Metadata Report for BODC Series Reference Number 2014598
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
RRS James Clark Ross Cruise JR18007 Meteorology Data Quality Document
Humidity
An offset between the two humidity sensors was identified starting at 03:55 on 14/08/2019. Sensors do not appear to stabilise and return to normal until 13:39 the same day. A similar offset occured between 18:29 and 20:14 on 25/08/2019. All data during these periods were flagged.
Light sensorsThere is a sensor dropout in the total incident radiation (CSLRR101, CSLRR102) and photosynthetically active radiation (IRRDSV01, PARERXSD) channels between 08:42 and 12:31 on 09/08/2019. Data were flagged accordingly. BODC removed restricted observed environmental data between 05:01 and 11:59 on 06/08/2019.
Data Access Policy
Open Data supplied by Natural Environment Research Council (NERC)
You must always use the following attribution statement to acknowledge the source of the information: "Contains data supplied by Natural Environment Research Council."
Narrative Documents
Gill Windobserver 70 (ultrasonic) anemometer
A solid state, heated ultrasonic anemometer. Designed for use within the aviation industry and for more extreme weather conditions. It measures the times taken for an ultrasonic pulse of sound to travel from the North transducer to the South transducer, and compares it with the time for a pulse to travel from S to N transducer. Likewise times are compared between West and East, and E and W transducer. The wind speed and direction (and the speed of sound) can then be calculated from the differences in the times of flight on each axis. This calculation is independent of factors such as temperature. It uses 150 Watts of electrical heating in the anemometer head to prevent icing. Wind speed accuracy is +/-2% at 12 m/s. Wind direction accuracy is +/-2 degrees at 12 m/s.
For more information, please see this document: https://www.bodc.ac.uk/data/documents/nodb/pdf/Gill_WindObserver70_2017.pdf
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 JR18007 Meteorology Instrument Description Document
The meteorological suite of sensors is located on the bow between 20-22 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 | Unknown | No calibration required |
Kipp and Zonen (sensor 2) | SPLite 2 | Total Incident Radiation (TIR) | 172883 | Unknown | No calibration required |
Kipp and Zonen (sensor 1) | Proto Quantum Spectra 1 (PQS1) | Photosynthetically Active Radiation (PAR) | 160959 | Unknown | No calibration required |
Kipp and Zonen (sensor 2) | Proto Quantum Spectra 1 (PQS1) | Photosynthetically Active Radiation (PAR) | 160960 | Unknown | No calibration required |
Rotronic | MP402H-080300 | Air temperature and relative humidity (sensor 1) | 61019333 | Unknown | No calibration required |
Rotronic | MP402H-080300 | Air temperature and relative humidity (sensor 2) | 61019251 | Unknown | No calibration required |
Vaisala | PTB210 Class B (sensor 1) | Digital barometer | V1450002 | Unknown | No calibration required |
Vaisala | PTB210 Class B (sensor 2) | Digital barometer | V1450003 | Unknown | 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 JR18007 meteorology data processing procedures
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.
Files delivered to BODC
Filename | Content description | Format | Interval | Start date/time (UTC) | End date/time (UTC) | Comments |
anemometer.ACO | Relative wind speed and direction | SCS | 1 Hz | 2019/08/05 07:19:13 | 2019/08/29 12:01:01 | - |
oceanlogger.ACO | Air temperature, humidity, pressure, total incident radiation, and photosynthetically active radiation | SCS | 5 Hz | 2019/08/05 07:19:14 | 2019/08/29 12:09:50 | - |
BODC Data Processing
The data were reformatted to BODC internal format using standard banking procedures. Data were averaged at 60 second intervals. The following tables show how variables within the files were mapped to appropriate BODC parameter codes:
anemometer.ACO
Originator's variables | Originator's units | Description | BODC code | BODC unit | Conversion | Comments |
wind_dir | degrees | Relative wind direction (from) | ERWDSS01 | degrees | - | - |
wind_speed | m/s | Relative wind speed | ERWSSS01 | m/s | - | - |
oceanlogger.ACO
Originator's variables | Originator's units | Description | BODC code | BODC unit | Conversion | Comments |
airtemp1 | °C | Air temperature sensor 1 | CDTAZZ01 | °C | - | - |
airtemp2 | °C | Air temperature sensor 2 | CDTAZZ02 | °C | - | - |
baro1 | hPa | Air pressure sensor 1 | CAPHTU01 | mbar | Units equivalent | - |
baro2 | hPa | Air pressure sensor 2 | CAPHTU02 | mbar | Units equivalent | - |
humidity1 | %RH | Relative humidity sensor 1 | CRELZZ01 | % | - | - |
humidity2 | %RH | Relative humidity sensor 2 | CRELZZ02 | % | - | - |
par1 | Umol/S.m2 | Photosynthetically active radiation (PAR) sensor 1 | IRRDSV01 | uE/m^2/s | Units equivalent | - |
par2 | Umol/S.m2 | Photosynthetically active radiation (PAR) sensor 2 | PARERXSD | uE/m^2/s | Units equivalent | - |
tir1 | W/m2 | Total incident radiation (TIR) sensor 1 | CSLRR101 | W/m2 | - | - |
tir2 | W/m2 | Total incident radiation (TIR) sensor 2 | CSLRR102 | W/m2 | - | - |
All data expressed at measurement altitude.
Manufacturer's Calibrations
No manufacturer's calibrations were applied to the data at BODC.
Processing
ScreeningAll the reformatted data were visualised using the in-house EDSERPLO software. Suspect data were marked by adding an appropriate quality control flag.
Absolute wind speed and direction
Relative wind speed and direction were corrected to absolute winds using the ship's heading, speed over ground, course over ground and anemometer orientation on the bow in line with the SAMOS method.
Field Calibrations
No further calibration against independent variables were applied to these data at BODC.
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 | JR18007 |
Departure Date | 2019-08-04 |
Arrival Date | 2019-09-06 |
Principal Scientist(s) | David Pond (University of Stirling, Institute of Aquaculture) |
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 |