Velocity point-measurements: Difference between revisions

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The subgroup will provide recommendations on:
The subgroup will provide recommendations on:
# [[data processing of raw measurements]]
# [[data processing of raw measurements]]
# [[segmenting datasets]] and separating the turbulence signal from the total signals
# [[segmenting datasets]]
# [[spectral computations]]  and identifying the appropriate  [[Velocity inertial subrange model|inertial subrange model]]  
# [[spectral computations]]  and identifying the appropriate  [[Velocity inertial subrange model|inertial subrange model]] (e.g., surface wave considerations)
# [[Estimate epsilon|estimating <math>\varepsilon</math>]] from the spectral observations and associated [[quality control measures]]  
# [[Estimate epsilon|estimating <math>\varepsilon</math>]] from the spectral observations and associated [[quality control measures]]  


These four processing levels coincide with the [[benchmark datasets for velocity measurements]] hierarchal format. The benchmark datasets will follow the ATOMIX [[NetCDF velocimeters format]]. The [[benchmark datasets for velocity measurements|benchmarks]] are intended to be a resource that can be used by the community to evaluate routines in any programming language. Our recommendations are designed for measurements irrespective of the manufacturer, provided the data quality is sufficient for resolving the turbulence subrange of the velocity spectra.


We will also provide [[benchmark datasets for velocity measurements]] impacted and unaffected by surface waves. Although some work has been done in obtaining turbulence estimates from moored platforms, we will not be providing benchmark datasets at this time. However, appropriate references to existing literature will be included.
We will be providing [[benchmark datasets for velocity measurements|benchmarks]] for measurements both impacted and unaffected by surface waves. We will not be giving benchmark datasets for moored platforms at this time. However, we will include appropriate references to existing literature.


Our recommendations are intended to be applicable to measurements irrespective of the manufacturer provided the data is of sufficient quality for resolving the turbulence subrange of the velocity spectra.


The benchmark datasets will follow the ATOMIX [[NetCDF velocimeters format]]. The [[benchmark datasets for velocity measurements]] are intended to be a resource that can be used by the community to evaluate routines in any programming language.


[[Category:Velocity point-measurements]]
[[Category:Velocity point-measurements]]

Revision as of 20:56, 29 October 2021

Welcome to the velocity point-measurements subgroup!

This subgroup addresses best practices in obtaining turbulent kinetic energy dissipation rate estimates from time series of velocities measured at a point in space. These temporal measurements are converted into spectral observations in the wavenumber (space) domain before being fitted with a model spectrum to obtain turbulent kinetic energy dissipation.

Scope

The subgroup will provide recommendations on:

  1. data processing of raw measurements
  2. segmenting datasets
  3. spectral computations and identifying the appropriate inertial subrange model (e.g., surface wave considerations)
  4. estimating [math]\displaystyle{ \varepsilon }[/math] from the spectral observations and associated quality control measures

These four processing levels coincide with the benchmark datasets for velocity measurements hierarchal format. The benchmark datasets will follow the ATOMIX NetCDF velocimeters format. The benchmarks are intended to be a resource that can be used by the community to evaluate routines in any programming language. Our recommendations are designed for measurements irrespective of the manufacturer, provided the data quality is sufficient for resolving the turbulence subrange of the velocity spectra.

We will be providing benchmarks for measurements both impacted and unaffected by surface waves. We will not be giving benchmark datasets for moored platforms at this time. However, we will include appropriate references to existing literature.