduate School of Oceanography, Narragansett, United States, (2)Univ Rhode Island, Narragansett, United States, (3)Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, MS, United States
Blocked coastal propagation inhibits climate model representation of coastal sea level variability (2016789)
Christopher M Little, Atmospheric and Environmental Research Lexington, Lexington, MA, United States, Stephen G Yeager, NSF National Center for Atmospheric Research, Boulder, United States, Rui M Ponte, Verisk Atmospheric and Environmental Research, Lexington, United States and Carmine Donatelli, Atmospheric and Environmental Research, Lexington, United States
Development of an Ocean Color Satellite Data Assimilation Method for Coastal Ecosystem Models: A Case Study in Tokyo Bay (2017633)
Taiga Nakayama1, Hiroto Higa2, Hiroshi Murakami1 and Teruhisa Okada3, (1)Japan Aerospace Exploration Agency, Earth Observation Research Center, Tsukuba, Japan, (2)Yokohama National University, Institute of Urban Innovation, Yokohama, Japan, (3)Central Research Institute of Electric Power Industry, Sustainable System Research Laboratory, Abiko, Chiba, Japan
Improving the Representation of a Small-scale Intrathermocline Eddy in a Regional Ocean Model through SWOT and Glider Data Assimilation (2018445)
Jen-Ping Peng, Maximo Garcia-Jove2, Elisabet Verger-Miralles3, Nikolaos Zarokanellos2 and Ananda Pascual4, (1)Balearic Islands Coastal Observing And Forecasting System (SOCIB), Palma, Spain, (2)IMEDEA (CSIC - UIB), Esporles, Spain, (3)Mediterranean Institute for Advanced Studies (CSIC-UIB), Esporles, Spain
Accounting for Observation Error Correlations in Ocean Data Assimilation (2019695)
Olivier Goux1, Andrea Piacentini2, Anthony T. Weaver3 and Selime Gürol3, (1)UNITED STATES, (2)CERFACS European Centre for Research and Advanced Training in Scientific Computation, Toulouse Cedex 01, France, (3)CECI/CERFACS, ALGO, Toulouse, France
Impact of Assimilation of Absolute Dynamic Topography on Arctic Ocean Circulation (2021655)
Gregory C Smith1, Charlie Hébert-Pinard2, Audrey-Anne Gauthier3, Francois Roy2, Andrew Peterson2, Pierre Veillard4, Yannice Faugere5, Sandrine Mulet6 and Miguel Angel Morales Maqueda7, (1)Environment and Climate Change Canada, Meteorological Research Division, Quebec, QC, Canada, (2)Environment and Climate Change Canada, Meteorological Research Division, Dorval, QC, Canada, (3)Environment and Climate Change Canada, Meteorological Service of Canada, Dorval, QC, Canada, (4)Collecte Localisation Spatiale, Toulouse, France, (5)CNES French National Center for Space Studies, Toulouse, France, (6)CLS Collecte Localisation Satellites, Ramonville Saint Agne, France, (7)Newcastle University, School of Natural and Environmental Sciences, Newcastle upon Tyne, United Kingdom
A new suite of MATLAB based primary-level quality control tools for discrete-bottle based ocean carbonate chemistry measurements (2022104)
Liqing Jiang1, Atharva Bhalke2, Hye Lim Yoo - NOAA Affiliate3, Brendan R Carter4 and Larissa Dias4, (1)University of Maryland, Earth System Science Interdisciplinary Center,, College Park, United States, (2)University of Maryland College Park, Computer Science, College Park, United States, (3)University of Maryland College Park, College Park, United States, (4)University of Washington Seattle, Seattle, United States
Evaluating the Accuracy of Ocean Predictions: lesson learnt from the Copernicus Marine Service and Opportunities in the Digital Ecosystem (2023180)
