Metadata Report for BODC Series Reference Number 2022617
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
Data Description |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data Identifiers |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Time Co-ordinates(UT) |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Spatial Co-ordinates | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Parameters |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Problem Reports
No Problem Report Found in the Database
JR18006 CTD Data Quality Report
Screening and Quality Control
During BODC quality control, data were screened using in house visualisation software and any obvious outliers and spikes were looked at in closer detail and flagged if necessary.
POPTDR01
M flags were applied to several series where anomalous data were found, especially if spikes were identified but no similar features were identified in the Chlorophyll or Attenuation data.
OXYOCPVL
M flags were applied to several series where anomalous data were found, especially if spikes were identified but no similar features were identified in the Temperature, Chlorophyll or Attenuation data. No flags were applied to the associated DOXYSC01 and OXYSZZ01 as the oxygen data were calibrated prior to being submitted to BODC.
AHSFZZ01
The altimeter only collects good data within 100 m of the seabed and all instances where values are constant or not decreasing with depth have been flagged M.
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
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 JR18006 CTD
CTD Unit and Auxiliary Sensors
The CTD unit comprised a Sea-Bird Electronics (SBE) 9plus underwater unit, an SBE 11 plus deck unit, a 24-way SBE 32 carousel and 24 TMF Water Samplers; all of which were mounted on a stainless steel 24-way CTD frame. Listed below are the instruments attached to the CTD frame.
For the first three CTD casts, 20 L niskin bottles were used without issue. However, from cast 4 onwards, significant problems with bottle leaks were encountered. It was concluded that this was due to a drop in water temperature after cast 3, which affected the niskin bottle O-rings. A decision was made to supplement half of the 20 L bottles with 12 L bottles, whose O-rings were made of a different material which reduced the occurrence of leaks. The 12 L bottles were used for Oxygen and DMS samples, and the 20 L bottles were used for bulk water collections.
For further information, see the cruise report.
Sensor unit | Model | Serial number | Full specification | Calibration dates (YYYY/MM/DD) |
---|---|---|---|---|
CTD underwater unit | SBE 9plus | 0541 | SBE 911plus | - |
CTD deck unit | SBE 11plus | 0548 | SBE 911plus | - |
Pressure sensor | Paroscientific Digiquartz | 0541 | Paroscientific Digiquartz | 11-Apr-18 |
Temperature sensor | SBE 3P | 5043 | SBE 03P | 11-Apr-18 |
Temperature sensor | SBE 3P | 4874 | SBE 03P | 11-Apr-18 |
Conductivity sensor | SBE 4C | 1913 | SBE 04C | 07-Jun-18 |
Conductivity sensor | SBE 4C | 3491 | SBE 04C | 19-Apr-18 |
Dissolved oxygen sensor | SBE 43 | 0242 | SBE 43 | 08-May-18 |
Altimeter | Tritech PA-200 | 163162 | Tritech PA-200 | 07-May-19 |
Irradiance sensor | Biospherical QCP2350 PAR | 70688 | Biospherical QCP PAR sensor | 22-May-19 |
Fluorometer | Chelsea MKIII Aquatracka | 12-8513-001 | Chelsea MKII Aquatracka | 21-May-18 |
Transmissometer | WetLabs C-Star - 25 cm path | CST-527DR | C-Star Transmissometer | 31-Jul-18 |
Temperature sensor (Independent) | SBE 35 | 0051 | SBE 35 | 08-Jun-16 |
LADCP- Master (downward looking) | RDI Workhorse 300 kHz | 14443 | LADCP | |
LADCP- Slave (upward looking) | RDI Workhorse 300 kHz | 15060 | LADCP |
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.
Chelsea Technologies Group Aquatracka MKIII fluorometer
The Chelsea Technologies Group Aquatracka MKIII is a logarithmic response fluorometer. Filters are available to enable the instrument to measure chlorophyll, rhodamine, fluorescein and turbidity.
