(My organization)
Continents, countries, sea regions of the world.
Mechanical and physical properties of decane-saturated Purbeck Limestone (NERC Grant NE/K009656/1)
These data contain time series of stress, strain, confining pressure, pore pressure, pore volume, permeability and elastic wave velocities of samples of Purbeck Limestone deformed under hydrostatic and triaxial conditions at room temperature. All samples were saturated with decane as pore fluid.This dataset is used and fully described/interpreted in the paper: Brantut, N., M. Baker, L. N. Hansen and P. Baud, Microstructural control of physical properties during deformation of porous limestone, submitted to J. Geophys. Res.
The copyright of materials derived from the British Geological Survey's work is vested in the Natural Environment Research Council [NERC]. No part of this work may be reproduced or transmitted in any form or by any means, or stored in a retrieval system of any nature, without the prior permission of the copyright holder, via the BGS Intellectual Property Rights Manager. Use by customers of information provided by the BGS, is at the customer's own risk. In view of the disparate sources of information at BGS's disposal, including such material donated to BGS, that BGS accepts in good faith as being accurate, the Natural Environment Research Council (NERC) gives no warranty, expressed or implied, as to the quality or accuracy of the information supplied, or to the information's suitability for any use. NERC/BGS accepts no liability whatever in respect of loss, damage, injury or other occurence however caused.
Available under the Open Government Licence subject to the following acknowledgement accompanying the reproduced NERC materials "Contains NERC materials ©NERC [year]"
The dataset is made freely available for access, e.g. via the Internet. Either no third party data / information is contained in the dataset or BGS has secured written permission from the owner(s) of any third party data / information contained in the dataset to make the dataset freely accessible.
See methodology section in the paper: Brantut, N., M. Baker, L. N. Hansen and P. Baud, Microstructural control of physical properties during deformation of porous limestone, submitted to J. Geophys. Res
Datasets produced by Multiscale Impacts of Cyanobacterial Crusts on Landscape Stability (2/6) (NERC grant NE/K011464/1)
Data from laboratory experiments conducted as part of project NE/K011464/1 (associated with NE/K011626/1) Multiscale Impacts of Cyanobacterial Crusts on Landscape stability. Soils were collected from two sites in eastern Australia and transferred to a laboratory at Griffith University, Queensland for conduct of experiments. Soils were A, a sandy loam, and B a loamy fine sand. Trays 120 mm x 1200 mm x 50 mm were filled with untreated soil that contained a natural population of biota. Soils were either used immediately for experiments (physical soil crust only: PC) or were placed in a greenhouse and spray irrigated until a cyanobacterial crust has grown from the natural biota. Growth was for a period of 5 days (SS), c.30 days (MS2) or c.60 days (MS1). Following the growing period (if applicable) trays were placed in a temperature/humidity controlled room at 35º and 30% humidity until soil moisture (measured 5 mm below the surface) was 5%. Trays were then subject to rainfall simulation. Rainfall intensity of 60 mm hr-1 was used and rainfall was applied for 2 minutes (achieving 2 mm application), 8 minutes (achieving 8 mm application) or 15 minutes (achieving 15 mm application). Following rainfall, trays were returned to the temperature/humidity-controlled room under UV lighting until soil moisture at 5 mm below the surface was 5%. A wind tunnel was then placed on top of each tray in turn and a sequential series of wind velocities (5, 7, 8.5, 10, 12 m s-1) applied each for one minute duration. On each tray the five wind velocities were run without saltation providing a cumulative dust flux. For the highest wind speed, an additional simulation run was conducted with the injection of saltation sands. Three replicates of each rainfall treatment were made. Variables measured include photographs, spectral reflectance, surface roughness, fluorescence, penetrometry, chlorophyll content, extracellular polysaccharide content, Carbon, Nitrogen and splash erosion and particle-size analysis (of wind eroded material). Details of rainfall simulator, growth of cyanobacteria, laser soil surface roughness characterisation and wind tunnel design and deployment in Strong et al., 2016; Bullard et al. 2018, 2019. Bullard, J.E., Ockelford, A., Strong, C.L., Aubault, H. 2018a. Impact of multi-day rainfall events on surface roughness and physical crusting of very fine soils. Geoderma, 313, 181-192. doi: 10.1016/j.geoderma.2017.10.038. Bullard, J.E., Ockelford, A., Strong, C.L., Aubault, H. 2018b. Effects of cyanobacterial soil crusts on surface roughness and splash erosion. Journal of Geophysical Research – Biogeosciences. doi: 10.1029/2018. Strong, C.S., Leys, J.F., Raupach, M.R., Bullard, J.E., Aubault, H.A., Butler, H.J., McTainsh, G.H. 2016. Development and testing of a micro wind tunnel for on-site wind erosion simulations. Environmental Fluid Mechanics, 16, 1065-1083.
