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 http://oceancolor.gsfc.nasa.gov 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.

This dataset consists of eastward and northward current components at 32 depth levels. The dataset is a gridded dataset, with grid resolution of 1.85 km. It covers the entire Irish Sea area, with a precise range from -2.7 degrees longitude to -7 degrees longitude and from 51 degrees latitude to 56 degrees latitude. The data are daily averages and cover the period from 01 January 1996 to 01 January 2007. The dataset was generated by the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled with the Wave Modelling model (POLCOMS-WAM) as part of the Natural Environment Research Council (NERC) CoFEE project which ran from April 2007 to September 2010. The eastward and northward current components were used as input conditions into a coastal processes and sediment transport model which looked at the response of the north Liverpool coastline to extreme flooding events. The dataset was generated by the Proudman Oceanographic Laboratory (since April 2010, part of the UK National Oceanography Centre). The dataset consists of 132 data files in Climate and Forecast (CF) compliant NetCDF format.

This data collection consists of sea surface temperature (SST) data collected by recreational surfers around the southern UK and Western Ireland coastline over the period from 5th January 2014 to 8th February 2017. These data were collected as part of a research project supported by Plymouth Marine Laboratory. Over the study period, the recreational surfers collected 297 independent samples of SST. The surfers were equipped with a UTBI-001 Tidbit V2 Temperature Data Logger and a Garmin etrex 10 GPS. The Garmin etrex 10 device was used to extract GPS information (latitude and longitude) for each surf. The Tidbit V2 temperature logger was attached, using cable-ties, at mid-point to the leash of the surfboards to ensure continuous contact with seawater when surfing, measuring temperature in the top metre of the water column. Roughly every 6 months over the study period, the Tidbit V2 temperature loggers were rigorously compared with a VWR1620-200 traceable digital thermometer (with an accuracy of 0.05 degrees C at the range of 0 to 100 degrees C) at 1 degree C intervals from 6 to 25 degrees C using a PolyScience temperature bath. Over the study period, all sensors performed within the manufacturers technical specifications. A piecewise regression to model was used to correct any Tidbit V2 temperature data collected to remove systematic biases between sensors, such that the errors in each sensor were within the accuracy of VWR1620-200 traceable digital thermometer. Temperature data were collected at 10 second intervals during each surfing session. The data were processed to remove any data collected before and after entering the water and SST were extracted by computing the median of the remaining data. Standard deviations on the remaining data are also provided to give an index of SST variability during each surf session.

This dataset comprises sea surface temperature measurements taken close to the time of high water at intervals of three to four days. The measuring programme consisted of approximately 50 observing sites around the shoreline of England and Wales and the data set spans the time period from 1963 to 1990. A few observing sites were already in existence when the network was established, for example observations at the Seven Stones and Varne Light Vessels go back as far as 1905. The Ministry of Agriculture, Fisheries and Food Lowestoft Fisheries Laboratory (MAFF), now known as the Centre for Environment, Fisheries and Aquaculture Science Lowestoft Laboratory (CEFAS) - part of the Department for Environment, Food and Rural Affairs (Defra), set up a database for these data, supplemented by both the earlier data and also by data from non-MAFF sources. Data from 1963 until 1990 are held at the British Oceanographic Data Centre (BODC). The time series is ongoing but data later than 1990 are not stored at BODC, these data are available from CEFAS.

