The BGS GeoClimate: shrink–swell national datasets show potential change in subsidence due to changes in climate. They have been developed by combining long-term UK Climate Projection (UKCP) scenarios for rainfall and temperature changes with the geotechnical properties of the ground, to identify areas projected to experience the largest increases in susceptibility to subsidence over the next century.GeoClimate UKCP18 Open is provided for two time periods, 2030s and 2070s, with one projection provided for each time period based on the average outcome for the UKCP18 higher emissions scenario and the most susceptible GeoSure value (worst case) within the grid cell.FeaturesGeoClimate UKCP18 OpenUKCP18 emissions scenarioHigher emissions (RCP8.5)Temporal projections (11-year windows)2030s (2025–2035), 2070s (2065–2075)Projections providedMedian averageMore information on the GeoCimate UKCP18 Open Dataset can be found on the BGS website. The GeoClimate data can also be viewed alongside other BGS datasets in the GeoIndex viewer.The GeoClimate UKCP18 Premium dataset is available for purchase.GeoClimate UKCP18 Premium is a quasi-1:50 000-scale product (due to the variable scales of input datasets), provided as area polygons, for two projected 11-year windows, centered on 2030 and 2070. It is based on the UK Climate Projections 2018 (UKCP18) high emissions scenario and provides projections for average, wetter and drier climate conditions. For each scenario it describes five categories of projected susceptibility, from highly unlikely to extremely likely. BGS AGOL home page.

Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. The set of 28 projections is a combination of 15 coupled model simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5 contributed by different climate modelling centres. This data set provides information on changes in climate across the entire globe from 1900 to 2100 for RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across many climate variables at different times and spatial locations. This dataset contains regional averages for 16 administrative regions across the UK.

Shrink-swell is recognised as the most significant geohazard across Great Britain. This dataset identifies areas of shrink-swell hazard with increased potential due to changing climatic conditions based on forecasts derived from the UKCP18 climate projections. The dataset has been created at two levels of detail for RCP8.5 emissions scenario and dates up to 2070. The Basic dataset is an overview at 2Km grid resolution whilst the more detailed Premium dataset is generated at a 50m resolution. The Open versions are simplified versions of the premium versions and are shared via BGS GeoIndex. The premium versions are paid for products. UKCP18 - UK Climate Projections 2018 project RCP8.5 - A pathway where greenhouse gas emissions continue to grow unmitigated, leading to a best estimate global average temperature rise of 4.3°C by 2100. Representative Concentration Pathways (RCPs) are a method for capturing those assumptions within a set of scenarios.

This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate.

The data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 16 administrative regions in the UK is provided.

The Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to.

On 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to.

Enhanced Future Flows and Groundwater (eFLaG) is an 12-member ensemble projection of river flow, groundwater level, and groundwater recharge time series for 200 catchments, 54 boreholes and 558 groundwater bodies in Great Britain and Northern Ireland. It is derived from the UKCP18 dataset, specifically the 'Regional' 12km projections, to which a bias correction is applied. River flows, groundwater level and groundwater recharge data are at a daily time step. To be consistent with the driving meteorological dataset, eFLaG data use a simplified 360-day year, consisting of twelve 30-day months. eFLaG data span from 1981 to 2080. The development of eFLaG was made during the partnership project funded by the Met Office-led component of the Strategic Priorities Fund Climate Resilience programme under contract P107493 (CR19_4 UK Climate Resilience). Full details about this dataset can be found at https://doi.org/10.5285/1bb90673-ad37-4679-90b9-0126109639a9

Derived climate model projections data produced as part of the UK Climate Projections 2018 (UKCP18) project. The data produced by the UK Met Office Hadley Centre provides information on changes in 21st century climate for the UK helping to inform adaptation to a changing climate. The derived climate model projections are estimated using a methodology based on time shift and other statistical approaches applied to a set of 28 projections comprising of 15 coupled simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5. The derived climate model projections exist for the RCP2.6 emissions scenario and for 2°C and 4°C global warming above pre-industrial levels. The derived climate model projections are provided on a 60km spatial grid for the UK region and the projections consist of time series for the RCP2.6 emissions scenario that cover 1900-2100 and a 50 year time series for each of the global warming levels. This dataset contains realisations scenario with global warming stabilised at 4°C

