NEOPRENE
Neyman-Scott stochastic rainfall generation in Python — synthetic series and disaggregation, single or multi-site.
Programmatic access to ERA5 and the Copernicus Climate Data Store — the world's reanalysis workhorse.
by ECMWF / Copernicus
Install
pip install cdsapicdsapi is the official Python client for the Copernicus Climate Data Store, which serves ERA5 — the global reanalysis that has become hydrology's default gap-free climate record — along with seasonal forecasts, CMIP projections, and dozens of derived datasets. A short script with your API key downloads exactly the variables, levels, period and region you need.
For catchments with sparse gauge coverage (most of the world), ERA5 via cdsapi is frequently the difference between "no forcing data" and a runnable model. Free registration; generous quotas; queue times vary.
Other climate & change analysis tools covering similar workflow stages.
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.
EPA's Climate Adjustment Tool for SWMM — apply downscaled climate projections to rainfall and evaporation inputs.
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.