The data are projected future still water return levels. The data were produced by the Met Office using projections of future mean sea level change prepared at the Met Office and estimates of present-day still water return levels which were provided by the Environment Agency. The data were produced as a simple indication of the relative sizes and uncertainties in present day extreme water levels and projected future mean sea level change. The data were produced by combining projections of mean sea level change with best estimates of present day extreme still water levels. The data in marine strand 4.09 cover the period from 2020 to 2100 and are available for 46 UK tide gauge locations. Further information on this dataset and UKCP18 can be found in the documentation section.

The data are projected future still water return levels. The data were produced by the Met Office using projections of future mean sea level change prepared at the Met Office and estimates of present-day still water return levels which were provided by the Environment Agency. The data were produced as a simple indication of the relative sizes and uncertainties in present day extreme water levels and projected future mean sea level change. The data were produced by combining projections of mean sea level change with best estimates of present day extreme still water levels. The data in marine strand 4.10 cover the period from 2100 to 2300 and are available for 46 UK tide gauge locations. Further information on this dataset and UKCP18 can be found in the documentation section.

This data file contains two sets of optimised global surface fluxes of ethane (C2H6), produced through variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. Emissions were produced using an iterative method of optimisation, known as 4D-Var, which minimised the model-observation differences. These surface fluxes are produced as monthly mean values on the (approximately) 5.6 degree horizontal model grid. The associated uncertainty for the flux from each gridcell is also included. The fluxes and uncertainties are global, and cover the period Jan 2008 - Dec 2014. There are two alternative emissions sets, labelled EMIS_ALL and EMIS_ANTH, whilst the uncertainties are labelled ERROR_ALL and ERROR_ANTH, respectively. The two optimised emission estimates are produced through iterative minimisation of model-observation error in INVICAT. In all cases the observations are surface flask samples of ethane produced by by the National Oceanic and Atmospheric Administration’s Global Monitoring Division (NOAA GMD) and the University of Colorado’s Institute of Arctic and Alpine Research (INSTAAR). Whole air samples in flasks are collected weekly to bi-weekly at each site and C2H6 is measured using gas chromatography with a flame ionization detection method. The EMIS_ALL fluxes are produced through variation of all surface emission types (anthropogenic, biomass burning, oceanic and biospheric), whilst the EMIS_ANTH fluxes are produced by only allowing the surface anthropogenic emissions to vary, with prior estimates of other emission types then added back on. Flux and uncertainty units are kg(C2H6)/m2/s, and time units are days since January 1st 2008. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in the PDF documentation stored along side this data, as well as in Monks et al., 2018.

The data are simulated 21st century trends in the one-year return level (i.e. the location parameter) of skew surge due to simulated atmospheric storminess change only. No mean sea level change is included. The data were produced to investigate the magnitude of this component of extreme sea level change and to give an estimate of the minimum uncertainty in this component. To produce the data, atmospheric storminess data from five CMIP5 models was downscaled by the Swedish Meteorological and Hydrological Institute regional climate model RCA4 and used to drive the National Oceanography Centre/Met Office storm surge model CS3. The 5 largest simulated skew surges in each year were identified and a 4-parameter joint probability distribution (including a linear trend in location parameter over time) was fitted. The data given here are the trends in the location parameter from 2007 to 2099. By construction the scale parameter does not change and so the same trend applies to all return periods. The data covers the UK coast. Further information on this dataset and UKCP18 can be found in the documentation section.

The UKCP18 21st century sea level projections are provided as spatially a continuous dataset around the UK coastline. The projections are rooted in CMIP5 climate model simulations and the process-based methods described in IPCC AR5 (Church et al, 2013). The data consist of annual time series of the projected change in the time-mean coastal water level relative to the average value for the period 1981-2000. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). Nine percentiles are provided to characterise the projection uncertainty. The 5th, 50th and 95th percentiles are equivalent to the IPCC AR5 lower, central, and upper estimate of projected sea level change, based on underlying modelling uncertainty. Further information on this dataset and UKCP18 can be found in the documentation section. This dataset was updated in March 2023 to correct a minor processing error in the earlier version of the UKCP18 site-specific sea level projections relating to the adjustment applied to convert from the IPCC AR5 baseline of 1986-2005 to the baseline period of 1981-2000. The update results in about a 1 cm increase compared to the original data release for all UKCP18 site-specific sea level projections at all timescales. Further details can be found in the accompanying technical note.