Stefania Ciliberti1, Axel Alonso-Valle1, Arnau Buñuel1, Roland Aznar1, Bruno Levier2, Elodie Gutknecht2, Breogan Gomez1, Alice Dalphinet3, Jue Lin-Ye1, Luis Ferrer4, Yolanda Sagarminaga4, Francisco Campuzano5, Pedro Melo Da Costa6, Oscar Ballesteros1, Selma Cabo1, Cristina Ramos De Francisco1, José María García-Valdecasas1, Manuel Garcia-Leon1, Sylvain Cailleau7, Aouf Lotfi3 and Marcos Sotillo1, (1)Nologin Oceanic Weather Systems, Santiago de Compostela, Spain, (2)Mercator Océan International, Toulouse, France, (3)Meteo-France, Toulouse, France, (4)AZTI, Pasaia, Spain, (5)+ATLANTIC CoLAB, Lisbon, Portugal, (6)Meteo Galicia, Santiago de Compostela, Spain, (7)Mercator Ocean International, Toulouse, France
Data Assimilation for Improved Swell Forecasts (2023346)
Marzieh Derkani, The University of Western Australia, School of Earth and Oceans, and UWA Oceans Institute, Perth, Western Australia, Australia, Jeff Hansen, The University of Western Australia, School of Earth and Oceans, and UWA Oceans Institute, Crawley, Western Australia, Australia, Stefan Zieger, Bureau of Meteorology, Melbourne, VIC, Australia and Seyed Mostafa Siadatmousavi, Iran University of Science and Technology, Tehran, Iran
Optimising Global Physics-Biogeochemistry Reanalyses for Initialising Seasonal Forecasts (2026488)
David Ford1, Joan Llort, PhD2, Pablo Ortega3 and Andrea Rochner1, (1)Met Office, Exeter, United Kingdom, (2)ICM-CSIC, Barcelona, Spain, (3)Barcelona Supercomputing Center (BSC), Earth Science Department, Barcelona, Spain
The Met Office Glosea Global Ocean and Sea Ice Reanalysis (GloSia): A Description of the Updated Global Reanalysis System, and Assessment of Quality (2026676)
Tamara Collier1, Richard Renshaw2, Matthew Martin1, Jamie Kettleborough1, Adam A Scaife1 and Davi Mignac3, (1)Met Office Hadley center for Climate Change, Exeter, United Kingdom, (2)Met Office, Exeter, United Kingdom, (3)UK Met Office, Exeter, United Kingdom
The application of a machine learning framework to improve met ocean data at operational offshore wind farms. (2027757)
Ian Ashton1, David Darbinyan2, Alyona Naberezhnykh3, Chloe Blyth4 and Ajit Pillai1, (1)University of Exeter, Penryn, UNITED KINGDOM, (2)SSE Renewables, Met Ocean Team, Glasgow, United Kingdom, (3)SSE Renewables, Met Ocean, Glasgow, United Kingdom, (4)SSE Renewables, Glasgow, United Kingdom
Variational Data Assimilation for Cross-Scale Unstructured Grid Ocean Modelling (2028627)
Dr. Eric Jansen, PhD1, Ali Aydogdu2, Marco Stefanelli3,4, Ivan Federico5, Salvatore Causio5 and Giovanni Coppini1, (1)CMCC Foundation - Euro-Mediterranean Center on Climate Change, Bologna, Italy, (2)Euro-Mediterranean Center on Climate Change, Bologna, Italy, (3)Euro-Mediterranean Center on Climate Change, Naples, Italy, (4)University of Ljubljana, Faculty of Mathematics and Physics, Ljubljana, Slovenia, (5)CMCC Foundation - Euro-Mediterranean Center on Climate Change, Lecce, Italy
A novel method to constrain Loop Current forecasts through assimilation of APEX float profiles and deep velocities (2030342)
Andrew Smith1, D Randolph Watts2, Kathleen A Donohue2, Clark David Rowley3 and Prasad G Thoppil3, (1)University of Rhode Island Graduate School of Oceanography, WEST Greenwich, RI, UNITED STATES, (2)Univ Rhode Island, Narragansett, United States, (3)Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, MS, United States
Novel observations improve modelled mesoscale and submesoscale dynamics and reveal complex subsurface structures in a Western Boundary Current. (2031397)
