Skip to main content

Reference implementations of various climate indices typically used for drought monitoring

Project description

Banner Image

climate_indices

Actions Status License PyPI - Python Version

Python library of indices useful for climate monitoring

This project contains Python implementations of various climate index algorithms which provide a geographical and temporal picture of the severity and duration 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
  • PNP, Percentage of Normal Precipitation
  • PCI, Precipitation Concentration Index

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 scientific programming best practices

This is a developmental/forked version of code that was originally developed by NIDIS/NCEI/NOAA. See drought.gov.

Citation

You can cite climate_indices in your projects and research papers via the BibTeX entry below.

@misc {climate_indices,
    author = "James Adams",
    title  = "climate_indices, an open source Python library providing reference implementations of commonly used climate indices",
    url    = "https://github.com/monocongo/climate_indices",
    month  = "may",
    year   = "2017--"
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

climate_indices-2.0.1.tar.gz (56.7 kB view hashes)

Uploaded Source

Built Distribution

climate_indices-2.0.1-py3-none-any.whl (60.5 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page