The UKCP18 exploratory extended time-mean sea level projections are provided as spatially a continuous dataset around the UK coastline for the period 2007-2300. These exploratory projections have been devised to be used seamlessly with the UKCP18 21st Century projections and provide very similar values for the period up to 2100. Users should be aware that post-2100 projections have a far greater degree of uncertainty than the 21st Century projections and should therefore be treated as illustrative of the potential future changes. Note that we cannot rule out substantially larger sea level rise in the coming centuries than is represented in the projections presented here. The data consist of annual time series of the projected change in the time-mean coastal water level relative to the average value for the period 1981-2000. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). As with the 21st Century projections, nine percentiles are provided to characterise the projection uncertainty, based on underlying modelling uncertainty. However, users should view these uncertainties with a much lower degree of confidence for the period post-2100. Further information on this dataset and UKCP18 can be found in the documentation section. This dataset was updated in March 2023 to correct a minor processing error in the earlier version of the UKCP18 site-specific sea level projections relating to the adjustment applied to convert from the IPCC AR5 baseline of 1986-2005 to the baseline period of 1981-2000. The update results in about a 1 cm increase compared to the original data release for all UKCP18 site-specific sea level projections at all timescales. Further details can be found in the accompanying technical note.

Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the local meteorological conditions. This classification system is designed to identify cirrus clouds by the cloud formation mechanism. Using re-analysis and satellite data, cirrus clouds are separated in four main types: orographic, frontal, convective and synoptic. Comparisons with convection-permitting model simulations and back-trajectory based analysis have shown that this classification can provide useful information on the cloud scale updraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and a greater occurrence of liquid-origin ice compared to the synoptic regimes (see description paper). This classification is designed to be easily implemented in global climate models - the observational classification results are made available make this comparison easier. The classification has been generated globally for the years 2003-2013 inclusive. Making use of the moderate resolution imaging spectrometer (MODIS) on-board the Aqua satellite, the classification exists only at 13:30 local solar time each day. The regimes used within this classification are defined as follows (further details are given in the description paper) Orographic - proximity to regions of large-scale topography variation Frontal - satellite detected cirrus clouds that intersect to atmospheric fronts determined from reanalysis data Convective - satellite detected cirrus clouds in regions of large scale ascent determined from reanalysis data Synoptic - Not assigned as one of the other regimes. Data are gridded NetCDF V4 files, provided on a regular longitude-latitude grid at a 1 by 1 degree resolution across the whole globe. The files provide the classification at 13:30 local solar time (the satellite overpass time) and are at a daily resolution, within a folder defining the year. The filename structure is: {year}/IC-CIR.{year}.{day_of_year}.v1.nc where {year} is the year of the data and {doy of year} starts with 001 on the first of January. Further details about the data, including comparisons to convection-resolving model simulations can be found in the description paper (Gryspeerdt et al., ACP, 2018).

This v2.0 SST_cci Advanced Very High Resolution Radiometer (AVHRR) level 3 uncollated data (L3U) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 - 12/2016. This Level 3 Uncollated (L3U) product provides these SST data on a 0.05 regular latitude-longitude grid with a single orbit per file. The dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .

This dataset provides global clear-sky ice surface temperature data derived from infrared satellite measurements, with estimates of the uncertainty components included. It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques. The data provided here is Level 2 ice surface temperature data from the AVHRR (Advanced Very High Resolution Radiometer) series of satellite instruments, provided on the original satellite swath. This original AASTI (Arctic and Antarctic Ice Surface Temperatures from thermal infrared satellite sensors ) was produced under the EU NACLIM and the NORMAP projects; This version of the dataset has been extended under the EUSTACE (EU Surface Temperature for All Corners of Earth) project to also include components of uncertainty.

These data were produced to contribute towards the EU ENSEMBLES project. The agzkb model run was a historic anthropogenic experiment. The boundary conditions of this experiment were as follows: Time-varying from 1859 to 2000, well-mixed greenhouse gases (GHGs), ozone emissions datasets, sulphate and carbonaceous aerosols, land surface/vegetation, constant volcanic stratospheric aerosols & Solar irradiance. These data are provided in the Met Office PP format, but tools are available to extract subsets in NetCDF and other formats.