Soil A is a sandy loam, soil B is a loamy fine sand and the biota of both soils is dominated by cyanobacteria (28%) (detailed in Bullard et al. 2018b). Biological soil crusts were grown in a greenhouse for 5, 30 or 60 days and spray irrigated with filtered water (equiv. 2 mm rainfall per day. Rainfall was simulated using the Griffith University Mobile Rainfall simulator detailed in Bullard et al. 2018a. Soil surface topography was determined using a Micro-Epsilon ScanCONTROL 2900-100 laser profiler, scanner height was 24 cm above the soil surface and used to scan an area of 100 x 100 mm at a resolution of 0.078 mm (detailed in Bullard et al. 2018a). The trays were proportioned to fit exactly beneath the Micro Wind Tunnel with perimeter seals to avoid air leakage. Details of the wind tunnel development and testing are in Strong et al. 2016.
UKGEOS Glasgow superficial deposits pre-drill model
The UK Geoenergy Observatories (UKGEOS) Glasgow superficial deposits GSI3D model outputs, created by the British Geological Survey, provide a semi-regional overview of the depth, thickness and extent of glacial and post-glacial lithostratigraphic units above rockhead. The model allows users to visualise the likely subsurface sequence to be found beneath this part of Glasgow, applicable at a scale of around 1: 25,000 to 1: 10,000. The data is supplied as grids and shapefiles over a 7 by 4.15 km area, with the depth range to around 40 m below Ordnance Datum. This model describes an interpretation of the shallow geology before the UKGEOS Glasgow boreholes have been drilled, and was used to inform the expected sequence on drilling. Further details and model limitations can be found in the accompanying metadata report http://nora.nerc.ac.uk/id/eprint/524556
The model has been built using a standard BGS-GSI3D workflow where the geologist uses mapped extents and borehole data to interpret the 3D geometry of lithostratigraphic units via a number of intersecting cross-sections. The model presented in this report builds on previous superficial deposit models of the Glasgow area, developed in BGS since 2005. A number of reports have been published describing previous models of the area, including Merritt et al. (2009), Monaghan et al. (2012, 2014) and Arkley et al. (2013). This model incorporates additional borehole data to increase the model resolution in the vicinity of the UKGEOS borehole sites and incorporates any post-2005 borehole data more recently received by BGS than previous model versions.
Vitamin D and stable isotope data from human hair from the archaeological site, Nunalleq, Alaska
[This dataset is embargoed until June 1, 2026]. Vitamin D (25(OH)D3 and 1,25(OH)D3) concentrations of incrementally-sampled preserved human hair from non-mortuary contexts at the Yup’ik archaeological site of Nunalleq Alaska (~1650 AD). Multi-isotope isotope data (carbon, nitrogen, sulphur, oxygen and hydrogen) for the same samples are found in accompanying files. Full details about this dataset can be found at https://doi.org/10.5285/8d5af777-384c-4114-af6b-69cdac239810
If you reuse this data, you should cite: Britton, K., Czére, O., Gutierrez, E., Reynard, L.M., Duncan, G., de Roos, B. (2024). Vitamin D and stable isotope data from human hair from the archaeological site, Nunalleq, Alaska. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/8d5af777-384c-4114-af6b-69cdac239810
This resource is available under the terms of the Open Government Licence
The dataset was generated as a part of the NERC-funded project NE/X012980/1 ‘Determining vitamin D status in precontact Western Alaska: a new method for exploring past health and dietary adaptations to high-latitude living’, as well as from an earlier (internally-allocated) BBSRC-funded pilot study (in the case of some of the isotope data). Vitamin D data were all generated at the University of Aberdeen, and isotope data were generated at SUERC (carbon, nitrogen, sulphur) and Boise State University (oxygen, hydrogen).
