Natural Environment Research Council Designated Data Centres

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  • The data set comprises time series measurements from offshore pressure gauges mounted on the sea floor. The data holdings are approximately 100 observation months from 30 sites. The data are mainly from trans-ocean sections in the North Atlantic. Data records contain date/time, total pressure (or relative pressure) and, occasionally, temperature. The sampling interval is typically 15 minutes or hourly, over deployment periods ranging from 1 to 6 months. Data were collected mainly by the Proudman Oceanographic Laboratory (POL), now the National Oceanography Centre (NOC) at Liverpool, and are managed by the British Oceanographic Data Centre (BODC).

  • The dataset comprises chlorophyll-a concentrations from water samples taken during RRS James Clark Ross cruise JR304, from 15/11/2014 - 17/12/2014. The cruise sailed from Punta Arenas, Chile, returning to Stanley, Falkland Islands. Samples were taken during transit to Signy Island (South Orkneys), and then up through the Scotia Sea to BAS survey sites P2 and P3 as well as near South Georgia and in the Western Core Box survey area to the north of the island of South Georgia. 112 samples were collected from the ship’s uncontaminated underway supply, with an intake at approximately 6 m depth, every two hours during transit periods. 103 samples were collected, using a rosette sampler, from the upper 1000m during CTD (conductivity, temperature and depth probe) deployments. Each 300ml sample was filtered through a 0.8µm pore size, 25mm diameter, MPF300 filter, rinsed with milliQ water, placed in an eppendorf tube and stored at -20°C for later analysis. Samples were extracted in 90 % acetone for 22-24 hours at 4°C and measured on a Trilogy Turner Designs 7200 lab fluorometer calibrated with a pure chlorophyll-a standard (Sigma, UK) and set up following the method of Welschmeyer (1994). Data have not been adjusted for blanks. The data set was from the annual Western Core Box Cruise run by British Antarctic Survey (BAS). Data were collected to support the PhD of Anna Belcher and provide seasonal context for the cruise in terms of the primary production in the surface ocean. Chlorophyll samples were taken by Jenny Thomas (BAS), Gabi Stowasser (BAS), Sophie Fielding(BAS), Vicky Peck (BAS), Jess Gardner (University of East Anglia and BAS), Cecilia Liszka (BAS), Manon Duret (National Oceanography Centre, NOC), Anna Belcher (NOC), Anna Mikis (Cardiff University) , Marianne Wootton (Sir Alistair Hardy Foundation for Ocean Science), Sebastien Floter (GEOMAR Kiel). Chlorophyll samples were analysed aboard the R.R.S. James Clark Ross by Manon Duret and Anna Belcher from NOC.

  • Macrofauna and polychaete species abundance data were obtained from replicate megacore samples collected from inside the Whittard Canyon (N.E. Atlantic) and the adjacent slope to the west of the canyon during cruise JC036 in June and July 2009. Four sites were sampled, three in the Whittard Canyon branches (Western, Central and Eastern) and one site on the slope to the west of the canyon. Five deployments were conducted in the Western branch, six in the Central and Eastern branches and five at the slope site. One extra deployment was made in the Central and Eastern branches to compensate for the failure to recover sufficient cores. All sites were located at 3500 m depth. Samples were collected using a Megacorer fitted with eight large (100 mm internal diameter) core tubes. Core slices from the same sediment layer from one deployment were pooled to make one replicate sample. The number of cores pooled per deployment ranged from 3 to 7 and the area of seabed sampled varied accordingly. The top three sediment horizons (i.e. 0–1, 1–3 and 3–5 cm), were analysed in toto. Macrofauna were identified to higher taxa levels, and polychaetes to species level and counts of species/taxa recorded for each site. AphiaIDs have been assigned to the samples - where identification was only possible to genus or family level, the aphiaIDs for genus and family have been supplied. The supplied aphaIDs are those that were acceptable at the time of the analysis and not their more recent superseding terms. This cruise was part of the HERMIONE project and the data formed the basis of L. Gunton's PhD thesis 'Deep-Sea Macrofaunal Biodiversity of the Whittard Canyon (NE Atlantic)'.

  • Historic sea level data from 6 sites on the South coast of England, recovered as part of a PhD on sea level trends in the English Channel. Devonport: 1961-1986, 1988-1990 Newhaven: 1942-1948, 1950-1951, 1953-1957, 1964-1965, 1973, 1988 Portsmouth: 1961-1990 Southampton: 1935-1979, 1982-1990 St. Marys: 1968-1969, 1973, 1975, 1977-1978, 1987-1989 Weymouth: 1967-1971, 1983-1987 There are raw data files and cleaned data files. The cleaned files have been corrected for datum changes which are recorded in the readme files for each site.

