The Global SPEI database, SPEIbase, offers long-time, robust information about drought conditions at the global scale, with a 0.5 degrees spatial resolution and a monthly time resolution. It has a multi-scale character, providing SPEI time-scales between 1 and 48 months. Currently it covers the period between January 1901 and December 2020.
The SPEIbase can be accessed from spei_database.
The SPEIbase is based on monthly precipitation and potential evapotranspiration from the Climatic Research Unit of the University of East Anglia. Currently the version 4.05 of the CRU TS dataset has been used. The SPEIbase is usually updated as soon as new data becomes available.
The SPEIbase consists of standardized values over the emerged land pixels. No land pixels are assigned a value of 1.0x10^30. In some rare cases it was not possible to achieve a good fit to the log-logistic distribution, resulting in a NAN (not a number) value in the database.
The SPEIbase is based on the FAO-56 Penman-Monteith estimation of potential evapotranspiration. This is a major difference with respect to the SPEI Global Drought Monitor, that uses the Thornthwaite PET estimation. The Penman-Montheith method is considered a superior method, so the SPEIbase is recommended for most uses including long-term climatological analysis.
The R code used in generating the SPEIbase, since version 2.0, is accesible in GitHub, making the dataset completely reproducible.
(Use of the newest version is recommended. Older versions are still available to allow replicability.)
To calculate the SPEI we used the CRU TS 4.03 dataset. This is the most complete and updated dataset of gridded precipitation and potential evaporation at the global scale, has a spatial resolution of 0.5°, and covers the period 1901−2018.
Details of the SPEIbase and the comparison with other available drought data sets can be consulted in:
A number of users of our SPEIbase dataset worried because they could not read our netCDF files in their software. Indeed, some commercial softwares such as Matlab, ArcGIS and Idrisi do not have support for NetCDF4 or did not have it until recently. The main reason for us to use netCDF4 for the SPEIbase is because it allows for data compression, resulting in large file size and internet traffic saving. We did not use any of the other fancy options implemented in netCDF4 such as grouping, compound types or multiple unlimited dimensions. This means that our netCDF4 files conform to the classic model, so they can be converted back to the netCDF3 legacy format.
One way of converting to netCDF3 is by using the
nccopy program by unidata. For example, to convert a netCDF-4 classic-model format file foo4c.nc to a classic format file foo3.nc:
nccopy -k classic foo4c.nc foo3.nc.
Another way would be to install the netCDF operators (NCO) toolset from unidata, and then use the
ncks -3 foo4c.nc foo3.nc.
ncks allows for much greater functionality. For example, if one wants to extract the first 100 times from an SPEIbase file:
ncks -d time,0,100 spei_12.nc output_file.nc
would generate a (smaller) netCDF file with only those timesteps. In a similar fashion, it is possible to use
ncks to select a specific geographical region.
What follows is a human-readable summary of the ODbL 1.0 license. Please, read the full ODbL 1.0 license text for the exact terms that apply.Users of the dataset are free to:
The SPEIdata is provided as single files comprising the whole World for each SPEI time scale. The data format is netCDF.
All relevant metadata is self-contained in the .nc files, and can be read and displayed by any software allowing netCDF manipulation.
Manipulation of netCDF data is usually done at the programming level, and there are several libraries with functions for reading and manipulating netCDF data for a diversity of languages. For more information on the netCDF format and suggested tools, see http://en.wikipedia.org/wiki/NetCDF.
Panoply is a cross-platform netCDF viewer developed in Java (http://www.giss.nasa.gov/tools/panoply/). There are other netCDF viewers, such as ncBrowse, ncview, and nCDF_Browser.
netCDF data can be accessed and manipulated in the (open source) statistical analysis system R using the package netcdf.
Some commercial GIS packages allow reading netCDF data, such as ArcGIS (from version 9.2 on) and IDRISI Taiga.