Users are recommended to consult the author (malcolm.mistry@unive.it / malmistry1977@gmail.com) for an updated version which includes more recent years.71 core and non-core climate extreme indices (CEIs) based on the Expert Team on Climate Change Detection and Indices (ETCCDI), and the Expert Team on Sector-specific Climate Indices (ET-SCI). The indices are computed using R ClimPACT2 package. The dataset does not include two indices (Heating and Cooling Degree Days) as these are computed separately for various baseline temperature (thresholds) -See 'Historical Global-Gridded Degree-Days: A High Spatio-Resolution Database of CDD and HDD'-. All indices are computed using daily near-surface maximum and minimum temperature (deg C), and near-surface precipitation (mm/day) variables from Global Land Data Acquisation System (GLDAS) ver. 2 (@ 0.25 degree)Important: GLDAS ver-2 comprises of two sub-versions (ver. 2.0 for period 1970-2010 and ver 2.1 for period 2000-present day). The CEIs computed using the input temperature and precipitation variables may report a break in time-series at a few locations around the years 2010-11. Users are therefore advised caution when using the data for trend analysis for instance. Further details on the merging of the two versions can be found below:https://disc.gsfc.nasa.gov/information/faqs?title=Should%20I%20use%20GLDAS%20Version%202.0%20(GLDAS-2.0)%20or%20GLDAS%20Version%202.1%20(GLDAS-2.1)%3F
Data are in netCDF-4 format, at a spatial resolution of 0.25 degree by 0.25 degree (latitude by longitude)on a regular lon-lat grid. Some indices have data both at monthly and annual time-steps (as identified by the netCDF file name). Missing values are identified by values '1.e+20f'. Further details of the variables in the individual netCDF files can be checked using either NCO or CDO command line utilites as follows: "ncdump -h netcdf_file_name", "cdo sinfo netcdf_file_name". The developement of this dataset has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 756194 (ENERGYA).
Supplement to: Mistry, Malcolm Noshir (2019): A high resolution global gridded historical dataset of climate extreme indices. Data, 4(1)
