Site specific (293 individual stations) monthly average (1981 - 2010) The data consists of: Max Temp (degrees C) Min Temp (degrees C) Sunshine (hours) Rainfall (mm) Raindays >=1.0mm (days) Days of Air Frost (days) Monthly mean wind speeds at 10m (knots) District and Region monthly average (1961-1990, 1971-2000, 1981-2010) The data consists of: Max Temp (degrees C) Min Temp (degrees C) Sunshine (hours) Rainfall (mm) Raindays >=1.0mm (days) Days of Air Frost (days) UK monthly average (1961-1990, 1971-2000, 1981-2010) The data consists of: Max Temp (degrees C) Min Temp (degrees C) Sunshine (hours) Rainfall (mm) Raindays >=1.0mm (days) Days of Air Frost (days)

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

HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.

The gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.

This data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).

The changes for v1.3.0.ceda HadUK-Grid datasets are as follows:

• Added data for calendar year 2023

• Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)

• Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)

• Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)

• Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)

• The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.

• For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).

• For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.

• For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.

• We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.

• Net changes to the input station data:

• Total of 126970983 observations

• 125384735 (98.75%) unchanged

• 28487 (0.02%) modified for this version

• 1557761 (1.23%) added in this version

• 188522 (0.15%) deleted from this version

The primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project "Analysis of historic drought and water scarcity in the UK"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.

Site specific (293 individual stations) monthly average (1981 - 2010)

        The data consists of:
        Max Temp (degrees C) 
        Min Temp (degrees C) 
        Sunshine (hours) 
        Rainfall (mm) 
        Raindays >=1.0mm (days) 
        Days of Air Frost (days) 
        Monthly mean wind speeds at 10m (knots)

        District and Region monthly average (1961-1990, 1971-2000, 1981-2010)

        The data consists of:
        Max Temp (degrees C) 
        Min Temp (degrees C) 
        Sunshine (hours) 
        Rainfall (mm) 
        Raindays >=1.0mm (days) 
        Days of Air Frost (days)

        UK monthly average (1961-1990, 1971-2000, 1981-2010)

        The data consists of:
        Max Temp (degrees C) 
        Min Temp (degrees C) 
        Sunshine (hours) 
        Rainfall (mm) 
        Raindays >=1.0mm (days) 
        Days of Air Frost (days)

According to a 2024 survey conducted among UK residents, almost 80 percent had some concern about climate change. In comparison, 19 percent were not concerned, with four percent of those having no concerns at all. The survey was conducted by the Department for Business, Energy & Industrial Strategy (BEIS) as part of its Net Zero and Climate Change Public Attitudes Tracker. Climate change causesIn a recent BEIS survey, it was found that 38 percent of respondents believed climate change is mainly caused by human activity. 13 percent believed it is caused entirely by human activity, whilst one percent felt that there is no such thing as climate change. Climate change is the term used for global weather phenomena which results in new weather patterns, increasing global temperatures. This term also includes the climate effects these increasing temperatures cause. A move towards green energyOver the last decade, electricity generation from renewable sources in the UK has increased significantly, surpassing 122 terawatt-hours in 2021. In the same period of time, the UK has seen its greenhouse gas emissions decrease by nearly 30 percent – from approximately 609 MtCO2e in 2010 to 427 MtCO2e in 2021.

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.

For the purposes of this lesson and those that follow, a specimen data (Monthly Maximum Air Temperatures for 2019 at the 25km resolution) taken from from the HadUK-Grid archive and published as a Feature Layer in ArcGIS OnlineIn this activity we will see how to search ArcGIS Online for data and add it to the Map Viewer.

This data set was created using data from Copernicus for MEI's Big Earth Data Project.

MEI has developed resources to help students develop skills in exploring large Earth observation datasets while teaching them about the measurements satellites can take.

There are three sets of resources covering the ozone layer, climate change and flooding risks.

