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ATOMIX benchmark datasets for dissipation rate measurements using shear probes.
Fer, Ilker; Dengler, Marcus; Holtermann, Peter; Le Boyer, Arnaud; Lueck, Rolf.
Affiliation
  • Fer I; Geophysical Institute, University of Bergen, Bergen, Norway. ilker.fer@uib.no.
  • Dengler M; GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany.
  • Holtermann P; Leibniz Institute for Baltic Sea Research, Warnemünde, Rostock, Germany.
  • Le Boyer A; Scripps Institution of Oceanography, University of California San Diego, San Diego, CA, USA.
  • Lueck R; Rockland Scientific, Inc., Victoria, British Columbia, Canada.
Sci Data ; 11(1): 518, 2024 May 21.
Article in En | MEDLINE | ID: mdl-38773110
ABSTRACT
Turbulent mixing in the ocean, lakes and reservoirs facilitates the transport of momentum, heat, nutrients, and other passive tracers. Turbulent fluxes are proportional to the rate of turbulent kinetic energy dissipation per unit mass, ε. A common method for ε measurements is using microstructure profilers with shear probes. Such measurements are now widespread, and a non-expert practitioner will benefit from best practice guidelines and benchmark datasets. As a part of the Scientific Committee on Oceanographic Research (SCOR) working group on "Analysing ocean turbulence observations to quantify mixing" (ATOMIX), we compiled a collection of five benchmark data of ε from measurements of turbulence shear using shear probes. The datasets are processed using the ATOMIX recommendations for best practices documented separately. Here, we describe and validate the datasets. The benchmark collection is from different types of instruments and covers a wide range of environmental conditions. These datasets serve to guide the users to test their ε estimation methods and quality-assurance metrics, and to standardize their data for archiving.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Data Year: 2024 Document type: Article Affiliation country: Noruega Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Data Year: 2024 Document type: Article Affiliation country: Noruega Country of publication: Reino Unido