Metadata Report for BODC Series Reference Number 1746297
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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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
Sea-Bird Dissolved Oxygen Sensor SBE 43 and SBE 43F
The SBE 43 is a dissolved oxygen sensor designed for marine applications. It incorporates a high-performance Clark polarographic membrane with a pump that continuously plumbs water through it, preventing algal growth and the development of anoxic conditions when the sensor is taking measurements.
Two configurations are available: SBE 43 produces a voltage output and can be incorporated with any Sea-Bird CTD that accepts input from a 0-5 volt auxiliary sensor, while the SBE 43F produces a frequency output and can be integrated with an SBE 52-MP (Moored Profiler CTD) or used for OEM applications. The specifications below are common to both.
Specifications
| Housing | Plastic or titanium |
| Membrane | 0.5 mil- fast response, typical for profile applications 1 mil- slower response, typical for moored applications |
| Depth rating | 600 m (plastic) or 7000 m (titanium) 10500 m titanium housing available on request |
| Measurement range | 120% of surface saturation |
| Initial accuracy | 2% of saturation |
| Typical stability | 0.5% per 1000 h |
Further details can be found in the manufacturer's specification sheet.
Instrument Description for JR20130713 (JR288) CTD
CTD Unit and Auxiliary Sensors
The CTD unit comprised a Sea-Bird Electronics (SBE) 9plus underwater unit, an SBE 11plus deck unit, a BAS 24-way frame and 24x20 l OTE Water Samplers; all of which were mounted on a stainless steel 24-way CTD frame. Attached to the CTD were two SBE 3P temperature sensors, two SBE 4C conductivity sensors, one Paroscientific Digiquartz pressure sensor, one SBE 43 dissolved oxygen sensor, one CTG Aquatracka MKIII fluorometer and one CTG WETLabs C-Star transmissometer an a Biospherical QCD-905L underwater PAR sensor. An additional independent SBE35 temperature sensor was attached to the frame to perform observations each time a bottle is fired.
| Sensor unit | Model | Serial number | Full specification | Calibration dates (YYYY/MM/DD) | Comments |
|---|---|---|---|---|---|
| CTD underwater unit | SBE 9plus | 09P-35716-0771 | SBE 9plus | ||
| CTD deck unit | SBE 11plus | 11P20391-0502 | |||
| Pressure sensor | Paroscientific Digiquartz | 0771 | Paroscientific Digiquartz | 30/03/2013 | |
| Temperature sensor | SBE 3P | 3P-4472 | SBE 03P | 30/08/2012 | |
| Temperature sensor | SBE 3P | 3P-2366 | SBE 03P | 30/08/2012 | |
| Conductivity sensor | SBE 4C | 4C-2222 | SBE 04C | 21/08/2012 | cpcor= -9.57x10-8 |
| Conductivity sensor | SBE 4C | 4C-2289 | SBE 04C | 21/08/2012 | cpcor= -9.57x10-8 |
| Dissolved oxygen sensor | SBE 43 | 43-2290 | SBE 43 | 31/03/2012 | |
| Irradiance sensor (DWIRR) | Biospherical QCL PAR sensor | 70441 | Biospherical QCP PAR sensor | 16/05/2012 | Measuring downwelling irradiance |
| Fluorometer | Chelsea Aquatracka III | 088-216 | Chelsea MKII Aquatracka | 19/02/2013 | |
| Transmissometer | WETLabs C-Star - 25 cm path | CST-846DR | Alphatracka MKII | 13/03/2013 |
Sea-Bird Electronics SBE 911 and SBE 917 series CTD profilers
The SBE 911 and SBE 917 series of conductivity-temperature-depth (CTD) units are used to collect hydrographic profiles, including temperature, conductivity and pressure as standard. Each profiler consists of an underwater unit and deck unit or SEARAM. Auxiliary sensors, such as fluorometers, dissolved oxygen sensors and transmissometers, and carousel water samplers are commonly added to the underwater unit.
