Ocean Science (Feb 2023)

A turbulence data reduction scheme for autonomous and expendable profiling floats

  • K. G. Hughes,
  • J. N. Moum,
  • D. L. Rudnick

DOI
https://doi.org/10.5194/os-19-193-2023
Journal volume & issue
Vol. 19
pp. 193 – 207

Abstract

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Autonomous and expendable profiling-float arrays such as those deployed in the Argo Program require the transmission of reliable data from remote sites. However, existing satellite data transfer rates preclude complete transmission of rapidly sampled turbulence measurements. It is therefore necessary to reduce turbulence data on board. Here we propose a scheme for onboard data reduction and test it with existing turbulence data obtained with a modified SOLO-II profiling float. First, voltage spectra are derived from shear probe and fast-thermistor signals. Then, we focus on a fixed-frequency band that we know to be unaffected by vibrations and that approximately corresponds to a wavenumber band of 5–25 cpm. Over the fixed-frequency band, we make simple power law fits that – after calibration and correction in post-processing – yield values for the turbulent kinetic energy dissipation rate ϵ and thermal-variance dissipation rate χ. With roughly 1 m vertical segments, this scheme reduces the necessary data transfer volume 300-fold to approximately 2.5 kB for every 100 m of a profile (when profiling at 0.2 m s−1). As a test, we apply our scheme to a dataset comprising 650 profiles and compare its output to that from our standard turbulence-processing algorithm. For ϵ, values from the two approaches agree within a factor of 2 87 % of the time; for χ, they agree 78 % of the time. These levels of agreement are greater than or comparable to that between the ϵ and χ values derived from two shear probes and two fast thermistors, respectively, on the same profiler.