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Dataset

 

CRUTEM.5.0.0.0: Climatic Research Unit (CRU) gridded near-surface air temperature anomalies over land

Update Frequency: Not Planned
Latest Data Update: 2020-12-16
Status: Planned
Online Status: ONLINE
Publication State: Published
Publication Date: 2020-12-21
Download Stats: last 12 months
Dataset Size: 10.66K Files | 644MB
Abstract

CRUTEM (Climatic Research Unit TEMperature) is a gridded dataset of global historical near-surface air temperature anomalies over land at a monthly timescale. It is a collaborative product of the Climatic Research Unit at the University of East Anglia, the Met Office Hadley Centre and the National Centre for Atmospheric Science. CRUTEM also contributes the land air temperature station data to the global (land and ocean) temperature dataset called HadCRUT.

CRUTEM5 is the fifth major version of the dataset, covering the time period from 1850, with a spatial resolution of 5° latitude by 5° longitude and a monthly-mean time resolution. The gridded temperature anomaly fields are based on a compilation of monthly-mean temperature observational records from weather stations. This compilation contains 10639 station records, but only 7983 records had the necessary coverage to be used for producing the gridded dataset. Anomalies are differences from average conditions in the 1961-1990 period. Hemispheric and global mean time series of land air temperature anomalies are also provided.

Citable as:  University of East Anglia Climatic Research Unit; Met Office Hadley Centre; National Centre for Atmospheric Science; Osborn, T.; Jones, P.D.; Lister, D.; Morice, C.P.; Simpson, I.; Winn, J.P.; Hogan, E.; Harris, I.C. (2020): CRUTEM.5.0.0.0: Climatic Research Unit (CRU) gridded near-surface air temperature anomalies over land. Centre for Environmental Data Analysis, date of citation. https://catalogue.ceda.ac.uk/uuid/901f576dacae4e049630ab879d6fb476
Abbreviation: Not defined
Keywords: CRUTEM, Hadley, UEA, CRU, near-surface air temperature

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:

Daily or sub-daily measurement of near-surface air temperature at 10639 weather stations around the world.
Calculation of daily and then of monthly average temperature. Calculation of monthly averages is done by data providers.
Compilation by National Meteorological Services (NMS) of multiple stations, with quality control and in some cases homogeneity assessment and homogenisation.
Compilation by Climatic Research Unit (CRU) of data acquired from NMS and other compilations into a global station database.
Quality control and outlier identification by CRU.
Quality control and outlier identification by UK Met Office of near-real time data provided by NMS via global telecommunication systems.
Conversion to monthly temperature anomalies (relative to each station’s normal, i.e. the temporal mean over the 1961-1990 reference period) by CRU and Met Office.
Gridding of the station data onto a regular grid by CRU and Met Office.
Calculation of uncertainties from multiple sources that affect each grid-cell value by Met Office.
Calculation of global and hemispheric means, with uncertainties from multiple sources including incomplete spatial coverage, by CRU and Met Office.
Data Quality:
The Centre for Environmental Data Analysis have done no quality control on the data; they are as produced by the project team.
File Format:
The files are NetCDF4 formatted.

Related Documents

 Climatic Research Unit - Data
 Met Office Hadley Centre observations datasets - CRUTEM5
 Osborn, T. J., P. D. Jones, D. H. Lister, C. P. Morice, I. R. Simpson J. P. Winn, E. Hogan and I. C. Harris (2020), Land surface air temperature variations across the globe updated to 2019: the CRUTEM5 dataset, Journal of Geophysical Research

Process overview

This dataset was generated by the computation detailed below.
Title

CRUTEM5 data processing deployed on Met Office computers
Abstract

For details about the construction of the CRUTEM dataset, please refer to these papers:
Osborn, T.J. and Jones, P.D., 2014: The CRUTEM4 land-surface air temperature data set: construction, previous versions and dissemination via Google Earth. Earth System Science Data 6, 61-68, doi:10.5194/essd-6-61-2014
Osborn TJ, Jones PD, Lister DH, Morice CP, Simpson IR, Winn J, Hogan E and Harris IC (2020) Land surface air temperature variations across the globe updated to 2019: the CRUTEM5 dataset. Journal of Geophysical Research.
Input Description