  • The UK national network of sea level gauges was established after violent storms in the North Sea in 1953 resulted in serious flooding in the Thames Estuary. The data are required for research and operational use and to facilitate specific scientific studies of coastal processes such as tidal response, storm surge behaviour and sea level rise; and for underpinning local and national operational systems such as the Storm Tide Forecasting Service at the Met Office. BODC has a special responsibility for the remote monitoring and retrieval of sea level data from the network. Daily checks are kept on the performance of the gauges and the data are downloaded weekly. These are then routinely processed and quality controlled prior to being made available.

  • A set of underwater noise observations which provide information on noise levels over an 21 year period potentially setting a base line for future environmental monitoring. The data were collected for military operations by RAF Nimrod aircraft using air-deployed sonobuoys. They consist of averaged noise levels, measured in db, at a range of frequencies and depths throughout the UK Exclusive Economic Zone (EEZ).

  • This dataset consists of coccolithophore abundances in the North Atlantic that were collected from 37 CTD casts during three RRS Discovery cruises (D350, D351, D354) in the spring and summer of 2010. Water samples (0.2-1 L) were collected from CTD casts and filtered through cellulose nitrate (0.8 µm) and polycarbonate (0.45 µm or 0.8 µm) filters, rinsed with trace ammonium solution, oven dried (30-40 °C, 6-12 h) and stored in Millipore PetriSlides. The filters were examined using a Leo 1450VP scanning electron microscope, with coccolithophores identified following Young et al. (2003), and enumerated from 225 fields of view (Daniels et al., 2012). The detection limit was estimated to be 0.2-1.1 cells mL-1. The samples were collected to investigate coccolithophore community dynamics in the North Atlantic as part of the Irminger Basin Iron Study (IBIS)(D350, D354), Extended Ellett Line (EEL)(D351) and a NERC Fellowship. Samples were collected on D350 by Martine Couapel, on D351 by Stuart Painter and on D354 by Alex Poulton and Mike Lucas. In the lab, samples were prepared and processed by Chris Daniels, Elena Maher and Jonathan Hurst, and were analysed for coccolithophore abundances by Chris Daniels and Jeremy Mirza. The data are held at the British Oceanographic Data Centre (BODC). Daniels, C. J., Tyrrell, T., Poulton, A. J., and Pettit, L.: The influence of lithogenic material on particulate inorganic carbon measurements of coccolithophores in the Bay of Biscay, Limnol. Oceanogr., 57, 145-153, doi:10.4319/lo.2012.57.1.0145, 2012. Young, J. R., Geisen, M., Cros, L., Kleijne, A., Sprengel, C., Probert, I., and Ostergaard, J.: A guide to extant coccolithophore taxonomy, J. Nannoplankt. Res. Special Issue, 1, 1-132, 2003.

