In 2023/24, approximately 54 percent of people in England advised that they had volunteered at least once in the previous year, with 33 percent volunteering at least once a month. In general, the share of people saying they volunteered has been declining since 2013/14, when approximately 70 percent of the population volunteered in a year.

A multitude of smart phone and more traditional tools are used with increasing frequency by volunteers on roads for long-term monitoring of wildlife. Data collected by volunteers on roads has recently indicated large-scale declines of some widespread amphibians in Western Europe. However, it is unclear how representative such data are or not in relation to the actual species distribution. Spatial biases could skew results towards more urbanised areas and consequently produce incorrect or partial trend estimations at regional or national scales. Our objective was to compare and verify potential spatial biases of road based data using distribution datasets of different origins. As a case study, we used the common toad (Bufo bufo), a fast-declining species and the main amphibian targeted by conservation action on roads in Europe. We calculated ecological niche models with the built used Maxent models to compare road survey data obtained from the UK flagship, 35 year-long “Toads on Roads” project, containing almost 2 million amphibian records, in Great Britain with models using national-scale toad distribution records in Great Britain as well as with models using randomly generated points on roads. Road based distribution models that used data collected by volunteers on roads produced similar results to those obtained from overall species distribution, indicating the lack of selection bias and a high spatial coverage of volunteer-collected data on roads. Toads were present in most parts of the country but were generally absent from mountainous areas and, despite the high availability of potential recorders, showed nearly complete absence in large urban areas. To our knowledge, this is the first study that comparatively evaluates species distribution models created using datasets of different origin in order to verify the influence of potential spatial bias of data collected by volunteers on roads. We show that for countries with high road density road network coverage, such as Great Britain, road based data collected by volunteers represent a robust dataset in terms of coverage and a critical citizen science contribution to conservation.

This statistic shows the results of a survey on the number of people who volunteered to support sport and physical activity in England in 2020, by age group. The survey was conducted online and the latest update on it was conducted for the time period between May 2019 and November 2020 with a total of 66,196 respondents. The data collected resulted in the conclusion that as of May 2020 approximately 1.2 million people between the age of 45 and 54 participated in volunteering to support sport and physical activities in England. More information on participation levels as well as other facts on snow sports can be found in the Dossier: Winter sports in the United Kingdom.

This dataset comprises species recorded on Scottish Wildlife Trust reserves through surveys or monitoring undertaken by reserve convenors or Trust volunteers. Records in this dataset have undergone a level of verification, either using the rules provided by national recording schemes and societies available via the NBN Record Cleaner, or other experts, such as Vice County Recorders. These data are provided "as is" and Scottish Wildlife Trust do not have the resources to interpret these data. The Trust would recommend using a Local Record Centre for interpretation purposes and to gain a clear picture of all datasets available, many of which will not yet be on the NBN Atlas.

Abstract copyright UK Data Service and data collection copyright owner.

The aims of this survey series are to ascertain :
the proportion of the population who are involved in voluntary activity in the UK;
the type of people most likely to volunteer;
the types of activities in which volunteers are engaged;
the motivations for volunteering;
the benefits and drawbacks of voluntary work.

The 1997 survey was carried out by BMRB International on behalf of the National Centre for Volunteering (formerly the Volunteer Centre). The need to compare trends in voluntary activity over time required that the survey was to a large extent a repeat of the previous surveys conducted by SCPR in 1981 and 1991, although some new topics were covered.

A research project was carried out by the National Centre for Social Research in partnership with the Institute for Volunteering Research in 2006/7, as a follow-up to the Citizenship Survey, 2005. The resulting study, the National Survey of Volunteering and Charitable Giving, 2006-2007, is held at the UKDA under SN 5793.

Main Topics:

The survey covered the following subjects :
working status; voluntary activity connected with work; marital status, disabilities and caring responsibilities; formal volunteering; organisation or group helped most, and most in past year (current and previous volunteers); barriers to volunteering and attitudes of irregular or former volunteers; informal volunteering; attitudes towards voluntary workers, and our society's attitudes towards them; receipt of voluntary help; donations.

Users should note, a few variables on the questionnaire are not included in the dataset if they were used to create derived variables. There are many derived variables included (particularly in Section 4 of the questionnaire). Comparison of the topline and the questionnaire of the technical report is recommended for Section 4.

A collection of marine life surveys collated by the Marine Life Information Network (MarLIN) as part of their data access program and now incoporated into the DASSH Data Archive Centre. Although this data is freely available Data ownership remains with the original data provider and permission must be saught to use this data for academic or commercial purposes. This data is released under DASSH Terms and Conditions available from www.dassh.ac.uk.

