Dataset
HadCRUT4: gridded dataset of global historical surface temperature anomalies. Version 4.4.0.0
Abstract
This is the HadCRUT.4.4.0.0 version of the HadCRUT4 data.
Data are available for each month since January 1850, on a 5 degree grid.
The gridded data are a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record. The ensemble median is provided and is provided as r0.
Error covariance information are available from the Met Office (see the link to the HadCRUT4 homepage in Docs)
To keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.
References:
When using the dataset in a paper you must cite the following paper (see Docs for link to the publication) and this dataset (using the "citable as" reference) :
Morice, C. P., J. J. Kennedy, N. A. Rayner, and P. D. Jones (2012), Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset, J. Geophys. Res., 117, D08101, doi:10.1029/2011JD017187
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/version/2/. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
HadCRUT4 is a surface air temperature product that is a blend of the CRUTEM4 and HadSST3, it is produced by the Met Office Hadley Centre in collaboration with the Climatic Research Unit of the University of East Anglia. It is passed to the BADC for archival and distribution. |
| Data Quality: |
The data have been quality controlled by the data provider but not by the Centre for Environmental Data Analysis (CEDA), see dataset associated documentation.
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| File Format: |
Data are netCDF formatted.
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Process overview
| Title | HadCRUT4: gridded dataset of global historical surface temperature anomalies produced by the Met Office Hadley Centre |
| Abstract | The gridded data are near surface temperature anomalies from 1850 (relative to 1961-1990) produced as a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record given current understanding of non-climatic factors affecting near-surface temperature observations. This ensemble approach allows characterisation of spatially and temporally correlated uncertainty structure in the gridded data, for example arising from uncertainties in methods used to account for changes in SST measurement practices, homogenisation of land station records and the potential impacts of urbanisation. The HadCRUT4 data are neither interpolated nor variance adjusted. |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
- long_name: Near Surface Air Temperature
- names: Near Surface Air Temperature
- long_name: field_status
- var_id: field_status
- names: field_status
- var_id: latitudebnds
- var_id: longitudebnds
- units: K
- long_name: near_surface_temperature_anomaly
- var_id: temperature_anomaly
- names: near_surface_temperature_anomaly
- units: K
- var_id: standard_error
- long_name: near_surface_temperature_anomaly standard_error
- names: near_surface_temperature_anomaly standard_error
- var_id: timebnds
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
Temporal Range
1850-01-01T00:00:00
2017-06-30T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |