NEOPRENE
Neyman-Scott stochastic rainfall generation in Python — synthetic series and disaggregation, single or multi-site.
The reference R implementation of SPEI and SPI from the index's own authors.
Install
install.packages("SPEI")The SPEI package is maintained by Santiago Beguería — co-author of the Standardised Precipitation-Evapotranspiration Index itself — making it the closest thing to a canonical implementation. It computes SPEI and SPI at any timescale, with the PET routines (Thornthwaite, Hargreaves, Penman-Monteith) the index depends on, and kernel-weighting and distribution options documented against the original papers.
For drought analyses that will be reviewed, "computed with the authors' own package" is a satisfying provenance line. Simple API, stable on CRAN, widely cited.
Other climate & change analysis tools covering similar workflow stages.
Neyman-Scott stochastic rainfall generation in Python — synthetic series and disaggregation, single or multi-site.
EPA's Climate Adjustment Tool for SWMM — apply downscaled climate projections to rainfall and evaporation inputs.
Programmatic access to ERA5 and the Copernicus Climate Data Store — the world's reanalysis workhorse.
Reference Python implementations of SPI, SPEI and Palmer indices for drought monitoring.
Statistical downscaling and bias correction of climate projections in R — part of the climate4R framework.
Climate indices and bias adjustment on xarray — the operational-grade library for climate-data engineering.