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

Dataset

 

UKCP09: Met Office gridded land surface climate observations - precipitation and temperature indices at 5km resolution

Update Frequency: Not Planned
Latest Data Update: 2017-08-17
Status: Completed
Online Status: ONLINE
Publication State: Published
Publication Date: 2017-08-21
Download Stats: last 12 months
Dataset Size: 9.1K Files | 4GB

Abstract

This dataset contains a set of observed climate indices on a 5km resolution grid. The data are derived from daily temperature and precipitation grids (see related dataset) to provide annual indicies: 9 temperature based indices (for example summer heatwave duration); and 12 precipitation indices (for example maximum 1 day precipitation amount).

The data are provide in CF-1.5 compliant NetCDF format. The data are additionally provided in ESRI-ascii format, suitable for ingestion in GIS applications, and a simple timeseries format for users requiring a limited number of points.

Citable as:  Met Office (2017): UKCP09: Met Office gridded land surface climate observations - precipitation and temperature indices at 5km resolution. Centre for Environmental Data Analysis, date of citation. https://catalogue.ceda.ac.uk/uuid/68dfe0967cea4320a3889c2594fb1e0f
Abbreviation: Not defined
Keywords: UKCP09, Met Office, DEFRA, land surface, climate observations

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 an account to gain access.
Use of these data is covered by the following licence: 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 were produced by the Met Office for the UKCP09 service and then prepared for archiving with Centre for Environmental Data Analysis (CEDA).

Data Quality:
For details on data quality checks, grid accuracy etc. please see the linked "UKCP09 Frequently Asked Questions".
File Format:
The data are provide in CF-1.5 compliant NetCDF format. The data are additionally provided in ESRI-ascii format, suitable for ingestion in GIS applications, and a simple timeseries format for users requiring a limited number of points.

Process overview

This dataset was generated by the computation detailed below.
Title

UKCP09 gridded land surface 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 1914 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 monthly and annual grids are described in more detail in a paper published in the International Journal of Climatology, vol. 25 (2005), pages 1,041-1,054, which can be downloaded here: Generation of monthly gridded data sets for a range of climatic variables over the UK (PDF, 590 kB). The methods used to generate the daily grids are described in more detail in the report 'The generation of the daily gridded data sets of temperature and rainfall for the UK' (PDF, 2.27 MB).

The 5 × 5 km grids of the 1961-1990 baseline climate average available on these webpages are simply calculated by averaging or summing the 30 monthly or annual gridded data sets for each variable. They are not the same as the 1 × 1 km data sets presented on our UK Climate pages. The methods used to generate the 1 × 1 km data sets for 30-year average periods, which were used to normalise the station data prior to the generation of monthly and annual grids, are described in a paper published in the International Journal of Climatology, vol. 25 (2005), pages 1,023-1,039, which can be downloaded here: Development of a new set of long-term averages for the UK
(PDF, 1.08 MB)

To help users combine the 5 × 5 km baseline data sets with the UK Climate Projections, values of the 1961-1990 baseline climate average have also been generated for the 25 × 25 km grid boxes of the HadRM3 regional climate model and for administrative regions and river basins.

Each 25 × 25 km grid box value is an average of the 5 × 5 km grid cell values that fall within it. Averages have been calculated for each month, season and the year as a whole (17 data sets). For the days of frost and days of rain variables the seasonal and annual averages are the total of the individual monthly averages. For the remaining variables the seasonal and annual averages are the mean of the monthly averages (allowing for differences in month length). To facilitate combining the baseline data with the UKCP09 climate projections, the 25 km baseline averages for rainfall have been expressed in units of millimetres per day (rather than total millimetres, as for the 5 km data sets).

Each regional value is also an average of the 5 × 5 km grid cell values that fall within it. Monthly averages (12 values) have been calculated for each monthly variable and an annual average has been calculated for each annual variable. As with the 25 km data, the averages for rainfall have been expressed in units of millimetres per day.

Input Description

MIDAS land surface station data

Output Description

None

Software Reference

None

  • units: degC
  • long_name: Annual extreme temperature range
  • var_id: annual_extremetemperaturerange
  • units: 1.0
  • long_name: Annual number of rain days with precipitation that exceed the 1961-1990 90th percentile.
  • var_id: annual_raindays90percentile
  • units: 1.0
  • long_name: Annual number of rain days with precipitation that exceed the 1961-1990 99th percentile.
  • var_id: annual_raindays99percentile
  • units: degC day
  • long_name: Annual total cooling degree days
  • standard_name: integral_of_air_temperature_excess_wrt_time
  • var_id: annual_coolingdegreedays
  • units: degC day
  • standard_name: integral_of_air_temperature_excess_wrt_time
  • long_name: Annual total growing degree days
  • var_id: annual_growingdegreedays
  • units: degC day
  • long_name: Annual total heating degree days
  • standard_name: integral_of_air_temperature_deficit_wrt_time
  • var_id: annual_heatingdegreedays
  • units: mm
  • standard_name: lwe_thickness_of_precipitation_amount
  • long_name: Annual total precipitation amount
  • var_id: annual_rainfall
  • units: 1
  • long_name: Day of year of maximum precipitation
  • var_id: Day_number
  • units: mm
  • standard_name: lwe_thickness_of_precipitation_amount
  • long_name: Seasonal total precipitation amount
  • var_id: seasonal_rainfall
  • standard_name: air_temperature
  • var_id: air_temperature
  • units: degC
  • units: mm
  • standard_name: lwe_thickness_of_precipitation_amount
  • var_id: lwe_thickness_of_precipitation_amount
  • units: m
  • standard_name: projection_x_coordinate
  • var_id: projection_x_coordinate
  • var_id: projection_x_coordinate_bnds
  • units: m
  • standard_name: projection_y_coordinate
  • var_id: projection_y_coordinate
  • var_id: projection_y_coordinate_bnds
  • var_id: time_bnds
  • var_id: transverse_mercator

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • var_id: lat
  • units: degrees_east
  • standard_name: longitude
  • var_id: lon
  • standard_name: time
  • var_id: time
Coverage
Temporal Range
Start time:
1961-01-01T00:00:00
End time:
2014-12-31T23:59:59
Geographic Extent

 
61.1101°
 
-8.5649°
 
4.4195°
 
49.5310°