Global Ocean Data Providers for Forecasting Systems
The first lecture showed what upstream data is. This one, with Nathanaël Dossa, answers the natural next question: where do all these observations come from, and how do they become the reliable datasets forecasting centres use every day?
Every day, millions of observations are collected by satellites, Argo floats, buoys, ships, gliders, and tide gauges – in different formats, from different programmes. Before a forecasting centre can use them, they must be collected, quality-controlled, standardised, archived, and distributed. That essential work is done by global ocean data providers, which turn raw observations into reliable, interoperable datasets shared worldwide.
The lecture covers:
- Why data providers are essential – they are the bridge between raw observations and operational forecasting. Rather than every centre processing everything itself, providers aggregate, quality-control, and standardise data into products used for model initialisation, data assimilation, and validation
- Global coordination through GOOS – the Global Ocean Observing System, co-sponsored by IOC-UNESCO and the WMO, coordinates the worldwide network of platforms and monitors the Essential Ocean Variables (physical, biogeochemical, and biology/ecosystem)
- The FAIR principles – the foundation of modern data management: data should be Findable, Accessible, Interoperable, and Reusable
- The major providers, by category:
- In-situ: NOAA’s World Ocean Database, the Argo network, Copernicus Marine (INS TAC), SeaDataNet, and EMODnet
- Satellite: Copernicus Marine, GHRSST (sea surface temperature), AVISO++ (altimetry), EUMETSAT, and NSIDC (sea ice)
- Bathymetry: ETOPO, GEBCO, SRTM+, and EMODnet Bathymetry
- The challenges that remain – uneven coverage (the Southern Ocean, parts of the tropics), limited deep-ocean monitoring, coastal complexity, and integrating many observing systems into consistent datasets
The takeaway: global ocean data providers transform millions of scattered observations into the standardised, accessible, high-quality datasets that operational forecasting depends on. They are a critical, often invisible, part of the infrastructure. The next lecture zooms in on one of the largest of them – the Copernicus Marine Service.
