HadISDH.extremes utilises simultaneous sub-daily dry bulb and wet bulb temperature (calculated from dry bulb and dew point temperature) data from over 4000 quality controlled HadISD stations that have sufficiently long records. After checking for sufficient completeness at the daily, monthly, annual, climatological and whole record scale, monthly indices are created from the maximum and minimum of the available daily values. Note that these likely underestimate the true extremes. Climatological averages are calculated over 1991-2020 and monthly climate anomalies obtained. These anomalies (in addition to climatological mean and standard deviation, actual values) are then averaged over 5° by 5° gridboxes centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N. Each gridbox month has an associated homogeneity score obtained from the homogenisation information from HadISDH.landT and HadISDH.landTw. Users can filter the data to remove those gridboxes likely affected by large inhomogeneity. While unlikely to be perfect, this process does help remove large errors from the data an improve robustness of long-term climate monitoring. For greater detail please see: Willett, K, in press: HadISDH.extremes Part 1: a gridded wet bulb temperature extremes index product for climate monitoring. Advances in Atmospheric Sciences, doi: 10.1007/s00376-023-2347-8. http://www.iapjournals.ac.cn/aas/en/article/doi/10.1007/s00376-023-2347-8. Willett, K. in press: HadISDH.extremes Part 2: exploring humid heat extremes using wet bulb temperature indices. Advances in Atmospheric Sciences, doi: 10.1007/s00376-023-2348-7. http://www.iapjournals.ac.cn/aas/en/article/doi/10.1007/s00376-023-2348-7. Docs contains links to both these publications.