[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 0.0.]What does the data show? The Annual Count of Extreme Summer Days is the number of days per year where the maximum daily temperature is above 35°C. It measures how many times the threshold is exceeded (not by how much) in a year. Note, the term ‘extreme summer days’ is used to refer to the threshold and temperatures above 35°C outside the summer months also contribute to the annual count. The results should be interpreted as an approximation of the projected number of days when the threshold is exceeded as there will be many factors such as natural variability and local scale processes that the climate model is unable to represent.The Annual Count of Extreme Summer Days is calculated for two baseline (historical) periods 1981-2000 (corresponding to 0.51°C warming) and 2001-2020 (corresponding to 0.87°C warming) and for global warming levels of 1.5°C, 2.0°C, 2.5°C, 3.0°C, 4.0°C above the pre-industrial (1850-1900) period. This enables users to compare the future number of extreme summer days to previous values.What are the possible societal impacts?The Annual Count of Extreme Summer Days indicates increased health risks, transport disruption and damage to infrastructure from high temperatures. It is based on exceeding a maximum daily temperature of 35°C. Impacts include:Increased heat related illnesses, hospital admissions or death affecting not just the vulnerable. Transport disruption due to overheating of road and railway infrastructure.Other metrics such as the Annual Count of Summer Days (days above 25°C), Annual Count of Hot Summer Days (days above 30°C) and the Annual Count of Tropical Nights (where the minimum temperature does not fall below 20°C) also indicate impacts from high temperatures, however they use different temperature thresholds.What is a global warming level?The Annual Count of Extreme Summer Days 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 Annual Count of Extreme Summer Days, an average is taken across the 21 year period. Therefore, the Annual Count of Extreme Summer Days show the number of extreme summer days that could occur each year, for each given level of warming. 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?This data contains a field for each global warming level and two baselines. They are named ‘ESD’ (where ESD means Extreme Summer Days, the warming level or baseline, and ‘upper’ ‘median’ or ‘lower’ as per the description below. E.g. ‘Extreme Summer Days 2.5 median’ is the median value for the 2.5°C warming level. Decimal points are included in field aliases but not field names e.g. ‘Extreme Summer Days 2.5 median’ is ‘ExtremeSummerDays_25_median’. To understand how to explore the data, see this page: https://storymaps.arcgis.com/stories/457e7a2bc73e40b089fac0e47c63a578Please note, if viewing in ArcGIS Map Viewer, the map will default to ‘ESD 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 Annual Count of Extreme Summer Days 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 ‘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. Useful linksThis dataset was calculated following the methodology in the ‘Future Changes to high impact weather in the UK’ report and uses the same temperature thresholds as the 'State of the UK Climate' report.Further information on the UK Climate Projections (UKCP).Further information on understanding climate data within the Met Office Climate Data Portal.

The highest average temperature recorded in 2024 until November was in August, at 16.8 degrees Celsius. Since 2015, the highest average daily temperature in the UK was registered in July 2018, at 18.7 degrees Celsius. The summer of 2018 was the joint hottest since institutions began recording temperatures in 1910. One noticeable anomaly during this period was in December 2015, when the average daily temperature reached 9.5 degrees Celsius. This month also experienced the highest monthly rainfall in the UK since before 2014, with England, Wales, and Scotland suffering widespread flooding. Daily hours of sunshine Unsurprisingly, the heat wave that spread across the British Isles in 2018 was the result of particularly sunny weather. July 2018 saw an average of 8.7 daily sun hours in the United Kingdom. This was more hours of sun than was recorded in July 2024, which only saw 5.8 hours of sun. Temperatures are on the rise Since the 1960s, there has been an increase in regional temperatures across the UK. Between 1961 and 1990, temperatures in England averaged nine degrees Celsius, and from 2013 to 2022, average temperatures in the country had increased to 10.3 degrees Celsius. Due to its relatively southern location, England continues to rank as the warmest country in the UK.

