Puneet Varma (Editor)

CORA dataset

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CORA dataset

CORA (standing for Coriolis Ocean database ReAnalysis) is a global oceanographic temperature and salinity dataset produced and maintained by the French institute IFREMER. Most of those data are real-time data coming from different types of platforms (research vessels, profilers, underwater gliders, drifting buoys, moored buoys, sea mammals, opportunity ships, ...).

Contents

Description

This in-situ dataset produced by the French institute Ifremer in the framework of the European project MyOcean and French project CORIOLIS is a picture of the content of the operational oceanographic database CORIOLIS. This database is the main tool of Coriolis project which is a global data assembly center of in situ data: such as US-GODAE centre of Monterey in California. The latest version of CORA product is v3.3, it covers the years 1990 up to 2011 and has been released in July 2012. Observations are profiles distributed on measured levels (pressure or depth) and organized by dates of measurement and type of platform. Main users of CORA dataset are ocean modelers who needs to constraint and initialize their model. Mercator Océan is a privileged partner of CORA dataset since feedbacks from models assimilation (meteorology) are used to check suspicious profiles found thanks to innovation computing. CORA is free of access and can be download via CORIOLIS website in netCDF file format. The main different of CORA dataset with other available datasets is that CORA gives the data on the levels where measurements have been done rather than standard levels such in World Ocean Atlas or ENACT3. In addition data in CORA are retrieved from Coriolis database where each profile is visually checked by specialist operators if suspicious.

Validation in database

  • duplicate observation check
  • automatic checks (spikes, climatology, monotonic depth, valid date/position,...)
  • objective analysis (ISAS software with 21 days, 300 km covariance ray): suspicious observations are visualized by an operator
  • Validation post extraction

  • second duplicate observation check (detection and choice parameters tuned)
  • raffined climatological test
  • XBT depth correction
  • second objective analysis with tuned parameters: anomalies are visualized
  • ARGO special diagnostics
  • References

    CORA dataset Wikipedia