Gridded potential evapotranspiration calculated from United Kingdom Climate Projections 2018 (UKCP18) regional climate model (RCM) ensemble at 12 km resolution over the United Kingdom for the years 1980-2080 under the Representative Concentration Pathway 8.5 (RCP8.5) scenario. This dataset contains two potential evapotranspiration variables: daily total potential evapotranspiration (PET; kg m-2 d-1) and daily total potential evapotranspiration with interception correction (PETI; kg m-2 d-1). PET and PETI were calculated for each member of the UKCP18 RCM perturbed parameter ensemble. The units kg m-2 d-1 are equivalent to mm d-1. The data are provided in gridded netCDF files. There is one file for each variable, for each ensemble member, for each decade. Full details about this dataset can be found at https://doi.org/10.5285/eb5d9dc4-13bb-44c7-9bf8-c5980fcf52a4

GeoClimateUKCP18 provides modelled data on ground movement and subsidence due to climate change for Great Britain. The methodology combines BGS GeoSure, the UKCP18 Representative Concentration Pathway (RCP) 8.5 climate projections, ZOODRM groundwater recharge model and expert knowledge on the behaviour of geological formations.

GeoClimateUKCP18 OPEN provides a 2km generalised vector grid which is populated with the projected effects of climate change on clay shrink-swell susceptibility. For each 11-year window, 2030 (2025-2035) and 2070 (2065-2075) a single dataset illustrating the median average projected change in susceptibility is provided.

National coverage is available for Great Britain.

This dataset contains:

1. Estimates of future and historical daily soil moisture values at 34 locations of the UK COsmic-ray Soil Moisture Observing System (COSMOS-UK) network (three netCDF files starting with "SM"). Each file is for one of the three time periods: 01 December 1980 - 29 November 2000, 01 December 2020 - 29 November 2040 and 01 December 2060 - 29 November 2080. Each file contains data for all 34 locations and 12 UKCP18 ensemble members.
2. Hourly bias-corrected Local (2.2 km) UK Climate Projections 2018 (UKCP18) data (three netCDF files starting with "UKCP18"). Each file is for one of the three time periods: 01 December 1980 - 30 November 2000, 01 December 2020 - 30 November 2040 and 01 December 2060 - 30 November 2080. Each file contains data for all 34 locations, 12 UKCP18 ensemble members and seven variables: specific humidity, precipitation, temperature, downward shortwave radiation, downward longwave radiation, wind speed and atmospheric pressure.
3. Coordinates of the 34 COSMOS-UK locations (csv file).
4. Vegetation information for the considered sites (docx file).

The soil moisture estimates are obtained by first optimising pedotransfer function parameters of the JULES land model and driving the model with bias-corrected 2.2 km UKCP18 data. This dataset was generated and analyzed in article: "Future increases in soil moisture drought frequency at UK monitoring sites: merging the JULES land model with observations and convection-permitting UK Climate Projections", by Magdalena Szczykulska, Chris Huntingford, Elizabeth Cooper and Jonathan G. Evans, which is to be submitted to Environmental Research Letters. Details are given in the above-mentioned article and the corresponding supplementary information.

Standardised Precipitation Index (SPI; McKee et al., 1993) and Standardised Precipitation Evapotranspiration Index (SPEI; Vicente-Serrano et al., 2009) computed from UKCP18 Strand 3 simulations (Met Office Hadley Centre, 2018).