Underwater unit
The CTD underwater unit (SBE 9 or SBE 9 plus) comprises a protective cage (usually with a carousel water sampler), including a main pressure housing containing power supplies, acquisition electronics, telemetry circuitry, and a suite of modular sensors. The original SBE 9 incorporated Sea-Bird's standard modular SBE 3 temperature sensor and SBE 4 conductivity sensor, and a Paroscientific Digiquartz pressure sensor. The conductivity cell was connected to a pump-fed plastic tubing circuit that could include auxiliary sensors. Each SBE 9 unit was custom built to individual specification. The SBE 9 was replaced in 1997 by an off-the-shelf version, termed the SBE 9 plus, that incorporated the SBE 3 plus (or SBE 3P) temperature sensor, SBE 4C conductivity sensor and a Paroscientific Digiquartz pressure sensor. Sensors could be connected to a pump-fed plastic tubing circuit or stand-alone.
Temperature, conductivity and pressure sensors
The conductivity, temperature, and pressure sensors supplied with Sea-Bird CTD systems have outputs in the form of variable frequencies, which are measured using high-speed parallel counters. The resulting count totals are converted to numeric representations of the original frequencies, which bear a direct relationship to temperature, conductivity or pressure. Sampling frequencies for these sensors are typically set at 24 Hz.
The temperature sensing element is a glass-coated thermistor bead, pressure-protected inside a stainless steel tube, while the conductivity sensing element is a cylindrical, flow-through, borosilicate glass cell with three internal platinum electrodes. Thermistor resistance or conductivity cell resistance, respectively, is the controlling element in an optimized Wien Bridge oscillator circuit, which produces a frequency output that can be converted to a temperature or conductivity reading. These sensors are available with depth ratings of 6800 m (aluminium housing) or 10500 m (titanium housing). The Paroscientific Digiquartz pressure sensor comprises a quartz crystal resonator that responds to pressure-induced stress, and temperature is measured for thermal compensation of the calculated pressure.
Additional sensors
Optional sensors for dissolved oxygen, pH, light transmission, fluorescence and others do not require the very high levels of resolution needed in the primary CTD channels, nor do these sensors generally offer variable frequency outputs. Accordingly, signals from the auxiliary sensors are acquired using a conventional voltage-input multiplexed A/D converter (optional). Some Sea-Bird CTDs use a strain gauge pressure sensor (Senso-Metrics) in which case their pressure output data is in the same form as that from the auxiliary sensors as described above.
Deck unit or SEARAM
Each underwater unit is connected to a power supply and data logging system: the SBE 11 (or SBE 11 plus) deck unit allows real-time interfacing between the deck and the underwater unit via a conductive wire, while the submersible SBE 17 (or SBE 17 plus) SEARAM plugs directly into the underwater unit and data are downloaded on recovery of the CTD. The combination of SBE 9 and SBE 17 or SBE 11 are termed SBE 917 or SBE 911, respectively, while the combinations of SBE 9 plus and SBE 17 plus or SBE 11 plus are termed SBE 917 plus or SBE 911 plus.
Specifications
Specifications for the SBE 9 plus underwater unit are listed below:
| Parameter | Range | Initial accuracy | Resolution at 24 Hz | Response time |
|---|---|---|---|---|
| Temperature | -5 to 35°C | 0.001°C | 0.0002°C | 0.065 sec |
| Conductivity | 0 to 7 S m-1 | 0.0003 S m-1 | 0.00004 S m-1 | 0.065 sec (pumped) |
| Pressure | 0 to full scale (1400, 2000, 4200, 6800 or 10500 m) | 0.015% of full scale | 0.001% of full scale | 0.015 sec |
Further details can be found in the manufacturer's specification sheet.
