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HadISD - global sub-daily station dataset - preliminary version

HadISD is a global sub-daily dataset based on the ISD dataset from NOAA's NCDC. As well as station selection criteria, a suite of quality control tests has been run on the major climatological variables. The data span 1/1/1931 to end 2015 and each station is available individually. The current version of HadISD is This is a preliminary version to include data up to the end of 2015. It is likely that it will be updated in the near future. To return to the previous version (, click here. For previous versions please contact the dataset maintainers.

A station listing with IDs, names and location information is here.

Brief description of the data

Individual stations within the ISD were composited when it was appropriate to do so. Then stations were selected on the basis of their length of record and reporting frequency. There are 7677 stations in HadISD., and these were passed through a suite of automated quality control tests designed to remove bad data while keeping the extremes. None of the ISD flags were used. The QC tests focussed on the temperature, dewpoint temperature and sea-level pressure variables, although some were applied to the wind speed and direction and cloud data. The data files also contain other variables which were pulled through from the raw ISD record, but have had no QC applied. Note: These data have not yet been homogenised and so trend fitting should be undertaken with caution.

Keep in touch

Follow us on twitter: @metofficeHadOBS for updates, news and announcements.

For more detailed information, follow our HadISD blog. Here we describe bug fixes, routine updates and other exploratory analysis.

HadISD sample image

Go to download page Data are available from the download page. Please read the terms and conditions.

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When using the dataset in a paper, the following are the correct citations to use. Please also state the version number used

Dunn, R. J. H., et al. (2016), Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491

Dunn, R. J. H., et al. (2014), Pairwise homogeneity assessment of HadISD, Climate of the Past, 10, 1501-1522

Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Climate of the Past, 8, 1649-1679

Smith, A., et al. (2011): The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704-708

Quality Control Code

The python code used for the station selection and quality control can be found on github. We do not intend to provide in-depth support for this code. We emphasise that the choices we have made in the selection and QC one of a number of other equally reasonable choices, and encourage other interested parties to develop their own QC and filtering procedures to allow the structural uncertainties of this sub-daily dataset to be investigated.

Online Material

A number of summary and diagnostic outputs from the quality control code as well as station lists for a number of selection criteria are available here. Also available is the information from the homogeneity assessment of v2.0.0.2015p.

We have adapted our versioning system from CRUTEM4, and so the dataset numbering is of the form HadISD.X.Y.Z.1234i, and is outlined in more detail in the paper linked above. X is for a major change and would be accompanied by a peer-reviewed paper. Y is a more minor change, e.g. in one of the QC tests and would be described in a tech-note. Finally Z is a small change, for example addition or changes to data in the past. The last complete year of the dataset is given by 1234, and the final character shows if the dataset is f-final or p-preliminary. Therefore HadISD. is the final version of the dataset containing data up to the end of 2012, and there have been some changes to past data over HadISD.

NEW: A number of images and movies created from HadISD to show its capabilities are here.

Dataset produced in collaboration with: