This project contains Python implementations of various climate index algorithms which provide a geographical and temporal picture of the severity of precipitation and temperature anomalies useful for climate monitoring and research.
The following indices are provided:
- SPI, Standardized Precipitation Index, utilizing both gamma and Pearson Type III distributions
- SPEI, Standardized Precipitation Evapotranspiration Index, utilizing both gamma and Pearson Type III distributions
- PET, Potential Evapotranspiration, utilizing either Thornthwaite or Hargreaves equations
- PDSI, Palmer Drought Severity Index
- scPDSI, Self-calibrated Palmer Drought Severity Index
- PHDI, Palmer Hydrological Drought Index
- Z-Index, Palmer moisture anomaly index (Z-index)
- PMDI, Palmer Modified Drought Index
- PNP, Percentage of Normal Precipitation
This Python implementation of the above climate index algorithms is being developed with the following goals in mind:
- to provide an open source software package to compute a suite of climate indices commonly used for climate monitoring, with well documented code that is faithful to the relevant literature and which produces scientifically verifiable results
- to provide a central, open location for participation and collaboration for researchers, developers, and users of climate indices
- to facilitate standardization and consensus on best-of-breed climate index algorithms and corresponding compliant implementations in Python
- to provide transparency into the operational code used for climate monitoring activities at NCEI/NOAA, and consequent reproducibility of published datasets computed from this package
- to incorporate modern software engineering principles and programming best practices
This is a developmental/forked version of code that is originally developed and maintained by NIDIS/NCEI/NOAA. The official release version is available at drought.gov.