Trace element and Vanadium isotope compositions of basalt glass samples from the Reykjanes Ridge (NERC Grant NE/N009886/1)
The data forms the basis of the paper Novella et al (2020 (https://doi.org/10.1016/j.epsl.2019.115973) and full interpretation can be found there. Basalt glass chips were supplied by Bramley Murton (Southampton) and the sample contexts are detailed in https://doi.org/10.1093/petrology/43.11.1987. New trace element data is provided for the clean basaltic glasses (all reported in ppm). The Vanadium isotope composition (del51V) is also reported for these chips. Uncertainties in these analyses are provided as 2-sigma. Updated estimates of the ferric iron content of these chips also provided, based on recalibration of the data reported by Shorttle et al 2015 (https://doi.org/10.1016/j.epsl.2015.07.017).
TRACE ELEMENTS: Clean glass chips were selected and mounted for Laser-Ablation ICP-MS. Trace and rare earth element (REE) concentrations were measured by laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) at the Department of Earth Sciences, the University of Cambridge. This analytical setup combines a NWR193 excimer laser ablation systems with a Perkin Elmer NexION 350D ICP mass spectrometer. VANADIUM ISOTOPES: Clean glass shards without visible minerals, inclusions or weathering features were hand-picked under an optical microscope and ground in an agate mortar to obtain a homogeneous, fine powder. Dissolved basalts were processed through ion exchange chromatography following the protocol of Nielsen et al. (2011). Vanadium isotopic compositions were measured with a Nu Plasma II multi collector inductively coupled plasma mass spectrometer (Hopkins et al., 2019).
Daily and sub-daily hydrometeorological and soil data (2013-2016) [COSMOS-UK] v2
[THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains daily and sub-daily hydrometeorological and soil observations from COSMOS-UK (cosmic-ray soil moisture monitoring network) from the start of the network, in October 2013, to the end of 2016. These data are from 42 sites active across UK during this time, recording a range of hydrometeorological and soil variables. Each site in the network hosts a cosmic-ray sensing probe; a novel sensor technology which can be used, in combination with hydrometeorological data, to calculate the volumetric water content of soil over a field scale. The hydrometeorological and soil data are recorded at a 30 minute resolution and they include neutron counts from the Cosmic-ray sensing probe, humidity and atmospheric pressure data that are used to derive volumetric water content at two temporal resolutions (hourly and daily). Also included are soil heat flux, air temperature, wind speed and net radiation data which are used to derive potential evapotranspiration at a daily resolution. Full details about this dataset can be found at https://doi.org/10.5285/486f049b-c51b-4496-97e3-1d66137e4296
If you reuse this data, you should cite: COSMOS-UK (2018). Daily and sub-daily hydrometeorological and soil data (2013-2016) [COSMOS-UK] v2. NERC Environmental Information Data Centre https://doi.org/10.5285/486f049b-c51b-4496-97e3-1d66137e4296
This resource is made available under the terms of the Open Government Licence
Hydrometeorological and soil variables are recorded on site and telemetered to a central data system at CEH Wallingford every hour. These data are then loaded to an Oracle database and subject to quality control tests. Soil volumetric water content data are derived from 30 minute hydrometeorological data and data from the cosmic-ray sensing probe by python scripts run every hour and at the end of the day a daily value is calculated. The data are calculated using the method outlined in Evans et al. (2016). Potential evapotranspiration data are derived by python scripts at the end of the day from the hydrometeorological data according to the Penman-Monteith method (FAO 56). See supporting documentation for further information.
High-precision CA-ID-TIMS U-Pb geochronology of zircon from Rio Blanco - Los Bronces Cu Porphyry system
High-precision CA-ID-TIMS (Chemical Abrasion Isotope Dilution Thermal Ionization Mass Spectrometry) Uranium-Lead geochronology of zircon, extracted from igneous plutonic and mineralised porphyry intrusions in the Rio Blanco-Los Bronces Cu Porphyry area, Chile. Eleven parent samples cover an age range of ca. 14 Ma to ca. 5 Ma. Sample Identifiers correspond to the NERC Highlight topic consortium project FAMOS (From Arc Magmas to Ores) samples from the Natural History Museum component of the project and Large et al.(2024) J. Pet, where full rock types, geo-references, petrography, and geochemistry of parent samples can be found in addition to zircon Cathodoluminesence and SEM characterization of zircon of samples, and the corresponding zircon trace element analyses (inclusive of U-Pb) by laser ablation ICPMS. This data provides insights into the crystallisation of zircon and timescales of porphyry copper deposits.
