Theme 5 - Session Recordings

Impact of observations on forecasting systems
Session 5.4

Session 5.1 Machine learning

Optimizing Global-Scale Seasonal Marine Biogeochemical Forecasting with Compact Neural Networks

G. Martinez Balbontin - Mercator Ocean International Optimizing Global-Scale Seasonal Marine Biogeochemical Forecasting with Compact Neural Networks

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Differentiable Programming for hybrid ocean data assimilation and machine learning

P. Heimbach - UT Austin Differentiable Programming for hybrid ocean data assimilation and machine learning

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Integrating SWOT data into a deep learning model for real-time high-resolution prediction of ocean surface currents

A. Pesnec & H. Bull - Amphitrite Integrating SWOT data into a deep learning model for real-time high-resolution prediction of ocean surface currents

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Integrating BGC-Argo predicted profiles via Convolutional Neural Networks into the Data Assimilation of the Copernicus Mediterranean biogeochemical model

C. Amadio - OGSIntegrating BGC-Argo predicted profiles via Convolutional Neural Networks into the Data Assimilation of the Copernicus Mediterranean biogeochemical model

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Model-Based Feasibility of Using Data-Driven Techniques to Reconstruct Ocean Interiors from Surface and In-Situ Data

A. Garcia - ICM-CSICModel-Based Feasibility of Using Data-Driven Techniques to Reconstruct Ocean Interiors from Surface and In-Situ Data

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Evaluating the prediction skill of correlative estuarine species distribution models trained with mechanistic model output

D. Horemans - Virginia Institute of Marine Science Evaluating the prediction skill of correlative estuarine species distribution models trained with mechanistic model output

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Session 5.2 Data assimilation

Validation and assimilation of satellite sea surface temperature to characterize sub-mesoscale features in assimilative ocean and coupled earth system prediction models

C. Barron - U.S. Naval Research Laboratory Validation and assimilation of satellite sea surface temperature to characterize sub-mesoscale features in assimilative ocean and coupled earth system prediction models

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Hybrid covariance super-resolution data assimilation

F. Counillon - NERSCHybrid covariance super-resolution data assimilation

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Supermodelling towards improved climate prediction

T. Singh - NERSCSupermodelling towards improved climate prediction

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Ocean Data Assimilation Towards Submesoscales

J. D'Addezio - U.S. Naval Research LaboratoryOcean Data Assimilation Towards Submesoscales

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Deterministic and Ensemble forecasts of Kuroshio south of Japan

S. Ohishi - RIKENDeterministic and Ensemble forecasts of Kuroshio south of Japan

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Weak Constraint 4D-Var Data Assimilation in the Regional Ocean Modeling System (ROMS) using a Saddle-Point Algorithm

A. Moore - University of California Santa CruzWeak Constraint 4D-Var Data Assimilation in the Regional Ocean Modeling System (ROMS) using a Saddle-Point Algorithm

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Session 5.3 Observational systems

Preliminary results of SynObs Flagship OSEs–Assessments on impact of satellite altimetry versus Argo profiles–

S. Kido - JAMSTECPreliminary results of SynObs Flagship OSEs–Assessments on impact of satellite altimetry versus Argo profiles– 

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Impact of Observations on ECCC's Global Ocean Analysis, GIOPS

G. Smith - Environment and Climate Change CanadaImpact of Observations on ECCC's Global Ocean Analysis, GIOPS

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Retrieval of Biogeochemical Properties in Marine Waters Using a Newly Introduced Inversion of the Three-stream Irradiance Model

M. Gharbi Dit Kacem - OGSRetrieval of Biogeochemical Properties in Marine Waters Using a Newly Introduced Inversion of the Three-stream Irradiance Model 

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Observing and assimilating total surface velocities: Challenges and perspectives with the ODYSEA mission

E. Remy - Mercator Ocean InternationalObserving and assimilating total surface velocities: Challenges and perspectives with the ODYSEA mission 

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Identifying spatial and temporal oceanic scales constrained by existing and future observations

F. Gasparin - IRD-LEGOSIdentifying spatial and temporal oceanic scales constrained by existing and future observations 

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European contribution to the OneArgo array

C. Gourcuff - Euro-Argo ERICEuropean contribution to the OneArgo array 

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Session 5.4 Impact of observations on forecasting systems

OneArgo – Evolving and extending Argo’s missions and data delivery. Achievements, status and outlook

B. King - National Oceanography CentreOneArgo – Evolving and extending Argo’s missions and data delivery. Achievements, status and outlook 

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Impact of SWOT Data in a global high-resolution analysis and forecasting system

