Abstract. We report on preliminary steps in the homogenisation of HadISD, a sub-daily, station-based data set covering 1973–2013. Using temperature, dew point temperature, sea-level pressure and wind speeds, change points are detected using the Pairwise Homogenisation Algorithm from Menne and Williams Jr. (2009). Monthly-mean values and monthly-mean diurnal ranges (temperature and dew point temperature) or monthly-maximum values (wind speeds) are processed using the full network of 6103 stations in HadISD. Where multiple change points are detected within 1 year, they are combined and the average date is used. Under the assumption that the underlying true population of inhomogeneity magnitudes is Gaussian, inhomogeneity magnitudes as small as around 0.5 °C, 0.5 hPa or 0.5 m s−1 have been successfully detected. The change point dates and inhomogeneity magnitudes for each of the calculation methods will be provided alongside the data set to allow users to select stations which have different levels of homogeneity. We give an example application of this change point information in calculating global temperature values from HadISD and comparing these to CRUTEM4. Removing the most inhomogeneous stations results in a better match between HadISD and CRUTEM4 when matched to the same coverage. However, further removals of stations with smaller and fewer inhomogeneities worsen the match.