This data was produced for the study by Reyniers et al. (in prep) analysing (diferences in) drought projections using these indicators. The methodology used to produce this data can be found there if/when the paper is accepted, however do not hesitate to reach out with any further questions. Please note the RCM data was bias adjusted prior to SPI and SPEI computation. There is one file per ensemble member containing the full simulated period on a monthly time step, using aggregation periods of 1, 3, 6, 12, 24 and 36 months for the computation of SP(E)I.

References

McKee, T. B., Doesken, N. J., Kleist, J., et al.: The relationship of drought frequency and duration to time scales, in: Proceedings of the 8th Conference on Applied Climatology, vol. 17, pp. 179–183, Boston, 1993

Met Office Hadley Centre (2018): UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080. Centre for Environmental Data Analysis, date of citation. https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604

Reyniers, N., Osborn, T. J., Addor, N., Darch, G.: Projected changes in droughts and extreme droughts in Great
Britain are strongly influenced by the choice of drought index. Hydrology and Earth System Sciences, in prep. for HESS

Vicente-Serrano, S. M., Beguería, S., and López-Moreno, J. I.: A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index, Journal of Climate, 23, 1696–1718, https://doi.org/10.1175/2009JCLI2909.1, 2009.

Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. The projections cover Europe and a 100 year period, 1981-2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. This dataset contains regional averages for 23 river basin regions across the UK.

What does the data show?

This data shows the monthly averages of minimum surface temperature (°C) for 2070-2099 using a combination of the CRU TS (v. 4.06) and UKCP18 global RCP2.6 datasets. The RCP2.6 scenario is an aggressive mitigation scenario where greenhouse gas emissions are strongly reduced.

The data combines a baseline (1981-2010) value from CRU TS (v. 4.06) with an anomaly from UKCP18 global. Where the anomaly is the change in temperature at 2070-2099 relative to 1981-2010.

The data is provided on the WGS84 grid which measures approximately 60km x 60km (latitude x longitude) at the equator.

Limitations of the data

We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.

What are the naming conventions and how do I explore the data?

This data contains a field for each month’s average over the period. They are named 'tmin' (temperature minimum), the month and ‘upper’ ‘median’ or ‘lower’. E.g. ‘tmin Mar Lower’ is the average of the daily minimum temperatures in March throughout 2070-2099, in the second lowest ensemble member.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘tmin Jan Median’ values.

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

To select which ensemble members to use, the monthly averages of minimum surface temperature for the period 2070-2099 were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

Data source

CRU TS v. 4.06 - (downloaded 12/07/22)

UKCP18 v.20200110 (downloaded 17/08/22)

Useful links

Further information on CRU TS Further information on the UK Climate Projections (UKCP) Further information on understanding climate data within the Met Office Climate Data Portal

The dataset contains 2 km resolution gridded daily potential groundwater recharge time series covering the British mainland from the Enhanced Future Flows and Groundwater (eFLaG) project. The data include simulations driven with historical observed climate data (1962-2018) and simulations driven with bias-corrected UKCP18 'Regional' 12km projections. Full details about this dataset can be found at https://doi.org/10.5285/b14839e5-03e0-43ff-9382-1be2daf3baba

What does the data show?

This data shows annual averages of precipitation (mm/day) for 2050-2079 from the UKCP18 regional climate projections. The data is for the high emissions scenario (RCP8.5).

Limitations of the data

We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.

What are the naming conventions and how do I explore the data?

This data contains a field for the average over the period. They are named 'pr' (precipitation), the month, and 'upper' 'median' or 'lower'. E.g. 'pr Median' is the median value.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘pr January Median’ values.

