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

This is the HadCRUT.4.5.0.0 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 data consist of 100 ensemble members and the ensemble median, each are available as a separate file where the fourth component of the filename denotes the ensemble member or median. In addition, the variance information is provided under the name uncorrelated. Full error covariance data 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

HadCRUT5 (Met Office Hadley Centre/Climatic Research Unit global surface temperature anomalies, version 5) is a gridded dataset of global historical near-surface air temperature anomalies since the year 1850. It has been developed and maintained by the Met Office Hadley Centre and University of East Anglia Climatic Research Unit. Air temperature information over land is derived from CRUTEM5 monthly average meteorological station temperature series, an expanded compilation of station series with revised quality control methods. Temperatures over ocean are derived from the HadSST4 sea-surface temperature dataset, including revised assessments of instrumental biases. Temperature data are presented as monthly average near-surface temperature anomalies, relative to the 1961-1990 period, on a regular 5° latitude by 5° longitude grid from 1850 to 2018, with derived global and hemispheric time series. Two variants of the dataset are provided. The first represents temperature anomaly data on a grid for locations where measurement data are available. The second, more spatially complete, variant uses a Gaussian process based statistical method to make better use of the available observations, extending temperature anomaly estimates into regions for which the underlying measurements are informative. Each is provided as a 200‐member ensemble accompanied by additional uncertainty information. Monthly updates to HadCRUT5 are available from the Met Office Hadobs website (see documentation links).

HadISD is a station based dataset comprising 6103 stations covering 1973-present. These stations are a subset of the stations available in the Integrated Surface Database (ISD), and are ones selected to be those most useful for climate studies (long records and high reporting frequency). Individual stations within the ISD were composited when it was appropriate to do so to improve the coverage. HadISD is a multi-variate dataset, where the following fields are available: temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud data (total, low, mid and high levels). These variables are all quality controlled using an automatic suite of tests, the code for which is available on request. The QC tests were designed to remove bad data whilst keeping true extremes. A number of other variables are also carried through to the final NetCDF files, but have not been quality controlled (e.g. precipitation period, precipitation depth, sunshine duration).