Moninya Roughan, University of New South Wales, Coastal and Regional Oceanography Lab, School of Biological, Earth & Environmental Sciences, Sydney, NSW, Australia, Colette Gabrielle Kerry, University of New South Wales, Coastal and Regional Oceanography Lab, School of Biological Earth and Environmental Sciences, UNSW, Sydney, NSW, Australia and Shane R Keating, University of New South Wales, Sydney, NSW, Australia
Vertical projection of assimilated surface observations in an idealized eddy in the Gulf of Mexico (2031790)
Eduardo Ashida Hernández1, Sheila Natali Estrada-Allis1, Andrew M Moore2 and Julio Sheinbaum1, (1)Center for Scientific Research and Higher Education at Ensenada, Physical Oceanography, Ensenada, BJ, Mexico, (2)University of California Santa Cruz, Santa Cruz, CA, United States
An Observation System Simulation Experiment for MOM6-Based Coastal Current Prediction in Yeosu-Gwangyang Bay with Coastal Acoustic Tomography Data Assimilation (2032816)
Nayoung Park1, Inseong Chang2, Jin-Yong CHOI3 and Young Ho Kim1, (1)Pukyong National University, Division of Earth & Environmental System Sciences, Busan, South Korea, (2)Pukyong National University, Korea Institute of Ocean Sciences and Technology, Busan, South Korea, (3)Korea Institute of Ocean Science & Technology, Marine Natural Disaster Research Department, Busan, South Korea
A High-Resolution Ensemble Analysis and Forecasting System for the Red Sea (2034307)
Siva Sanikommu1, Sateesh Masabathini1, Naila Raboudi1, George Krokos2, Daquan Guo3, Charls Antony Dr.1 and Ibrahim Hoteit3, (1)King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, (2)King Abdullah University of Science and Technology, Physical Science and Engineering Division, Thuwal, Saudi Arabia, (3)King Abdullah University of Science and Technology, Physical Sciences and Engineering Division, Thuwal, Saudi Arabia
Development and Validation Benchmarks for Short-Term Neural Ocean Surface Forecasts (2034670)
Daria Botvynko, Lab-STICC, UMR CNRS 6285, IMT Atlantique, Odyssey, INRIA, Brest, France, Clement de boyer Montégut, IFREMER, LOPS, Plouzané, France, Bertrand Chapron, IFREMER, Univ. Brest, CNRS, IRD, Laboratoire d'Océanographie Physique et Spatiale, Brest, France, Lucile Gaultier, OceanDataLab, Brest, France, Anass El Aouni, Mercator Ocean International, Toulouse, France, Julien Lesommer, Université Grenoble Alpes (UGA)/CNRS, Institut des Géosciences de l'Environnement (IGE), Grenoble, France and Ronan Fablet, IMT Atlantique, CNRS UMR Lab-STICC, Brest, France
On the evaluation and intercomparison of Mercator Ocean global ocean forecasting systems, including Data-Driven Forecasting systems (2035032)
Charly Regnier1, Marie Drevillon1, Anass El Aouni1, Simon van Gennip1, Yann Drillet2, Pierre-Yves Le Traon Dr1, Jean-Michel Lellouche1, Sylvain Cailleau1, Giovanni Ruggiero3, Quentin Gaudel4 and Clement Bricaud1, (1)Mercator Ocean International, Toulouse, France, (2)Mercator Ocean international, Toulouse, France, (3)Mercator Océan International, Toulouse, France, (4)Mercator Ocean International, Digital Ocean, Toulouse, France
A Regional Ocean Data Assimilation system for the Arabian Gulf Using Hybrid Ensemble Kalman Filtering in an MITgcm-DART Framework (2035499)
Naila Raboudi1, Siva Sanikommu1, Panagiotis Vasou2 and Ibrahim Hoteit3, (1)King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, (2)King Abdullah University of Science and Technology, Physical Science and Engineering Division, Thuwal, Saudi Arabia, (3)King Abdullah University of Science and Technology, Physical Sciences and Engineering Division, Thuwal, Saudi Arabia
Observation Vertical Resolution Relation to Ocean Analysis (2036009)
