The data are NetCDF formatted and adhere to v1.0 of the CF data conventions.
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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 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.
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.
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.