It uses a pulsed (5.5 Hz) xenon light source discharging along two signal paths to eliminate variations in the flashlamp intensity. The reference path measures the intensity of the light source whilst the signal path measures the intensity of the light emitted from the specimen under test. The reference signal and the emitted light signals are then applied to a ratiometric circuit. In this circuit, the ratio of returned signal to reference signal is computed and scaled logarithmically to achieve a wide dynamic range. The logarithmic conversion accuracy is maintained at better than one percent of the reading over the full output range of the instrument.
Two variants of the instrument are available, both manufactured in titanium, capable of operating in depths from shallow water down to 2000 m and 6000 m respectively. The optical characteristics of the instrument in its different detection modes are visible below:
Excitation | Chlorophyll a | Rhodamine | Fluorescein | Turbidity |
---|---|---|---|---|
Wavelength (nm) | 430 | 500 | 485 | 440* |
Bandwidth (nm) | 105 | 70 | 22 | 80* |
Emission | Chlorophyll a | Rhodamine | Fluorescein | Turbidity |
Wavelength (nm) | 685 | 590 | 530 | 440* |
Bandwidth (nm) | 30 | 45 | 30 | 80* |
* The wavelengths for the turbidity filters are customer selectable but must be in the range 400 to 700 nm. The same wavelength is used in the excitation path and the emission path.
The instrument measures chlorophyll a, rhodamine and fluorescein with a concentration range of 0.01 µg l-1 to 100 µg l-1. The concentration range for turbidity is 0.01 to 100 FTU (other wavelengths are available on request).
The instrument accuracy is ± 0.02 µg l-1 (or ± 3% of the reading, whichever is greater) for chlorophyll a, rhodamine and fluorescein. The accuracy for turbidity, over a 0 - 10 FTU range, is ± 0.02 FTU (or ± 3% of the reading, whichever is greater).
Further details are available from the Aquatracka MKIII specification sheet.
Biospherical Instruments QCP-2350 [underwater] PAR sensor
A cosine-corrected PAR quantum irradiance profiling sensor. For use in underwater applications with 24 bit ADC systems. Measures light available for photosynthesis on a flat surface. Operation is by a single channel compressed analog output voltage that is proportional to the log of incident PAR (400-700 nm) irradiance. The sensor is designed for operation in waters to depths of up to 2,000 m (standard) or 6,800 m (optional).
For more information, please see this document: https://www.bodc.ac.uk/data/documents/nodb/pdf/Biospherical_QCP2300_QCP2350_Apr2014.pdf
Tritech Digital Precision Altimeter PA200
This altimeter is a sonar ranging device that gives the height above the sea bed when mounted vertically. When mounted in any other attitude the sensor provides a subsea distance. It can be configured to operate on its own or under control from an external unit and can be supplied with simultaneous analogue and digital outputs, allowing them to interface to PC devices, data loggers, telemetry systems and multiplexers.
These instruments can be supplied with different housings, stainless steel, plastic and aluminum, which will limit the depth rating. There are three models available: the PA200-20S, PA200-10L and the PA500-6S, whose transducer options differ slightly.
Specifications
Transducer options | PA200-20S | P200-10L | PA500-6S |
Frequency (kHz) | 200 | 200 | 500 |
Beamwidth (°) | 20 Conical | 10 included conical beam | 6 Conical |
Operating range | 1 to 100 m 0.7 to 50 m | - | 0.3 to 50 m 0.1 to 10 m |
Common specifications are presented below
Digital resolution | 1 mm |
Analogue resolution | 0.25% of range |
Depth rating | 700 , 2000, 4000 and 6800 m |
Operating temperature | -10 to 40°C |
Further details can be found in the manufacturer's specification sheet.
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.
