ADCP Environment - Revision history

CynthiaBluteau: Links burst sampling

2022-03-08T19:14:49Z

Links burst sampling

← Older revision		Revision as of 19:14, 8 March 2022
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	# Stratification for stratified environments		# Stratification for stratified environments
	## Stratified flows can have significant background shear (boundary layer or otherwise)		## Stratified flows can have significant background shear (boundary layer or otherwise)
	##. Estimate expected shear if possible: in the presence of shear, any variation in instrument orientation (pitch, roll or heading) will result in velocity differences due to background shear not being correctly removed, leading to bias in epsilon estimates.		## Estimate expected shear if possible: in the presence of shear, any variation in instrument orientation (pitch, roll or heading) will result in velocity differences due to background shear not being correctly removed, leading to bias in epsilon estimates.
	# Waves		# Waves
	## Expected influence of wave field Stokes drift on surface measurements		## Expected influence of wave field Stokes drift on surface measurements

CynthiaBluteau at 19:14, 8 March 2022

2022-03-08T19:14:22Z

← Older revision		Revision as of 19:14, 8 March 2022
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	### No smaller than advective lengthscale if using across beam methods		### No smaller than advective lengthscale if using across beam methods
	### Factor this into ambiguity velocity		### Factor this into ambiguity velocity
	### Links between bin size/nominal velocity accuracy, sub-pings (averaging across pings) duration of data aggregation (burst)		### Links between bin size/nominal velocity accuracy, sub-pings (averaging across pings) duration of data aggregation ([[burst sampling]])
	## No of samples		## No of samples
	### will be determined by whether sampling is burst vs continuous		### will be determined by whether sampling is [[Burst sampling\|burst]] vs continuous
	### Note burst periods can save power and reduce required storage capacity, but must be carefully chosen to capture the required dynamics		### Note burst periods can save power and reduce required storage capacity, but must be carefully chosen to capture the required dynamics
	# Time averaging (important to specify whether the averaging is over the ensemble period for the full deployment period.)		# Time averaging (important to specify whether the averaging is over the ensemble period for the full deployment period.)

CynthiaBluteau: Categorization

2021-11-23T15:47:57Z

Categorization

← Older revision		Revision as of 15:47, 23 November 2021
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			----
			Return to [[Deployment]]

	~~Return to~~ [[~~Deployment~~]]		[[Category:Velocity profilers]]

Djwain at 20:14, 22 October 2021

2021-10-22T20:14:33Z

← Older revision		Revision as of 20:14, 22 October 2021
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	# Time and length-scales		# Time and length-scales
	#: ~~Commute~~ these to horizontal and vertical in order to make the best choices for:		#: Compute these to horizontal and vertical in order to make the best choices for:
	## Sampling time		## Sampling time
	### Repetition rate		### Repetition rate

Yuengdjern at 18:29, 22 September 2021

2021-09-22T18:29:09Z

← Older revision		Revision as of 18:29, 22 September 2021
Line 1:		Line 1:
	~~Sampling~~ strategy		The best sampling strategy will depend on the environmental flow regimes, specifically the following parameters:

	~~Time and length-scales~~

	~~Commute these to horizontal and vertical~~



	~~Sampling time~~

	~~Repetition rate~~

	~~Sample as fast as possible (spread out~~ the ~~spectral density of noise)~~

	~~Trade off against power/storage~~

	~~Bin size~~

	~~No smaller than advective lengthscale if using across beam methods~~

	~~Factor this into ambiguity velocity~~

	~~Links between bin size/nominal velocity accuracy~~, ~~sub-pings (averaging across pings) duration of data aggregation (burst)~~


			# Time and length-scales
			#: Commute these to horizontal and vertical in order to make the best choices for:
			## Sampling time
			### Repetition rate
			### Sample as fast as possible (spread out the spectral density of noise)
			### Optimize trade off against power/storage
			## Bin size
			### No smaller than advective lengthscale if using across beam methods
			### Factor this into ambiguity velocity
			### Links between bin size/nominal velocity accuracy, sub-pings (averaging across pings) duration of data aggregation (burst)
			## No of samples
			### will be determined by whether sampling is burst vs continuous
			### Note burst periods can save power and reduce required storage capacity, but must be carefully chosen to capture the required dynamics
			# Time averaging (important to specify whether the averaging is over the ensemble period for the full deployment period.)
			# Max expected flow velocities used to set the ADCP ambiguity velocity
			# Account for likely SNR
			## scatterers if known.
			## Water velocities; energy.
			## Likely turbulence ROT 10%
			# Stratification for stratified environments
			## Stratified flows can have significant background shear (boundary layer or otherwise)
			##. Estimate expected shear if possible: in the presence of shear, any variation in instrument orientation (pitch, roll or heading) will result in velocity differences due to background shear not being correctly removed, leading to bias in epsilon estimates.
			# Waves
			## Expected influence of wave field Stokes drift on surface measurements
			## Consider becoming familiar with wave removal algorithms.

	~~No of samples~~

	~~Burst vs continuous~~

	~~Consider Burst periods~~

	~~Power/Storage saving ~~

	~~Ensure capture required dynamics ~~

	~~Time averaging (important to specify whether the averaging is over the ensemble period for the full deployment period. )~~



	~~what your max velocities will be ~~

	~~ambiguity velocity - set it accordingly for your flows ~~

	~~Likely SNR~~

	~~scatterers if known. ~~

	~~Water velocities; energy.~~

	~~Likely turbulence ROT 10%~~



	~~Stratification for stratified environments~~



	~~Shear (boundary layer or otherwise)~~

	Estimate expected shear if possible: in the presence of shear, any variation in instrument orientation (pitch, roll or heading) will result in velocity differences due to background shear not being correctly removed, leading to bias in epsilon estimates.



	~~Waves~~

	~~Expected influence of wave field Stokes drift on surface measurements~~

	~~Consider becoming familiar with wave removal algorithms.~~







	Return to [[Deployment]]		Return to [[Deployment]]

Yuengdjern: Created page with "Sampling strategy Time and length-scales Commute these to horizontal and vertical Sampling time Repetition rate Sample as fast as possible (spread ou..."

2021-09-22T15:13:09Z

Created page with "Sampling strategy Time and length-scales Commute these to horizontal and vertical Sampling time Repetition rate Sample as fast as possible (spread ou..."

New page

Sampling strategy

Time and length-scales

Commute these to horizontal and vertical

Sampling time

Repetition rate

Sample as fast as possible (spread out the spectral density of noise)

Trade off against power/storage

Bin size

No smaller than advective lengthscale if using across beam methods

Factor this into ambiguity velocity

Links between bin size/nominal velocity accuracy, sub-pings (averaging across pings) duration of data aggregation (burst)

No of samples

Burst vs continuous

Consider Burst periods

Power/Storage saving

Ensure capture required dynamics

Time averaging (important to specify whether the averaging is over the ensemble period for the full deployment period. )

what your max velocities will be

ambiguity velocity - set it accordingly for your flows

Likely SNR

scatterers if known.

Water velocities; energy.

Likely turbulence ROT 10%

Stratification for stratified environments

Shear (boundary layer or otherwise)

Estimate expected shear if possible: in the presence of shear, any variation in instrument orientation (pitch, roll or heading) will result in velocity differences due to background shear not being correctly removed, leading to bias in epsilon estimates.

Waves

Expected influence of wave field Stokes drift on surface measurements

Consider becoming familiar with wave removal algorithms.

Return to [[Deployment]]