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land

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  • 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.

  • 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 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.

  • 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 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.

  • 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. 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.

  • 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.

  • 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

  • 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').