Argo is one of the Global Ocean Observing System components. Initiated in the late 90s in the context of GODAE (the Global Ocean Data Assimilation Experiment) and CLIVAR (Climate and Ocean: Variability, Predictability and Change) to provide in situ measurements of temperature and salinity in the upper 2000m of the global ice-free ocean, Argo has always had a strong connection with ocean predictions.
OneArgo is the ongoing extension of the Argo array into seasonal ice zones, marginal seas, deeper waters (Deep-Argo) and biogeochemical parameters (BGC-Argo). The aim of the Argo programme is to achieve the full implementation of this new ambitious global, full-depth and multidisciplinary OneArgo array by the end of the UN Ocean Decade (2030).
The session focuses on the use of Argo data in physical and biogeochemical ocean monitoring, forecasting and reanalysis systems. It covers the use of Argo data for model parameter optimization, model trajectory correction through data assimilation, verification/validation activities, field reconstruction through AI methods, and model/data fusion (e.g., bias correction, AI tools). The session also covers design studies such as results from Observing System Experiments and Observing System Simulation Experiments. Specific focus will be put on highlighting the role of Deep-Argo and BGC-Argo data, and synergies between OneArgo and other observing systems. Contributions are also expected from research teams involved in the development and implementation of the OneArgo array in terms of design, data processing, and novel functionalities.
OneArgo is the ongoing extension of the Argo array into seasonal ice zones, marginal seas, deeper waters (Deep-Argo) and biogeochemical parameters (BGC-Argo). The aim of the Argo programme is to achieve the full implementation of this new ambitious global, full-depth and multidisciplinary OneArgo array by the end of the UN Ocean Decade (2030).
The session focuses on the use of Argo data in physical and biogeochemical ocean monitoring, forecasting and reanalysis systems. It covers the use of Argo data for model parameter optimization, model trajectory correction through data assimilation, verification/validation activities, field reconstruction through AI methods, and model/data fusion (e.g., bias correction, AI tools). The session also covers design studies such as results from Observing System Experiments and Observing System Simulation Experiments. Specific focus will be put on highlighting the role of Deep-Argo and BGC-Argo data, and synergies between OneArgo and other observing systems. Contributions are also expected from research teams involved in the development and implementation of the OneArgo array in terms of design, data processing, and novel functionalities.