Either: (i) the dataset is made freely available, e.g. via the Internet, for a restricted category of use (e.g. educational use only); or (ii) the dataset has not been formally approved by BGS for access and use by external clients under licence, but its use may be permitted under alternative formal arrangements; or (iii) the dataset contains 3rd party data or information obtained by BGS under terms and conditions that must be consulted in order to determine the permitted usage of the dataset. Refer to the BGS staff member responsible for the creation of the dataset if further advice is required. He / she should be familiar with the composition of the dataset, particularly with regard to 3rd party IPR contained in it, and any resultant use restrictions. This staff member should revert to the IPR Section (ipr@bgs.ac.uk) for advice, should the position not be clear.
The dataset has been formally approved by BGS for access by external clients under a BGS Digital Data Licence, issued via BGS's IPR Section. The dataset must not be provided to, or be accessible by, an external client until the IPR Section confirms that signed licence documentation is in place. Refer to the IPR Section (DigitalLE@bgs.ac.) if further advice is required.. Constraint applies until 2026-01-31
Zircon were analysed by High-precision CA-ID-TIMS (Chemical Abrasion Isotope Dilution Thermal Ionization Mass Spectrometry) Uranium-Lead geochronology methods at the Geochronology and Tracers Facility, British Geological, Keyworth UK.
Maritime and Coastguard Agency (MCA) Bathymetric Survey HI1428, Newarp Banks to Cross Sand, (12/04/2014 to 14/09/2014)
Samples and associated geological data are held at the British Geological Survey for Maritime Coastguard Agency (MCA), Civil Hydrography Programme (CHP), Bathymetric Survey HI1428; Newarp Banks to Cross Sand, Area in SqKm: 448, (12/04/2014 to 14/09/2014), Standard: IHO S44ed5 Order 1a. Contract: Shallow. FY 2014/15. Contractor: Gardline.
Gardline was contracted to undertake the survey on behalf of Maritime and Coastguard Agency. For more detailed information on the acquisition equipment and data collection techniques, operational standards, data processing methods and quality control procedures used on this survey see the Report of Survey/Cruise Report and associated documentation where available. The information available may vary depending on the age of the survey. Data are checked and loaded to the BGS Coastal and Marine data management system following BGS marine data management procedures.
UKCCSRC Call 2 project poster: CO2 Flow Metering through Multi-Modal Sensing and Statistical Data Fusion, UKCCSRC Manchester Biannual Meeting, 13.04.2016
This poster on the UKCCSRC Call 2 project CO2 Flow Metering through Multi-Modal Sensing and Statistical Data Fusion was presented at the UKCCSRC Manchester Biannual Meeting, 13.04.2016. Grant number: UKCCSRC-C2-218.
Either : (i) the dataset has not been formally approved by BGS for access and use by external clients under license; and / or (ii) the dataset contains 3rd party data or information obtained by BGS under terms and conditions that must be consulted before the dataset can be provided to, or accessed by, BGS staff or external clients. Refer to the BGS staff member responsible for the creation of the dataset if further advice is required. He / she should be familiar with the composition of the dataset, particularly with regard to 3rd party IPR contained in it, and any resultant access restrictions. This staff member should revert to the IPR Section (IPR@bgs.ac.uk) for advice, should the position not be clear.
UKCCSRC Call 2 project, grant number: UKCCSRC-C2-218, Lead institution: University of Kent
Density Functional Theory Calculations of Rare Earth Systems (NERC Grant NE/M01147X/1)
This data set contains example input and output files from density functional theory calculations of rare earth systems, using the Vienna Ab initio Simulation Package (VASP), The data set it split into two parts. The first data set contains the input and output files of molecular dynamics simulations of MCl3 in solution, where (M = Nd, Gd and Er) at ambient conditions, which was modelled at 341 K using the optB88 exchange-correlation functional. The calculations were run in order to investigate speciation in rare earth chloride solutions, including trends across the row, using a light (Nd), medium (Gd) and heavy (Er) rare earth. These particular calculations were used to validate classical interatomic potentials that were used to perform more complex simulation on larger systems and longer timescales. Only the first 2 ps of the trajectories are deposited here, since the complete trajectories are large. The second data set contains example input and output files for lattice dynamics calculations of the thermodynamics properties (heat capacity and entropy) of Nd-monazite and Nd-xenotime at ambient conditions up to 1200 K. In addition, it includes scripts for processing and plots of final results. These are useful for thermodynamical modelling of rare earth systems. Only the input and output files for Nd are deposited here, since the files are large and input files for Gd and Er are identical, save for the change in element.