Collection of marine life surveys collated by the Marine Life Information Network (MarLIN) as part of their data access program.

Data were gathered through citizen science volunteers, who used the i-Tree Canopy tool (https://canopy.itreetools.org/) to assess percentage canopy cover within ward boundaries. A User Guide was provided to the volunteers, with step-by-step instructions and pictorial support (https://cdn.forestresearch.gov.uk/2018/11/canopy_cover_webmap_user_guide_-_updated_march_2021.pdf). i-Tree Canopy randomly distributes points within a study area (ward boundary), overlain on Google aerial imagery. Users examine the points in sequence to determine whether the point lies over a tree canopy or not, classifying each point as either “tree” or “non-tree” accordingly. Typically 350 to 600 points were assessed per ward, leading to a standard error of less than 2%. Percentage tree canopy cover was calculated as (n/N)*100 where n is the number of “tree” points and N is the total number of sample points. Results were returned to Forest Research in the form of percentage canopy cover, standard error, number of points, and the i-Tree Canopy project file. Data quality was monitored through screening of submitted results by Forest Research project staff for all new participants, and at regular intervals for experienced contributors. Most wards were assessed only once. Where a ward was assessed by more than one contributor, the results were combined where possible. Field Attributes;country [Country] The country within which the Ward is located as defined by the Ward code. [E050000xx = England; N08000xxx = Northern Ireland; S1300xxxx = Scotland; W050000xx = Wales] wardcode [Ward code] The unique code associated with the Ward boundary. Ward boundaries are based on OS Boundary-Line data (OS data © Crown copyright and database right 2017). Most Ward boundaries are from the 2017 OS Boundary-Line dataset. However, a few users returned boundaries from the 2018 OS Boundary-Line dataset; the dataset was amended to reflect which boundary was used in the i-Tree Canopy assessment. wardname [Ward name] The name of the Ward boundary. Ward boundaries are based on OS Boundary-Line data (OS data © Crown copyright and database right 2017). Most Ward boundaries are from the 2017 OS Boundary-Line dataset. However, a few users returned boundaries from the 2018 OS Boundary-Line dataset; the dataset was amended to reflect which boundary was used in the i-Tree Canopy assessment. designated [Urban/Rural] Whether the Ward has been identified as an Urban or Rural Ward. Wards were classified as Urban or Rural based on size: wards larger than 1,000 Ha were classed as Rural. status [Status] Current analysis status of the ward. All Wards in the dataset have been Completed.survyear [Survey year] The year the i-Tree Canopy assessment was completed. Data collected between 2018 and 2022. percancov [Percentage canopy cover] The average canopy cover for the ward boundary as calculated by the i-Tree Canopy model. standerr [Standard Error] The Standard Error associated with the average canopy cover value as calculated by the i-Tree Canopy model. numpts [Number of points] Number of points completed for the i-Tree Canopy assessment of the ward. warea [Ward area] The area of the Ward boundary (m2)

https://www.openstreetmap.org/images/osm_logo.png" alt="" /> OpenStreetMap (openstreetmap.org) is a global collaborative mapping project, which offers maps and map data released with an open license, encouraging free re-use and re-distribution. The data is created by a large community of volunteers who use a variety of simple on-the-ground surveying techniques, and wiki-syle editing tools to collaborate as they create the maps, in a process which is open to everyone. The project originated in London, and an active community of mappers and developers are based here. Mapping work in London is ongoing (and you can help!) but the coverage is already good enough for many uses.

Browse the map of London on OpenStreetMap.org

Downloads:

The whole of England updated daily:

• england.osm.bz2 ~185M - .osm formatted raw XML data (compressed)
• england.shp.zip ~156M - ESRI shapefiles

For more details of downloads available from OpenStreetMap, including downloading the whole planet, see 'planet.osm' on the wiki.

Data access APIs:

Download small areas of the map by bounding-box. For example this URL requests the data around Trafalgar Square:
http://api.openstreetmap.org/api/0.6/map?bbox=-0.13062,51.5065,-0.12557,51.50969

Data filtered by "tag". For example this URL returns all elements in London tagged shop=supermarket:
http://www.informationfreeway.org/api/0.6/*[shop=supermarket][bbox=-0.48,51.30,0.21,51.70]

The .osm format

The format of the data is a raw XML represention of all the elements making up the map. OpenStreetMap is composed of interconnected "nodes" and "ways" (and sometimes "relations") each with a set of name=value pairs called "tags". These classify and describe properties of the elements, and ultimately influence how they get drawn on the map. To understand more about tags, and different ways of working with this data format refer to the following pages on the OpenStreetMap wiki.