JR18006 BODC CTD Data Processing
Data Processing
Processed and calibrated CTD data from Changing Arctic Ocean cruise JR18006 were submitted to BODC in csv format. The files were transferred to BODC internal format using standard BODC procedures. The variables provided in the files were mapped to BODC parameter codes as follows:
Originator's Variable | Originator's Units | BODC Parameter Code | BODC Units | Comment |
---|---|---|---|---|
CTDpres | db | PRESPR01 | db | - |
CTDdepth | m | DEPHPR01 | m | This channel was dropped as can be derived from Pressure. |
CTDtemp1 | °C | TEMPST01 | °C | - |
CTDtemp2 | °C | TEMPST02 | °C | The channel was transferred and then dropped following BODC processing as there was no difference in the quality of the data from the first or second sensor. |
CTDsal1_cal_despiked | PSU | PSALCC01 | Dimensionless | - |
CTDsal2_cal_despiked | PSU | PSALCC02 | Dimensionless | The channel was transferred and then dropped following BODC processing as there was no difference in the quality of the data from the first or second sensor. |
CTDcond1_cal | mS cm-1 | CNDCST01 | S m-1 | Conversion of /10 applied. |
CTDcond2_cal | mS cm-1 | CNDCST02 | S m-1 | Conversion of /10 applied. The channel was transferred and then dropped following BODC processing as there was no difference in the quality of the data from the first or second sensor. |
CTDfluor | µg L-1 | CPHLPR01 | mg m-3 | Equivalent units. |
CTDatt | m-1 | ATTNMR01 | m-1 | - |
CTDxmiss | % | POPTDR01 | % | |
CTDpar | µE cm-2 s -1 | IRRDUV01 | µE cm-2 s -1 | |
CTDaltim | m | AHSFZZ01 | m | |
CTDoxy1_umoll_cal | µmol L-1 | DOXYSC01 | µmol L-1 | |
CTDoxy1_volts | V | OXYOCPVL | V | |
CTDsound_vel1_cal_despiked | m s-1 | SVELCV01 | m s-1 | |
CTDsound_vel2_cal_despiked | m s-1 | SVELCT01 | m s-1 | The channel was transferred and then dropped following BODC processing as there was no difference in the quality of the data from the first or second sensor. |
Screening
Post transfer analysis and crosschecks were applied according to BODC procedures. This involved the screening of data using BODC's in house visualisation software where any suspect data were flagged but not removed.
JR18006 Originator CTD Data Processing
Sampling Strategy
A total of 15 CTD casts were performed during Changing Arctic Ocean cruise JR18006, which includes two test casts.
Data Processing
CTD data processing procedures were kept as similar as possible to those on previous NERC Changing Arctic Ocean cruises, specifically developed by Jo Hopkins and Estelle Dumont on JR16006 and JR17006. Processing was carried out using Seabird Data Processing software version 7.26.7 and Matlab software version R2017b.
Data were initially converted in Seabird to output pressure, oxygen, temperature, conductivity and depth. These data were run through Matlab routines onboard to check what values to use for sensor alignment, then a batch file was set up to run various modules through Seabird to process the data.
It should be noted that the data processed onboard during the cruise have since been re-processed as an error was found in the CT alignment used originally for sensor 1. In the AlignCTD module, conductivity sensor 1 was advanced by -0.041666s (1/24) and sensor 2 was left with and advance of +0.0625s.
Data were then processed further in Matlab (R2017b) using the above-mentioned CAO processing routines developed by Jo Hopkins and Estelle Dumont as used on JR16006 and JR17006. The following steps were taken:
1. MATLAB - Reading and plotting of *.cnv files produced by Seabird modules.
- Inputs: JR18006_NNN.cnv, JR18006_NNN_2hz.cnv, JR18006_CTDcnv_24Hz_driver.csv, JR18006_CTDcnv_2Hz_driver.csv
- Outputs: JR18006_NNN.mat, JR18006_NNN_2hz.mat
- Driver files for JR18006 set up with variable lists as per cruise setup.
2. MATLAB - Creation of bottle files.
- Inputs: JR18006_NNN.cnv, JR18006_NNN.bl
- Outputs: JR18006_NNN_BTL.mat, JR18006_NNN_BTL.csv
- Data extracted according to scan numbers from bl files. Averages, standard deviations, minimum and maximum values over each 5 second window were saved. SBE35 temperature data added if present.
