Metadata Report for BODC Series Reference Number 2207567
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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Parameters |
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Problem Reports
The primary humidity readings appeared suspect, often saturating. The whole channel was deemed unfit for purpose and flagged.
RRS James Clark Ross JR17007 Meteorology Quality Control Report
Wind sensors
Screened relative Heading, wind direction, Air Temperature and true wind speed together.
There were some periods where spiking was observed as wind speed was seen to accelerate in tandem with the wind changing direction rapidly. In addition, wind shielding was observed at various points throughout the dataset. These occurrences were flagged accordingly.
There is a drop-out within the dataset when the ship experienced the full power failure on the 22/07/2018 from 22:40 to 23:36. This was automatically flagged by Edserplo.
Light Sensors
The light channels look good overall. There was occasional shading on both the port and the starboard of the PAR and TIR sensors.
There is a drop-out within the dataset when the ship experienced the full power failure on the 22/07/2018 from 22:40 to 23:36.
Air Temperature, Relative Humidity and Atmospheric Pressure
The primary humidity readings appeared suspect and the whole channel was deemed unfit for purpose. The remaining temperature, pressure and humidity readings are within their expected ranges. There is a drop-out within the dataset when the ship experienced a full power failure on the 22/07/2018 from 22:40 to 23:36 UTC. This was automatically flagged.
Data Access Policy
Open 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.
If the Information Provider does not provide a specific attribution statement, or if you are using Information from several Information Providers and multiple attributions are not practical in your product or application, you may consider using the following:
"Contains public sector information licensed under the Open Government Licence v1.0."
Narrative Documents
RRS James Clark Ross Cruise JR17007 Underway Document
Cruise details
| Dates | 10th July 2018 - 05th August 2018 (UTC) |
|---|---|
| Principal Scientific Officer | Martin Solan (University of Southampton School of Ocean and Earth Science) |
Kipp & Zonen Photosynthetically Active Radiation Quantum Sensor PQS1
The PQS1 is an atmospheric radiometer designed to measure incident radiation at photosynthetically active radiation (PAR) wavelengths. It incorporates a diffuser with an excellent directional (cosine) response and a silicon photodiode detector.
If used in field research applications, the PQS1 can be connected with the METEON handheld display unit, which also as data-logging capability. For permanent installations, it can be connected to the LOGBOX SD data logger.
Specifications
| Spectral range | 400 to 700 nm (± 4 nm) |
| Sensitivity | 4 to 10 µV µmol-1 m-2 s-1 |
| Response time | < 1 µs |
| Non linearity | < 1% (0 to 10000 µV µmol-1 m-2 s-1) |
| Temperature dependence | < -0.1% °C-1 |
| Sensitivity change per year | < 2% |
| Directional error | < 3% (up to 80° zenith angle) |
| Field of view | 180° |
| Operating temperature | -30 to 70°C |
| Relative humidity | 0 to 100 % RH |
A link to the PQS1 specification sheet can be found here: PQS1 Spec sheet
Kipp and Zonen SP Lite and SP Lite2 Silicon Pyranometer
An atmospheric pyranometer that measures solar radiation over the range 400-1100 nm by means of a silicon photo-diode detector mounted in a diffuser. The sensor measures the radiation received over the entire hemisphere and the diffuser's sensitivity is proportional to the cosine of the angle of incidence of the incoming radiation. The photodiode creates a voltage output that is proportional to the incoming radiation. The SP Lite2 supersedes the SP Lite and features an improved sensitivity and faster response time than its predecessor.
Specifications
| Specification | SP Lite | SP Lite2 |
|---|---|---|
| Spectral range | 400-1100 nm | 400-1100 nm |
| Sensitivity | 100 µV W-1 m-2 | 60 to 100 µV W-1 m-2 |
| Response time | < 1 s | < 500 ns |
| Maximum irradiance | 2000 W m-2 | 2000 W m-2 |
| Operating temperature | -30 to 70°C | -30 to 70°C |
| Temperature dependence | 0.15% °C-1 | 0.15% °C-1 |
Further details can be found in the manufacturer's specification sheets for the SP Lite and SP Lite2.
