This is the 4.0.0.2017f version of the HadISDH land data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2017. The data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format. This version extends the 3.0.0.2016p version to the end of 2017 and constitutes a major update to HadISDH due to a change to using the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. Users are advised to read the update document in the docs section for full details. This version now uses the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. Additionally, there has been a small methodological change. Stations with large adjustments made during homogenisation are removed based on thresholds for q (>3g/kg), RH (>15%rh), T (>5degC) and Td (>5degC) rather than just T and Td. This results in 54 stations being removed as opposed to 29 last year. All other processing steps for HadISDH remain identical. The new version of HadISD2 (2.0.2.2017p) has pulled through some historical changes to stations which are passed on to HadISDH. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data. To keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS. For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/ References: When using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the "citable as" reference) : Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. Smith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1 We strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication: Willett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.

The Shoeburyness Field Trial: Investigation of Meteorological Effects on the Sound Propagation from a Helicopter Operating Near a Land Sea Interface Project was a QinetiQ applied research programme 3G23, funded by Ministry of Defence (MOD). The project duration was from April 2004 to March 2007 and had the aim to investigate noise modelling of helicopters with regard to long range sound propagation. The trial sought to understand more fully the meteorological effects on sound propagation over a land sea interface. This dataset collection contains measurements from the Universities Facility for Atmospheric Measurement (UFAM) Doppler lidar system, which was used to obtain profiles of the radial velocity to determine turbulence measurements at points along the aircraft flight path.

The Shoeburyness Field Trial: Investigation of Meteorological Effects on the Sound Propagation from a Helicopter Operating Near a Land Sea Interface Project was a QinetiQ applied research programme 3G23, funded by Ministry of Defence (MOD). The project duration was from April 2004 to March 2007 and had the aim to investigate noise modelling of helicopters with regard to long range sound propagation. The trial sought to understand more fully the meteorological effects on sound propagation over a land sea interface. This dataset collection contains measurements from the automatic weather station, which was used to gather standard meteorological measurements. The Universities Facility for Atmospheric Measurement (UFAM) automatic weather station was operated by the University of Salford.

The UK Climate Projections (UKCP09) probabilistic climate projections of climate change over land. These data consist of various meteorological parameters such as temperature, precipitation, surface pressure, humidity. The projections of future absolute climate that assign a probability level to different climate possibilities, the absolute values, percentage change relative to the observed climate (1961-1990) and percentiles of the parameter projections are provided over 30 year time periods over the projection period 2010-2099. The averaging periods provided are: 2010-2039, 2020-2049, 2030-2059, 2040-2069, 2050-2079, 2060-2089, 2070-2099. Data are provided over three aggregated areas, (1) a 25km grid over the UK, (2) administrative regions that are areas of the UK based on administrative boundaries and (3) river basins that are based on a division of the UK land area based on the Water Framework Directive River Basin Districts. In 2009 the first version of the UK probabilistic projections of climate change over land were provided. In 2013 an update was made to some of the files (version 2). Both versions of this data are made available here with the version 2 data being the most recent. These projections provides an absolute value for the future climate (as opposed to giving values that are relative to a baseline period). A probabilistic climate projection is a measure of strength of evidence in different future climate change outcomes. This measure is dependent on the method used, is based on the current available evidence and encapsulates some, but not all, of the uncertainty associated with projecting future climate. The climate projections report contains further details.

The project was a QinetiQ applied research programme 3G23, funded by Ministry of Defence (MOD). The project duration was from April 2004 to March 2007. Field experiment in May 2006 was to investigate noise modelling of helicopters with regard to long range sound propagation. The trial sought to understand more fully the meteorological effects on sound propagation over a land sea interface. This dataset collection contains profiles of the radial velocity at points along the aircraft flight path and standard meteorological measurements from an automatic weather station. The Universities Facility for Atmospheric Measurement (UFAM) Doppler lidar system and automatic weather station were operated by the University of Salford.

