xclim
Open Source
Climate indices and bias adjustment on xarray — the operational-grade library for climate-data engineering.
climate_indices
StableReference Python implementations of SPI, SPEI and Palmer indices for drought monitoring.
- Pricing
- Open Source
- License
- BSD-3-Clause
- Commercial use
- Permitted
- Ecosystem
- Python, xarray
- Platform
- Windows, macOS, Linux
Install
pip install climate-indicesAbout climate_indices
The climate_indices package provides carefully validated Python implementations of the standard drought indices — SPI and SPEI (with proper distribution fitting), PET methods, PNP and the Palmer suite — designed for both single-station series and gridded NetCDF processing from the command line.
Drought indices are easy to implement subtly wrongly (fitting, calibration periods, zero-precipitation handling); this package exists so agencies and researchers converge on defensible numbers. It has been used in NOAA and NIDIS-adjacent monitoring contexts, which is exactly the pedigree a compliance-facing drought study wants.
Where it fits in the workflow
TerrainCatchmentRainfallRunoffRoutingHydraulicsMappingReporting
Alternatives to climate_indices
Ranked by the topics, categories and workflow stages they share with climate_indices.
SPEI (R package)
Open Source
The reference R implementation of SPEI and SPI from the index's own authors.
ERA5 / ERA5-Land
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The longest satellite soil moisture record available — merged active+passive retrievals back to 1978, free, no login.
Google Earth Engine
Freemium
Planetary-scale geospatial analysis in the cloud — the data catalogue and compute behind modern water remote sensing.
NEOPRENE
Open Source
Neyman-Scott stochastic rainfall generation in Python — synthetic series and disaggregation, single or multi-site.