RRS James Clark Ross Cruise JR17007 Meteorology Instrument Description Document
The meteorological suite of sensors is located on the bow at 22 m height. The instruments used to collect this dataset are displayed in the table below.
| Manufacturer | Model | Main Function | Serial number | Last calibration date | Comments |
| Kipp and Zonen (sensor 1) | SPLite 2 | Total Incident Radiation (TIR) | 172882 | 02/02/2017 | Manufacturer calibration applied |
| Kipp and Zonen (sensor 2) | SPLite 2 | Total Incident Radiation (TIR) | 172883 | 02/02/2017 | Manufacturer calibration applied |
| Kipp and Zonen (sensor 1) | Proto Quantum Spectra 1 (PQS1) | Photosynthetically Active Radiation (PAR) | 160959 | 03/10/2016 | Manufacturer calibration applied |
| Kipp and Zonen (sensor 2) | Proto Quantum Spectra 1 (PQS1) | Photosynthetically Active Radiation (PAR) | 160960 | 03/10/2016 | Manufacturer calibration applied |
| Rotronic | MP402H-080300 | Air temperature and relative humidity (sensor 1) | 60743897 | 13/03/2017 | No calibration required |
| Rotronic | MP402H-080300 | Air temperature and relative humidity (sensor 2) | 61698922 | 13/03/2017 | No calibration required |
| Vaisala | PTB210 Class B (sensor 1) | Digital barometer | V1450002 | 10/04/2000 | No calibration required |
| Vaisala | PTB210 Class B (sensor 2) | Digital barometer | V1450003 | 10/04/2000 | No calibration required |
| Windobserver | 70 | Anemometer | - | - | No calibration required |
Rotronic Hygromet MP102H and MP402H temperature and humidity probes
This meteorological probe measures humidity and temperature with the plug-in HygroClip HC2-S3 sensor module, and can also be equipped with a signal conditioned Pt100 temperature probe.
The two models differ in that the MP102H produces a voltage output while the MP402H produces a current output. Other characteristics are common to both models.
The specification sheet can be accessed here Rotronic MP102H and MP402H.
Specifications
| Start up time | 3 s (typical) |
| Data refresh time | 1 s (typical) |
| Humidity range | 0 to 100% RH |
| Humidity accuracy | 0.8% RH |
| Temperature range | -40 to 80°C |
| Temperature accuracy | 0.1°C |
| Maximum air velocity ar probe | 20 m s-1 |
| User configurable limits | -999 to 9999 engineering units |
| HC2-S3 Probe material | Polycarbonate |
| Probe dust filter | Polyethylene |
Vaisala PTB210 Digital Barometer
The basic specifications for this pressure sensor are as follows:
- Manufacturer: Vaisala
- Type: Silicon capacitive sensor
- Model: PTB210
- Range: 900 - 1100 hPa
- Output: 0-5VDC
- Total Accuracy (20°C): ±0.30hPa
- Operating temperature: -40 to +60 deg C
- Weight: 110g
- Certification Ingress Protection: IP65
Further details can be found in the manufacturer's specification sheet.
RRS James Clark Ross Cruise JR17007 Meteorology Processing Procedures Document
Originator's Data Processing
Meterological data were measured from instruments located on the RRS James Clark Ross meterological mast. The data streams were logged every second to the SCS system and merged into comma separated file formats (.ACO). The instruments logged the meterological data to the oceanlogger and anemometer ACO files and the header information was stored in the corresponding .TPL files. The start and end times of the meterological files are shown in the table below.
| Filename | Content Discription | Format | Interval | Start date | Start Time | End date | End Time |
| oceanlogger.ACO |
| ASCII (.ACO) | ~5 sec | 05/07/2018 | 06:52:59 | 02/08/2018 | 12:50:29 |
| Anemometer.ACO | Relative wind speed and direction | ASCII (.ACO) | ~1 sec | 05/07/2018 | 06:52:55 | 04/08/2018 | 07:29:34 |
BODC Data Processing
The files were reformatted to BODC internal format using standard data banking procedures. All files were averaged to 60 second intervals. The following table shows how the variables within the files were mapped to appropriate BODC parameter codes.