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the annual averages of precipitation for 2050-2079 were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

Data source

pr_rcp85_land-rcm_uk_12km_12_ann-30y_200912-207911.nc (median)

pr_rcp85_land-rcm_uk_12km_05_ann-30y_200912-207911.nc (lower)

pr_rcp85_land-rcm_uk_12km_04_ann-30y_200912-207911.nc (upper)

UKCP18 v20190731 (downloaded 04/11/2021)

Useful links

Further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal

Shrink-swell er anerkendt som den mest betydningsfulde geohazard i Storbritannien. Dette datasæt identificerer områder med risiko for krympe-svulme med øget potentiale som følge af ændrede klimaforhold baseret på prognoser fra UKCP18-klimafremskrivningerne. Datasættet er oprettet på to detaljeringsniveauer for RCP8.5-emissionsscenariet og daterer frem til 2070. Basisdatasættet er et overblik ved 2 km netopløsning, mens det mere detaljerede Premium-datasæt genereres ved en opløsning på 50 m. Open-versionerne er forenklede versioner af premium-versionerne og deles via BGS GeoIndex. Præmieversionerne betales for produkter. UKCP18 - UK Climate Projections 2018 projekt RCP8.5 - En vej, hvor drivhusgasemissionerne fortsætter med at vokse uformindsket, hvilket fører til et bedste skøn over den globale gennemsnitlige temperaturstigning på 4,3 ° C i 2100. Repræsentative koncentrationsveje (RCP'er) er en metode til at opfange disse antagelser inden for et sæt scenarier.

Gridded hydrological model river flow estimates on a 1km grid over Northern Ireland for the period Dec 1980 - Nov 2080. The dataset includes monthly mean river flow, annual maxima of daily mean river flow (water years Oct - Sept), along with the date of occurrence, and annual minima of 7-day mean river flow (years spanning Dec-Nov), along with the date of occurrence (units: m3/s). The data are provided in gridded netCDF files. There is one file for each variable and ensemble member. To aid interpretation, two additional spatial datasets are provided: a) digitally-derived catchment areas and b) estimated locations of flow gauging stations both on the 1km x 1km grid and c) a 1km x 1km grid identifying majority lake cells. The data were produced as part of UK-SCAPE (UK Status, Change And Projections of the Environment, Work Package 2: Case Study - Water) a NERC-funded National Capability Science Single Centre award.

What does the data show?

This data shows the monthly averages of maximum surface temperature (°C) for 2040-2069 using a combination of the CRU TS (v. 4.06) and UKCP18 global RCP2.6 datasets. The RCP2.6 scenario is an aggressive mitigation scenario where greenhouse gas emissions are strongly reduced.

The data combines a baseline (1981-2010) value from CRU TS (v. 4.06) with an anomaly from UKCP18 global. Where the anomaly is the change in temperature at 2040-2069 relative to 1981-2010.

The data is provided on the WGS84 grid which measures approximately 60km x 60km (latitude x longitude) at the equator.

Limitations of the data

We recommend the use of multiple grid cells or an average of grid cells around a point of interest to help users get a sense of the variability in the area. This will provide a more robust set of values for informing decisions based on the data.

What are the naming conventions and how do I explore the data?

This data contains a field for each month’s average over the period. They are named 'tmax' (temperature maximum), the month and ‘upper’ ‘median’ or ‘lower’. E.g. ‘tmax Mar Lower’ is the average of the daily minimum temperatures in March throughout 2040-2069, in the second lowest ensemble member.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘tmax Jan Median’ values.

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

To select which ensemble members to use, the monthly averages of maximum surface temperature for the period 2040-2069 were calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

Data source

CRU TS v. 4.06 - (downloaded 12/07/22)

UKCP18 v.20200110 (downloaded 17/08/22)

Useful links

Further information on CRU TS Further information on the UK Climate Projections (UKCP) Further information on understanding climate data within the Met Office Climate Data Portal