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
2. variable and location and

3. variable and temporal average.

4. UK Probabilistic Projections of Climate Change over Marine Regions: Grouped by

5. emissions scenario,

6. location,

7. temporal average,

8. time period,

9. variable,

10. variable and location and

11. variable and temporal average.

12. Projections of Trend in Storm Surge for UK Waters: all data is grouped into one file.

13. Projections of Sea Level Rise for UK Waters: Grouped by

14. emissions scenario,

15. location and

16. emissions scenario and location.

17. Global average temperature change values for each time period and emissions scenario:

18. all cumulative distribution function (CDF) data in a single file

19. all sampled data in a single file.

20. UK Probabilistic Projections of Climate Change over Land conditioned by a given global average temperature change: Grouped by

21. probability level and

22. variable and probability level

23. 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.

The annual mean temperature in the United Kingdom has fluctuated greatly since 1990. Temperatures during this period were at their highest in 2025, surpassing ** degrees Celsius. In 2010, the mean annual temperature stood at **** degrees, the lowest recorded during this time. Daily temperatures Average daily temperatures have remained stable since the turn of the century, rarely dropping below ** degrees Celsius. In 2010, they dropped to a low of **** degrees Celsius. The peak average daily temperature was recorded in 2022 when it reached **** degrees. This was an increase of *** degree Celsius compared to the long-term mean, and the most positive deviation during the period of consideration. Highs and lows The maximum average temperature recorded across the UK since 2015 was in July 2018. This month saw a maximum temperature of **** degrees Celsius. In comparison, the lowest monthly minimum temperature was in February of the same year, at just minus *** degrees. This was an especially cold February, as the previous year the minimum temperature for this month was *** degrees.

[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 0.26°C.]What does the data show? This dataset shows the change in summer maximum air temperature for a range of global warming levels, including the recent past (2001-2020), compared to the 1981-2000 baseline period. Here, summer is defined as June-July-August. The dataset uses projections of daily maximum air temperature from UKCP18. For each year, the highest daily maximum temperature from the summer period is found. These are then averaged to give values for the 1981-2000 baseline, 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 summer maximum 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 Summer Maximum 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 Summer Maximum 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 'tasmax summer change' (change in air 'temperature at surface'), the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. e.g. 'tasmax summer change 2.0 median' is the median value for summer for the 2.0°C warming level. Decimal points are included in field aliases but not in field names, e.g. 'tasmax summer change 2.0 median' is named 'tasmax_summer_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 ‘tasmax summer 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 Summer Maximum 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.

Monthly reports. Contains maps and data for England, Wale, Scotland and Northern Ireland

What does the data show?

The data shows projections of population age structure (thousands of people per age class) from the UK Climate Resilience Programme UK-SSPs project. The data is available for each Office for National Statistics Local Authority District (ONS LAD) shape simplified to a 10m resolution.

The age structure is split into 19 age classes e.g. 10-14 and is available for the end of each decade. For more information see the table below.

This dataset contains only SSP2, the 'Middle of the Road' scenario.

Indicator

Demography

Metric

Age Structure

Unit

Thousands per age class

Spatial Resolution

LAD

Temporal Resolution

Decadal

Sectoral Categories

19 age classes

Baseline Data Source

ONS 2019

Projection Trend Source

IIASA

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

This data contains a field for the year at the end of each decade. A separate field for 'Age Class' allow the data to be filtered e.g. by age class '10-14'.

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 2020 values.

What are Shared Socioeconomic Pathways (SSPs)?

The global SSPs, used in Intergovernmental Panel on Climate Change (IPCC) assessments, are five different storylines of future socioeconomic circumstances, explaining how the global economy and society might evolve over the next 80 years. Crucially, the global SSPs are independent of climate change and climate change policy, i.e. they do not consider the potential impact climate change has on societal and economic choices.