• .osm - About the raw XML data format of OpenStreetMap
• Downloading data - More details of the API and extract download options
• Xapi - The extended api for filtering by tag
• Map Features - A list of tags, and what map features they represent
• Converting map data between formats - catalogue of tools for converting from .osm to other formats

Simple embedded maps

Rather than working with raw map data, you may prefer to embed maps from OpenStreetMap on your website with a simple bit of javascript. You can also present overlays of other data, in a manner very similar to working with google maps. In fact you can even use the google maps API to do this. See OSM on your own website for details and links to various javascript map libraries.

Help build the map!

The OpenStreetMap project aims to attract large numbers of contributors who all chip in a little bit to help build the map. Although the map editing tools take a little while to learn, they are designed to be as simple as possible, so that everyone can get involved. This project offers an exciting means of allowing local London communities to take ownership of their part of the map.

Read about how to Get Involved and see the London page for details of OpenStreetMap community events.

The indicator aims to create a culture in which individuals are able to contribute to their communities by volunteering. High levels of volunteering are one sign of strong, active communities. Volunteers are vital in supporting the range of activity undertaken by third sector organisations and within the public services.

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 dataset at 60 km resolution is derived from the associated 1 km x 1 km resolution 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. (2018, 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.

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 dataset at 25 km resolution is derived from the associated 1 km x 1 km resolution 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. (2018, 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.

This dataset is the output from the UK canopy cover webmap project, which aimed to assess the percentage tree canopy cover in every ward in the UK. Forest Research delivered the project with partners Brillianto, Trees for Cities, and Woodland Trust. Wards were classified as urban or rural based on size: wards larger than 1,000 Ha were classed as rural. Data were gathered through citizen science volunteers, who used the i-Tree Canopy tool (https://canopy.itreetools.org/) to assess percentage canopy cover within ward boundaries. A User Guide was provided to the volunteers, with step-by-step instructions and pictorial support (https://cdn.forestresearch.gov.uk/2018/11/canopy_cover_webmap_user_guide_-_updated_march_2021.pdf). i-Tree Canopy randomly distributes points within a study area (ward boundary), overlain on Google aerial imagery. Users examine the points in sequence to determine whether the point lies over a tree canopy or not, classifying each point as either “tree” or “non-tree” accordingly. Typically 350 to 600 points were assessed per ward, leading to a standard error of less than 2%. Percentage tree canopy cover was calculated as (n/N)*100 where n is the number of “tree” points and N is the total number of sample points. Results were returned to Forest Research in the form of percentage canopy cover, standard error, number of points, and the i-Tree Canopy project file. Data quality was monitored through screening of submitted results by Forest Research project staff for all new participants, and at regular intervals for experienced contributors. Most wards were assessed only once. Where a ward was assessed by more than one contributor, the results were combined where possible. Data were collected between 2018 and 2022. All urban wards were completed.

country [Country] The country within which the Ward is located as defined by the Ward code. [E050000xx = England; N08000xxx = Northern Ireland; S1300xxxx = Scotland; W050000xx = Wales]

wardcode [Ward code] The unique code associated with the Ward boundary. Ward boundaries are based on OS Boundary-Line data (OS data © Crown copyright and database right 2017). Most Ward boundaries are from the 2017 OS Boundary-Line dataset. However, a few users returned boundaries from the 2018 OS Boundary-Line dataset; the dataset was amended to reflect which boundary was used in the i-Tree Canopy assessment.

wardname [Ward name] The name of the Ward boundary. Ward boundaries are based on OS Boundary-Line data (OS data © Crown copyright and database right 2017). Most Ward boundaries are from the 2017 OS Boundary-Line dataset. However, a few users returned boundaries from the 2018 OS Boundary-Line dataset; the dataset was amended to reflect which boundary was used in the i-Tree Canopy assessment.

designated [Urban/Rural] Whether the Ward has been identified as an Urban or Rural Ward. Wards were classified as Urban or Rural based on size: wards larger than 1,000 Ha were classed as Rural.

status [Status] Current analysis status of the ward. All Wards in the dataset have been Completed.

survyear [Survey year] The year the i-Tree Canopy assessment was completed, Data collected between 2018 and 2022.

percancov [Percentage canopy cover] The average canopy cover for the ward boundary as calculated by the i-Tree Canopy model.

standerr [Standard Error] The Standard Error associated with the average canopy cover value as calculated by the i-Tree Canopy model.

numpts [Number of points] Number of points completed for the i-Tree Canopy assessment of the ward.

warea [Ward area] The area of the Ward boundary (m2)

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. These data at 1 km resolution have been averaged across a set of discrete geographies defining UK administrative regions consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2022 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. (2018, see linked documentation).