| Originator's File | Originator's Parameter | Originator's Units | Description | BODC parameter | BODC Units | Comments and unit conversions |
| oceanlogger.ACO | baro1 | hPa | Pressure (measured variable) exerted by the atmosphere by barometer and expressed at measurement altitude | CAPHTU01 | mbar | Units are equivalent |
| oceanlogger.ACO | baro2 | hPa | Pressure (measured variable second sensor) exerted by the atmosphere by barometer and expressed at measurement altitude | CAPHTU02 | mbar | Units are equivalent |
| oceanlogger.ACO | airtemp1 | °C | Temperature (second sensor) of the atmosphere by dry bulb thermometer | CDTAZZ01 | °C | - |
| oceanlogger.ACO | airtemp2 | °C | Temperature (second sensor) of the atmosphere by dry bulb thermometer | CDTAZZ02 | °C | - |
| oceanlogger.ACO | humidity1 | % | Relative humidity (second sensor) of the atmosphere | CRELZZ01 | % | - |
| oceanlogger.ACO | humidity2 | % | Relative humidity (second sensor) of the atmosphere | CRELZZ02 | % | - |
| oceanlogger.ACO | par1 | µmol m-2 s-1 | Downwelling vector irradiance as photons (PAR wavelengths) in the atmosphere by cosine-collector radiometer | IRRDSV01 | µE m-2 s-1 | Units are equivalent |
| oceanlogger.ACO | par2 | µmol m-2 s-1 | Downwelling vector irradiance as photons (PAR wavelengths) in the atmosphere by cosine-collector radiometer | PARERXSD | µE m-2 s-1 | Units are equivalent |
| oceanlogger.ACO | tir1 | W m-2 | Downwelling vector irradiance as energy (solar (300-3000 nm) wavelengths) in the atmosphere by pyranometer | CSLRR101 | W m-2 | Dropped after transfer due to poor quality. |
| oceanlogger.ACO | tir2 | W m-2 | Downwelling vector irradiance as energy (solar (300-3000 nm) wavelengths) in the atmosphere by pyranometer | CSLRR102 | W m-2 | Dropped after transfer due to poor quality |
| anemometer.ACO | wind_dir | Degrees | Wind direction (relative to moving platform) in the atmosphere by in-situ anemometer | ERWDSS01 | Degrees | - |
| anemometer.ACO | wind_speed | m s-1 | Wind speed (relative to moving platform) in the atmosphere by in-situ anemometer | ERWSSS01 | m s-1 | - |
| - | - | - | Wind speed in the atmosphere by in-situ anemometer | EWSBSS01 | m s-1 | Channel derived using BODC Matlab routine 'wincor' |
| - | - | - | Wind direction in the atmosphere by in-situ anemometer | EWDASS01 | Degrees true | Channel derived using BODC Matlab routine 'wincor' |
Wind sensors
The BODC Matlab procedure 'wincor' was run using the relative wind speed and direction and ship's north-south and east-west velocities, with the vane set to 0 degrees at the bow. This program generated the absolute wind speed and direction.
Calibrations
No calibrations were applied to the meteorological data.
Project Information
Changing Arctic Ocean: Implications for marine biology and biogeochemistry
Changing Arctic Ocean (CAO) is a £16 million, five year (2017-2022) research programme initially funded by the Natural Environment Research Council (NERC). The aim of the CAO programme is to understand how change in the physical environment (ice and ocean) will affect the large-scale ecosystem structure and biogeochemical functioning of the Arctic Ocean, the potential major impacts and provide projections for future ecosystem services. In July 2018, additional projects were added to the programme that were jointly funded by NERC and the German Federal Ministry of Education and Research.
Background
The Arctic Ocean is responding to global climate change in ways that are not yet fully understood and in some cases, not yet identified. The impacts of change in the Arctic are global in range and international in importance. To achieve the aim, the programme has two key research challenges:
- To develop quantified understanding of the structure and functioning of Arctic ecosystems.
