3D-calibration of three- and four-sensor hot-film probes based on collocated sonic using neural networks

Eliezer Kit, Dan Liberzon

Research output: Contribution to journalArticlepeer-review


High resolution measurements of turbulence in the atmospheric boundary layer (ABL) are critical to the understanding of physical processes and parameterization of important quantities, such as the turbulent kinetic energy dissipation. Low spatio-temporal resolution of standard atmospheric instruments, sonic anemometers and LIDARs, limits their suitability for fine-scale measurements of ABL. The use of miniature hot-films is an alternative technique, although such probes require frequent calibration, which is logistically untenable in field setups. Accurate and truthful calibration is crucial for the multi-hot-films applications in atmospheric studies, because the ability to conduct calibration in situ ultimately determines the turbulence measurements quality. Kit et al (2010 J. Atmos. Ocean. Technol. 27 23-41) described a novel methodology for calibration of hot-film probes using a collocated sonic anemometer combined with a neural network (NN) approach. An important step in the algorithm is the generation of a calibration set for NN training by an appropriate low-pass filtering of the high resolution voltages, measured by the hot-film-sensors and low resolution velocities acquired by the sonic. In Kit et al (2010 J. Atmos. Ocean. Technol. 27 23-41), Kit and Grits (2011 J. Atmos. Ocean. Technol. 28 104-10) and Vitkin et al (2014 Meas. Sci. Technol. 25 75801), the authors reported on successful use of this approach for in situ calibration, but also on the method's limitations and restricted range of applicability. In their earlier work, a jet facility and a probe, comprised of two orthogonal x-hot-films, were used for calibration and for full dataset generation. In the current work, a comprehensive laboratory study of 3D-calibration of two multi-hot-film probes (triple- and four-sensor) using a grid flow was conducted. The probes were embedded in a collocated sonic, and their relative pitch and yaw orientation to the mean flow was changed by means of motorized traverses. The study demonstrated that NN-calibration is a powerful tool for calibration of multi-sensor 3D-hot film probes embedded in a collocated sonic, and can be employed in long-lasting field campaigns.

Original languageEnglish
Article number095901
JournalMeasurement Science and Technology
Issue number9
StatePublished - 25 Jul 2016


  • atmospheric flows
  • hot wire anemometer
  • in situ calibration
  • multi-sensor hot-film probes
  • neural networks
  • sonic anemometer
  • turbulence in grid flow


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