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

The data deposited here underlie an assessment of the exposure of UK habitats to climate change, and a linked assessment of how well current UK plant monitoring schemes cover these exposure gradients (see Wilson & Pescott, 2023 in press). The current dataset consists of spatially explicit (1 km gridded) classifications of predicted Köppen-Geiger climate types (Peel et al., 2007), based on both past (observed) and future (modelled) climate data. Full details about this dataset can be found at https://doi.org/10.5285/4aed4496-f9e2-494d-a0f9-adc297f033a4

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.

Natural England has developed a GIS model that provides an assessment of the vulnerability of priority habitats to climate change based on principles of adaptation for biodiversity. It identifies why areas are vulnerable and which possible interventions can have the biggest impact in increasing resilience to the changing climate. This will inform prioritisation of adaptation action and assist in the development of adaptation strategies for biodiversity both within Natural England and with our partners. The NBCCVA uses a 200m x200m GIS grid model to assess priority habitats for their Sensitivity to climate change, Adaptive Capacity; including habitat fragmentation, topographic variety and current management and condition and Conservation Value. The metrics can then be added together to produce an overall vulnerability assessment. Key outputs are maps showing the metric results and the range of relative vulnerability across the country, giving a visual representation of the areas vulnerable to climate change.

The wettest months in the United Kingdom tend to be at the start and end of the year. In the period of consideration, the greatest measurement of rainfall was nearly 217 millimeters, recorded in December 2015. The lowest level of rainfall was recorded in April 2021, at 20.6 millimeters. Rainy days The British Isles are known for their wet weather, and in 2024 there were approximately 164 rain days in the United Kingdom. A rainday is when more than one millimeter of rain falls within a day. Over the past 30 years, the greatest number of rain days was recorded in the year 2000. In that year, the average annual rainfall in the UK amounted to 1,242.1 millimeters. Climate change According to the Met Office, climate change in the United Kingdom has resulted in the weather getting warmer and wetter. In 2022, the annual average temperature in the country reached a new record high, surpassing 10 degrees Celsius for the first time. This represented an increase of nearly two degrees Celsius when compared to the annual average temperature recorded in 1910. In a recent survey conducted amongst UK residents, almost 80 percent of respondents had concerns about climate change.

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.

The annual mean temperature in the United Kingdom has fluctuated greatly since 1990. Temperatures during this period were at their highest in 2022, surpassing 10 degrees Celsius. In 2010, the mean annual temperature stood at 7.94 degrees, the lowest recorded during this time. Daily temperatures Average daily temperatures have remained stable since the turn of the century, rarely dropping below 10 degrees Celsius. In 2010, they dropped to a low of nine degrees Celsius. The peak average daily temperature was recorded in 2022 when it reached 11.2 degrees. This was an increase of one 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 22.6 degrees Celsius. In comparison, the lowest monthly minimum temperature was in February of the same year, at just minus 0.6 degrees. This was an especially cold February, as the previous year the minimum temperature for this month was 2.6 degrees.

PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.

Risk of Flooding from Surface Water (RoFSW) map is an assessment of where surface water flooding may occur when rainwater does not drain away through the normal drainage systems or soak into the ground, but lies on or flows over the ground instead. It includes information about flooding extents and depths. It is produced using national scale modelling and enhanced with compatible, locally produced modelling from lead local flood authorities (LLFAs).

RoFSW is a probabilistic product, meaning that it shows the overall risk, rather than the risk associated with a specific event or scenario. In externally published versions of this dataset, risk is displayed as one of three likelihood bandings: High - greater than or equal to 3.3% chance in any given year (1 in 30) Medium - less than 3.3% (1 in 30) but greater than or equal to 1% (1 in 100) chance in any given year Low - less than 1% (1 in 100) chance in any given year

This dataset presents the risk which takes account of the following climate change allowances based on the latest UK Climate Projections (UKCP18) from the Met Office, using the Representative Concentration Pathway (RCP) 8.5:

- the ‘Central’ allowance for the 2050s epoch (2040-2060) for risk of flooding from surface water.

These allowances include anticipated changes to peak rainfall intensity.

NB. This is a complex dataset, with preview available only on certain zoom levels. The Web Mapping service has been set to 1:50 000 in the

[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 percentage change between the 'lower' values before and after this update is -1%.]What does the data show? A Heating Degree Day (HDD) is a day in which the average temperature is below 15.5°C. It is the number of degrees above this threshold that counts as a Heating Degree Day. For example if the average temperature for a specific day is 15°C, this would contribute 0.5 Heating Degree Days to the annual sum, alternatively an average temperature of 10.5°C would contribute 5 Heating Degree Days. Given the data shows the annual sum of Heating Degree Days, this value can be above 365 in some parts of the UK.Annual Heating Degree 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 HDD to previous values.What are the possible societal impacts?Heating Degree Days indicate the energy demand for heating due to cold days. A higher number of HDD means an increase in power consumption for heating, therefore this index is useful for predicting future changes in energy demand for heating.What is a global warming level?Annual Heating Degree Days are 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 Heating Degree Days, an average is taken across the 21 year period. Therefore, the Annual Heating Degree Days show the number of heating degree 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 warming level and two baselines. They are named ‘HDD’ (Heating Degree Days), the warming level or baseline, and 'upper' 'median' or 'lower' as per the description below. E.g. 'HDD 2.5 median' is the median value for the 2.5°C projection. Decimal points are included in field aliases but not field names e.g. 'HDD 2.5 median' is 'HDD_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 ‘HDD 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, Annual Heating Degree Days 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.‘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.

