Quality control on Argo data: from the automatic tests to the MinMax method

Enhancing Argo Data Quality: From Automated Tests to the MinMax Method

In response to the need for rapid data delivery within 12 to 24 hours of a float reaching the sea surface, Argo data undergo automatic real-time quality control tests, albeit with limitations. To enhance data quality, the Coriolis Data Center employs additional methods to detect anomalies missed by these automatic tests. Upon uploading/updating files to the GDAC, they are also added to the Coriolis Oracle database. Subsequently, these files undergo analysis using the MinMax test (Gourrion et al., 2020). This method identifies contaminated profile sections and anomalies caused by sensor drift. Visual verification of resulting alerts is performed using Scoop software, and necessary adjustments are made to the quality control indicators in the Coriolis database. Proposed corrections to the quality flags are then relayed to relevant DACs via automated messages, also accessible on the Ifremer ftp site. The objective is swift removal of erroneous measurements from the data flow. These processes were extensively discussed by the Blue-Cloud team during a dedicated webinar with Dr. Christine Coatanoan on 7 June 2023.

Blue-Cloud EOV Workbenches

In Blue-Cloud 2026, advanced Workbenches (WBs) are being developed to streamline data handling for Essential Ocean Variables (EOV). These tools enhance data harmonisation, validation, and qualification from various sources. These novel Workbenches leverage cloud tech, AI, and advanced analytics for improved data handling. They are set to be adopted by key initiatives, consistently producing validated data collections, enhancing oceanic simulations. The EOV Workbenches cover Physics, Eutrophication, and Ecosystem-level Variables.

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