Search the data

Metadata Report for BODC Series Reference Number 1761294


Metadata Summary

Data Description

Data Category Surface temp/sal
Instrument Type
NameCategories
WETLabs C-Star transmissometer  transmissometers
Sea-Bird SBE 45 MicroTSG thermosalinograph  thermosalinographs; water temperature sensor; salinity sensor
Sea-Bird SBE 38 thermometer  water temperature sensor
Turner 10-AU chlorophyll field fluorometer  fluorometers
Litre Meter flow meter  flow meters
Kongsberg Seatex Seapath 320+ Precise Heading, Attitude and Positioning Sensor  Global Navigation Satellite System receivers; Differential Global Positioning System receivers; inertial navigation systems
Instrument Mounting research vessel
Originating Country United Kingdom
Originator Dr Rosie Chance
Originating Organization University of York Department of Chemistry
Processing Status banked
Online delivery of data Download available - Ocean Data View (ODV) format
Project(s) ACCACIA
Arctic Research Programme
 

Data Identifiers

Originator's Identifier JR20130713-PRODQXF_SURF
BODC Series Reference 1761294
 

Time Co-ordinates(UT)

Start Time (yyyy-mm-dd hh:mm) 2013-07-13 10:31
End Time (yyyy-mm-dd hh:mm) 2013-08-16 10:35
Nominal Cycle Interval 60.0 seconds
 

Spatial Co-ordinates

Start Latitude 53.54250 N ( 53° 32.5' N )
End Latitude 83.32400 N ( 83° 19.4' N )
Start Longitude 20.70033 W ( 20° 42.0' W )
End Longitude 34.83600 E ( 34° 50.2' E )
Positional Uncertainty 0.0 to 0.01 n.miles
Minimum Sensor or Sampling Depth 6.5 m
Maximum Sensor or Sampling Depth 6.5 m
Minimum Sensor or Sampling Height -
Maximum Sensor or Sampling Height -
Sea Floor Depth -
Sea Floor Depth Source -
Sensor or Sampling Distribution Fixed common depth - All sensors are grouped effectively at the same depth which is effectively fixed for the duration of the series
Sensor or Sampling Depth Datum Approximate - Depth is only approximate
Sea Floor Depth Datum -
 

Parameters

BODC CODERankUnitsTitle
AADYAA011DaysDate (time from 00:00 01/01/1760 to 00:00 UT on day)
AAFDZZ011DaysTime (time between 00:00 UT and timestamp)
ALATGP011DegreesLatitude north relative to WGS84 by unspecified GPS system
ALONGP011DegreesLongitude east relative to WGS84 by unspecified GPS system
CNDCSG011Siemens per metreElectrical conductivity of the water body by thermosalinograph
CPHLUMTF1Milligrams per cubic metreConcentration of chlorophyll-a {chl-a CAS 479-61-8} per unit volume of the water body [particulate >unknown phase] by through-flow fluorometer plumbed into non-toxic supply and manufacturer's calibration applied
INFLTF011Litres per minuteFlow rate through instrument
POPTDR011PercentTransmittance (red light wavelength) per 25cm of the water body by 25cm path length red light transmissometer
PSALSU011DimensionlessPractical salinity of the water body by thermosalinograph and computation using UNESCO 1983 algorithm and NO calibration against independent measurements
TEMPHU011Degrees CelsiusTemperature of the water body by thermosalinograph hull sensor and NO verification against independent measurements
TMESSG011Degrees CelsiusTemperature of electrical conductivity measurement by thermosalinograph

Definition of Rank

  • Rank 1 is a one-dimensional parameter
  • Rank 2 is a two-dimensional parameter
  • Rank 0 is a one-dimensional parameter describing the second dimension of a two-dimensional parameter (e.g. bin depths for moored ADCP data)

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

ACCACIA RRS James Clark Ross JR20130713 (JR288) Underway Cruise Document

Cruise details

Dates 2013-07-13 — 2013-08-16
Principal Scientific Officer

Lucy Carpenter, University of York

Rosie Chance, University of York

Data supplied by Polar Data Centre, British Antarctic Survey

RRS James Clark Ross departed from TImmingham, United Kingdom on 13 July 2013 and docked in Dundee, United Kingdom on 16 August 2013.

