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This dataset contains weather conditions, water quality, water chemistry and crustacean zooplankton counts sampled at Loch Leven throughout the year 2019. Loch Leven is a lowland lake in Scotland, United Kingdom. The data were collected as part of a long-term monitoring programme, which began in 1968 and is still underway. Sampling occurs roughly every 2 weeks with laboratory analysis and data processing being performed at the UK Centre for Ecology & Hydrology Edinburgh site. The sampling and processing has been performed under the UK-SCAPE project. Full details about this dataset can be found at https://doi.org/10.5285/e404f64c-ddbc-4e3e-8dca-9bea3d68959a
This is a dataset of environmental variables, total invertebrate abundance, and mean invertebrate body mass, sampled at 60 soil habitat patches in the Hengill geothermal valley, Iceland, from May to July 2015. The habitat patches span a temperature gradient of 5-22 °C on average over the sampling period, yet they occur within 2 km of each other and have similar soil moisture, pH, total carbon, and total nitrogen. Full details about this dataset can be found at https://doi.org/10.5285/e00770f3-4acf-4fd5-ba29-0a4dbdca09a4
The BGS Permeability data product shows estimated rates of water movement from the ground surface to the water table. BGS Permeability version 8 incorporates the latest geology mapping (BGS Geology 50k). This includes updates to the lithology-coding schema, the LEX_RCS. A 2-part code used to identify the named rock unit from the BGS lexicon of named rock units (LEX) followed by a Rock Classification Scheme (RCS) code which describes the rocks lithological characteristics e.g. texture and composition. Updates to these codes and latest dissolution hazard data sourced from BGS GeoSure: Soluble Rocks have been reviewed and classified as part of the version 8 release. The product covers Great Britain and is presented at a scale of 1:50 000, based on the geological data at the same scale. However, in areas where the geology is not mapped to this scale, the next best available scale is used. The BGS Permeability data product can be used to compare the relative permeability of deposits at the regional scale, indicating where highly permeable rocks could allow rapid infiltration to occur, or where less permeable rocks are present and water could pond on the ground surface. The dataset can be used as a component in a wide range of geo-environmental assessments such as natural flood management, Sustainable Drainage Systems, engineering desk studies, slope stability, and aquifer vulnerability. It is for use at the regional scale and is not recommended for use at the site-specific scale.
The BGS Permeability Index dataset shows estimated rates of water movement from the ground surface to the water table. The v8 dataset incorporates the latest geology mapping (BGS Geology 50k). This includes updates to the lithology-coding schema, the LEX_RCS. A 2-part code used to identify the named rock unit from the BGS lexicon of named rock units (LEX) followed by a Rock Classification Scheme (RCS) code which describes the rocks lithological characteristics e.g. texture and composition. Updates to these codes and latest dissolution hazard data sourced from BGS GeoSure: Soluble Rocks have been reviewed and classified as part of the version 8 release. The dataset covers Great Britain and is presented at a scale of 1:50 000, based on the geological data at the same scale. However, in areas where the geology is not mapped to this scale, the next best available scale is used. The BGS Permeability Index can be used to compare the relative permeability of deposits at the regional scale, indicating where highly permeable rocks could allow rapid infiltration to occur, or where less permeable rocks are present and water could pond on the ground surface. The dataset can be used as a component in a wide range of geo-environmental assessments such as natural flood management, Sustainable Drainage Systems, engineering desk studies, slope stability, and aquifer vulnerability. It is for use at the regional scale and is not recommended for use at the site-specific scale.
This dataset provides a version of the Cloud_cci AVHRR-AMv3 monthly gridded dataset in Obs4MIPs format. The Cloud_cci AVHRR-AMv3 dataset (covering 1991-2016) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is based on intercalibrated measurements from the Advanced Very High Resolution Radiometer (AVHRR) sensors on-board the NOAA prime morning (AM) satellite NOAA-12,-15,-17, and the EUMETSAT Metop-A satellite. It contains a multi-annual, global dataset of cloud and radiation properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval framework. This particular Obs4MIPS product has been generated for inclusion in Obs4MIPs (Observations for Model Intercomparisons Project), which is an activity to make observational products more accessible for climate model intercomparisons. Individual files are provided covering seven cloud variables: Cloud area fraction in atmospheric layer (clCCI); Atmospheric cloud ice content (clivi); Cloud area fraction (cltCCI); Liquid water cloud area fraction in atmospheric layer(clwCCI); Liquid water cloud area fraction (clwtCCI); Atmosphere mass content of cloud condensed water (clwvi); Air pressure at cloud top (pctCCI)
This dataset contains ERA5 initial release (ERA5t) model level analysis parameter data. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record. Surface level analysis and forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.
