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  • This data file contains processed data derived from the Environment Agency's Ecology and Fish Explorer Macroinvertebrate database. The recorded data is the abundance of freshwater macroinvertebrates taken by the Environment Agency (EA). The data were collected from sites throughout England, between 2002-2019, from March to May, and September to November. Samples were collected using three-minute kick-samples, whereby a net is used to catch invertebrates and debris flowing downstream of an area in a river which is disturbed by a recorder for three minutes. Data before 2002 were excluded as abundance of macroinvertebrates was not recorded widely before this year. The data were originally collected for the purpose of understanding water quality by the Environment Agency. The original EA data contains raw counts of mixed-taxonomic groupings of invertebrates and some diatoms and other taxa, from rivers in England with multiple sampling methodologies. Here, the derived data has been processed in such a way to combine counts at a single taxonomic level (family) containing only taxonomic groups of interest for the research, and the data are limited to one sampling method. Full details about this dataset can be found at https://doi.org/10.5285/f6b9b2b3-1ad0-4ac1-a19b-bb340427fbf1

  • This data set comprises of hourly water quality monitoring and flow data of a site within the River Loddon catchment, UK, from September 2017 to September 2018. Parameters measured were temperature, conductivity, pH, ammonium, turbidity, dissolved oxygen, UV-Vis spectral scan from 197-720nm. Daily samples were also taken at 9am GMT and occasional storm samples were taken hourly and then analysed in the laboratory for pH, conductivity, turbidity, total suspended solids, non-purgeable organic carbon, UV-Vis spectral scan from 200-800nm and 12 pesticide concentrations: 2-4-D, Bentazone, Carbendazim, Carbetamide, Chlorotoluron, Clopyralid, MCPA, Mecoprop, Metaldehyde, Propyzamide, Quinmerac and Metazachlor. This data was created as part of the TWENTY65 project, funded by the Engineering and Physical Sciences Research Council (Grant number: EP/N010124/1) and with some additional funding from Affinity Water and Syngenta. Full details about this dataset can be found at https://doi.org/10.5285/331659d7-da72-48a2-9b52-63c003557990

  • The UK Climate Projections 2009 (UKCP09) projections of temperature from low, medium and high emissions scenarios' equivalent global temperature changes. They are probabilistic climate predictions based on families of runs of the Met Office Hadley Centre climate models HadCM3, HadRM3 and HadSM3, plus climate models from other climate centres contributing to IPCC AR4 and CMIP3. The equivalent changes in global temperatures are taken from three emissions scenarios: low (IPCC SRES: B1), medium (IPCC SRES: A1B), and high (IPCC SRES: A1FI). Each scenario provides estimates over seven 30 year period averages: 2010-2039, 2030s = 2020-2049, 2040s = 2030-2059, 2050s = 2040-2069, 2060s = 2050-2079, 2070s = 2060-2089, 2080s = 2070-2099. Temperature changes are given relative to 1961-1990.

  • The UK Climate Projections 2009 (UKCP09) probabilistic marine projections data are projections of a future climate with an associated probability. Monthly and annual data are provided for mean sea level pressure, temperature, precipitation and total cloud cover in 30 year averages (2010-2039, 2020-2049, 2030-2059, 2040-2069, 2050-2079, 2060-2089, 2070-2099). These projections provide an absolute value for the future climate (as opposed to giving values that are relative to a baseline period). A probabilistic climate projection is a measure of the strength of evidence in different future climate change outcomes. This measure is dependent on the method used, is based on the currently available evidence and encapsulates some, but not all, of the uncertainty associated with projecting future climate. The marine and coastal projections report contains further details (see linked documentation).

  • The UK climate projections 2009 (UKCP09) marine and coastal multi-level ocean projections provide detailed information on the potential future implications of climate change on the marine environment in UK waters. Marine parameters are provided for projections of changes in water temperature, salinity, currents and stability of the water column over a 12km marine grid, for the 30 year time period 2070-2099 (and the baseline period 1961-1990) for the medium emissions scenario (IPCC SRES: A1B). Note: The multi-level ocean projections are based on a single model simulation. In contrast to some other components of UKCP09 these are not probabilistic projections, meaning they do not quantify the range of future changes associated with modelling uncertainties or natural climate variability. More information about the variables and methodology (including assumptions and caveats) are given in Chapter 6 of the Marine & coastal projections report (see linked documentation).