This was the second cruise of the NERC funded project called Aerosol-Cloud Coupling and Climate interactions in the Arctic (ACCACIA). The aims of the cruise were to:

  • obtain surface based in-situ measurements of marine aerosol composition and properties and aerosol precursos gases (DMS, VOC, halocarbon)
  • Collect standard oceanographic measurements such as salinity, chlorophyll-a and nutrient concentrations
  • Conduct bubble tank experiments to develop a primary multicomponent seaspray aerosol flux parameterisation

The data provided to BODC includes the entire cruise period from 2013-07-13 — 2013-08-16. Date and time were supplied in UT. The span of the data covers all scientific activities.

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.

Turner Designs 10AU Field Fluorometer

The Turner Designs 10AU is designed for continuous-flow monitoring or discrete sample analyses of fluorescent species. A variety of optical kits with appropriate filters and lamps are available for a wide range of applications. Individual filters and lamps are also available for customised applications.

Standard optical kits include those for chlorophyll-a (extracted and/or in vivo), phycocyanin, phycoerythrin, CDOM, ammonium, rhodamine and fluorescein dye tracing, crude oil, refined oil, histamine and optical brighteners.

The instrument's light source is a 4 watt lamp and the detector is a photomultiplier tube with a standard detection range of 300-650 nm. A red-sensitive version with a detetion range of 185-970 nm is also available.

Specifications

Operating temperature 0 to 55°C
Detector PhotoMultiplier Tube

300 to 650 nm (standard)

185 to 870 nm (Red)

Detection Limits:
Extracted Chlorophyll-a
Rhodamine WT Dye
Fluorescein Dye

0.025 µg L-1
0.01 ppb (in potable water)
0.01 ppb (in potable water)
Linear range:
Extracted Chlorophyll-a
Rhodamine WT Dye
Fluorescein Dye

0 to 250µg L-1
0 to 250 ppb
0 to 250 ppb

Further details can be found in the manufacturer's specification sheet.

Kongsberg Seatex Seapath 320+ Precise Heading, Attitude and Positioning Sensor

The Seapath 320+ is a navigational system that combines two Global Navigation Satellite System (GNSS) receivers with a MRU 5+ inertial sensor to provide high resolution and accuracy positional data. The inertial sensor employs linear accelerometers and unique microelectromechanical systems (MEMS)-type angular rate gyros to provide 0.01 RMS pitch and roll accuracy. The GNSS receivers can use multiple satellite constellations (GPS, GLONASS and Galileo, when available), and combine data from these to improve heading and positional measurements. In case of missing data from one GNSS receiver, the other receiver provides position and velocity, and the inertial sensor provides heading from its internal rate sensors.

The main characteristics are presented below, and the specification sheet can be accessed here Kongsberg Seatex Seapath 320+ .

Specifications

Heading accuracy

0.04° RMS (4m baseline)

0.065° RMS (2.5 baseline)

Roll and pitch accuracy 0.02° RMS for ± 5° amplitude
Scale factor error in roll, pitch and heading 0.05% RMS
Heave accuracy (real time) 5 cm or 5%, whichever is highest
Heave accuracy (delayed signal) 2 cm or 2%, whichever is highest
Heave motion periods (real time) 1 to 20 seconds
Heave motion periods (delayed signal) 1 to 50 seconds
Position accuracy (DGPS/DGlonass) 1 m (95% CEP)
Position accuracy (SBAS) 1 m (95% CEP)
Position accuracy (with RTK corrections) 0.2 m (95% CEP)
Velocity accuracy 0.07 m s-1 (95% CEP)
Data update rate Up to 100Hz

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.