1:1.5M scale 'Geology Through Climate Change' poster map covering UK mainland, Northern Ireland and Eire. This poster map shows the rocks of Britain and Ireland in a new way, grouped and coloured according to the environment under which they were formed. Photographs illustrate modern-day environments, alongside images of the typical rock types which are formed in them. The ages of the rocks are shown in a timeline, which also shows global temperatures and sea levels changing through time. The changing positions of Britain and Ireland as they drifted northwards through geological time are illustrated too. It was jointly produced by the BGS, the Geological Survey of Northern Ireland and the Geological Survey of Ireland. It has been endorsed by a range of teaching organisations including WJEC (previously the Welsh Joint Education Committee), OCR (Oxford Cambridge and RSA Examinations), The Association of Teaching Organisations of Ireland and the Earth Science Teachers Association. Although primarily intended as a teaching resource, the poster map will be of interest to anyone seeking to understand the imprint geological time has left in the rocks of our islands. This poster map is free, all you pay is the postage and packing.

The United Kingdom experienced an average of 1,242.1 millimeters of rainfall in 2024, a decrease of 5.8 percent in comparison to the previous year. While 2024 saw substantial rainfall, it did not surpass the thus-far peak of the century, with 1,373 millimeters of rain recorded in 2000. Regional variations and seasonal patterns Rainfall distribution across the UK is far from uniform, with Scotland and Wales consistently receiving the highest annual precipitation. In 2024, they recorded an average of 1,571.7 millimeters and 1,600.8 millimeters, respectively, significantly above the UK’s average. This disparity is largely due to both countries’ mountainous terrain, which is more susceptible to Atlantic weather systems. Seasonally, the wettest months in the UK typically occur in the winter, with the highest precipitation levels seen between November and February. Climate change impact on UK weather Climate change is influencing UK weather patterns, leading to warmer and wetter conditions overall. While annual rainfall fluctuates, there is a trend towards more extreme weather events. For example, 2020 and 2022 saw rain deviations from the long-term mean in the UK of more than 100 millimeters in February. As weather patterns continue to evolve, monitoring rainfall trends remains crucial for understanding and adapting to a changing climate.

England's highest monthly mean air temperatures are typically recorded in July and August of each year. Since 2015, the warmest mean temperature was measured in July 2018 at 18.8 degrees Celsius. On the other hand, February of that same year registered the coolest temperature, at 2.6 degrees Celsius. In February 2025, the mean air temperature was five degrees Celsius, 50 percent lower than the same month the previous year. The English weather England is the warmest region in the United Kingdom and the driest. In 2024, the average annual temperature in England amounted to 10.73 degrees Celsius – around 1.1 degrees above the national mean. That same year, precipitation in England stood at about 1,020 millimeters. By contrast, Scotland – the wettest region in the UK – recorded over 1,500 millimeters of rainfall in 2024. Temperatures on the rise Throughout the last decades, the average temperature in the United Kingdom has seen an upward trend, reaching a record high in 2022. Global temperatures have experienced a similar pattern over the same period. This gradual increase in the Earth's average temperature is primarily due to various human activities, such as burning fossil fuels and deforestation, which lead to the emission of greenhouse gases. This phenomenon has severe consequences, including more frequent and intense weather events, rising sea levels, and adverse effects on human health and the environment.

The data describes future land use projections at 1 km^2 resolution developed by CRAFTY-GB. For each of six Shared Socioeconomic Pathways (SSP-RCP) scenarios, gridded land use maps for Great Britain are provided, each as a stacked raster file with seven bands representing land use at each decadal timestep, from 2020 to 2080. CRAFTY-GB is a new agent-based model of the British land system operating at a 1 km^2 resolution and based on a broad range of available land system data . The model is based on linked UK-RCP climate scenarios and UK-SSPs socio-economic pathway (SSP) scenarios, based on global SSPs developed by the Intergovernmental Panel on Climate Change (IPCC). It extrapolates the impact of these on the British Land system at decadal timesteps from 2020-2080. Full details about this dataset can be found at https://doi.org/10.5285/f9ab3051-4f85-415f-b691-371ff8e951f2

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

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

This data is to illustrate the theory, data analysis, and exemplary results of the array processing described in the corresponding publication entitled 'First map of coherent low frequency continuum radiation in the sky'.