Biospherical Instruments Log Quantum Cosine Irradiance Sensor QCP-2300 & QCP-2350
The QCP-2300 is a submersible cosine-collector radiometer designed to measure irradiance over Photosynthetically Active Radiation (PAR) wavelengths. It features a constant (better than ±10%) quantum response from 400 to 700 nm with the response being sharply attenuated above 700 nm and below 400 nm.
The sensor is a blue-enhanced high stability silicon photovoltaic detector with dielectric and absorbing glass filter assembly. The output is a DC voltage typically between 0 and 5 VDC that is proportional to the log of the incident irradiance.
The QCP-2300 is specifically designed for integration with 12-bit CTD systems and dataloggers requiring a limited-range of signal input.
Specifications
| Wavelength | 400 to 700 nm |
| PAR Spectral Response | better than ± 10% over 400-700 nm |
| Cosine Directional Response | ± 5% 0 to 65°; ± 10% 0 to 85° |
| Noise level | < 1 mV |
| Temperature Range | -2 to 35 °C |
| Depth Range (standard) | 1000 m |
Further details can be found in the manufacturer's manual.
.WETLabs C-Star transmissometer
This instrument is designed to measure beam transmittance by submersion or with an optional flow tube for pumped applications. It can be used in profiles, moorings or as part of an underway system.
Two models are available, a 25 cm pathlength, which can be built in aluminum or co-polymer, and a 10 cm pathlength with a plastic housing. Both have an analog output, but a digital model is also available.
This instrument has been updated to provide a high resolution RS232 data output, while maintaining the same design and characteristics.
Specifications
| Pathlength | 10 or 25 cm |
| Wavelength | 370, 470, 530 or 660 nm |
| Bandwidth | ~ 20 nm for wavelengths of 470, 530 and 660 nm ~ 10 to 12 nm for a wavelength of 370 nm |
| Temperature error | 0.02 % full scale °C-1 |
| Temperature range | 0 to 30°C |
| Rated depth | 600 m (plastic housing) 6000 m (aluminum housing) |
Further details are available in the manufacturer's specification sheet or user guide.
Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) James Clark Ross cruise JR20130713 (JR288) BODC CTD data processing
The files were processed at the Chemistry Department, at the Univeristy of York and were sent to BODC in Sea-Bird cnv format. The following parameters were sent: time, press, primary and secondary temperature, salinity, conductivity, fluorescence, oxygen, par and transmittance but not all were transferred as they were either not relevant, or it was not clear how the originator obtained them.
In addition to the raw CTD data, BODC were provided with the intermediate versions created at by the different processing procedures. Files for casts 1-26 the data were not binned by the originator, so this procedure was done at BODC, but casts 27 to 45 were binned to one dbar. All the files were reformatted into BODC's internal NetCDF format. The following table shows the mapping of the originator's variables to the appropriate BODC parameter codes:
| Originator's Variable | Units | Description | BODC Parameter Code | Units | Comment |
|---|---|---|---|---|---|
| prDM | db | Pressure (spatial co-ordinate) exerted by the water body by profiling pressure sensor and corrected to read zero at sea level | PRESPR01 | Decibars | - |
| t090C | °C | Temperature of the water body by CTD or STD | TEMPST01 | °C | - |
| c0mS/cm | mS cm-1 | Electrical conductivity of the water body by CTD | CNDCST01 | S m-1 | *0.1 |
| sal00 | PSU | Practical salinity of the water body by CTD and computation using UNESCO 1983 algorithm | PSALST01 | Dimensionless | derived from temp1 and cond1 |
| sbeox0Mm/Kg | µmol kg-1 | Concentration of oxygen {O2 CAS 7782-44-7} per unit volume of the water body [dissolved plus reactive particulate phase] by in-situ sensor | DOXYZZ01 | µmol kg-1 | Converted during transfer |
| sbeox0V | Volts | Instrument output (voltage) by oxygen sensor | OXYOCPVL | Volts | |