Instead, they are designed to be coupled with a set of future climate scenarios, the Representative Concentration Pathways or ‘RCPs’. When combined together within climate research (in any number of ways), the SSPs and RCPs can tell us how feasible it would be to achieve different levels of climate change mitigation, and what challenges to climate change mitigation and adaptation might exist.

Until recently, UK-specific versions of the global SSPs were not available to combine with the RCP-based climate projections. The aim of the UK-SSPs project was to fill this gap by developing a set of socioeconomic scenarios for the UK that is consistent with the global SSPs used by the IPCC community, and which will provide the basis for further UK research on climate risk and resilience.

Useful links:

Further information on the UK SSPs can be found on the UK SSP project site and in this storymap. Further information on RCP scenarios, SSPs and understanding climate data within the Met Office Climate Data Portal.

Temperature or temperature-change from a baseline, for a range of future Global Warming Levels, averaged over sub-Local Authority areas.

What does the data show? The dataset uses projections of daily mean air temperature close to the surface, which are averaged over the whole year.

Scenario

Data Units

1981-2000 (equivalent to a 0.51°C global warming scenario)

Temperature (°C)

2001-2020 (equivalent to a 0.87 °C global warming scenario)

Temperature (°C)

1.5°C global warming level

Temperature change from baseline* (°C)

2°C global warming level

Temperature change from baseline* (°C)

2.5°C global warming level

Temperature change from baseline* (°C)

3°C global warming level

Temperature change from baseline* (°C)

3.5°C global warming level

Temperature change from baseline* (°C)

4°C global warming level

Temperature change from baseline* (°C)

• baseline for the data values is 1981-2000

What is a global warming level? A scenario where the global average temperature is this many degrees above the pre-industrial period (1850-1900). Estimates based on current international agreements on greenhouse gas emissions suggest we’ll reach a warming level in the region of 2.4-2.8°C.

What do the 'median', 'upper', and 'lower' values mean? For each scenario, we provide a range of estimates to capture the inherent uncertainty in climate projections. In the climate projections that underpin this service (UKCP Local), a group of 16 models were run, each with slightly different formulations to create a set (“ensemble”) of 16 projections - and this dataset provides the median, 2nd lowest (lower) and 2nd highest (upper) of these 16 ensemble members. Please note that projections over Shetland are derived from UKCP Regional (12 km) resolution. The fields are named accordingly, e.g. ‘_25_lower’ for the 2nd lowest at 2.5°C.

Where can I find out more? The data source is a 1km product derived from the Local UK Climate Projections (UKCP18). Please note that projections over Shetland are derived from UKCP Regional (12 km) resolution, due to the lack of availability of UKCP Local over Shetland. To understand the data, refer to the LACS Scientific Detail. To understand how to explore the data, see the User Guides available on the Climate Data Portal. This dataset forms part of the Met Office’s Climate Data Portal service where other datasets can be found:https://climatedataportal.metoffice.gov.uk

This dataset consists of spatially explicit (1 km gridded) metrics of climate change 'exposure' (i.e. an index of the amount of expected change in a location) derived from quantifying the difference in observed historical and predicted future climatic conditions. Four comparisons are included between five discrete time periods: 1901–1930 v. 1961–1990; 1961–1990 v. 2010–2019; 2010–2019 v. 2021–2040; and 2021–2040 v. 2061–2080.

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).

The 5km temperature time-series data for four climate projection scenarios produced in support of the UK Climate Impacts Programme 2002 (UKCIP02). Monthly temperature time-series data for four alternative future climates for the UK. The four emissions scenarios are Low (LO), Medium-Low (ML), Medium-High (MH) and High (HI).

Projections show that the climate emergency could have considerable impacts in England. The current annual temperature is roughly *** degrees Celsius, but by 2050 temperatures could rise to between *** degrees Celsius and **** degrees Celsius. The probability of heatwaves could also increase five-fold. In July 2021, the highest ever temperature in England was recorded in Heathrow at **** degrees Celsius.