This website uses cookies. By continuing to use this website you are agreeing to our use of cookies. 

Dataset

 

HadUK-Grid Climate Observations by UK countries, v1.0.1.0 (1862-2018)

Update Frequency: Not Planned
Latest Data Update: 2019-11-05
Status: Superseded
Online Status: ONLINE
Publication State: Citable
Publication Date: 2019-11-07
DOI Publication Date: 2019-11-14
Download Stats: last 12 months
Dataset Size: 132 Files | 12MB

This dataset has been superseded. See Latest Version here
Abstract

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 1km resolution have been averaged across a set of discrete geographies defining UK countries consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids 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 UKCP09 gridded observations and the earlier v1.0.0.0 version. 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 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 data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project "Analysis of historic drought and water scarcity in the UK". The dataset is provided under Open Government Licence.

Citable as:  Met Office; Hollis, D.; McCarthy, M.; Kendon, M.; Legg, T.; Simpson, I. (2019): HadUK-Grid Climate Observations by UK countries, v1.0.1.0 (1862-2018). Centre for Environmental Data Analysis, 14 November 2019. doi:10.5285/1715a1c03e544f47a3e803324f0bf4ca. https://dx.doi.org/10.5285/1715a1c03e544f47a3e803324f0bf4ca
Abbreviation: Not defined
Keywords: Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Access to these data is available to any registered CEDA user. Please Login or Register for a CEDA account to gain access.
Use of these data is covered by the following licence(s):
http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Data provided by the UK Met Office

Data Quality:
Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2018). See linked documentation for further details.
File Format:
Data are NetCDF formatted

Process overview

This dataset was generated by the computation detailed below.
Title

HadUK-Grid gridded climate observations methodology

Abstract

The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.

The methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).

To help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography.

Input Description

None

Output Description

None

Software Reference

None

  • var_id: geo_region
  • long_name: Country
  • units: no_unit
  • names: Country
  • standard_name: air_temperature
  • units: degC
  • var_id: tasmax
  • long_name: Maximum air temperature
  • names: air_temperature, Maximum air temperature
  • standard_name: air_temperature
  • var_id: tas
  • units: degC
  • long_name: Mean air temperature
  • names: air_temperature, Mean air temperature
  • standard_name: air_temperature
  • units: degC
  • var_id: tasmin
  • long_name: Minimum air temperature
  • names: air_temperature, Minimum air temperature
  • units: 1.0
  • long_name: Number of days with ground frost (minimum grass temperature below zero)
  • var_id: groundfrost
  • names: Number of days with ground frost (minimum grass temperature below zero)
  • units: 1.0
  • standard_name: surface_snow_binary_mask
  • long_name: Number of days with snow lying at 0900
  • var_id: snowLying
  • names: surface_snow_binary_mask, Number of days with snow lying at 0900
  • units: hPa
  • var_id: psl
  • standard_name: air_pressure_at_sea_level
  • long_name: Pressure at mean sea level
  • names: air_pressure_at_sea_level, Pressure at mean sea level
  • standard_name: relative_humidity
  • long_name: Relative humidity
  • var_id: hurs
  • units: 0.01
  • names: Relative humidity, relative_humidity
  • standard_name: duration_of_sunshine
  • units: hour
  • long_name: Sunshine hours
  • var_id: sun
  • names: duration_of_sunshine, Sunshine hours
  • units: mm
  • var_id: rainfall
  • standard_name: lwe_thickness_of_precipitation_amount
  • long_name: Total precipitation amount
  • names: lwe_thickness_of_precipitation_amount, Total precipitation amount
  • units: m s-1
  • standard_name: wind_speed
  • var_id: sfcWind
  • long_name: Wind speed at 10m
  • names: wind_speed, Wind speed at 10m
  • standard_name: area_type
  • var_id: area_type
  • units: no_unit
  • names: area_type
  • units: 1
  • long_name: calendar_year
  • var_id: calendar_year
  • names: calendar_year
  • units: no_unit
  • long_name: clim_season
  • var_id: clim_season
  • names: clim_season
  • units: 1
  • long_name: month_number
  • var_id: month_number
  • names: month_number
  • units: hPa
  • var_id: pv
  • standard_name: water_vapor_partial_pressure_in_air
  • long_name: partial pressure of water vapour
  • names: water_vapor_partial_pressure_in_air, partial pressure of water vapour
  • units: 1
  • standard_name: region
  • var_id: region
  • names: region
  • units: 1
  • long_name: season_year
  • var_id: season_year
  • names: season_year
  • units: 1
  • standard_name: surface_snow_area_fraction
  • var_id: surface_snow_area_fraction
  • names: surface_snow_area_fraction
  • units: degC
  • standard_name: surface_temperature
  • var_id: surface_temperature
  • names: surface_temperature
  • var_id: time_bnds

Co-ordinate Variables

  • standard_name: time
  • var_id: time
  • names: time
Coverage
Temporal Range
Start time:
1862-01-01T00:00:00
End time:
2018-12-31T23:59:59
Geographic Extent

 
60.8600°
 
-8.1800°
 
1.7600°
 
49.1600°