This 1 km summary pixel data set represents the land surface of Great Britain and Northern Ireland, classified using two classification schemas: target and aggregate classes. The target class schema comprise 21 UKCEH land cover classes based upon Biodiversity Action Plan broad habitats. The aggregate class schema comprises 10 aggregate classes that are groupings of the 21 target classes. The aggregate classes group some of the more specialised target classes into more general classes. For example, the five coastal classes in the target class are grouped into a single aggregate class. The 1km percentage products describe percentage cover for each of the 21 land cover classes for 1km x 1km pixels. These contain one band per habitat class, producing 21 images for the target class product and 10 images for the aggregate class product. The 1km dominant coverage products are based on the 1km percentage products, and describe the land cover class with the highest percentage cover for each 1km pixel. A full description of these and all UKCEH LCM2020 products are available from the LCM2020 product documentation which accompanies the data. Full details about this dataset can be found at https://doi.org/10.5285/d6f8c045-521b-476e-b0d6-b3b97715c138

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.

The Netatmo V1 dataset contains observations from all Public Weather Stations (PWS) contributing to the Netatmo database within Europe. Netatmo is a company that designs and manufactures a range of smart weather station instruments for the home. The dataset is for a single year (2020), made available for use within the EUMETNET Sandbox project. EUMETNET (a grouping of 31 European National Meteorological Services) instigated the EUMETNET Sandbox project to bring novel observations and observations from technology trials and field campaigns to the research community to enable R&D activities. The data are not quality controlled and are presented in the format provided by Netatmo. The data are provided in a single file per month per country*. The data were extracted from the Netatmo database country by country. The meteorological values are unchanged from those extracted from the Netatmo archive. For example, there is no Quality Control of the data, no calibration of the instruments and no unit conversions have been applied. The data were extracted from the Netatmo database by Netatmo operators of the Netatmo system. The data have not been manipulated to meet any international data format standards. For each station there is always a metadata file 'n'.metadata.json. There are up to 4 data files associated with each station represented by a metadata file. In some cases, all 4 data files are present for the station. In other cases, only one data file is present. The 'n' in the file name allows the metadata file to be associated with the meteorological data files 1. n.pressure.historic.csv - surface pressure for station n 2. n.outdoor.historic.csv - Contains air temperature and humidity for station n 3. n.wind.historic.csv - Contains wind and gust data for station n 4. n.rain.historic.csv - rainfall data for station n The data files are semi-colon separated and use UNIX epoch time *Countries present in the Netatmo dataset Austria, Spain, Iceland, Norway, Belgium, Finland, Italy, Poland, Switzerland, France, Luxembourg, Portugal, Cyprus, United Kingdom, Latvia, Serbia, Czech Republic, Greece, Montenegro, Sweden, Germany, Croatia, North Macedonia, Slovenia, Denmark, Hungary, Malta, Slovakia, Estonia, Ireland and the Netherlands

The Met Office WOW V1 dataset contains observations from all Public Weather Stations (PWS) contributing to WOW (Weather Observations Website) within Europe. The dataset is for a single year (2020), made available for use within the EUMETNET Sandbox project. EUMETNET (a grouping of 31 European National Meteorological Services) instigated the EUMETNET Sandbox project to bring novel observations and observations from technology trials and field campaigns to the research community to enable R&D activities. The data are not quality controlled and are presented in the format provided by the Met Office. The data are provided in a single file per month. The data were extracted from the WOW database using a latitude/longitude bounding box (North West corner 90N 70W to South East corner 10N 40E) so there are a small number of stations outside of Europe present. The meteorological values are unchanged from those extracted from the WoW archive. For example, there is no Quality Control of the data, no calibration of the instruments and no unit conversions have been applied. The data were extracted from the WoW archive by the Met Office operators of the WoW system. The data have not been manipulated to meet any international data format standards. The file names have been modified, from those provided by the Met Office, to contain location, data and status information. The records for each station are comma separated. Not all sites report all variables, nor at all times. In most cases only the principle meteorological variables, e.g., Air temperature, Wet bulb, etc. are present. For a full list of available parameters within the files see the 'variables' information on this record.

MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc. The collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product. All of these data are provided under an Open Government Licence. The current collection contains the following proportions of the fuller MIDAS dataset collection: 96% of daily temperature observations 96% of daily weather observations 92% of hourly weather observations 94% of daily rainfall observations 96% of hourly rainfall observations 98% of soil temperature observations 96% of solar radiation observations 93% of mean wind observations Daily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations. The fuller "Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)" collection is made available for academic use via the Centre for Environmental Data Analysis. The MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed. Each version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023). Note: This collection does not supersede the full MIDAS collection which is also archived at CEDA.