Density functional theory based calculations using VASP, such as geometry optimization, lattice dynamics and equilibrium molecular dynamics
Model metadata report for the Glasgow Geothermal Energy Research Field Site superficial deposits model
Citation Information - Digital Object Identifier (DOI)
NERC EDS Environmental Information Data Centre
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CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.hfls.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.hurs.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.huss.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.mrro.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.mrso.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.mrsos.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.pr.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.prsn.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.psl.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.rlut.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.rsds.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.ta.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.tas.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.tasmax.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.tasmin.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.ua.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.uas.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.va.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.day.vas.gr.v20200821.v20200821 CMIP6.CMIP.EC-Earth-Consortium.EC-Earth3-AerChem.piControl.r1i1p1f1.fx.sftlf.gr.v20200624.v20200624
WCRP CMIP6: the EC-Earth-Consortium team EC-Earth3-AerChem model output for the "piControl" experiment
The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the the EC-Earth-Consortium team EC-Earth3-AerChem model output for the "pre-industrial control" (piControl) experiment. These are available at the following frequencies: 3hr, 6hrPlevPt, AERmon, AERmonZ, Amon, CFmon, Lmon, Oday, Ofx, Omon, SIday, SImon, day and fx. The runs included the ensemble member: r1i1p1f1. CMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6). The the EC-Earth-Consortium team team consisted of the following agencies: La Agencia Estatal de Meteorología (AEMET), Barcelona Supercomputing Centre (BSC), Institute of Atmospheric Sciences and Climate (CNR-ISAC), Danish Meteorological Institute (DMI), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Finnish Meteorological Institute (FMI), Helmholtz Centre for Ocean Research Kiel (Geomar), Irish Centre for High-End Computing (ICHEC), International Centre for Theoretical Physics (ICTP), Instituto Dom Luiz (IDL), Institute for Marine and Atmospheric research Utrecht (IMAU), Portuguese Institute for Sea and Atmosphere (IPMA), KIT Karlsruhe Institute of Technology, Royal Netherlands Meteorological Institute (KNMI), Lund University, Met Eireann, The Netherlands eScience Center (NLeSC), Norwegian University of Science and Technology (NTNU), University of Oxford, SURFsara, Swedish Meteorological and Hydrological Institute (SMHI), Stockholm University, Unite ASTR, University College Dublin, University of Bergen, University of Copenhagen, University of Helsinki, University of Santiago de Compostela, Uppsala University, University of Utrecht, Vrije Universiteit Amsterdam and Wageningen University. The official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record.
Public data: access to these data is available to both registered and non-registered users.
Under the following licence https://artefacts.ceda.ac.uk/licences/specific_licences/CMIP6_Terms_of_Use.pdf, appropriate use of these data may fall under unclassified use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were produced and verified by the EC-Earth-Consortium team scientists before publication via the Earth Systems Grid Federation (ESGF) and a copy obtained by the Centre for Environmental Data Analysis (CEDA).
CMIP6 ES-Doc ensemble member r1i1p1f1 entry for the piControl run with EC-Earth3-AerChem model.
Detailed experiment description for: "pre-industrial control" (piControl)
Official CMIP6 DOI Citation: EC-Earth Consortium (EC-Earth) (2020). EC-Earth-Consortium EC-Earth3-AerChem model output prepared for CMIP6 CMIP piControl. Version YYYYMMDD*.Earth System Grid Federation. https://doi.org/10.22033/ESGF/CMIP6.4843
NERC EDS Centre for Environmental Data Analysis
La Agencia Estatal de Meteorología (AEMET)
Institute of Atmospheric Sciences and Climate (CNR-ISAC)
Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA)
Helmholtz Centre for Ocean Research Kiel (Geomar)
Irish Centre for High-End Computing (ICHEC)
International Centre for Theoretical Physics (ICTP)
Institute for Marine and Atmospheric research Utrecht (IMAU)
Portuguese Institute for Sea and Atmosphere (IPMA)
Royal Netherlands Meteorological Institute (KNMI)
Norwegian University of Science and Technology (NTNU)
Swedish Meteorological and Hydrological Institute (SMHI)