Metadata associated with the MOCNESS tows taken in the Red Sea near Economic City (ECDEEP) on the R/V Thuwal cruise during January 2014 (Red Sea Krill project)

Website: https://www.bco-dmo.org/dataset/625883
Version: 2015-10-28

Project
» Red Sea Krill (Red Sea Krill)
ContributorsAffiliationRole
Wiebe, Peter H.Woods Hole Oceanographic Institution (WHOI)Principal Investigator
Copley, NancyWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager


Dataset Description

Metadata associated with the MOCNESS tows taken in the Red Sea near Economic City (ECDEEP), January 2014 including net opening and closing depth, volume filtered per net.


Methods & Sampling

Three day trips were made aboard the R/V Thuwal to a location referred to as the Economic City Deep or ECDEEP: a ~700 m deep basin located north of KAUST at 22.5o N, 39.03o E).  A 1/4-m MOCNESS (Multiple Opening/Closing Net and Environmental Sensing System; Wiebe et al., 1985) with 200 µm mesh nets was used to sample the zooplankton.

Field sampling: The MOCNESS was obliquely towed four times from the stern A-frame using 11.43 mm conducting cable to 600 m depth with a ship speed nominally of 2 kts (Fig. 2; Table 1). Two MOCNESS tows were taken during daytime, one each on 7 and 8 January 2014, and two night tows were taken on 12 January 2014. The first day tow (m-25-001) was equipped with 5 nets that sampled 600-400, 400-200, 200-100, and 100-0 m. The second day tow (m-25-002) and the two night tows (m-25-003, m-25-004) each had six nets that sampled 600-400, 400-200, 200-100, 100-50, and 50-0 m. The first tow was done without having GPS data input to the MOCNESS acquisition program, so positions from the bridge were obtained for the tow start and end, and at each opening of a net. GPS positions were logged for the other three tows. The MOCNESS system was equipped with the standard SeaBird temperature and conductivity probes. Volume of water filtered by each net was based on the net frame angle and flowmeter counts using equation 10b in Wiebe et al., 1985.


Data Processing Description

BCO-DMO Processing:

- added conventional header with dataset name, PI name, version date
- renamed parameters to BCO-DMO standard
- added columns: time_start_local, time_end_local, lat_start, lon_start, lat_end, lon_end


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Data Files

File
moc_meta.csv
(Comma Separated Values (.csv), 2.20 KB)
MD5:e17e19438a431b865bd90a717b01db64
Primary data file for dataset ID 625883

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Parameters

ParameterDescriptionUnits
cruise_idcruise identification unitless
stationsequential station unitless
towMOCNESS tow number unitless
yearyear yyyy
month_locallocal month mm
day_locallocal day dd
yrday_local_startlocal year-day at start tow unitless
yrday_local_endlocal year-day at end tow unitless
lat_startlatitude at start of tow; north is positive decimal degrees
lat_endlatitude at end of tow; north is positive decimal degrees
lon_startlongitude at end of tow; east is positive decimal degrees
lon_endlongitude at end of tow; east is positive decimal degrees
netnet number unitless
depth_opendepth at which net was opened meters
depth_closedepth at which net was closeed meters
vol_filtvolume of water filtered by net cubic meter


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Instruments

Dataset-specific Instrument Name
MOCNESS-.25 m^2
Generic Instrument Name
MOCNESS.25
Dataset-specific Description
This MOCNESS sampled with either 5 or 6 nets, 200 micron mesh.
Generic Instrument Description
The Multiple Opening/Closing Net and Environmental Sensing System or MOCNESS is a family of net systems based on the Tucker Trawl principle. The MOCNESS-1/4 carries nine 1/4-m2 nets usually of 64 micrometer mesh and is used to sample the larger micro-zooplankton.


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Deployments

Thuwal-2014-01

Website
Platform
R/V Thuwal
Start Date
2014-01-07
End Date
2015-01-12
Description
Three day trips to sample krill at ECDEEP station near Economic City, Saudi Arabia, north of KAUST.


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Project Information

Red Sea Krill (Red Sea Krill)

Coverage: Red Sea


The krill population at station ECDEEP was characterized via MOCNESS sampling and CTD casts.



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Funding

Funding SourceAward
King Abdullah University of Science and Technology (KAUST)

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