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  • HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110').

  • HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110'). Version 3.0.2 was added due to a correction to the land-sea mask used. More details can be found in the HadEX3 blog under 'Details/Docs' tab.

  • HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110'). Version 3.0.3 was added due to an error in how the Rx1day and Rx5day data were being handled for one of the West African data sources. More details can be found in the HadEX3 blog under 'Details/Docs' tab.

  • HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid covering 1901-2018. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Indices are available on an annual, and for some a monthly, basis. Some indices use a reference period to calculate thresholds, and for these, we provide versions using 1961-90 and 1981-2010. The indices are available in NetCDF files, with one index per file and separate files for annual and monthly values, as well as the different reference periods if appropriate. The codes used to create the dataset are available online, and a wide number of analysis plots are on the dataset homepage. For a detailed description of the methods behind the dataset, please see the paper in Details/Docs.

  • HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). Spatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010. All indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110'). In September 2020, a user identified some issues in the DTR and TN90p (61-90) indices. These were found to have arisen from erroneous values in a few stations which were not picked up by any quality control checks. These stations were noted on the bad list and these two indices re-run, hence v3.0.1.

  • Collated indices are a relative measure of butterfly abundance across monitored sites in the UK, calculated from data collected by the UK Butterfly Monitoring Scheme (UKBMS). Collated indices are calculated annually for each individual butterfly species that has been recorded on five or more sites in that year. Based on this criterion collated indices have been calculated for the entire UKBMS time series from 1976 to the current year for the majority of species. For some rarer species the time series starts in a later year due to lack of data. Collated indices are calculated using a statistical model that accounts for missing data. The number of sites for each species ranges from 5 to several hundred and varies from year to year. Since 2008 more than 1,000 sites have been monitored across the UK each year. Collated indices are calculated so that we can determine how butterfly populations are changing over time across the UK. This data can be used, for example, to determine where to target conservation efforts and to measure the condition of the UK countryside. Butterflies are recognised as important indicators of biodiversity and environmental change (e.g. as official UK Biodiversity Indicators), and have been used in numerous research studies to understand the impacts of changes in climate and the extent and condition of habitats. Although the UK Centre for Ecology & Hydrology (UKCEH) and Butterfly Conservation (BC) are responsible for the calculation and interpretation of the Collated indices, the collection of the data used in their creation is ultimately reliant on a large volunteer community. The UKBMS is funded by a consortium of organisations led by the Joint Nature Conservation Committee (JNCC). This dataset is updated annually and more recent versions of the UKBMS collated indices are available. Full details about this dataset can be found at https://doi.org/10.5285/ff55462e-38a4-4f30-b562-f82ff263d9c3

  • This dataset provides linear trends, over varying time periods, for the UK Butterfly Monitoring Scheme (UKBMS) Collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976 to 2016), for the last 20 years, and for the last decade. In addition a trend class, based on slope direction and its significance, and a percentage change for that time period are provided to describe the statistical trends. These trend data are provided for 59 UK butterfly species. Trends across different time series allow us to determine the long and short-term trends for individual species. This enables us to focus conservation and research and also to assess species responses to conservation already in place. The Centre for Ecology & Hydrology (CEH) and Butterfly Conservation (BC) are responsible for the calculation and interpretation of the trend datasets. The collection of the underlying UKBMS data is reliant on a large volunteer community. The UK Butterfly Monitoring Scheme is funded by a consortium of organisations led by the Joint Nature Conservation Committee (JNCC). Full details about this dataset can be found at https://doi.org/10.5285/5c5bbee4-fe39-40b2-a58b-16e05f994a74

  • [THIS DATASET HAS BEEN WITHDRAWN]. 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. 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 Centre for Ecology & Hydrology (CEH) and Butterfly Conservation (BC) collate the data and the UKBMS is funded by a consortium of organisations led by the Joint Nature Conservation Committee (JNCC). Full details about this dataset can be found at https://doi.org/10.5285/9b7fa1d0-2580-46a5-a2d6-b17d30fd7723

  • Collated indices are a relative measure of butterfly abundance across monitored sites in the UK, calculated from data collected by the UK Butterfly Monitoring Scheme (UKBMS). Collated indices are calculated annually for each individual butterfly species that has been recorded on five or more sites in that year. Based on this criterion collated indices have been calculated for the entire UKBMS time series from 1976 to the current year for the majority of species. For some rarer species the time series starts in a later year due to lack of data. Collated indices are calculated using a statistical model that accounts for missing data. The number of sites for each species ranges from 5 to several hundred and varies from year to year. Since 2008 more than 1,000 sites have been monitored across the UK each year. Collated indices are calculated so that we can determine how butterfly populations are changing over time across the UK. This data can be used, for example, to determine where to target conservation efforts and to measure the condition of the UK countryside. Butterflies are recognised as important indicators of biodiversity and environmental change (e.g. as official UK Biodiversity Indicators), and have been used in numerous research studies to understand the impacts of changes in climate and the extent and condition of habitats. Although the UK Centre for Ecology & Hydrology (UKCEH) and Butterfly Conservation (BC) are responsible for the calculation and interpretation of the Collated indices, the collection of the data used in their creation is ultimately reliant on a large volunteer community. The UKBMS is funded by a consortium of organisations led by the Joint Nature Conservation Committee (JNCC). This version supersedes the original version due to an error in the precision of the reported figures. This dataset is updated annually and recent versions of the UKBMS collated indices are available. Full details about this dataset can be found at https://doi.org/10.5285/c6c5e93c-06c2-44d5-ab2a-8f6f10951888

  • This dataset provides linear trends, over varying time periods, for the UK Butterfly Monitoring Scheme (UKBMS) Collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976 to 2015), for the last 20 years, and for the last decade. In addition a trend class, based on slope direction and its significance, and a percentage change for that time period are provided to describe the statistical trends. These trend data are provided for 59 UK butterfly species. Trends across different time series allow us to determine the long and short-term trends for individual species. This enables us to focus conservation and research and also to assess species responses to conservation already in place. The Centre for Ecology & Hydrology (CEH) and Butterfly Conservation (BC) are responsible for the calculation and interpretation of this trend datasets. The collection of the underlying UKBMS data is reliant on a large volunteer community. The UK Butterfly Monitoring Scheme is funded by a consortium of organisations led by the Joint Nature Conservation Committee (JNCC). This version supersedes the original version due to an error in the precision of the reported figures. This dataset is updated annually and a more recent version of the UKBMS species trends (2016) is now available. Full details about this dataset can be found at https://doi.org/10.5285/0383e234-daad-4f0e-8482-c227661f4941