M. Benkiran - Mercator Ocean InternationalImpact of SWOT Data in a global high-resolution analysis and forecasting system

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Investigating the potential impact of assimilating total surface current velocity data in the Met Office’s global ocean forecasting system

J. Waters - Met OfficeInvestigating the potential impact of assimilating total surface current velocity data in the Met Office’s global ocean forecasting system 

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Comparison of two ways of assimilating SWOT observations using NCODA-4DVAR

H. Ngodock - U.S. Naval Research LabComparison of two ways of assimilating SWOT observations using NCODA-4DVAR 

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OSSEs with SWOT and Gliders in the Southwest South Atlantic with HYCOM+RODAS

C. Tanajura - UFBA and REMOOSSEs with SWOT and Gliders in the Southwest South Atlantic with HYCOM+RODAS 

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Development of Observing Quantitative Assessment Capabilities for Ocean Applications at NOAA

L. Cucurull - NOAADevelopment of Observing Quantitative Assessment Capabilities for Ocean Applications at NOAA 

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Session 5.5 Biogeochemistry

Mitigating Phytoplankton Phenology Mismatches in the Arctic Ocean Biogeochemical Reanalysis

T. Wakamatsu - The Nansen CenterMitigating Phytoplankton Phenology Mismatches in the Arctic Ocean Biogeochemical Reanalysis 

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Incorporating the Framework for Aquatic Biogeochemical Models (FABM) into the ocean modelling framework NEMO v4.2.1

H. Morrison - BSHIncorporating the Framework for Aquatic Biogeochemical Models (FABM) into the ocean modelling framework NEMO v4.2.1 

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Enhancing BGC-Argo Chlorophyll-a Data Quality and Uniformity Using Machine Learning

R. Sauzede - CNRSEnhancing BGC-Argo Chlorophyll-a Data Quality and Uniformity Using Machine Learning 

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Contribution of radiative transfer modelling to a stochastic biogeochemical forecasting system in the Black Sea L. Macé - University of Liège

L. Macé - University of LiègeContribution of radiative transfer modelling to a stochastic biogeochemical forecasting system in the Black Sea L. Macé - University of Liège

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Improving Forecasts and Nowcasts at High Latitudes

E. Douglass - U.S. Naval Research LabImproving Forecasts and Nowcasts at High Latitudes 

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Optimisation of biogeochemical model parameters using BGC-ARGO profiling floats

Q. Hyvernat - CNRS/Mercator Ocean InternationalOptimisation of biogeochemical model parameters using BGC-ARGO profiling floats 

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Session 5.6 Digital twins

Data-driven sea-ice modelling with generative deep learning

T. Finn - CEREA, École des Ponts ParisTechData-driven sea-ice modelling with generative deep learning 

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High-resolution operational forecasts of ocean surface currents for optimal ship routing

I. Larroche - AmphitriteHigh-resolution operational forecasts of ocean surface currents for optimal ship routing 

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Tracking harmful algae blooms in the western English Channel using digital twins

J. Skakala - PMLTracking harmful algae blooms in the western English Channel using digital twins

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Four-dimensional variational data assimilation with a sea-ice thickness emulator

C. Durand - ENPCFour-dimensional variational data assimilation with a sea-ice thickness emulator

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EDITO-Model Lab: towards the next generation of ocean numerical models

Y. Drillet - Mercator Ocean InternationalEDITO-Model Lab: towards the next generation of ocean numerical models

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Digital Twins for Ocean Robots

G. Forget - MITDigital Twins for Ocean Robots

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Session 5.7 Improvements of operational systems

Effects of atmosphere and ocean horizontal model resolution on upper ocean response forecasts in four major hurricanesEffects of atmosphere and ocean horizontal model resolution on upper ocean response forecasts in four major hurricanes

K. Mogensen - ECMWF Effects of atmosphere and ocean horizontal model resolution on upper ocean response forecasts in four major hurricanesEffects of atmosphere and ocean horizontal model resolution on upper ocean response forecasts in four major hurricanes

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Towards a lightweight global ocean forecasting system: Development of “Mazu” Ocean Models in China

F. YU - NMEFC Towards a lightweight global ocean forecasting system: Development of “Mazu” Ocean Models in China

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Ocean Data Assimilation in the Earth System Model of the DWD

M. Sprengel - Deutscher Wetterdienst Ocean Data Assimilation in the Earth System Model of the DWD

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Development and initial performance evaluation of the KIAPS weakly-coupled atmosphere-ocean-sea ice data assimilation system

J. Kim - KIASPDevelopment and initial performance evaluation of the KIAPS weakly-coupled atmosphere-ocean-sea ice data assimilation system

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