  • The dataset contains 39148 years of sea level data from 1355 station records, with some stations having alternative versions of the records provided from different sources. GESLA-2 data may be obtained from The site also contains the file format description and other information. The text files contain headers with lines of metadata followed by the data itself in a simple column format. All the tide gauge data in GESLA-2 have hourly or more frequent sampling. The basic data from the US National Atmospheric and Oceanic Administration (NOAA) are 6-minute values but for GESLA-2 purposes we instead settled on their readily-available 'verified hourly values'. Most UK records are also hourly values up to the 1990s, and 15-minute values thereafter. Records from some other sources may have different sampling, and records should be inspected individually if sampling considerations are considered critical to an analysis. The GESLA-2 dataset has global coverage and better geographical coverage that the GESLA-1 with stations in new regions (defined by stations in the new dataset located more than 50 km from any station in GESLA-1). For example, major improvements can be seen to have been made for the Mediterranean and Baltic Seas, Japan, New Zealand and the African coastline south of the Equator. The earliest measurements are from Brest, France (04/01/1846) and the latest from Cuxhaven, Germany and Esbjerg, Denmark (01/05/2015). There are 29 years in an average record, although the actual number of years varies from only 1 at short-lived sites, to 167 in the case of Brest, France. Most of the measurements in GESLA-2 were made during the second half of the twentieth century. The most globally-representative analyses of sea level variability with GESLA-2 will be those that focus on the period since about 1970. Historically, delayed-mode data comprised spot values of sea level every hour, obtained from inspection of the ink trace on a tide gauge chart. Nowadays tide gauge data loggers provide data electronically. Data can be either spot values, integrated (averaged) values over specified periods (e.g. 6 minutes), or integrated over a specified period within a longer sampling period (e.g. averaged over 3 minutes every 6 minutes). The construction of this dataset is fundamental to research in sea level variability and also to practical aspects of coastal engineering. One component is concerned with encouraging countries to install tide gauges at locations where none exist, to operate them to internationally agreed standards, and to make the data available to interested users. A second component is concerned with the collection of data from the global set of tide gauges, whether gauges have originated through the GLOSS programme or not, and to make the data available. The records in GESLA-2 will have had some form of quality control undertaken by the data providers. However, the extent to which that control will have been undertaken will inevitably vary between providers and with time. In most cases, no further quality control has been made beyond that already undertaken by the data providers. Although there are many individual contributions, over a quarter of the station-years are provided by the research quality dataset of UHSLC. Contributors include: British Oceanographic Data Centre; University of Hawaii Sea Level Center; Japan Meteorological Agency; US National Oceanic and Atmospheric Administration; Puertos del Estado, Spain; Marine Environmental Data Service, Canada; Instituto Espanol de Oceanografica, Spain; idromare, Italy; Swedish Meteorological and Hydrological Institute; Federal Maritime and Hydrographic Agency, Germany; Finnish Meteorological Institute; Service hydrographique et oc?anographique de la Marine, France; Rijkswaterstaat, Netherlands; Danish Meteorological Institute; Norwegian Hydrographic Service; Icelandic Coastguard Service; Istituto Talassographico di Trieste; Venice Commune, Italy;

  • This dataset consists of data from one station (Batiki01) that is are part of a network of temperature sensors on the coastal domain of about twenty territories ReefTEMPS ( coordinated by the Grand Observatoire de l'environment et de la biodiversite terrestre et marine du Pacifique Sud (GOPS). The dataset consists of temperature data from a temperature logger attached to a coral head recording temperature every 30 minutes at around 10 metres depth with QC being applied following collection of the logger. The data were collected in the coastal waters of Batiki Island, Fiji (latitude=-17.777467, longitude=179.179867, 2012 to 2015).

  • GreenSeas was an EU FP7 programme funded to advance the quantitative knowledge of how planktonic marine ecosystems, including phytoplankton, bacterioplankton and zooplankton, will respond to environmental and climate changes. To achieve this GreenSeas employed a combination of observation data, numerical simulations and a cross-disciplinary synthesis to develop a high quality, harmonized and standardized plankton and plankton ecology long time-series, data inventory and information service. This contribution to the programme developed a number of indices to characterize quantitatively the seasonality of phytoplankton (Platt and Sathyendranath, 2008, Racault et al., 2014a). Specifically, indices that relate to the study of timing of periodic biological events as influenced by the environment are referred to as phytoplankton phenology. These indices include: timings of initiation, peak, and termination as well as the duration of the phytoplankton growing period. Changes in phytoplankton phenology (triggered by variations in climate) can profoundly alter: (1) the efficiency of the biological pump, with inevitable impact of the global carbon cycle; and (2) the interactions across trophic levels, which can engender trophic mismatch with major impacts on the survival of commercially important fish and crustacean larvae. Phenology indices were estimated using the R2010.0 reprocessing of Level 3 Mapped chlorophyll-a concentration from the Sea-viewing Wide Field-of-view (SeaWiFS) sensor. The chlorophyll-a data were retrieved from NASA Ocean Color Web for the period 1997-2008 at 9 km spatial resolution and 8-day temporal resolution. Linear interpolation was applied to map the chlorophyll-a concentration onto a 1degreex1degree fixed grid. The phenology indices were estimated following the method described in Racault et al. (2012). Missing chlorophyll-a data were reduced from the time-series prior to estimating the timing of ecological events. Missing values were filled by interpolating spatially adjacent values (average of 3 × 3 pixels on the 9km grid), when these were available. Any remaining missing values were filled by interpolating temporally adjacent values (average of previous and following 8-day composites), when these were available. Otherwise the value was not filled. A 3-week running mean was applied to remove small peaks in chlorophyll-a. The timings of initiation and end of the phytoplankton growing period were detected as the weeks when the chlorophyll concentration in a particular year rose above the long-term median value plus 5% and later fell below this same threshold (Racault et al., 2012). The duration of the growing season is defined as the number of weeks between initiation and end.