[Updated 28/01/25 to fix an issue in the ‘Lower’ values, which were not fully representing the range of uncertainty. ‘Median’ and ‘Higher’ values remain unchanged. The size of the change varies by grid cell and fixed period/global warming levels but the average difference between the 'lower' values before and after this update is 0.21°C.]What does the data show? This dataset shows the change in winter average temperature for a range of global warming levels, including the recent past (2001-2020), compared to the 1981-2000 baseline period. Here, winter is defined as December-January-February. Note, as the values in this dataset are averaged over a season they do not represent possible extreme conditions.The dataset uses projections of daily average air temperature from UKCP18 which are averaged over the winter period to give values for the 1981-2000 baseline, the recent past (2001-2020) and global warming levels. The warming levels available are 1.5°C, 2.0°C, 2.5°C, 3.0°C and 4.0°C above the pre-industrial (1850-1900) period. The recent past value and global warming level values are stated as a change (in °C) relative to the 1981-2000 value. This enables users to compare winter average temperature trends for the different periods. In addition to the change values, values for the 1981-2000 baseline (corresponding to 0.51°C warming) and recent past (2001-2020, corresponding to 0.87°C warming) are also provided. This is summarised in the table below.PeriodDescription1981-2000 baselineAverage temperature (°C) for the period2001-2020 (recent past)Average temperature (°C) for the period2001-2020 (recent past) changeTemperature change (°C) relative to 1981-20001.5°C global warming level changeTemperature change (°C) relative to 1981-20002°C global warming level changeTemperature change (°C) relative to 1981-20002.5°C global warming level changeTemperature change (°C) relative to 1981-20003°C global warming level changeTemperature change (°C) relative to 1981-20004°C global warming level changeTemperature change (°C) relative to 1981-2000What is a global warming level?The Winter Average Temperature Change is calculated from the UKCP18 regional climate projections using the high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g. decades) for this scenario, the dataset is calculated at various levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), whilst this dataset allows for the exploration of greater levels of warming.The global warming levels available in this dataset are 1.5°C, 2°C, 2.5°C, 3°C and 4°C. The data at each warming level was calculated using a 21 year period. These 21 year periods are calculated by taking 10 years either side of the first year at which the global warming level is reached. This time will be different for different model ensemble members. To calculate the value for the Winter Average Temperature Change, an average is taken across the 21 year period.We cannot provide a precise likelihood for particular emission scenarios being followed in the real world future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected with current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate as it will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.What are the naming conventions and how do I explore the data?These data contain a field for each warming level and the 1981-2000 baseline. They are named 'tas winter change' (change in air 'temperature at surface'), the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. e.g. 'tas winter change 2.0 median' is the median value for winter for the 2.0°C warming level. Decimal points are included in field aliases but not in field names, e.g. 'tas change winter 2.0 median' is named 'tas_winter_change_20_median'. To understand how to explore the data, refer to the New Users ESRI Storymap. Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘tas winter change 2.0°C median’ values.What do the 'median', 'upper', and 'lower' values mean?Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, the Winter Average Temperature Change was calculated for each ensemble member and they were then ranked in order from lowest to highest for each location.The ‘lower’ fields are the second lowest ranked ensemble member. The ‘higher’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and higher fields, the greater the uncertainty.‘Lower’, ‘median’ and ‘upper’ are also given for the baseline period as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past. Useful linksFor further information on the UK Climate Projections (UKCP).Further information on understanding climate data within the Met Office Climate Data Portal.

What does the data show?

The dataset is derived from projections of seasonal mean wind speeds from UKCP18 which are averaged to produce values for the 1981-2000 baseline and two warming levels: 2.0°C and 4.0°C above the pre-industrial (1850-1900) period. All wind speeds have units of metres per second (m / s). These data enable users to compare future seasonal mean wind speeds to those of the baseline period.

What is a warming level and why are they used?

The wind speeds were calculated from the UKCP18 local climate projections which used a high emissions scenario (RCP 8.5) where greenhouse gas emissions continue to grow. Instead of considering future climate change during specific time periods (e.g., decades) for this scenario, the dataset is calculated at two levels of global warming relative to the pre-industrial (1850-1900) period. The world has already warmed by around 1.1°C (between 1850–1900 and 2011–2020), so this dataset allows for the exploration of greater levels of warming.