The study in three coal mining regions: Lower Silesia, Upper Silesia and Lublin (each N=500) was conducted using Computer Assisted Web Interview (CAWI). The questionnaire includes the block of questions concerning mine water awareness, climate change and local/place attachment. The survey online took 15 to 20 minutes and was prepared after in-depth pilot research among participants with different education level from the mining regions. We used the uninformed approach to the survey, so there were no additional questions nor requirements for participants prior to the survey. Since the mine water energy extraction is a technical issue that is neither well known nor commonly used in the narratives of Poles, we tested survey questions with pilot cognitive interviews to remove the technical language and reduce the number of replies without understanding. The interviews were conducted with 10 participants in July 2020 and due to the pilot's recommendations and results, we implemented additional changes in the final version of the questionnaire. Specifically, some questions were simplified and the background information on mine water extraction was simplified and shortened The survey CAWI was completed by adult people aged 18-65 (N=1500) between 14-19 August 2020 by Kantar Research Agency. The sample was constructed using KANTAR’s internet panel profiled for the basic demographics, such as gender, age, and the town size. Particular attention paid to the quality of the panel is reflected in its structure. Kantar’s internet panel reflects the profile of the Polish population of Internet users in terms of its participants’ demographic characteristics. The sample from each region was 500 respondents and among the full sample (N=1500) we reached only 192 people who chose to call “mining areas” as best description of the area where they live. Although the three voivodships were chosen due to its mining industry the selected sample covers the region in general in which mining communities are statically not fully represented. We also asked about the subjective perception of the area respondents live in, which we further analysed with spatial distribution. The dataset was created within SECURe project (Subsurface Evaluation of CCS and Unconventional Risks) - https://www.securegeoenergy.eu/. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 764531
The National Centre for Earth Observation (NCEO) Long Term Science Single Centre (LTSS) Global Ocean Lagrangian Trajectories (OLTraj) provides 30-day forward and backward Lagrangian trajectories based on AVISO (Satellite Altimetry Data project) surface velocities. Each trajectory represents the path that a water mass would move along starting at a given pixel and a given day. OLTraj can be thus used to implement analyses of oceanic data in a Lagrangian framework. The purpose of OLTraj is to allow non-specialists to conduct Lagrangian analyses of surface ocean data. The dataset has global coverage and spans 1998-2018 with a daily temporal resolution. The trajectories were generated starting from zonal and meridional model velocity fields that were integrated using the LAMTA (6-hour time step - part of ) as described in Nencioli et al., 2018 and SPASSO (Software package for and adaptive satellite-based sampling for ocean graphic cruises containing LAMTA) software user guide. Please see the documentation section below for further information.
The UK Geoenergy Observatories (UKGEOS) Glasgow baseline surface water chemistry dataset1 released from the BGS comprises an excel file with two spreadsheets. The first spreadsheet contains information on the chemical composition of 98 surface water samples (84 samples and 14 field duplicates) collected monthly for 14 months between February 2019 and March 2020 from six sampling locations. These comprised three on the River Clyde at the UKGEOS Glasgow Cuningar Loop borehole cluster and three from control sites (two on the River Clyde and one on the Tollcross Burn). Field measurements of pH, redox potential, specific electrical conductance, temperature, dissolved oxygen and alkalinity and laboratory chemical data for concentrations of 71 inorganic and 10 organic substances in the surface water samples are presented. The dataset contains locational and descriptive information about the samples also. The analyte name, element chemical symbols, analytical method, units of measurement and long-term limits of detection are recorded in header rows at the top of the spreadsheet. The limits of detection/quantification for each monthly batch of samples are documented in rows at the head of each batch. The dataset includes abbreviations documenting quality control issues such as missing values. A guide to abbreviations used in the dataset is provided in the second excel spreadsheet released with the data. Further details about the dataset can be found in the accompanying report http://nora.nerc.ac.uk/id/eprint/529818.
2020 data consists of high frequency (100 Hz) data from two horizontal induction coils measuring the Earth's magnetic field at the Eskdalemuir Observatory in the United Kingdom (Location in Geographic Coordinates: 55.314° N 356.794° E and Elevation: 245m above mean sea level).