Spectral computations: Difference between revisions
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After the initial round of data QA/QC, there are three stages to estimating the turbulent dissipation rate: | After the initial round of data QA/QC, there are three stages to estimating the turbulent dissipation rate: | ||
* [[Compute the spectra]] with sufficient degrees of freedom to get a statistically robust <math>\varepsilon</math> {{FontColor|fg=white|bg=red|text= The dof is only a requirement when cleaning with cospectral techniques given the MLE fitting algorithm will take into account the dof when yielding epsilon. If we were integrating the spectra like the shear probe, then sure the dof is very important. As for surface waves? Someone else needs to chime in}} | |||
* Conduct further [[QA/QC specific to spectral analysis]] | * Conduct further [[QA/QC specific to spectral analysis]] | ||
* [[ | * Estimate the [[Velocity past the sensor| mean flow past the sensor]] and if applicable the [[Surface wave statistics|surface wave statistics]] to choose the appropriate [[Velocity inertial subrange model| inertial subrange model]] for [[Spectral fitting|spectral fitting]]. | ||
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Return to [[Spectral estimates and identifying the inertial subrange]] | |||
[[Category:Velocity point-measurements]] |
Latest revision as of 15:47, 11 July 2022
This page could be removed and included with the one that links here.
After the initial round of data QA/QC, there are three stages to estimating the turbulent dissipation rate:
- Compute the spectra with sufficient degrees of freedom to get a statistically robust [math]\displaystyle{ \varepsilon }[/math] The dof is only a requirement when cleaning with cospectral techniques given the MLE fitting algorithm will take into account the dof when yielding epsilon. If we were integrating the spectra like the shear probe, then sure the dof is very important. As for surface waves? Someone else needs to chime in
- Conduct further QA/QC specific to spectral analysis
- Estimate the mean flow past the sensor and if applicable the surface wave statistics to choose the appropriate inertial subrange model for spectral fitting.
Return to Spectral estimates and identifying the inertial subrange