| flC | µ g l-1 | Concentration of chlorophyll-a {chl-a CAS 479-61-8} per unit volume of the water body [particulate >unknown phase] by in-situ chlorophyll fluorometer | CPHLPR01 | mg m-3 | µ g l-1 = mg m-3 |
| CStarTr0 | % | Transmittance (red light wavelength) per 25cm of the water body by 25cm path length red light transmissometer | POPTDR01 | % | |
| par | Downwelling vector irradiance as photons (PAR wavelengths) in the water body by cosine-collector radiometer | IRRDUV01 | µE m-2 s-1 | ||
| Potential temperature of the water body by computation using UNESCO 1983 algorithm | POTMCV01 | °C | Derived from TEMPPR01, PSALST01 and PRESPR01 | ||
| Sigma-theta of the water body by CTD and computation from salinity and potential temperature using UNESCO algorithm | SIGTPR01 | kg m-3 | Derived from POTMCV01, PSALST01 and PRESPR01 | ||
| Saturation of oxygen {O2 CAS 7782-44-7} in the water body [dissolved plus reactive particulate phase] by Sea-Bird SBE 43 sensor and computation from concentration using Benson and Krause | OXYSSU01 | % | Derived from TEMPPR01, PSALST01 and DOXYZZ01 |
Additional variables (secondary temperature, salinity, conductivity, density, potential temperature) are avaiable upon request.
The reformatted data were visualised using the in-house EDSERPLO software. Suspect data were marked by adding an appropriate quality control flag, and missing data by setting the data to an appropriate value and applying the quality control flag.
Durign visual inspection it was evident that not all casts had Oxygen data as oxygen voltages were null. For these DOXYZZ01 and OXYSU01 are not present in the final file. Oxygen voltage was kept on all files.
Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) James Clark Ross cruise JR20130713 (JR288) Originator's CTD data processing
Sampling Strategy
A total of 45 CTD casts were deployed during RRS James Clark Ross ACCACIA Arctic Summer cruise JR20130713 (JR288). In general, CTD operations consisted of two casts per day: one shallow cast at approximately 07:15 UTC, and one deeper cast at approximately 14:00 UTC. Cast depths ranged from approximately 100 meters to as near to the seabed as possible, typically around 3500 meters.
The CTD carousel was fitted with 24 sampling bottles of 20 litres each. Typically two bottles were fired at each sampling depth, allowing for any seal or misfire problems, which rarely took place throughout the cruise.
Data processing
CTD data were processed using the SBE Data Processing software V7.22.3. The raw data files were converted using the basic on-board data processing guidelines for SBE 911 CTD:
- DatCnv- Data conversion
- BottleSum- Bottle file generation
- Filter- Low pass filter applied with the following constants, A= 0.03 and B= 0.15
- AlignCTD- To ensure oxygen corrections, the channels were adjusted by 5.0 seconds
- CellTM- Used to remove conductivity cell thermal mass effects from the primary and secondary conductivity channels. The values applied were α= 0.03 and β= 7.0
- Loopedit- applied with a minimum velocity threshold of 0.25
- Derive- Used to obtain Depth, Oxygen concentration, primary and secondary salinity
- BinAve- Bin Average to 0.5 second intervals
- Strip- Used to remove surplus channels
Calibration
No independent calibrations were carried out by the Originator.
Project Information
ACCACIA- Aerosol Cloud Coupling and Climate Interactions in the Arctic
The ACCACIA project is a £2.05 million component of the Natural Environment Research Council (NERC) Arctic Research programme (ARP) running from 2012 to 2016. The aim of ACCACIA is to collect data using both airplanes and ships based in the Svalbard archipelago near the margin of permanent Arctic sea ice cover and study fluxes of solar and infrared radiation above and below the clouds, the vertical structure of the low-level atmosphere and how aerosol concentration levels change with the seasons and with the extent of sea-ice cover. The results from this research will inform not only cutting-edge modelling of the global climate system and predictions for future climatic change, but also more immediate weather forecasts for mid-to-high-latitude locations such as the UK.