The CreamT project converted the prototype WireWall wave overtopping field measurement system into a ruggedised monitoring system between August 2020 and August 2023. The system was deployed for up to a year in two high-energy coastal environments along the Southwest coast, UK (Dawlish and Penzance). The system was designed to have a 3-month maintenance interval and was programmed to measure overtopping condition ±3hrs either side of predicted high tide. The wave-by-wave overtopping data were telemetered to the British Oceanographic Data Centre (BODC) every 10 minutes. At the time of the project, the coastal structures at these sites comprised a vertical sea wall with small return lip or curve at the top. Both sea walls were fronted by a beach. During the project period the Dawlish beach levels exposed a concreate toe at the base of the wall. In Penzance, the beach covered the sea wall toe and was higher in the southwest monitoring location. The system was designed at the National Oceanography Centre (NOC) and had previously been validated in HR Wallingford’s flume facility and field tested with Sefton Council (https://www.channelcoast.org/northwest/). During CreamT, three different system configurations were deployed: full WireWall systems each with an array of six capacitance sensors; smaller WireWand systems with two capacitance sensors mounted on a single pole to detect overtopping at hazard hotspots; and a WaveWell using a single sensor on the face of the sea wall. Six datasets are available from the CreamT project. These contain delayed mode data from: 1) a WireWall deployed at the crest of the sea wall in Dawlish; 2) a WireWand deployed at the wall just seaward of the railway line in Dawlish; 3) a WireWand deployed at the fence just inland of the railway line in Dawlish; 4) a WaveWell deployed on the face of the sea wall in Dawlish; 5) a WireWall deployed at the crest of the sea wall in Penzance near Queen’s Hotel, and; 6) a WireWall deployed at the crest of the sea wall in Penzance near the Lidal store at Wherrytown. The datasets in Dawlish provide information about the inland distribution of overtopping, and the two datasets in Penzance provide information about the alongshore variability in overtopping hazard. These data can be used alongside the regional monitoring data available from the Southwest Regional Monitoring Programme to investigate the drivers of wave overtopping. All these data can be visualised in a hazard dashboard developed by the BODC and hosted on JASMIN, https://coastalhazards.app.noc.ac.uk/. This project was delivered by the National Oceanography Centre in collaboration with BODC and the University of Plymouth under NERC Grant References NE/V002538/1 and NE/V002589/1. Project partners were Network Rail, Southwest Regional Monitoring Programme, Environment Agency and Channel Coastal Observatory.

This dataset comprises measurements of microbial uptake activities of betaine and choline, particulate phase osmolytes, amplicon sequencing of marker genese involved in Nitrogenous-osmolyte catabolism, and single cell genome data. Water samples were collected from at the L4 station of the Western Channel Observatory between April 27, 2015 to April 24, 2017 using Niskin bottles attached to a rosette sampler deployed from the RV Plymouth Quest. Nitrogenous osmolytes (glycine betaine, choline and trimethylamine N-oxide are essential components for most organisms in the marine environment. They enable cells to exist in a salty environment, but also have several other proposed uses. The aim of the project is to understand the seasonal cycle of glycine betaine, trimethylamine N-oxide and choline at Station L4. The water samples were analysed for the microbial assimilation and dissimilation activities using 14C labelled betaine and choline, respectively. The data will be incorporated to the European Regional Seas Ecosystem Model (ERSEM) coupled with the hydrodynamic model General Ocean Turbulent Model (GOTM) to simulate the N-osmolyte cycling at the L4 station. The data were collected under the project Biogeochemical cycling of N-osmolytes in the surface ocean funded by NERC Discovery Science grants NE/M002233/1 (parent), NE/M003361/1 (child), NE/M002934/1 (child). The grants were led by Dr Yin Chen, Dr Ruth Airs, and Dr Wei Huang respectively.

This dataset provides yearly estimates of near-global (65N-65S) ocean heat content and thermosteric sea-level depth-integrated for the upper 700 meters of the ocean for 1970 - 2023. The yearly values are presented with three-year smoothing and one-sigma error estimates. The dataset builds upon and updates the methodology established in Domingues et al. (2008, Nature), incorporating temperature measurements from ocean observation systems and applying corrections for instrumental biases and sampling irregularities. To estimate ocean heat content for the upper 700 m and the associated thermosteric sea level, we used ocean temperature profiles from the ENACT/ENSEMBLES version 3 (EN3) data set (1970-2004), and Argo/Ifremer profiling floats (2000-2023, updated January 2024). Empirical Orthogonal Functions (EOFs) were used to model variability of the time-varying sea level and were calculated from 23 years (1993–2015) of satellite altimeter data sourced from Commonwealth Scientific and Industrial Research Organisation (CSIRO), (TOPEX/Poseidon, Jason-1, Jason-2 and Jason-3).

