What Is Deep Argo?

The scientific community agrees that a systematic sampling of the full ocean depth is needed to close the planetary budgets of heat and freshwater, and the global sea level budget. The strength and variability of the large-scale ocean circulations that extend from the sea surface to the ocean bottom play significant roles in the uptakes and transports of heat and freshwater, and melting of sea ice. Since the implementation of the Argo program, profiling floats were limited to the top half of the sea (0-2000 m) and the accuracy of sensors was similarly limited to upper ocean levels of temperature and salinity variability. A new generation of autonomous floats called Deep Argo will sample the full ocean volume. Deep Argo float models include the Deep SOLO and Deep APEX capable of reaching 6000 m, and the Deep ARVOR, the Deep NINJA and the HM4000 are designed to sample to 4000 m. Regional Deep Argo arrays in the Southwest Pacific Basin, South Australian Basin, Australian Antarctic Basin, and North Atlantic Ocean are leading the way forward to implement a standing Deep Argo array of 1228 floats. An exciting transition to systematic full-depth global ocean observations is happening.

Technology challenges

One of the challenges facing Deep Argo is that the CTD sensor used on standard Argo floats was not designed to go below 2000 m depth. Therefore, SeaBird has been working to develop a new CTD sensor that will be accurate down to 6000 m. This new CTD, named the SBE-61, has not yet achieved its aspirational goals of (± .001C, ±.002 psu, and ± 3 dbar) but is progressing relative to those goals.  To see the Deep Argo float models, click here.

Pilot arrays


Terms of Reference

Within the Argo program, the Deep Argo Mission Team acts as a scientific committee to provide recommendations and guidance for the progressive development and implementation of a Deep Argo program in the context of the larger global Argo array. The Deep Argo Mission Team will closely liaise with and report to the international Argo Steering Team. The co-chairs of the Deep Argo Mission Team will be members of the International Argo Steering Team.

More specifically, the Deep Argo Mission Team’s terms of reference are to:

  • Develop and update the Deep Argo science plan with respect to regional pilot projects and the implementation and evolution of the global design.
  • Coordinate implementation, in particular to optimize the various national efforts.
  • Interact with other Mission Teams (e.g. “BGC”) to prepare and coordinate the possible implementation of enhancements to Deep Argo observations.
  • Elaborate “good practices” with respect to float and sensor preparation, calibration, deployments and associated in situ simultaneous measurements.
  • Provide advice regarding new variables in the Deep Argo data stream, in particular based on an evaluation of the degree of readiness of their sensors.
  • In close interaction with Argo Data Management Team coordinate and organize the Deep data management.
  • Establish and /or strengthen interactions and exchanges with other related observing programs (GO-SHIP, OceanSITES) or groups of experts (DOOS).
  • Establish and develop interactions with the operational oceanography community (e.g. GODAE OceanView) and relevant satellite science teams.

Deep Argo Mission Team

Name Country Institution
Annie Foppert Australia CSIRO
Tetjana Ross Canada DFO
Zhaohui Chen China OUC
Zenghong Lui China SIO
Cecile Cabanes France IFREMER
Damien Desbruyeres France IFREMER
Virginie Thierry
Deep Argo Mission Team co-chair
France IFREMER
Shigeki Hosoda Japan JAMSTEC
Taiyo Kobayashi Japan JAMSTEC
Phil Sutton New Zealand NIWA
Henrik Søilad Norway Institute of Marine Research
Alberto Gonzalez Santana Spain IEO
Brian King UK NOC
John Gilson USA Scripps
Pelle Robbins USA WHOI
Greg Johnson USA PMEL
Sarah Purkey USA Scripps
Dean Roemmich USA Scripps
Nathalie Zilberman
Deep Argo Mission Team co-chair
USA Scripps

 

Links to related papers

Please visit the Deep Argo Mission bibliography page for a list of all papers published using Deep Argo data.