A Biodegradable Surface Drifter for Ocean Sampling on a Massive Scale

Academic Article

Abstract

  • AbstractTargeted observations of submesoscale currents are necessary to improve science’s understanding of oceanic mixing, but these dynamics occur at spatiotemporal scales that are currently challenging to detect. Prior studies have recently shown that the submesoscale surface velocity field can be measured by tracking hundreds of surface drifters released in tight arrays. This strategy requires drifter positioning to be accurate, frequent, and to last for several weeks. However, because of the large numbers involved, drifters must be low-cost, compact, easy to handle, and also made of materials harmless to the environment. Therefore, the novel Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) drifter was designed following these criteria to facilitate massive sampling of near-surface currents during the Lagrangian Submesoscale Experiment (LASER). The drifting characteristics were determined under a wide range of currents, waves, and wind conditions in laboratory settings. Results showed that the drifter accurately follows the currents in the upper 0.60 m, that it presents minimal wave rectification issues, and that its wind-induced slip velocity is less than 0.5% of the neutral wind speed at 10 m. In experiments conducted in both coastal and deep ocean conditions under wind speeds up to 10 m s−1, the trajectories of the traditional Coastal Ocean Dynamics Experiment (CODE) and the CARTHE drifters were nearly identical. Following these tests, 1100 units were produced and deployed during the LASER campaign, successfully tracking submesoscale and mesoscale features in the Gulf of Mexico. It is hoped that this drifter will enable high-density sampling near metropolitan areas subject to stress by the overpopulation, such as lakes, rivers, estuaries, and environmentally sensitive areas, such as the Arctic.
  • Authors

  • Novelli, Guillaume
  • Guigand, Cedric M
  • Cousin, Charles
  • Ryan, Edward H
  • Laxague, Nathan
  • Dai, Hanjing
  • Haus, Brian K
  • Ozgokmen, Tamay M
  • Status

    Publication Date

  • November 2017
  • Digital Object Identifier (doi)

    Start Page

  • 2509
  • End Page

  • 2532
  • Volume

  • 34
  • Issue

  • 11