Dataset: LB_2012_LB2_ADCP_76m

Name: ADCP data from the South Atlantic Bight (SAB) continental shelf off Long Bay (Mooring #2) at 76 meters collected from January to April in 2012 (Long Bay Wintertime Bloom project)
Published: 2014-12-18
Keywords: oceans

Cite This Dataset

DOI:10.26008/1912/bco-dmo.544479.1

Spatial Extent: N:32.9403 E:-78.0988 S:32.9403 W:-78.0988

Temporal Extent: 2012-01-19 - 2012-04-03

Project:

Mechanisms of nutrient input at the shelf margin supporting persistent winter phytoplankton blooms downstream of the Charleston Bump (Long Bay Wintertime Bloom)

Principal Investigator:

James Nelson (Skidaway Institute of Oceanography, SkIO)

Co-Principal Investigator:

Catherine Edwards (Skidaway Institute of Oceanography, SkIO)

Harvey E. Seim (University of North Carolina at Chapel Hill, UNC-Chapel Hill)

Contact:

Sara Haines (University of North Carolina at Chapel Hill, UNC-Chapel Hill)

BCO-DMO Data Manager:

Nancy Copley (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version:

Version Date:

2014-12-18

Restricted:

Validated:

Yes

Current State:

Final no updates expected

ADCP data from the South Atlantic Bight (SAB) continental shelf off Long Bay (Mooring #2) at 76 meters collected from January to April in 2012 (Long Bay Wintertime Bloom project)

Abstract:

Time series of horizontal and vertical current profiles measured every 5 minutes (300sec) with an acoustic doppler current profiler (ADCP) mounted on the bottom frame looking upward. The depth resolution is 1 meter. The mooring is located at Long Bay, S. Carolina in the South Atlantic Bight and recorded from 76 meters depth.

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Archival Copy

Version Date	Archive	Persistent Identifier	Date Assigned
2014-12-18	Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)	10.26008/1912/bco-dmo.544479.1	2023-10-09

Methods & Sampling

A Teledyne RDI 600 kHz Work Horse Acoustic Doppler Current Profiler (RDI ADCP) was mounted looking upward on a bottom frame at nominal depth of 30m. Sampling was set for every 300 seconds (5min). Depth resolution was set to 1 meter.

LB2 ADCP did not have a pressure sensor and LB3 ADCP pressure sensor malfunctioned. Pressure records from the collocated bottom-frame CTDs were used to form the surface mask in ADCP profile data

Data Processing Description

Data were read from ADCP binary format using Rich Pawlowicz’s MATLAB functions to read binary and processed RDI ADCP files. [1]

Quality control (QC) steps applied are based on Teledyne RDI recommendations [2] and QARTOD guidance [3]. Quality controlled ADCP data were flagged with Not-a-Number (NaN) (changed to nd by BCO-DMO) under the following conditions:

1. when bottom frame not at deployment depth (trimming beginning and end values)
2. sensor health parameters (pitch, roll, heading, water temperature) not within tolerances
3. quality and strength of returned signal not sufficient based on the following parameters:
a. Echo Intensity
b. Correlation Magnitude
c. Error Velocity
d. Percent Good
4. surface masking based on beam angle and addition roll and/or pitch and surface location from water level determined from pressure sensor on ADCP or collocated on the bottom frame.

The ADCP configuration info and tolerances used in the QC processing for each ADCP (LB1, LB2, and LB3) are provided with each dataset.

As a final step, the horizontal velocity components were rotated to be relative to True North based on magnetic variation of the deployment location after verifying no internal application of magnetic variation was applied to data.

Further ADCP data processing information (pdf)

References:
[1] Pawlowicz’s Matlab Stuff. Accessed December 2014.
[2] D.R. Symonds 2006.
[3] IOOS, 2013. Accessed December 17, 2014.