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 JR20130713 (JR288) ACCACIA Underway Surface Hydrography Document

Content of data series

Parameter Units Parameter code
Latitude Degrees (+ve N) ALATGP01
Longitude Degrees (+ve E) ALONGP01
Temperature (sea surface) °C TMESSG01
Temperature (hull sensor) °C TEMPHU01
Salinity Dimensioneless PSALSU01
Conductivity S m-1 CNDCSG01
Chlorophyll mg m-3 CPHLUMTF
Transmittance % POPTDR01
Flow meter l min-1 INFLTF01

Instrumentation

The sea surface hydrographical suite of sensors was fed by the pumped-seawater, non-toxic supply. The seawater intake was located approximately 7 m below the sea surface. The SBE 38 sea surface temperature sensor was located towards the hull near the seawater intake. All other sensors were located in the clean seawater laboratory on the main deck, directly above the intake pipe.

Manufacturer Model Serial number Comments
Sea Bird SBE45 4524698-0018 Thermosalinograph
Sea Bird SBE38   Hull sensor
WetLabs C-Star CST-396DR Transmissometer (25 cm pathlength)
Chelsea technologies 10-AU 005   Fluorometer
Litre Metre F112P   Flow pump

Data Processing Procedures

Originator's Data Processing

Data were not processed by the PSO or any sceintists on board or, at a later stage, at the office.

Files delivered to BODC

Filename Content description Format Interval Start date/time (UTC) End date/time (UTC)
oceanlogger.ACO Meteorology and Surface Hydrography data .ACO 5 seconds 13/07/2013 11:17:38 hours 16/08/2013 11:09:56 hours

BODC Data Processing

Data were banked at BODC following standard data banking procedures, including reduction through averaging, checking surface hydrography channels for improbable values and screening the data for anomalous values. The originator's variables were mapped to appropriate BODC parameter codes as follows:

oceanlogger.ACO

Originator's variable Originator's units Description BODC Code BODC Units
oceanlogger-tstemp celsius Temperature of the water body by thermosalinograph TMESSG01 °C
oceanlogger-sstemp celsius Temperature of the water body by thermosalinograph hull sensor and NO verification against independent measurements TEMPHU01 °C
oceanlogger-conductivity S ma-1 Electrical conductivity of the water body by thermosalinograph CNDCSG01 S m-1
oceanlogger-salinity psu Practical salinity of the water body by thermosalinograph and computation using UNESCO 1983 algorithm and NO calibration against independent measurements PSALSU01  
oceanlogger-chlorophyll µg l-1 Concentration of chlorophyll-a {chl-a CAS 479-61-8} per unit volume of the water body [particulate >unknown phase] by through-flow fluorometer plumbed into non-toxic supply and manufacturer's calibration applied CPHLUMTF mg m-3
oceanlogger-trans 0<tr<1 Transmittance (red light wavelength) per 25cm of the water body by 25cm path length red light transmissometer POPTDR01 %
oceanlogger-flowrate l min-1 Flow rate through instrument INFLTF01 l min-1

This file also contains meteorological paramaters (Air temperature, Relative humidity, Air pressure, PAR and TIR) which will be dealt with in the meteorological processing document.

Chlorophyll

The following periods were flagged M:

  • 13/07/2013 14:57 hours
  • 21/07/2013 04:41 hours to 21/07/2013 06:36 hours
  • 21/07/2013 14:23 hours to 21/07/2013 14:28 hours
  • 23/07/2013 15:57 hours to 23/07/2013 16:17 hours
  • 23/07/2013 17:55 hours
  • 23/07/2013 18:15 hours
  • 25/07/2013 03:00 hours to 25/07/2013 06:57 hours
  • 25/07/2013 07:41 hours
  • 26/07/2013 01:20 hours to 26/07/2013 03:34 hours
  • 26/07/2013 16:58 hours to 27/07/2013 03:58 hours
  • 27/07/2013 06:00 hours to 27/07/2013 09:37 hours
  • 27/07/2013 16:59 hours to 28/07/2013 03:55 hours
  • 28/07/2013 20:25 hours to 29/07/2013 05:20 hours
  • 29/07/2013 20:49 hours to 30/07/2013 03:10 hours
  • 31/07/2013 05:14 hours to 31/07/2013 17:47 hours
  • 03/08/2013 01:25 hours to 03/08/2013 05:22 hours
  • 03/08/2013 18:33 hours to 04/08/2013 05:06 hours
  • 04/08/2013 05:29 hours to 04/08/2013 05:30 hours
  • 04/08/2013 05:59 hours to 04/08/2013 06:57 hours
  • 04/08/2013 14:15 hours to 04/08/2013 20:17 hours
  • 04/08/2013 23:58 hours to 05/08/2013 08:12 hours
  • 05/08/2013 14:37 hours to 05/08/2013 16:52 hours
  • 06/08/2013 01:12 hours to 06/08/2013 06:49 hours
  • 06/08/2013 14:45 hours
  • 10/08/2013 06:06 hours to 10/08/2013 15:37 hours
  • 11/08/2013 18:52 hours
  • 11/08/2013 18:55 hours to 12/08/2013 07:37 hours
  • 12/08/2013 10:11 hours to 12/08/2013 17:16 hours
  • 12/08/2013 18:25 hours to 13/08/2013 07:34 hours
  • 13/08/2013 17:01 hours to 14/08/2013 07:14 hours
  • 16/08/2013 08:59 hours to 16/08/2013 11:10 hours

Surface temperature, conductivity, salinity and transmittance

  • 13/07/2013 14:51 hours
  • 21/07/2013 04:41 hours to 21/07/2013 06:38 hours
  • 21/07/2013 14:23 hours to 21/07/2013 14:28 hours
  • 23/07/2013 15:57 hours to 23/07/2013 16:20 hours
  • 23/07/2013 17:55 hours
  • 23/07/2013 18:15 hours
  • 25/07/2013 03:00 hours to 25/07/2013 06:57 hours
  • 25/07/2013 07:41 hours
  • 26/07/2013 01:20 hours to 26/07/2013 03:36 hours
  • 26/07/2013 16:58 hours to 27/07/2013 04:02 (and to 27/07/2013 05:59 hours for POPTDR01)
  • 27/07/2013 06:00 hours to 27/07/2013 09:41 hours
  • 27/07/2013 16:59 hours to 28/07/2013 04:00 hours
  • 28/07/2013 20:25 hours to 29/07/2013 05:22 hours
  • 29/07/2013 20:49 hours to 30/07/2013 03:12 hours
  • 31/07/2013 05:14 hours to 31/07/2013 17:47 hours
  • 03/08/2013 01:25 hours to 03/08/2013 05:23 hours
  • 03/08/2013 18:33 hours to 04/08/2013 05:08 hours
  • 04/08/2013 05:59 hours to 04/08/2013 06:58 hours
  • 04/08/2013 14:15 hours to 04/08/2013 20:19 hours
  • 04/08/2013 23:58 hours to 05/08/2013 08:13 hours
  • 05/08/2013 14:37 hours to 05/08/2013 16:53 hours
  • 06/08/2013 01:12 hours to 06/08/2013 06:51 hours
  • 06/08/2013 14:45 hours
  • 10/08/2013 06:06 hours to 10/08/2013 15:38 hours
  • 11/08/2013 18:55 hours to 12/08/2013 07:37 hours
  • 12/08/2013 10:11 hours to 12/08/2013 17:16 hours
  • 12/08/2013 18:25 hours to 13/08/2013 07:34 hours
  • 13/08/2013 17:01 hours to 14/08/2013 07:15 hours
  • 16/08/2013 08:59 hours to 16/08/2013 11:10 hours

Quality control

M flags were applied to all surface hydrography channels when the flow pump recorded values < 0.4 l min-1 and up until the sensors stabilised.


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