- To understand the sensitivity of Arctic ecosystem structure, functioning and services to multiple stressors and the development of projections of the impacts of change.
The decision to fund the CAO project was both scientific and political and is the second largest research programme funded by NERC.
The programme involves 33 organisations, the majority of which are research institutions in the UK and Germany, and over 170 scientists. The programme consists of four large projects with an additional 12 research projects added in July 2018.
Further information can be found on the Changing Arctic Ocean website.
Participants
There are 33 organisations involved in the Changing Arctic Ocean project, these are:
- Alfred Wegener Institut (AWI)
- Bangor University
- British Antarctic Survey (BAS)
- Centre for Environment, Fisheries and Aquaculture Science (CEFAS)
- Durham University
- GEOMAR
- Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research
- Lancaster University
- Marine Biological Association (MBA)
- Max Planck Institute for the Science of Human History
- National Oceanography Centre (NOC)
- Newcastle University
- Northumbria University
- Ocean Atmosphere Systems GmbH
- Plymouth Marine Laboratory (PML)
- Scottish Association for Marine Science (SAMS)
- Scottish Universities Environmental Research Centre (SUERC)
- Université Libre de Bruxelles
- University College London (UCL)
- University of Bristol
- University of East Anglia (UEA)
- University of Edinburgh
- University of Glasgow
- University of Huddersfield
- University of Leeds
- University of Liverpool
- University of Manchester
- University of Oldenburg
- University of Oxford
- University of Southampton
- University of St Andrews
- University of Stirling
- University of Strathclyde
In addition to the core organisation, there are a number of international collaborators.
Research Details
The four large projects funded by NERC are:
- Arctic Productivity in the seasonal Ice Zone (Arctic PRIZE)
- Can we detect changes in Arctic ecosystems? (ARISE)
- The Changing Arctic Ocean Seafloor (ChAOS) - How changing sea ice conditions impact biological communities, biogeochemical processes and ecosystems
- Mechanistic understanding of the role of diatoms in the success of the Arctic Calanus complex and implications for a warmer Arctic (DIAPOD)
The additional 12 projects added in July 2018 funded jointly by NERC and the German Federal Ministry of Education and Research are:
- Advective Pathways of nutrients and key Ecological substances in the Arctic (APEAR)
- How will changing freshwater export and terrestrial permafrost thaw influence the Arctic Ocean? (CACOON)
- Chronobiology of changing Arctic Sea Ecosystems (CHASE)
- Potential benefits and risks of borealisation for fish stocks and ecosystems in a changing Arctic Ocean (Coldfish)
- Diatom Autecological Responses with Changes To Ice Cover (Diatom-ARCTIC)
- Ecosystem functions controlled by sea ice and light in a changing Arctic (Eco-Light)
- Effects of ice stressors and pollutants on the Arctic marine cryosphere (EISPAC)
- Linking Oceanography and Multi-specific, spatially-Variable Interactions of seabirds and their prey in the Arctic (LOMVIA)
- Understanding the links between pelagic microbial ecosystems and organic matter cycling in the changing Arctic (Micro-ARC)
- Microbes to Megafauna Modelling of Arctic Seas (MiMeMo)
- Primary productivity driven by escalating Arctic nutrient fluxes? (PEANUTS)
- Pathways and emissions of climate-relevant trace gases in a changing Arctic Ocean (PETRA)
Fieldwork and Data Collection
The programme consists of seven core cruises that survey areas in the Barents Sea and the Fram Strait on board the NERC research vessel RRS James Clark Ross. Measurements will include temperature, salinity, dissolved oxygen, dissolved inorganic carbon, total alkalinity, inorganic nutrients, oxygen and carbon isotopes and underway meteorological and surface ocean observations. In addition to ship based cruise datasets gliders, moorings and animal tags are part of the fieldwork. Further data are collected from model runs.
Data Activity or Cruise Information
Cruise
| Cruise Name | JR17007 |
| Departure Date | 2018-07-10 |
| Arrival Date | 2018-08-05 |
| Principal Scientist(s) | Martin Solan (University of Southampton School of Ocean and Earth Science) |
| 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 |