The Access Network Map of England is a national composite dataset of Access layers, showing analysis of extent of Access provision for each Lower Super Output Area (LSOA), as a percentage or area coverage of access in England. The ‘Access Network Map’ was developed by Natural England to inform its work to improve opportunities for people to enjoy the natural environment. This map shows, across England, the relative abundance of accessible land in relation to where people live. Due to issues explained below, the map does not, and cannot, provide a definitive statement of where intervention is necessary. Rather, it should be used to identify areas of interest which require further exploration. Natural England believes that places where people can enjoy the natural environment should be improved and created where they are most wanted. Access Network Maps help support this work by providing means to assess the amount of accessible land available in relation to where people live. They combine all the available good quality data on access provision into a single dataset and relate this to population. This provides a common foundation for regional and national teams to use when targeting resources to improve public access to greenspace, or projects that rely on this resource. The Access Network Maps are compiled from the datasets available to Natural England which contain robust, nationally consistent data on land and routes that are normally available to the public and are free of charge. Datasets contained in the aggregated data:•
Agri-environment scheme permissive access (routes and open access)•
CROW access land (including registered common land and Section 16)•
Country Parks•
Cycleways (Sustrans Routes) including Local/Regional/National and Link Routes•
Doorstep Greens•
Local Nature Reserves•
Millennium Greens•
National Nature Reserves (accessible sites only)•
National Trails•
Public Rights of Way•
Forestry Commission ‘Woods for People’ data•
Village Greens – point data only Due to the quantity and complexity of data used, it is not possible to display clearly on a single map the precise boundary of accessible land for all areas. We therefore selected a unit which would be clearly visible at a variety of scales and calculated the total area (in hectares) of accessible land in each. The units we selected are ‘Lower Super Output Areas’ (LSOAs), which represent where approximately 1,500 people live based on postcode. To calculate the total area of accessible land for each we gave the linear routes a notional width of 3 metres so they could be measured in hectares. We then combined together all the datasets and calculated the total hectares of accessible land in each LSOA. For further information about this data see the following links:Access Network Mapping GuidanceAccess Network Mapping Metadata Full metadata can be viewed on data.gov.uk.

This dataset shows the future risk presented to sites across the UK from North Easterly winds , based on data projected for a 2060-2080 future period. This data is the Met Office UKCP18 data depicting NE storm winds will have more impact on the UK. Historically SW winds dominate the UK.

Risk of Flooding from Rivers and the Sea (RoFRS) shows the chance of flooding from rivers and the sea taking into account the presence and condition of flood defences. It is our main way of communicating flood risk from rivers and sea to the public through our ‘Check Your Long Term Flood Risk’ service on gov.uk. Climate change scenarios have been produced for this dataset to indicate the predicted impacts of climate change on future risk.

While flood defences reduce the level of risk they do not completely remove it. For example, water can flow over the top of the defence, or they can fail in extreme weather conditions or if they are in poor condition. As a result, the RoFRS maps may show that there is risk to areas behind some flood defences.

RoFRS is a probabilistic product, meaning that it shows the overall risk, rather than the risk associated with a specific event or scenario. In externally published versions of this dataset, risk is displayed as one of four likelihood bandings:

High - greater than or equal to 3.3% chance in any given year (1 in 30) 
Medium - less than 3.3% (1 in 30) but greater than or equal to 1% (1 in 100) chance in any given year 
Low - less than 1% (1 in 100) but greater than or equal to 0.1% (1 in 1,000) chance in any given year 
Very Low - less than 0.1% chance in any given year (1 in 1,000) 

Our climate change allowances include anticipated changes to:

- Peak river flow 
- Sea level rise 
- Offshore wind speed and extreme wave height 

The climate change allowances are based on the latest UK Climate Projections (UKCP18) from the Met Office, using the Representative Concentration Pathway (RCP) 8.5.

Our Flood risk assessment: climate change allowances include several different allowances reflecting the range of possible future climates. They also provide allowances for different periods of time, acknowledging that some users will want to look further into the future than others. The periods of time vary for each source of risk because equivalent datasets for each source are not always available.

Check Your Long-Term Flood Risk is aimed at supporting individuals, communities and organisations making short- and medium-term decisions to manage future flood risk. We have therefore chosen:

- the ‘Central’ allowance for the 2050s epoch (2040-2069) for risk of flooding from rivers 
- the ‘Higher Central’ allowance for risk of flooding from the sea, accounting for cumulative sea level rise to 2065 

This data also presents the likelihood of flooding for the following depths:

0.2m 
0.3m 
0.6m 
0.9m 
1.2m 

NB. This is a complex dataset, with preview available only on certain zoom levels. The Web Mapping service has been set to 1:50 000 in the