Metadata Report for BODC Series Reference Number 129449
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
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Time Co-ordinates(UT) |
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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
Christian Albrechts University of Kiel Multisonde CTD profiler
A prototype conductivity-temperature-pressure profiler developed in the 1970s by what was then the Institute for Applied Physics of Kiel University. The instrument could measure up to six parameters in total, including sound velocity and light attenuation by means of an auxiliary light sensor. The unit was used by the then Institute for Marine Science, Kiel.
Specifications
Pressure | Temperature | Conductivity | |
---|---|---|---|
Range | 600 or 6000 dbar | -2 to 40 °C | 5 to 55 mmho cm-1 |
Accuracy | ± 0.01% | ± 0.01 °C | ± 10 µmho cm-1 |
FS Meteor 49 CTD Data Documentation
Instrumentation
Two instruments were used, the Multisonde (Kroebel, 1973) and, as a back-up device, the Bathysonde (Hinkelmann, 1957). Both units measure electrical conductivity, temperature and hydrostatic pressure. They were lowered on a single-conductor cable.
The manufacturer's specifications for the Multisonde are given below:
Pressure | Range | 0-6000dbar 0-600dbar |
---|---|---|
Accuracy of calibration | ±0.01 % | |
Repeatability | ±0.3% | |
Resolution | 0.1 dbar | |
Temperature | Range | -2 to + 40 °C |
Accuracy of calibration | ±0.01 °C | |
Repeatability | ±0.001 °C | |
Resolution | ±0.001 °C | |
Conductivity | Range | 5 to 55 mmho/cm |
Accuracy of calibration | ±10 micro mho/cm | |
Repeatability within 6 months | ±20 micro mho/cm |
Profiles Taken
Phase 0 | Phase 1 | Phase 2 | |
---|---|---|---|
No. of Profiles | 6 | 1303 | 3316 |
No. of Good Quality Profiles | 6 | 1250 | 3293 |
Throughout all phases, the lowering depth was 60 - 1600m, the lowering speed was 60 m/min and the sampling rate was 10/sec.
Calibration
In order to check the calibration during the experiment, a Nansen bottle with two protected reversing thermometers was attached to the cable close to the underwater unit. Various combinations of 9 thermometers on FS Meteor were used. 59 water samples were taken mostly from the upper 20 m during Multisonde casts. It was assumed that a proper re-calibration could be achieved by determining the off-set in temperature and conductivity at these depth levels. The pressure off-set was found by reading the pressure value at the sea surface. There was no time dependence of these re-calibration terms.
The results of the re-calibration analysis are summarised below:
Pressure Offset[dbar] 600 dbar | -0.8 |
---|---|
Pressure Offset[dbar] 6000 dbar | 3.0 |
TNansen - TCTD [°C] | 0.012 ± 0.005 |
Delta TNansen [°C] | 0.009 ± 0.003 |
CNansen - CCTD [µS/cm] | -0.0451 ± 0.0048 |
Time Constant of Thermometer [ms] | 75 |
where:
- Pressure off-set is the CTD pressure reading at the surface
- TNansen is the temperature reading of reversing thermometer
- TCTD is the temperature reading of CTD
- TNansen - TCTD is the mean difference between reversing thermometer and CTD temperature reading
- Delta TNansen is the mean temperature difference between two reversing thermometers in a Nansen bottle
- CNansen is the conductivity determined from Nansen bottle sample
- CCTD conductivity reading of CTD
- CNansen - CCTD is the mean difference between Nansen bottle and CTD conductivity reading
- Time constant is the best time constant of the thermometer to optimise the reduction of salinity spikes.
The salinity measurements of the Nansen samples were carried out using a Beckmann RS7B lab and an Autosal 8400 salinometer. Conductivity was calculated from the salinity values by an iterative reversal of Fofonoff's (1974) formula using Newton's formula (Peters, 1978).
Data Processing
Due to the slow response of the Multisonde thermometers compared to the conductivity sensors, spikes occurred in the salinity profiles. The thermometer time constants were changed in the calculations to optimise the spike reduction. After clipping remaining spikes in salinity, a running mean over about 0.5 dbar was taken. The data were then interpolated to 0.5 dbar increments and, again, a running mean over 1.5 dbar was calculated. A detailed description of this kind of data editing was given by Peters (1976).