The global warming levels available in this dataset are 2°C and 4°C in line with recommendations in the third UK Climate Risk Assessment. The data at each warming level were calculated using 20 year periods over which the average warming was equal to 2°C and 4°C. The exact time period will be different for different model ensemble members. To calculate the seasonal mean wind speeds, an average is taken across the 20 year period. Therefore, the seasonal wind speeds represent those for a given level of warming.

We cannot provide a precise likelihood for particular emission scenarios being followed in the real world in the future. However, we do note that RCP8.5 corresponds to emissions considerably above those expected under current international policy agreements. The results are also expressed for several global warming levels because we do not yet know which level will be reached in the real climate; the warming level reached will depend on future greenhouse emission choices and the sensitivity of the climate system, which is uncertain. Estimates based on the assumption of current international agreements on greenhouse gas emissions suggest a median warming level in the region of 2.4-2.8°C, but it could either be higher or lower than this level.

What are the naming conventions and how do I explore the data?

The columns (fields) correspond to each global warming level and two baselines. They are named 'windspeed' (Wind Speed), the season, warming level or baseline, and ‘upper’ ‘median’ or ‘lower’ as per the description below. For example, ‘windspeed winter 2.0 median’ is the median winter wind speed for the 2°C projection. Decimal points are included in field aliases but not field names; e.g., ‘windspeed winter 2.0 median’ is ‘ws_winter_20_median’.

To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578

What do the ‘median’, ‘upper’, and ‘lower’ values mean?

Climate models are numerical representations of the climate system. To capture uncertainty in projections for the future, an ensemble, or group, of climate models are run. Each ensemble member has slightly different starting conditions or model set-ups. Considering all of the model outcomes gives users a range of plausible conditions which could occur in the future.

For this dataset, the model projections consist of 12 separate ensemble members. To select which ensemble members to use, seasonal mean wind speeds were calculated for each ensemble member and then ranked in order from lowest to highest for each location.

The ‘lower’ fields are the second lowest ranked ensemble member. The ‘upper’ fields are the second highest ranked ensemble member. The ‘median’ field is the central value of the ensemble.

This gives a median value, and a spread of the ensemble members indicating the range of possible outcomes in the projections. This spread of outputs can be used to infer the uncertainty in the projections. The larger the difference between the lower and upper fields, the greater the uncertainty.

‘Lower’, ‘median’ and ‘upper’ are also given for the baseline periods as these values also come from the model that was used to produce the projections. This allows a fair comparison between the model projections and recent past.

Data source

The seasonal mean wind speeds were calculated from daily values of wind speeds generated from the UKCP Local climate projections; they are one of the standard UKCP18 products. These projections were created with a 2.2km convection-permitting climate model. To aid comparison with other models and UK-based datasets, the UKCP Local model data were aggregated to a 5km grid on the British National grid; the 5km data were processed to generate the seasonal mean wind speeds.

Useful links

Further information on the UK Climate Projections (UKCP). Further information on understanding climate data within the Met Office Climate Data Portal.

[THIS DATASET HAS BEEN WITHDRAWN]. Gridded hydrological model river flow estimates on a 1km grid over Great Britain for the period Dec 1980 - Nov 2080. The dataset includes monthly mean river flow, annual maxima of daily mean river flow (water years Oct - Sept), along with the date of occurrence, and annual minima of 7-day mean river flow (years spanning Dec-Nov), along with the date of occurrence (units: m3/s). The data are provided in gridded netCDF files. There is one file for each variable and ensemble member. To aid interpretation, two additional spatial datasets are provided: a) digitally-derived catchment areas and b) estimated locations of flow gauging stations both on the 1km x 1km grid. The data were produced as part of UK-SCAPE (UK Status, Change And Projections of the Environment; www.ceh.ac.uk/ukscape, Work Package 2: Case Study – Water) programme, a NERC-funded National Capability Science Single Centre award number NE/R016429/1. Full details about this dataset can be found at https://doi.org/10.5285/b7a98440-8742-40d5-a518-46dc6420416e