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The Climatic Research Unit Global Climate Dataset

The CRU Global Climate Dataset, available through the IPCC DDC, consists of a multi-variate 0.5º latitude by 0.5º longitude resolution mean monthly climatology for global land areas, excluding Antarctica. Together with a mean climatology, which is strictly constrained to the period 1961-1990, there is a monthly time series at the same resolution for the period 1901-2000. The mean 1961-1990 climatology comprises a suite of eleven surface variables: precipitation (PRE) and wet-day frequency (WET); mean, maximum and minimum temperature (TMP, TMX, TMN); vapour pressure (VAP) and relative humidity (REH); sunshine percent (SUN) and cloud cover (CLD); frost frequency (FRS); and wind speed (WND). The time series component comprises all variables except sunshine per cent, frost frequency and wind speed. These are still under development.

The mean 1961-90 climatology

The mean climate surfaces have been constructed from a new dataset of station 1961-1990 climatological normals, numbering between 19,800 (precipitation) and 3615 (windspeed). The station data were interpolated as a function of latitude, longitude and elevation using thin-plate splines. The accuracy of the interpolations were assessed using cross-validation and by comparison with other climatologies (New et al., 1999).

The anomaly timeseries

The anomaly time series were constructed using historic anomalies derived from the monthly data holdings of the Climatic Research Unit (CRU) and the Global Historic Climatology Network (GHCN). For the purposes of developing monthly gridded time series, the variables were classified as either primary or secondary. For the primary variables - PRE, TMP, TMX, TMN - sufficient data were available to enable interpolation directly from the station time series. In the case of secondary variables - CLD, VAP, REH, WET - the available station time series were sparsely sampled in space and time. These variables had to be derived indirectly from gridded time series of primary variables. Station data that were available for secondary variables were used to develop relationships to the primary variables, and to validate the derived gridded time series.

The full global climate dataset

To calculate monthly time series, grids of monthly anomalies relative to 1961-90 were calculated for each variable and applied to their respective 1961-90 climatology. The anomaly approach was adopted because the network of station normals was much more comprehensive than the network of station time series. The spatial variability in mean climate was best captured by the denser network of station normals, while the more sparse network of primary variable time series captured as much temporal variability as possible.

Viewing and availability

Selected fields and time series from this climatology can be viewed through the Data Visualisation pages of the DDC. Decadal-mean and 30-year mean monthly fields can also be downloaded. Monthly data can be obtained from the Climatic Research Unit high resolution data page.


Mitchell TD and Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. International Journal of Climatology 25, 693-712 (doi:10.1002/joc.1181).

New, M., Hulme, M. and Jones, P.D., 1999: Representing twentieth century space-time climate variability. Part 1: development of a 1961-90 mean monthly terrestrial climatology. Journal of Climate 12, 829-856.