Metadata Report for BODC Series Reference Number 1981550
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
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
SeaBird Digital Oceanographic Thermometer SBE38
The SBE38 is an ultra-stable thermistor that can be integrated as a remote temperature sensor with an SBE21 Thermosalinograph or an SBE 45 Micro TSG, or as a secondary temperature sensor with an SBE 16 plus, 16plus-IM, 16plus V2, 16plus-IM V2 or 19plus V2 SEACAT CTD.
Temperature is determined by applying an AC excitation to reference resistances and an ultra-stable aged thermistor. The reference resistor is a hermetically sealed VISHAY. AC excitation and ratiometric comparison using a common processing channel removes measurement errors due to parasitic thermocouples, offset voltages, leakage currents and gain errors.
The SBE38 can operate in polled sampling, where it takes one sample and transmits the data, or in continuous sampling.
Specifications
| Depth rating | up to 10500 m |
| Temperature range | -5 to 35°C |
| Initial accuracy | ± 0.001°C |
| Resolution | 0.00025°C |
| Stability | 0.001°C in 6 months |
| Response time | 500 ms |
| Self-heating error | < 200 µK |
Further details can be found in the manufacturer's specification sheet.
WET Labs WETStar Fluorometers
WET Labs WETStar fluorometers are miniature flow-through fluorometers, designed to measure relative concentrations of chlorophyll, CDOM, uranine, rhodamineWT dye, or phycoerythrin pigment in a sample of water. The sample is pumped through a quartz tube, and excited by a light source tuned to the fluorescence characteristics of the object substance. A photodiode detector measures the portion of the excitation energy that is emitted as fluorescence.
Specifications
By model:
| Chlorophyll WETStar | CDOM WETStar | Uranine WETStar | Rhodamine WETStar | Phycoerythrin WETStar | |
|---|---|---|---|---|---|
| Excitation wavelength | 460 nm | 370 nm | 485 nm | 470 nm | 525 nm |
| Emission wavelength | 695 nm | 460 nm | 530 nm | 590 nm | 575 nm |
| Sensitivity | 0.03 µg l-1 | 0.100 ppb QSD | 1 µg l-1 | - | - |
| Range | 0.03-75 µg l-1 | 0-100 ppb; 0-250 ppb | 0-4000 µg l-1 | - | - |
All models:
| Temperature range | 0-30°C |
|---|---|
| Depth rating | 600 m |
| Response time | 0.17 s analogue; 0.125 s digital |
| Output | 0-5 VDC analogue; 0-4095 counts digital |
Further details can be found in the manufacturer's specification sheet, and in the instrument 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.
Litre Meter flow meter
A flow meter used to monitor water flow rates for pumped systems such as ships' continuous seawater supplies.
RRS James Clark Ross Cruise JR17005 Surface Hydrography Instrument Description Document
The sea surface hydrographical suite of sensors was fed by the pumped-seawater, non-toxic supply. The seawater intake was located at 6.5 m below the sea surface. The following surface hydrology sensors were fitted:
| Manufacturer | Model | Main Function | Serial number | Last calibration date | Comments |
| Sea Bird Electronics | SBE45 | Thermosalinograph | 4524698-0018 | Unknown | Manufacturer calibration applied |
| Sea Bird Electronics | SBE38 | Sea surface temperature (sensor 1) | 3862856-0599 | 11/08/2017 | Manufacturer calibration applied |
| Sea Bird Electronics | SBE38 | Sea surface temperature (sensor 2) | 3862856-0601 | 11/08/2017 | Manufacturer calibration applied |
| WetLabs | WetStar | Chlorophyll fluorescence | 1498 | 17/01/2017 | Manufacturer calibration applied |
| Wet Labs | C-Star | Transmissometer | CST-846DR | 22/06/2017 | Manufacturer calibration applied |
SeaBird MicroTSG Thermosalinograph SBE 45
The SBE45 MicroTSG is an externally powered instrument designed for shipboard measurement of temperature and conductivity of pumped near-surface water samples. The instrument can also compute salinity and sound velocity internally.