3. MATLAB - Manual removal of surface soak and post-cast data
- Inputs: JR18006_NNN_2hz.mat, JR18006_NNN.mat
- Outputs: JR18006_castcrop_times.mat, JR18006_NNN_cropped.mat
- Plots of pressure, pump status and oxygen were produced, and the start and end of each cast manually selected. Start and end times were saved in a master file and used to crop the 24 Hz data.
4. MATLAB - Splitting of upcast and downcast data
- Input: JR18006_NNN_cropped.mat
- Outputs: JR18006_NNN_cropped_down.mat, JR18006_NNN_cropped_up.mat
- The 24Hz data was split into up and down casts using the maximum pressure extracted from the data.
5. MATLAB - Manual removal of temperature spikes and anomalies
- Input: JR18006_NNN_cropped_down.mat
- Output: JR18006_NNN_cropped_down_despiked.mat
- Large outliers removed. Primary and secondary temperature and salinity, Oxygen, fluorometer and PAR data were plotted. A graphical user interface within the Matlab toolbox was used to manually flag bad temperature data. Derived parameters, salinity and density were also flagged for those indices, along with oxygen as the measurement would have been made from the same (usually displaced) parcel of water. Salinity spikes that were not flagged by this process were flagged manually.
6. MATLAB - Averaging into 1db bins
- Input: JR18006_NNN_cropped_down_despiked.mat
- Output: JR18006_NNN_cal_1dbd.mat, JR18006_NNN_cropped_up.mat
7. MATLAB - Application of Conductivity and Oxygen calibration
Calibrations for oxygen and conductivity were calculated from bottle samples and entered in to the cruise_setup file.
The following calibration was applied to the oxygen sensor:
O2_cal = (O2_raw-O2_int) / O2_gra
O2_cal = (O2_raw-54.444) / 0.745
See the cruise report for details.
The following calibration was applied to the conductivity readings:
Cond1_cal=cond1-0.0024 mS/cm
Con2_cal=cond2-0.0008 mS/cm
See section below for details.
- Input: JR18006_NNN_cropped_down_despiked.mat
- Output: JR18006_NNN_cropped_down_despiked_calib.mat
8. Despike salinity derived from calibrated conductivity
- Input: JR18006_NNN_cropped_down_despiked_calib.mat
- Output: JR18006_NNN_cropped_down_despiked_calib_v2.mat
9. Binavg despiked calibrated 24Hz file
- Input: JR18006_NNN_cropped_down_despiked_calib_v2.mat
- Output: JR18006_NNN_ cal_1dbd_v2.mat
10. Export to Ascii
- Inputs: JR18006_NNN_cropped_down_despiked_calib_v2.mat, JR18006_NNN_ cal_1dbd_v2.mat
- Outputs: JR18006_NNN_final_24Hz_down.csv, JR18006_NNN_final_1db_down.csv
CTD Salinity Calibration
20 discrete salinity samples were taken from the CTD Niskins, covering a wide range of salinity values. For each sample the bottle was rinsed 3 times with the Niskin seawater, filled, plastic insert fitted, bottle neck wiped, and lid put on.
Samples were placed in the Autosal laboratory to acclimate to temperature for at least one day prior to analysis. At the start and end of each crate a standard seawater (SSW) sample was analysed (batch P161, K15=0.99987), enabling to monitor the drift of the instrument. No clear drift pattern was visible, and the readings showed little difference from the theoretical value (less than 0.001psu). For each crate, the average of the two SSW offsets was used as the offset to correct the Autosal readings.
There did not appear to be any temporal drift in the sensors, or a drift relative to pressure, so a constant offset was used to correct the data of both sensors. The median and standard deviation of the differences between the raw CTD and the Autosal readings were calculated, and all readings with a difference larger than 0.2 standard deviations of the median were excluded from the dataset. The median offset of each subset of selected points was then calculated and used as the correction offset.
Sensor 1 | Sensor 2 | |
---|---|---|
Total numbers of samples | 20 | 20 |
Number of samples rejected | 4 (20%) | 3 (15%) |
Conductivity sensor offset (condcalib = condraw - offset) | -0.0024 mS/cm | -0.0008 mS/cm |
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.