Background
Over most of the globe low clouds act to cool the surface since they reflect sunlight; over the arctic the highly reflective ice surface reduces the significance of cloud reflectivity, and the absorption of infrared radiation by cloud water droplets becomes the dominant effect - this acts to trap heat below cloud, warming the surface. Although climate models generally show a strong greenhouse warming effect in the Arctic, they also disagree with each other more in the Arctic than anywhere else, producing a wider range of possible future climate conditions. The models also tend not to be able to reproduce current Arctic climate conditions very accurately. This large uncertainty in models of the Arctic climate results primarily from poor representation of physical processes within the models, and some unique and particularly challenging conditions. The largest single source of uncertainty is the representation of clouds. The models use simple representations of cloud properties that were developed from observations in mid latitude or tropical cloud systems - very different conditions from those that exist in the Arctic.
The main activities of this project are to make airborne in situ measurements of cloud microphysical properties, the vertical structure of the boundary layer and aerosol properties, and the fluxes of solar and infra red radiation above, below, and within cloud. It will also measure the production rates and properties of aerosol at the surface and their variability with season and extent of sea ice cover. These measurements will be used, along with a range of numerical models of aerosol and cloud processes, and atmospheric dynamics to evaluate the interactions between sea ice extent, aerosol production and cloud properties. New and improved descriptions of these processes suitable for use within climate models will be developed, tested, and implemented within the MetOffice climate model HadGEM. The ability of the current MetOffice models to reproduce the observed Arctic cloud and boundary layer properties will be tested and the impact of the new parameterization schemes evaluated. Finally we will undertake a series of climate simulations to examine how future climate will evolve, and the feedbacks between warming of the Arctic, melting of sea ice, production of aerosol, and the properties of clouds evaluated.
Participants
Dr Ian Brooks is the Lead Investigator and Professor Lucy Carpenter and Dr Amélie Kirchgaessner are Co-Investigators. The project is made up of collaborations with universities and research organisations including:
- British Antarctic Survey
- University of East Anglia
- University of Leeds
- University of Manchester
- University of York
Fieldwork and data collection
The ACCACIA project involves the collection of data in the Svalbard archipelago near the margin of permanent sea ice cover using research vessels as well as the BAS MASIN and FAAM BAe146 aircrafts. The project consisted of two cruises, as detailed below:
| Cruise identifier | Research ship | Cruise dates |
|---|---|---|
| Lance ACCACIA | RV Lance | 15 March 2013 - 31 March 2013 |
| JR20130713 (JR288) | RRS James Clark Ross | 13 July 2013 - 16 August 2013 |
The aims of the research cruises are to make surface based in-situ measurements of marine aerosol composition and its properties, and aerosol precursor gases including DMS, VOCs and halocarbons. Trace gases were measured in air and water, and high volume aerosol samples were collected for off-line characterisation of organic composition. Ambient aerosol measurements and bubble tank experiments were conducted to characterise aerosol physical and chemical properties using a suite of instrumentation by the Manchester group. Together with black carbon/soot optical measurements and CCN measurements made as function of particle size and super-saturation, these will be used as input in cloud microphysical models to investigate their influence on aerosol-cloud feedback sensitivity whereas bubble tank results will be used to develop a primary multicomponent sea-spray aerosol flux parameterisation.
Arctic Research Programme
The Arctic Research Programme (ARP) is a £15m, five year (2010-2015) research programme funded by the Natural Environment Research Council (NERC). The aim of the programme is to improve our capability to predict changes in the Arctic, particularly over timescales of months to decades, including regional impacts and the potential for feedbacks on the global Earth System.
Background
The Arctic is a region of higher than average climate change and is predicted to remain so, the main evidences of this rapid climate change are the loss of summer sea ice, the thawing of permafrost (perennially frozen earth), melting of land ice, including ice sheets and glaciers, and the changing physical environment of Arctic ecosystems.