The MicroTSG comprises a platinum-electrode glass conductivity cell and a stable, pressure-protected thermistor temperature sensor. It also contains an RS-232 port for appending the output of a remote temperature sensor, allowing for direct measurement of sea surface temperature.
The instrument can operate in Polled, Autonomous and Serial Line Sync sampling modes:
- Polled sampling: the instrument takes one sample on command
- Autonomous sampling: the instrument samples at preprogrammed intervals and does not enter quiescence (sleep) state between samples
- Serial Line Sync: a pulse on the serial line causes the instrument to wake up, sample and re-enter quiescent state automatically
Specifications
| Conductivity | Temperature | Salinity | |
|---|---|---|---|
| Range | 0 to 7 Sm-1 | -5 to 35°C | |
| Initial accuracy | 0.0003 Sm-1 | 0.002°C | 0.005 (typical) |
| Resolution | 0.00001 Sm-1 | 0.0001°C | 0.0002 (typical) |
| Typical stability (per month) | 0.0003 Sm-1 | 0.0002°C | 0.003 (typical) |
Further details can be found in the manufacturer's specification sheet.
RRS James Clark Ross Cruise JR17005 Surface Hydrography Processing Procedures Document
Originator's Data Processing
The sea surface hydrography measurements were performed by a Sea Bird electronics thermosalinograph in the ship's flow through system and by a temperature sensor located near the flow through intake, at the hull. The depth of the flow through intake was 6.5 m. The data streams were logged every second to the SCS system and merged into a comma separated file format, and logged to the Oceanlogger.ACO file. The header information was stored in the associated .TPL files.
Sea surface hydrography was then further processed by the originator by filtering noise and erroneous measurements, and then applying per minute medians to generate smoothed data and smaller file sizes. Further information on processing can be found in the originator's supporting document.
Calibrations
Field Calibrations
Salinity
The underway salinity was calibrated using 37 samples taken from the underway system and analysed on a Guildline Autosal and a further 16 salinity samples taken from niskin bottles fired within the top 10 m of the water column. Readings from the underway sensor at the times of bottle samples were extracted and the offsets calculated. Offsets greater than 0.1 were immediately removed. The mean offset was 0.0074 psu (std of 0.0082). Offsets more than 1.5 standard deviations above and below the mean were then removed. Of the remaining pairs a significant (pval = 6 e-4) trend over time was found. The following regression was subsequently used to calculate the offset required to correct the underway salinity time series.
offset = -0.054 + (daynumber x 4.04e-4)
After applying this time varying offset the mean offset was reduced to 0.0012 psu.
| Filename | Content Description | Format | Interval | Start date | Start Time | End date | End Time |
| JR17005_underway_calibrated.mat | Sea surface hydrography | .MAT | 60 sec | 13-05-2018 | 00:00:00 | 07-06-2018 | 06:43 |
| oceanlogger.ACO | Flow metre | SCS | 1 sec | 08-05-2018 | 10:01:24 | 08-06-2018 | 06:23:39 |
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 |
| JR17005_underway_calibrated.mat | chlor | mg/l | Chlorophyll concentration | CPHLUMTF | mg/m^3 | Units equivalent |
| JR17005_underway_calibrated.mat | Conductivity | S/m | Conductivity | CNDCSG01 | S/m | - |
| JR17005_underway_calibrated.mat | dd | - | Matlab serial date | - | - | - |
| JR17005_underway_calibrated.mat | lat | degrees | Latitude | ALATGP01 | degrees | - |
| JR17005_underway_calibrated.mat | lon | degrees | Longitude | ALONGP01 | degrees | - |
| JR17005_underway_calibrated.mat | salinity | psu | Practical salinity (calibrated against underway and CTD salt samples) | PSALSG01 | psu | - |
| JR17005_underway_calibrated.mat | tstemp | celsius | TSG housing temperature | TMESSG01 | celsius | - |
| JR17005_underway_calibrated.mat | sstemp1 | celsius | Sea surface temperature | TEMPHU01 | celsius | - |
| JR17005_underway_calibrated.mat | sstemp2 | celsius | Sea surface temperature | TEMPSU01 | celsius | - |
| JR17005_underway_calibrated.mat | trans | 0<Tr<1 | Beam transmittance | POPTDR01 | % | X 100 |
| oceanlogger.ACO | flowrate | l/min | Flow rate | INFLTF01 | l/min | - |
Calibrations
Field Calibrations
No calibration against independent variables were applied to these data.