The Changing Arctic Ocean Seafloor (ChAOS) - how changing sea ice conditions impact biological communities, biogeochemical processes and ecosystems
The Changing Arctic Ocean Seafloor (ChAOS) project is a £2.1 million, four year (2017-2021) research programme funded by the Natural Environment Research Council (NERC) as part of the Changing Arctic Ocean (CAO) programme. The ChAOS project aims to quantify the effect of changing sea ice cover on organic matter quality, benthic biodiversity, biological transformations of carbon and nutrient pools, and resulting ecosystem function at the Arctic Ocean seafloor. The focal region is a N-S transect along 30°E in the Barents Sea.
Changes in sea ice are resulting in longer more extensive open water conditions which will prolong the growing season, influence primary production and the amount of organic matter reaching the sea floor. This results in a number of questions for the project:
- How will changes in the surface ocean influence seafloor processes?
- What are the consequences of this for carbon sequestration in seafloor sediments?
- How will seafloor biota respond to changes in food quantity and quality?
- Will there be changes to benthic ecosystem services, for example, the recycling of nutrients to overlying waters?
Further information can be found on the Changing Arctic Ocean ChAOS webpage.
Participants
There are nine organisations involved in the ChAOS project, these are:
- University of Leeds
- British Antarctic Survey (BAS)
- University of Newcastle
- University of Bristol
- University of Southampton
- Plymouth Marine Laboratory (PML)
- Durham University
- Université Libre de Bruxelles
- University of Edinburgh
In addition to these core organisations, there are 21 international collaborators involved in the project.
Research Details
The project consists of a detailed study of representative Arctic shelf sea habitats that intersect the ice edge with broad-scale in situ validation studies, shipboard experiments and manipulative laboratory experiments. The project also analyses highly spatially and temporally resolved data obtained by the Canadian, Norwegian and German Arctic programmes and integrates new understanding of controls and effects on biodiversity, biogeochemical pathways and nutrient cycles into modelling approaches.
The objectives of the project are to:
- Quantify the total amount and macronutrient stoichiometry of organic matter delivered to the Arctic seafloor, its source, bioavailability, age, and its fate below the sediment-water interface.
- Characterise the structure, activity and associated functioning of benthic infaunal assemblages under different ice cover scenarios.
- Experimentally determine how the benthic community structure, biogeochemical processes, and other ecosystem functions might change in a future, more ice free and warmer Arctic shelf.
- Analyse and monitor the amount and speciation of carbon and nutrient species recycled from the sediment into the water column under changing environmental conditions as induced by different sea ice scenarios.
- Provide data for improved modelling parameterisation of benthic carbon and nutrient cycling to allow for more reliable predictive tools of changes to Arctic Ocean benthic biological and biogeochemical processes and functions under future climate scenarios.
Fieldwork and Data Collection
The fieldwork will be primarily conducted onboard the NERC research vessel RRS James Clark Ross during the summer months of 2017, 2018 and 2019. The fieldwork will consist of extensive and multi-disciplinary sediment investigations and sampling using a variety of instrumentation and sampling devices such as trawls, boxcorer, megacorer at five benthic stations on a transect along 30°E that are variably influenced by winter sea ice cover. Additional cruises to locations that share similar sediment and water conditions in Norway and Canada will also be completed by international partners.
From the analyses of the field samples and data obtained by international partners, a range of well-constrained laboratory experiments will be conducted to collect further data. The experiments will expose incubated natural sediment to environmental conditions that are most likely to vary in response to changing sea ice cover and analyse the response of biology and biogeochemistry to these changes in present versus future environments.
These datasets will be complemented further by existing data provided by international partners in Norway, Canada, USA, Italy, Poland and Germany.
Data Activity or Cruise Information
Cruise
Cruise Name | JR18006 |
Departure Date | 2019-06-30 |
Arrival Date | 2019-08-01 |
Principal Scientist(s) | David Barnes (British Antarctic Survey) |
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 |