Metadata Report for BODC Series Reference Number 1206947

• Metadata Summary

• Problem Reports

• Data Access Policy

• Narrative Documents

• Project Information

• Data Activity or Cruise Information

• Fixed Station Information

• BODC Quality Flags

• SeaDataNet Quality Flags

Metadata Summary

Problem Reports

No Problem Report Found in the Database

Data Access Policy

Public domain data

These data have no specific confidentiality restrictions for users. However, users must acknowledge data sources as it is not ethical to publish data without proper attribution. Any publication or other output resulting from usage of the data should include an acknowledgment.

The recommended acknowledgment is

"This study uses data from the data source/organisation/programme, provided by the British Oceanographic Data Centre and funded by the funding body."

Narrative Documents

Agilent 6890 networked gas chromatograph

A networked gas chromatograph that separates and analyses gas mixtures in water or air. The instrument includes a dual channel design supporting two inlets and two detectors. An automatic liquid sampling system is fully integrated into the mainframe control and atmospheric pressure and temperature compensation is standard. The instrument also supports 6 column oven ramps with 7 plateaus.

The 6890N is completely customisable depending on the application, with choices of inlets, columns, detectors and sampling systems. Available detectors include; flame ionization, thermal conductivity, micro-electron capture, nitrogen-phosphorus, single- or dual-wavelength flame photometric. Specialised detectors include: atomic emission, Helium ionization, sulphur chemiluminescence and pulsed discharge ionization. All detectors include electronic pneumatics control and electronic on/off for all detector gases. Carrier and makeup gas settings are selectable for He, H2, N2, and argon/methane. There is a choice of inlets including; packed purged injection port, split/splitless capillary inlet, temperature-programmable cool on-column, programmable temperature vaporizer and volatiles inlet. A full array of gas sampling and column switching valves are also available. The instrument has a 7683 ALS interface and incorporates local area network technology as standard.

The Agilent 6890N uses many of the same components as the Agilent 6850N GC producing virtually identical results, but the Agilent 6850N is only half as wide. The Agilent 6890N replaces the HP Agilent 5890 and is no longer in production.

Please see the Agilent 6890N brochure and data sheet for further details.

Instrument Description

Vertical Microstructure Profiler and support sensors

The Vertical Microstructure Profiler (VMP) 5500 was deployed with the standard CTD and microstructure sensor configuration with the addition of the microconductivity probe (SBE7) and fitted with a Rockland Scientific geo-electromagnetic current meter (GEMCM).

Whilst submerged the profiler was tracked using an LBL telemetry system consisting of a Ixsea TT801 deck unit and Ixsea MT861S-R-P1 LBL acoustic transponder with pressure sensor. A 75 kHz VMADCP and a 150 kHz VMADCP were used to estimate the VMP drift direction and magnitude. In order to locate the instrument once it reached the surface, a flag on a mast along with the following recovery aid were used, Novatech ST-400A strobe, Novatech RF-700A1 RDF Beacon, Novatech AS-900A ARGOS Beacon. The RDF ceased functioning about 1/3 of the way through the cruise after it was dropped on the deck and no spare was available. An attempt was made to use the ARGOS beacon in RDF mode, but results were not satisfactory.

Please see the cruise report for further details of the instrumentation performance and recommendations.

BODC Processing

Forty seven VMP-CTD profiles provided by the originator in a structured Matlab format were converted into BODC internal format using standard BODC processing procedures. Potential temperature of the water body was derived by computation using UNESCO 1983 algorithm, sigma-theta was derived by computation from salinity and potential temperature also using UNESCO 1983 algorithm. The following table shows how the variables within the Matlab file were mapped to appropriate BODC parameter codes:

The reformatted data were visualised using the in-house EDSERPLO software. The data were screened and quality control flags were applied to data as necessary.

References

Fofonoff, N.P. and Millard, R.C., 1983. Algorithms for computations of fundamental properties of seawater. UNESCO Technical Papers in Marine Science, 44, 53.

Originator's Data Processing

Sampling Strategy

Forty seven Vertical Microstructure Profiler (VMP) deployments were carried out successfully as part of 71 scientific stations. After each VMP deployment, the CTD was deployed once the VMP had accelerated to its profiling velocity and was clear of the vessel.

A test cast was performed to a check for gross buoyancy (the instrument floated without weights) and the performance of the weight release mechanism. A second test cast was conducted using trimmed drag elements so as to reduce drag and increase the fall rate. A fall rate of 0.58 m s ^-1 was obtained, an increase over the 0.48 m s ^-1 with the standard drag elements.

Several stations were missed due to problems, seven were missed due to battery charge issues and eight stations were missed due to five seafloor impacts and down time associated with refurbishment and time used waiting for profiler surfacing (44 hours).

Data processing

The following processing steps were undertaken:

1) Near-surface data (nominally 5-10 dbar) were removed to eliminate the noisy data at the near surface from influencing further processing.

2) The VMP CTD data were then adjusted to account for the spatial displacement between the pressure sensor (at the VMP nose) and the CTD sensors (on the VMP body). The lag was computed as a function of depth to account for the slower fall rate of the instrument near the beginning and end of the extracted downcast.

3) The routine despike.m in the ODAS routine library was used to despike the CTD temperature, conductivity and pressure.