General Data Screening carried out by BODC
BODC screen both the series header qualifying information and the parameter values in the data cycles themselves.
Header information is inspected for:
- Irregularities such as unfeasible values
- Inconsistencies between related information, for example:
- Times for instrument deployment and for start/end of data series
- Length of record and the number of data cycles/cycle interval
- Parameters expected and the parameters actually present in the data cycles
- Originator's comments on meter/mooring performance and data quality
Documents are written by BODC highlighting irregularities which cannot be resolved.
Data cycles are inspected using time or depth series plots of all parameters. Currents are additionally inspected using vector scatter plots and time series plots of North and East velocity components. These presentations undergo intrinsic and extrinsic screening to detect infeasible values within the data cycles themselves and inconsistencies as seen when comparing characteristics of adjacent data sets displaced with respect to depth, position or time. Values suspected of being of non-oceanographic origin may be tagged with the BODC flag denoting suspect value; the data values will not be altered.
The following types of irregularity, each relying on visual detection in the plot, are amongst those which may be flagged as suspect:
- Spurious data at the start or end of the record.
- Obvious spikes occurring in periods free from meteorological disturbance.
- A sequence of constant values in consecutive data cycles.
If a large percentage of the data is affected by irregularities then a Problem Report will be written rather than flagging the individual suspect values. Problem Reports are also used to highlight irregularities seen in the graphical data presentations.
Inconsistencies between the characteristics of the data set and those of its neighbours are sought and, where necessary, documented. This covers inconsistencies such as the following:
- Maximum and minimum values of parameters (spikes excluded).
- The occurrence of meteorological events.
This intrinsic and extrinsic screening of the parameter values seeks to confirm the qualifying information and the source laboratory's comments on the series. In screening and collating information, every care is taken to ensure that errors of BODC making are not introduced.
Project Information
Joint Air Sea Interaction Experiment (JASIN)
The JASIN Project was designed to study the interaction of the atmospheric and oceanic boundary layers with the larger scale motions of the sea and the air.
The primary aims may be summarized as follows:
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To observe and distinguish between the physical processes causing mixing in the atmospheric and oceanic boundary layers and relate them to the mean properties of the layers.
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To examine and quantify aspects of the momentum and heat budgets in the atmospheric and oceanic boundary layers and fluxes across and between them.
The multiplicity of processes to be sampled necessitated a large experiment and JASIN involved 14 ships and 3 aircraft with more than 50 teams of investigators from 9 countries. Altogether 35 mooring systems were deployed.
The experiment lasted for 2 months from mid-July to mid-September 1978 and comprised 2 intensive measuring periods preceded by a preparatory test period. The project took place in the north Rockall Trough, an area of deep water (1000m - 2000m) several hundred kilometres off the west coast of Scotland.
Data Activity or Cruise Information
Cruise
Cruise Name | MT49 |
Departure Date | 1978-07-05 |
Arrival Date | 1978-09-11 |
Principal Scientist(s) | E Augstein (Max Planck Institute for Meteorology) |
Ship | FS Meteor |
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:
Flag | Description |
---|---|
Blank | Unqualified |
< | Below detection limit |
> | In excess of quoted value |
A | Taxonomic flag for affinis (aff.) |
B | Beginning of CTD Down/Up Cast |
C | Taxonomic flag for confer (cf.) |
D | Thermometric depth |
E | End of CTD Down/Up Cast |
G | Non-taxonomic biological characteristic uncertainty |
H | Extrapolated value |
I | Taxonomic flag for single species (sp.) |
K | Improbable value - unknown quality control source |
L | Improbable value - originator's quality control |
M | Improbable value - BODC quality control |
N | Null value |
O | Improbable value - user quality control |
P | Trace/calm |
Q | Indeterminate |
R | Replacement value |
S | Estimated value |
T | Interpolated value |
U | Uncalibrated |
W | Control value |
X | Excessive difference |
SeaDataNet Quality Control Flags
The following single character qualifying flags may be associated with one or more individual parameters with a data cycle:
Flag | Description |
---|---|
0 | no quality control |
1 | good value |
2 | probably good value |
3 | probably bad value |
4 | bad value |
5 | changed value |
6 | value below detection |
7 | value in excess |
8 | interpolated value |
9 | missing value |
A | value phenomenon uncertain |
B | nominal value |
Q | value below limit of quantification |