  • The UK climate projections 2009 (UKCP09) observed climate provides data for a range of climate variables (for example, temperature, pressure, vapour pressure, rainfall, snowfall, sunshine) over the climate averaging period 1961-1990. The observed data is provided over the UK at grid box resolutions of 25km and 5km. The observed data refers to data that has been directly measured and obtained in UK from a network of synoptic observations and weather stations. These data are commonly processed to convert irregularly spaced point observations to a regular grid. The observed climate data can be used both to explore past climate trends, to construct and validate climate models and to provide a baseline to construct climate differences.

  • The UKCP09 marine & coastal storm surge data provides projections of surge height for the linear trend, the 5th and 95th percentiles throughout the 21st Century for 2, 10, 20 and 50 year return period events (including statistical significance) over a 12km coastal grid. Data are available for a medium emissions scenario (IPCC SRES: A1B), to reflect some aspects of the uncertainty in modelling global and regional climate change eleven different variants of the Met Office Hadley Centre climate model HadCM3 were used to drive eleven corresponding variants of the HadRM3 regional model, which in turn drove the National Oceanography Centre storm surge model (POLCS3). Note: The projections do not cover all plausible future outcomes and unlike some other components of UKCP09, the storm surge height projections are not probabilistic, although a range is provided based on the assumption that the 11 simulations are equally likely. More information about the storm surge methodology (including assumptions and caveats) are given in Chapter 4 of the UKCP09 Marine & coastal projections report and the technical note on storm projections.

  • The UK climate projections (UKCP09) comma separated value (CSV) archive consists of probabilistic data for various climate parameters. Two products are available: firstly, zip files of batch processed UKCP09 data outputs that were provided as an alternative to having to generate multiple requests on the UKCP09 website; and, secondly, additional products that were not available under from the UKCP09 website. These are provided as raw data files. List of products: 1. UK Probabilistic Projections of Climate Change over Land: Grouped by - variable and location and - variable and temporal average. 2. UK Probabilistic Projections of Climate Change over Marine Regions: Grouped by - emissions scenario, - location, - temporal average, - time period, - variable, - variable and location and - variable and temporal average. 3. Projections of Trend in Storm Surge for UK Waters: all data is grouped into one file. 4. Projections of Sea Level Rise for UK Waters: Grouped by - emissions scenario, - location and - emissions scenario and location. 5. Global average temperature change values for each time period and emissions scenario: - all cumulative distribution function (CDF) data in a single file - all sampled data in a single file. 6. UK Probabilistic Projections of Climate Change over Land conditioned by a given global average temperature change: Grouped by - probability level and - variable and probability level 7. Spatially Coherent Projections of UK Climate Change over Land: grouped by variable, temporal average and scenario The file naming convention is provided in the documentation.

  • UK Climate Projections 2009 (UKCP09) sea level rise data provides projections of changes in absolute sea level rise in waters surrounding the UK and changes in relative sea level for coastal areas, where the influence of land movements is considered (and data included here) over the period 1999-2099. Data are provided for three emissions scenarios: Low (IPCC SRES: B1), Medium (IPCC SRES: A1B), and High (IPCC SRES: A1FI). These projections also include a high risk, low probability scenario (known as the H++ scenario). The H++ scenario has been included to reflect the fact that there considerable uncertainties about the upper limit of absolute sea-level rise. This scenario relies, in part, on expert judgement and is designed to encourage users to think about thresholds of existing systems and the limits to adaptation. Note: Unlike some other components of UKCP09, the sea level projections are not probabilistic. They provide a frequency distribution of projections based on results from eleven models contributed to the IPCC Fourth Assessment Report. The model projections of sea level rise have not been weighted based on comparison with historical sea level observations, and are therefore treated as equally plausible. More information about the sea level rise methodology (including assumptions and caveats) is given in Chapter 3 of the Marine & coastal projections report.

  • This data set comprises of hourly physical and nutrient monitoring data of The Cut at Bray Marina (National grid reference SU915786), from May 2010 to February 2012. Parameters measured are total phosphorus, total reactive phosphorus, ammonium, conductivity, temperature, dissolved oxygen, pH and total chlorophyll. The accompanying hourly averaged flow data (from the EA flow gauging station at Binfield, approximately 10 km upstream of the monitoring site) are also supplied. The monitoring programme was funded by the EPSRC, through the LIMPIDS project. Full details about this dataset can be found at https://doi.org/10.5285/abe4dd7c-a340-4595-a57f-8c1446ff7656