BCO-DMO Processing

BCO-DMO Processing:
-extracted data from MatLab .mat file
-added conventional header with dataset name, PI name, version date, reference information
-renamed parameters to BCO-DMO standard
-added deployment_id, lat, lon
-added 'day_local', 'month_local', 'year', 'yrday_local', ISO_DateTime_UTC to served view
-changed NaN to nd
-reduced number of significant digits

Data Files

File
ADCP_2.csv (Comma Separated Values (.csv), 16.20 MB) MD5:ebd85390137302bf5a1a4b040549dff8 Primary data file for dataset ID 544479

Supplemental Files

File
Further ADCP data processing information filename: README_mooring_ADCP_mat_files.pdf (Portable Document Format (.pdf), 14.93 KB) MD5:6158cb3d2ef6b98de19fbf394286d8e0 This README file describes the file contents and processing steps for each file of level1 mooring adcp data for the Long Bay Wintertime (2012) Project.

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-1032276
NSF Division of Ocean Sciences	OCE-1032285

Deployments

Deployment	Synonyms	Start Date	Platform	Investigator
LB_2012_LB2		2012-01-19	LB2 Mooring	James Nelson (Chief Scientist) Catherine Edwards (Co-Chief Scientist)	data info

Instruments

Acoustic Doppler Current Profiler

Supplied Name: ADCP

Supplied Description:

Instrument Type

Generic Name: Acoustic Doppler Current Profiler

Acronym: ADCP

Community Identifier: http://vocab.nerc.ac.uk/collection/L05/current/115/

Generic Description:

The ADCP measures water currents with sound, using a principle of sound waves called the Doppler effect. A sound wave has a higher frequency, or pitch, when it moves to you than when it moves away. You hear the Doppler effect in action when a car speeds past with a characteristic building of sound that fades when the car passes. The ADCP works by transmitting "pings" of sound at a constant frequency into the water. (The pings are so highly pitched that humans and even dolphins can't hear them.) As the sound waves travel, they ricochet off particles suspended in the moving water, and reflect back to the instrument. Due to the Doppler effect, sound waves bounced back from a particle moving away from the profiler have a slightly lowered frequency when they return. Particles moving toward the instrument send back higher frequency waves. The difference in frequency between the waves the profiler sends out and the waves it receives is called the Doppler shift. The instrument uses this shift to calculate how fast the particle and the water around it are moving. Sound waves that hit particles far from the profiler take longer to come back than waves that strike close by. By measuring the time it takes for the waves to bounce back and the Doppler shift, the profiler can measure current speed at many different depths with each series of pings. (More from WHOI instruments listing).

Parameters

Date and time formats are described in python strftime() syntax.

Supplied Name	Supplied description	Supplied Units	Standard Name
deploy_id	mooring identification	unitless	deploy
lat	latitude; north is positive	decimal degrees	lat
lon	longitude; east is positive	decimal degrees	lon
year	year	yyyy	year
month_utc	UTC month	mm	month_utc
day_utc	UTC day	dd	day_utc
date_utc	UTC date	yyyy-mm-dd	date_utc
time_utc	UTC time	HH:MM:SS	time_utc
yrday_utc	UTC day and decimal time: 326.5 for the 326th day of the year or November 22 at 1200 hours (noon)	yyy.fraction_of_day	yrday_utc
ISO_DateTime_UTC	Date/Time (UTC) ISO formatted	yyyy-mm-ddTHH:MM:SS.00Z	ISO_DateTime_UTC
pitch	degree of fore and aft movement from the horizontal	degrees	no_bcodmo_term
roll	degree of side to side movement from the horizontal	degrees	no_bcodmo_term
heading	direction of movement; compass heading	degrees	heading
depth	depth	meters	depth
temperature	temperature	degrees Celsius	temp
pressure	pressure	decibars	press
salinity	salinity	PSU	sal
u#	eastward component of water velocity relative to true north; '#' represents the depth range in meters of each profile depth cell above the ADCP	meters/second	U
v#	northward component of water velocity relative to true north; '#' represents the depth range in meters of each profile depth cell above the ADCP	meters/second	V
w#	vertical velocity; '#' represents the depth range in meters of each profile depth cell above the ADCP	meters/second	vtvel

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Database

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Dataset: LB_2012_LB2_ADCP_76m