Manufacturers Calibrations
Transmissometer
Beam transmission ( beamtrans ) was converted to beam attenuation ( atten ) as follows:
atten [per m] = (-1/ pathlength ) ln(beamtrans /100)
where pathlength = 0.25 m.
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.
Can we detect changes in Arctic ecosystems? (ARISE)
The ARISE project is a £2.1 million, three year (2017-2020) research programme funded by the Natural Environment Research Council (NERC) as part of the Changing Arctic Ocean (CAO) programme. The ARISE project sets out to understand Arctic ecosystem responses to rapid environmental change by identifying how Arctic food webs are changing now and in the recent past.
Rapid environmental change is affecting Arctic ecosystems as the Arctic Ocean is adjusting to new, warmer conditions. It is essential to understand the ecosystem response if the projections of future impacts are to be reliable as ocean ecosystems provide key services, such as control of climate and nutrient cycling. This response can be gauged by establishing how Arctic food webs are changing.
Further information can be found on the Changing Arctic Ocean ARISE webpage.
Participants
There are seven organisations involved in the ARISE project, these are:
- University of Liverpool
- National Oceanography Centre (NOC)
- University of Manchester
- Plymouth Marine Laboratory (PML)
- University of St Andrews
- University of Edinburgh
- Sir Alister Hardy Foundation for Ocean Science (SAHFOS)
- Scottish Association for Marine Science (SAMS)
In addition to these core organisations, there are 22 international collaborators involved in the project. This international collaboration may also result in the exchange of data with external partners.
Research Details
The ARISE project aims to understand Arctic ecosystem responses to rapid environmental change using a new set of tools that are able to detect pan-Arctic modifications to ecosystems and evaluate past and future change across a diverse set of Arctic environments whilst avoiding studies at a single site. ARISE combines pan-Arctic historical and contemporary observations with traditional isotope and novel biomarkers as food web tracers to gain a complete understanding of how environmental change affects both the base of the food web and two Arctic seal species, considered indicator species.
The project has three hypotheses that will be tested by three objectives designed around a stepwise accumulation of understanding. A fourth objective links the findings of the project to the conservation and management of seals in the Arctic.
Objectives
- Gain observational constraints on how environmental variability affects the isotope composition of the base of the food web, the isoscape.
- Combine data on seal foraging and migration to understand how variability in the isoscape is reflected in biomarker signals in seals.
- Use historical observations and link the new understanding to ocean and seal population models to provide a broad picture of factors driving past and contemporary Arctic ecosystem change.
- Quantitatively assess the conservation and management implications of the results, with strong links to stakeholders and policy makers.
Fieldwork and Data Collection
The project participates in a number of cruises during 2017 and 2018, primarily onboard the NERC research vessel RRS James Clark Ross. The aim of the data collection is to collect samples for δ15N of nitrate, particulate material and zooplankton to investigate the variability in the isoscape. The datasets collected include: CTD profiles; underway navigation, surface hydrography and meteorology; 13C-DIC, 15N, 18O-nitrate and 15N-DON samples; POM samples; zooplankton nets; stable nitrogen and carbon isotopes water samples; table nitrogen and carbon isotopes biomarkers particle samples; table nitrogen and carbon isotopes biomarker content and molecular data from zooplankton; seal tags; biomarker samples from seal tissue; 15N and 13C samples from seal teeth and Continuous Plankton Recorder zooplankton data from Arctic route. Telemetry is also used to track harp seals during the project.
Data Activity or Cruise Information
Cruise
| Cruise Name | JR17005 |
| Departure Date | 2018-05-08 |
| Arrival Date | 2018-06-08 |
| 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 |