The changes for v1.2.0.ceda HadUK-Grid datasets are as follows:

• Added data for calendar year 2022

• Added newly digitised data for monthly sunshine 1910-1918

  • Added Rainfall Rescue version 2 doi:10.5281/zenodo.7554242

  • Updated shapefiles used for production of area average statistics https://github.com/ukcp-data/ukcp-spatial-files

  • Updated controlled vocabulary for metadata assignment https://github.com/ukcp-data/UKCP18_CVs

  • Updated assignment of timepoint for some periods so that the datetime is the middle of the period (e.g. season) rather than a fixed offset from the period start.

  • Updated ordering of regions within regional values files. Alphabetical ordering.

  • Files use netcdf level 4 compression using gzip https://www.unidata.ucar.edu/blogs/developer/entry/netcdf_compression

• Net changes to the input station data used to generate this dataset:

• Total of 125601744 observations

• 122621050 (97.6%) unchanged

• 26700 (0.02%) modified for this version

• 2953994 (2.35%) added in this version

• 16315 (0.01%) deleted from this version

• Changes to monthly rainfall 1836-1960

• Total of 4823973 observations

• 3315657 (68.7%) unchanged

• 21029 (0.4%) modified for this version

• 1487287 (30.8%) added in this version

• 11155 (0.2%) 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.

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. These data at 1 km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2021, 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. (2018, see linked documentation).

The changes for v1.1.0.0 HadUK-Grid datasets are as follows:

• The addition of data for calendar year 2021

• The addition of 30 year averages for the new reference period 1991-2020

• An update to 30 year averages for 1961-1990 and 1981-2010. This is an order of operation change. In this version 30 year averages have been calculated from the underlying monthly/seasonal/annual grids (grid-then-average) in previous version they were grids of interpolated station average (average-then-grid). This order of operation change results in small differences to the values, but provides improved consistency with the monthly/seasonal/annual series grids. However this order of operation change means that 1961-1990 averages are not included for sfcWind or snowlying variables due to the start date for these variables being 1969 and 1971 respectively.

• A substantial new collection of monthly rainfall data have been added for the period before 1960. These data originate from the rainfall rescue project (Hawkins et al. 2022) and this source now accounts for 84% of pre-1960 monthly rainfall data, and the monthly rainfall series has been extended back to 1836.

Net changes to the input station data used to generate this dataset:

-Total of 122664065 observations

-118464870 (96.5%) unchanged

-4821 (0.004%) modified for this version

-4194374 (3.4%) added in this version

-5887 (0.005%) 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.

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. These data at 1 km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with 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. (2018, 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.

This dataset provides the details of all sites which have been monitored as part of the UK Butterfly Monitoring Scheme (UKBMS). Data includes the location within the UK, the length and width of the line transect on each site, and how long the transect has been monitored. The UKBMS started in 1976 with fewer than 50 sites (a small number of pilot sites started from 1973). The number of sites monitored each year has increased to over a thousand since 2008. There is turnover in sites monitored each year and details of the first and last year in which each site was surveyed are given. The majority of site data is provided by recorders at the time a transect is created. The majority of these recorders are volunteers. The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the Centre for Ecology & Hydrology (CEH), the British Trust for Ornithology (BTO), and the Joint Nature Conservation Committee (JNCC). The UKBMS is indebted to all volunteers who contribute data to the scheme. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

The Ancient Tree Inventory is a citizen science project that maps the location of special trees. Anyone can add a record of an ancient or veteran tree to the website. The Ancient Tree Inventory is a dataset (the Data) managed and owned by the Woodland Trust, a registered charity in England and Wales (Number 294344) and in Scotland (Number SC038885) and the Tree Register of the British Isles (TROBI), a registered charity in England and Wales (Number 801565) and it is constantly being updated by our volunteers. By using the Data you acknowledge that you have read and agreed to the End User Licence Agreement which forms the legally binding agreement with the user in respect of the use of the Data.Data limitationsThe Ancient Tree Inventory database is not complete i.e. not all ancient / veteran trees have been recorded and therefore care should be taken and you must exercise your own skill, and judgement when using the data. An absence of records on the map does not mean an absence of ancient/veteran trees.The dataset shows only those records which have been verified and have a reasonable level of completion, however please note that inaccuracies are still possible within some records and some records may not be up to date with the latest information (e.g. standing / living status). For more information about this dataset, you should visit the following webpage: https://ati.woodlandtrust.org.uk/what-we-record-and-why/what-we-record/data