4) The short-term mismatch between temperature and conductivity signals due to dissimilar sensor responses were then corrected. The Ferrari and Rudnick (2000) two-term correction was chosen as the best method.

5) The long-time mismatch between temperature and conductivity signals due to the thermal inertia of the conductivity cell were corrected. The thermal inertia correction routine in the ODAS routine library (TI correction.m) which works by deriving the corrected temperature of the fluid in the conductivity cell to be used (in place of the temperature measured by the CTD temperature sensor) in the calculation of salinity based on Morrison, et al. (1994) was used.

6) The effects of conductivity cell thermal expansion and pressure contraction were corrected. The conductivity Tp corr.m routine from the ODAS routine library was used.

7) Low pass filters (using a npole order low pass Butterworth filter) the corrected pressure, temperature, conductivity and salinity profiles to eliminate high frequency noise. Default values are npole = 4 and cut off = 0.4 Hz, chosen to have a half-power point at 0.1 Hz, nominally the highest frequency where the temperature and conductivity signals are observed to be coherent.

8) Lastly, temperature, conductivity and salinity profiles were averaged in pressure bins of 0.5 dbar.

References cited

Ferrari, R. and Rudnick, D.L., 2000. Thermohaline structure of the upper ocean, Journal of Geophysical Research, 105.

Morrison, J., Anderson, R., Larson, N., D'Asaro, E. and Boyd, T., 1994. The correction for thermal-lag effects in Sea-Bird CTD data. Journal of Atmospheric Oceanic Technology, 11, 1151-1164.

Rockland Scientific Vertical Microstructure Profiler VMP 5500

A full ocean-depth untethered vertical microstructure turbulence profiler for the measurement of dissipation-scale turbulence along with temperature and conductivity for up to 5500 m depth. The instrument is fitted with pressure, temperature (SBE-3F) and conductivity (SBE-4C) sensors, three acceleration sensors, a PC104 computer data acquisition and communication system, anti-aliasing filters and a standard suite of microstructure sensors which includes two SPM-38-5 velocity shear probes, two FP07-38-5 fast thermistors and an optional microstructure conductivity probe (SBE7).

All microstructure sensors are held in the nose cone and can be exchanged or replaced in the field, without the need of disassemble the main pressure case of the VMP which can hold up to 6 microstructure probes in any combination. The main pressure case contains the pressure transducer as well as the accelerometers, electronics for signal conditioning A/D conversion and data logging, and is separated from the nose cone by a 38 mm thick bulkhead which prevents water penetration into the main pressure case.

The instrument has an aluminium frame with syntactic foam attached for floatation. Data are collected on the downcast and after reaching a pre-defined depth the profiler releases ballast weights so that the instrument becomes positively buoyant. The instrument rises to the surface with a nominal speed of 1.0 ms^-1. As a backup, there is a triple-redundancy emergency ballast release consisting of a corrosion trigger, time-out trigger and pressure rate-of-change trigger. The VMP 5500 has a strobe light and a radio beacon and can also be fitted with an Argos transmitter for locating the instrument after it has returned to the surface. The VMP 5500 was replaced by the VMP 6000 in 2010.

Please see the VMP 5500 specification sheet for further details.

Project Information

Southern Ocean FINEStructure (SOFINE) project document

The Southern Ocean FINEStructure (SOFINE) project was a UK field programme aimed at studying the frictional processes that slow down the Antarctic Circumpolar Current (ACC) and influence the meridional exchange of water masses in the Southern Ocean.

The study investigated the role of sea floor topography in slowing the ACC and driving meridional flow across the Southern Ocean, and the manner in which mesoscale and small scale oceanic phenomena modified water mass properties and affected their movement across the ACC. Specifically, SOFINE set out to:

• Determine the relative importance of oceanic processes associated with large scale (hundreds to thousands of kilometres) and small scale (a few kilometres) sea floor topography in the context of ACC flow rates and water mass exchange.
• Identify the oceanic processes controlling the rate at which water masses are transformed and fluxed across the ACC.

The SOFINE experiment focused on a major meander of the ACC around the northern Kerguelen Plateau in the Indian Ocean. Theories and models of Southern Ocean circulation indicated that this region experienced intensified 'friction' and cross-ACC flow. Fieldwork was undertaken over a 52 day period in November and December 2008, and included hydrographic observations, microcstructure and turbulence measurements, detailed bathymetric surveys and several deployments of floats, drifters and moorings.

SOFINE was funded by the UK Natural Environment Research Council and involved the collaboration of a number of international institutions: the National Oceanography Centre (UK), the University of East Anglia (UK), British Antarctic Survey (UK), Woods Hole Oceanographic Institution (US), the Commonwealth Scientific and Industrial Research Organisation (Australia), the University of Tasmania (Australia) and the Leibniz Institute of Marine Sciences (IFM-GEOMAR) at the University of Kiel (Germany).

For more information please see the official project website at SOFINE

Data Activity or Cruise Information

Cruise

Complete Cruise Metadata Report is available here

Fixed Station Information

No Fixed Station Information held for the Series

BODC Quality Control Flags

The following single character qualifying flags may be associated with one or more individual parameters with a data cycle:

SeaDataNet Quality Control Flags

The following single character qualifying flags may be associated with one or more individual parameters with a data cycle: