Metadata-Version: 2.1
Name: climate_indices
Version: 2.0.1
Summary: Reference implementations of various climate indices typically used for drought monitoring
Author: James Adams
Author-email: monocongo@gmail.com
Requires-Python: >=3.8,<3.12
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: cftime (>=1.6.4)
Requires-Dist: dask (>=2023.5.0)
Requires-Dist: h5netcdf (>=1.1.0)
Requires-Dist: scipy (==1.10.1)
Requires-Dist: xarray (>=2023.1.0)
Description-Content-Type: text/markdown

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# climate_indices

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#### 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](https://climatedataguide.ucar.edu/climate-data/standardized-precipitation-index-spi),
  Standardized Precipitation Index, utilizing both gamma and Pearson Type III distributions
- [SPEI](https://www.researchgate.net/publication/252361460_The_Standardized_Precipitation-Evapotranspiration_Index_SPEI_a_multiscalar_drought_index),
  Standardized Precipitation Evapotranspiration Index, utilizing both gamma and Pearson Type III distributions
- [PET](https://www.ncdc.noaa.gov/monitoring-references/dyk/potential-evapotranspiration), Potential Evapotranspiration, utilizing either [Thornthwaite](http://dx.doi.org/10.2307/21073)
  or [Hargreaves](http://dx.doi.org/10.13031/2013.26773) equations
- [PNP](http://www.droughtmanagement.info/percent-of-normal-precipitation/),
  Percentage of Normal Precipitation
- [PCI](https://www.tandfonline.com/doi/abs/10.1111/J.0033-0124.1980.00300.X), 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](https://www.drought.gov/drought/python-climate-indices).

- [__Documentation__](https://climate-indices.readthedocs.io/en/latest/)
- [__License__](LICENSE)
- [__Disclaimer__](DISCLAIMER)

#### 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--"
}
```