None
Output Description

None
Software Reference

None
  • units: K
  • long_name: 2.5% confidence limit for air_temperature_anomaly
  • var_id: tas_lower
  • names: 2.5% confidence limit for air_temperature_anomaly
  • units: K
  • long_name: 2.5% confidence limit for air_temperature_anomaly over land given bias effects only
  • var_id: tas_lower_bias
  • names: 2.5% confidence limit for air_temperature_anomaly over land given bias effects only
  • units: K
  • long_name: 97.5% confidence limit for air_temperature_anomaly
  • var_id: tas_upper
  • names: 97.5% confidence limit for air_temperature_anomaly
  • units: K
  • long_name: 97.5% confidence limit for air_temperature_anomaly over land given bias effects only
  • var_id: tas_upper_bias
  • names: 97.5% confidence limit for air_temperature_anomaly over land given bias effects only
  • units: K
  • var_id: tas
  • standard_name: air_temperature_anomaly
  • long_name: air_temperature_anomaly over land
  • names: air_temperature_anomaly, air_temperature_anomaly over land
  • units: K
  • var_id: tas
  • standard_name: air_temperature_anomaly
  • long_name: air_temperature_anomaly over land (alternative grid)
  • names: air_temperature_anomaly, air_temperature_anomaly over land (alternative grid)
  • standard_name: air_temperature
  • units: deg_c
  • long_name: climatological air_temperature (2m) observed at meteorological station
  • var_id: tas_climatology_normal
  • names: air_temperature, climatological air_temperature (2m) observed at meteorological station
  • standard_name: air_temperature
  • units: deg_c
  • long_name: climatological standard deviation of air_temperature (2m) observed at meteorological station
  • var_id: tas_climatology_std
  • names: air_temperature, climatological standard deviation of air_temperature (2m) observed at meteorological station
  • var_id: climatology_normal_time_bnds
  • var_id: climatology_std_time_bnds
  • var_id: latitude_bnds
  • var_id: longitude_bnds
  • units: 1
  • standard_name: number_of_observations
  • long_name: number of stations per templates cell for air_temperature_anomaly over land
  • var_id: tas_nobs
  • names: number_of_observations, number of stations per templates cell for air_temperature_anomaly over land
  • units: K
  • long_name: standard_uncertainty in air_temperature_anomaly over land for station effects,spatially uncorrelated and temporally correlated
  • var_id: tas_corr
  • names: standard_uncertainty in air_temperature_anomaly over land for station effects,spatially uncorrelated and temporally correlated
  • units: K
  • long_name: standard_uncertainty in air_temperature_anomaly over land, spatially and temporally uncorrelated
  • var_id: tas_unc
  • names: standard_uncertainty in air_temperature_anomaly over land, spatially and temporally uncorrelated
  • standard_name: air_temperature
  • var_id: tas
  • units: deg_c
  • long_name: station air_temperature at approximately 2m
  • names: air_temperature, station air_temperature at approximately 2m
  • long_name: time for climatological normal statistics
  • var_id: climatology_normal_time
  • names: time for climatological normal statistics
  • long_name: time for climatological standard deviation statistics
  • var_id: climatology_std_time
  • names: time for climatological standard deviation statistics
  • var_id: time_bnds
  • units: K
  • long_name: uncertainty due to spatial sampling of gridded observations
  • var_id: coverage_unc
  • names: uncertainty due to spatial sampling of gridded observations

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • var_id: latitude
  • long_name: latitude
  • names: latitude
  • units: degrees_east
  • standard_name: longitude
  • var_id: longitude
  • long_name: longitude
  • names: longitude
  • long_name: time
  • standard_name: time
  • var_id: time
  • names: time
Coverage
Temporal Range
Start time:
1850-01-01T00:00:00
End time:
2019-12-31T23:59:59
Geographic Extent

 
90.0000°
  
-180.0000°
  
180.0000°
 
-90.0000°
  
Related parties
Authors (11)
Publishers (1)
Funders (1)