The Arctic represents a critical region for global environmental change and one where the UK has significant strategic interests. Understanding the drivers and feedbacks of this change, and predicting its scale and rate on timescales from months to decades, represents a major and urgent global scientific challenge of great societal importance.
The Arctic Programme will focus on four linked scientific objectives:
- Understanding and attributing the current rapid changes in the Arctic
- Quantifying processes leading to Arctic methane and carbon dioxide release
- Reducing uncertainty in Arctic climate and associated regional biogeochemistry predictions
- Assessing the likely risks of submarine hazards associated with rapid Arctic climate change
Deliverables from this programme will include:
- New or improved models for process studies
- Improved parameterisation of Arctic processes
- Improved capabilities for predicting changes in the Arctic
- Interpretation of current Arctic climate change and its implications for policy makers and Arctic communities
To achieve these objectives and deliverables, the Arctic Research Programme will aim to harness and co-ordinate UK scientific expertise and facilities in these areas, and link these to other international efforts. Fieldwork is expected to be highly interdisciplinary, potentially involving campaigns on land and ice stations, from ships, aircraft and satellites. Work on understanding longer term change in the Arctic will involve sediment cores and sampling on land. The use of a range of numerical models leading to improved predictability will be a vital element of this programme. Process-level understanding developed through observation-based work will be used to improve model components, and these will be used to test the impact of the processes on large-scale predictions. Clearly, integrated and innovative research across all science areas will be needed to achieve the programme's objectives.
Further details can be found on the ARP website.
Participants
34 different partner institutions are involved with the ARP. These are:
- University of Aberdeen
- Bangor University
- British Antarctic Survey
- British Geological Survey
- Centre for Ecology and Hydrology
- University of Cambridge
- University of Dundee
- Durham University
- University of East Anglia
- University of Leeds
- Loughborough University
- University of Manchester
- National Centre for Atmospheric Science
- National Oceanography Centre
- University of Nottingham
- Office of Naval Research
- University of Oxford
- University of Portsmouth
- University of Reading
- Royal Holloway, University of London
- University of Sheffield
- University of Southampton
- University of Stirling
- University of Sussex
- University College London
- University of Ulster
- University of York
- Natural Environment Research Council
- Department for Energy and Climate Change
- Department for Environment, Food and Rural Affairs
- Foreign and Commonwealth Office
- Met Office
- Royal Navy
- Living with Environmental Change
Research details
Overall 15 projects have been funded through ARP:
- ACCACIA- Aerosol Cloud Coupling and Climate Interactions in the Arctic
- APPOSITE- Arctic Predictability and Prediction on Seasonal to Inter-annual Timescales
- CYCLOPS- Carbon Cycling Linkages to Permafrost Systems
- HYDRA- Hydrological Controls on Carbon Cycling and Greenhouse Gas Budgets
- LAC- Lakes and the Arctic Carbon Cycle
- Landslide-Tsunami
- MAMM- Methane and other Greenhouse Gases in the Arctic: Measurements, Process Studies and Modelling
- SEATS- Submarine Estimates of Arctic Turbulence Spectra
- TEA-COSI- The Environment of the Arctic: Climate, Ocean and Sea-Ice
- Arctic methane hydrates and climate change
- Canadian Archipelago Oceanography
- Effects of a warming climate on the key organic carbon cycle processes in the Eurasian Arctic
- Is the Arctic methane budget changing?
- MIZ- The role to atmospheric, ice and oceanic interactions in the marginal ice zone
- MIZ-WAVE- Wave-ice interaction and the marginal ice zone
Data Activity or Cruise Information
Cruise
| Cruise Name | JR20130713 (JR288) |
| Departure Date | 2013-07-13 |
| Arrival Date | 2013-08-16 |
| Principal Scientist(s) | Lucy J Carpenter (University of York Department of Chemistry), Rosie Chance (University of York Department of Chemistry) |
| Ship | RRS James Clark Ross |
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 |