Gregg A. Jacobs1, Charlie N. Barron2, Matthew Carrier3, Joseph Matthew D'Addezio4, Robert William Helber3, Vivian A Montiforte5, Hans Ngodock6, John Osborne7, Clark David Rowley2, Bailey Rester8 and Max Yaremchuk9, (1)Mississippi State University, Mississippi State, MS, United States, (2)Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, MS, United States, (3)U.S. Naval Research Laboratory, Ocean Dynamics and Prediction, Stennis Space Center, United States, (4)Naval Research Laboratory, Stennis Space Center, United States, (5)American Society for Engineering Education, Stennis Space Center, United States, (6)Naval Research Lab Stennis Space Center, Stennis Space Center, United States, (7)American Society for Engineering Education (ASEE), Washington, DC, United States, (8)US Naval Research Laboratory, Ocean Sciences Division, Stennis Space Center, United States, (9)Naval Research Lab, Stennis Space Center, MS, United States
An AI-Assisted Ensemble Analysis and Forecasting System for the Red Sea (2036116)
Dr. Hongxing Cui1, Siva Sanikommu2, Sateesh Masabathini1, Hari Prasad Dasari3 and Ibrahim Hoteit3, (1)King Abdullah University of Science and Technology, Physical Science and Engineering Division, Thuwal, Saudi Arabia, (2)King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, (3)King Abdullah University of Science and Technology, Physical Sciences and Engineering Division, Thuwal, Saudi Arabia
Quantification of scales not constrained by observations using an ensemble of ocean analysis (2039469)
Andrew Peterson, Environment and Climate Change Canada, Environmental Numerical Weather Prediction Division, Dorval, QC, Canada, Gregory C Smith, Environment Canada, Dorval, QC, Canada, Kamel Chikhar, Environment and Climate Change Canada, Dorval, QC, Canada and Dr. Andrea Storto, PhD, Fondazione CMCC, Bolognia, Italy
CONCEPTS Ice-Ocean Prediction Research Activities (2041268)
Fraser Davidson1, Gregory C Smith2, Jean-Francois Lemieux2, Leqiang Sun3, Pengcheng Wang4, Dr. Jean-Philippe Paquin, PhD5, Graigory Sutherland6 and Mathieu Plante1, (1)Environment Canada Dorval, Dorval, QC, Canada, (2)Environment Canada, Dorval, QC, Canada, (3)Environment Canada Dorval, Dorval, ON, Canada, (4)Environment and Climate Change Canada, Dorval, QC, Canada, (5)Environment Canada Dorval, Environment and Climate Change Canada, Dorval, Canada, (6)Environment Canada, Montreal, Canada
The US West Coast Ocean Forecast System (WCOFS): operational prediction, data assimilation research, and coastal ocean process studies (2042297)
Alexander L Kurapov1, Parisa Heidary2 and Bahram Khazaei2, (1)NOAA National Ocean Service, Office of Coast Survey, Coastal Survey Development Laboratory, Silver Spring, United States, (2)NOAA National Ocean Service and Ocean Associates Inc., Silver Spring, United States
Leveraging the memory in an identity retaining ocean ensemble (2042687)
Edel S U Rikardsen1,2, Victor de Aguiar2, Knut-Frode Dagestad3, Kai Christensen4 and Johannes Rohrs2, (1)University of Oslo, Meteorology and Oceanography, Oslo, Norway, (2)Norwegian Meteorological Institute, Oslo, Norway, (3)Norwegian Meteorological Institute, Oceanography and Marine Meteorology, Bergen, Norway, (4)Norwegian Meteorological Institute, Ocean and Ice, Oslo, Norway
Reconstructing Sea Surface Height from Sparse Satellite Tracks with Flow-Matching Generative Model (2044505)
Dmitrii Drozdov1, Dominique Béréziat1, Anastase Charantonis2 and Pierre Garcia3, (1)Sorbonne Université, LIP6, Paris, France, (2)INRIA, Paris, France, (3)CNRS, LIP6, Paris Cedex 16, France