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.

A collection of raw water temperature-depth-time profiles were recorded from a selection of dive computers, underwater cameras and baseline Castaway microCTD devices. Data were collected at Oban recompression chamber (owned and managed by Tritonia Scientific), as well as during sea dives local to 56.42 N, 5.47W, over a two-week period between 08/01/2020 and 07/02/2020. A number of different devices and models were tested during the study. Chamber dives were undertaken to test and compare device response time (29 devices over 11 dives) and accuracy (6 replicate dives). This was followed by local sea dives to further compare device accuracy. During each pair of sea dives (6 total), half of the devices were mounted on a frame with the remainder worn by two divers. For the subsequent dives in each pair, each device was switched to the alternate mounting position. Dive profiles were exported from individual dive computers into Subsurface open source software, then exported in ssrf (XML) format for each week of data collection. Profiles from all dive computers were combined for analysis. Castaway microCTDs and Paralenz Dive Camera+ profiles were exported as individual CSV files per dive. Data were collected as part of Celia Marlowe’s PhD project at the University of East Anglia, which aimed to assess the precision, accuracy and uncertainty in water temperature profiles collected from devices commonly carried by Scuba divers. The PhD project is part of the Next Generation Unmanned Systems Science (NEXUSS) Centre for Doctoral Training, funded by the Natural Environment Research Council (NERC) and the Engineering and Physical Science Research Council (EPSRC) (NE/N012070/1), and is additionally supported by Cefas Seedcorn (DP901D). The diving and chamber tests were supported through a NERC National Facility for Scientific Diving grant (NFSD/17/02).

This dataset includes two cruises of data collected to investigate Arctic hydrate dissociation as a consequence of climate change and to determine vulnerable methane reservoir and gas escape mechanisms. Work during both JR269A and JR269B was focused on two separate geographical areas. The first of these was west of Prins Karls Forland, in water depths of between 150 and 1200 m. At its landward end, this survey area crosses a region at water depths up to 400 m where a dense concentration of methane escape bubble plumes occur. The second survey area straddles the summit of the Vestnesa Ridge, in water depths of 1180 to 1400 m, and is also the site of methane escape bubble plumes within the water column and of fluid escape chimneys and pockmarks previously imaged at and beneath the sea bed. This area lies approximately 100 km west of the mouth of Kongsfjorden. Data collection took place between August 2011 and July 2012. The research expedition used a deep-towed, very high resolution seismic system to image the small-scale structures that convey gas to the seabed and to detect the presence of gas in the sediments. This was done in conjunction with an electromagnetic exploration system that uses a deep-towed transmitter and receivers on the seabed to derive the variations in electrical resistivity in the sediments beneath the seabed. The observations carried out on the two cruises included; underway, meteorological observations and echo sounder data, multichannel seismic reflection profiling data, wide angle seismic survey data, and ocean bottom seismometer (OBS) data, ocean bottom electro-magnetometer data and controlled source electromagnetic surveys (CSEM). The overall objectives of the project were to determine the spatial distribution of gas and hydrate accumulations beneath the sea bed; to investigate and understand gas transport and escape mechanisms, their spatial distribution, and the controls on these; and to quantify gas and hydrate saturation values in situ within the pore spaces of the shallow sediment reservoirs. The research is focused on specific areas where significant accumulations of methane hydrate and active methane venting through the sea floor were observed and documented during the earlier JR211 cruise in 2008. This is a NERC funded project hosted by University of Southampton. The data held at BODC include multichannel seismic reflection, TOPAS sub-bottom profiler and 2D seismic reflection data in SEG-Y format. No further data are expected.