Climate_Indices
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.
https://github.com/monocongo/climate_indices
Category: Climate Change
Sub Category: Climate Data Processing and Analysis
Keywords from Contributors
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Repository metadata
Climate indices for drought monitoring
- Host: GitHub
- URL: https://github.com/monocongo/climate_indices
- Owner: monocongo
- License: other
- Created: 2017-06-13T15:21:07.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2024-12-09T22:43:27.000Z (5 months ago)
- Last Synced: 2025-04-17T22:44:32.897Z (10 days ago)
- Language: Python
- Homepage: https://monocongo.github.io/climate_indices/
- Size: 29.3 MB
- Stars: 365
- Watchers: 20
- Forks: 171
- Open Issues: 107
- Releases: 2
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: code_of_conduct.md
README.md
climate_indices
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--"
}
Owner metadata
- Name: James Adams
- Login: monocongo
- Email:
- Kind: user
- Description:
- Website: https://www.drought.gov/drought/data-maps-tools/software
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/1328158?u=0ab524c4cf2027dd542cb00e6a3344d97ba30738&v=4
- Repositories: 75
- Last ynced at: 2024-06-11T15:57:38.274Z
- Profile URL: https://github.com/monocongo
GitHub Events
Total
- Issues event: 11
- Watch event: 21
- Issue comment event: 19
- Push event: 1
- Pull request review event: 1
- Pull request event: 1
- Fork event: 6
- Create event: 1
Last Year
- Issues event: 11
- Watch event: 21
- Issue comment event: 19
- Push event: 1
- Pull request review event: 1
- Pull request event: 1
- Fork event: 6
- Create event: 1
Committers metadata
Last synced: 5 days ago
Total Commits: 978
Total Committers: 19
Avg Commits per committer: 51.474
Development Distribution Score (DDS): 0.335
Commits in past year: 21
Committers in past year: 4
Avg Commits per committer in past year: 5.25
Development Distribution Score (DDS) in past year: 0.429
| Name | Commits | |
|---|---|---|
| James Adams | m****o@g****m | 650 |
| James.Adams | J****s@C****l | 213 |
| james.adams | j****s@o****m | 60 |
| James Adams | j****s@v****m | 11 |
| Benjamin Root | b****t@g****m | 10 |
| Arnab Paul Choudhury | a****4@g****m | 9 |
| Nathan Nayda | n****a@s****m | 6 |
| kikocorreoso | k****o@g****m | 4 |
| AGericke | g****e@i****n | 3 |
| dependabot[bot] | 4****] | 3 |
| Ben Lewis | b****n | 1 |
| David de Klerk | d****k@e****k | 1 |
| DeepSource Bot | b****t@d****o | 1 |
| Laura Guillory | l****y@g****m | 1 |
| deepsource-autofix[bot] | 6****] | 1 |
| kikocorreoso | y****u@e****m | 1 |
| snyk-bot | s****t@s****o | 1 |
| Scott Wales | s****s@u****u | 1 |
| haysengithub | d****e@g****m | 1 |
Committer domains:
- unimelb.edu.au: 1
- snyk.io: 1
- deepsource.io: 1
- ed.ac.uk: 1
- secondpillar.com: 1
- verisk.com: 1
- opensignal.com: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 321
Total pull requests: 245
Average time to close issues: 3 months
Average time to close pull requests: 11 days
Total issue authors: 108
Total pull request authors: 18
Average comments per issue: 2.76
Average comments per pull request: 0.96
Merged pull request: 218
Bot issues: 0
Bot pull requests: 3
Past year issues: 19
Past year pull requests: 12
Past year average time to close issues: 14 days
Past year average time to close pull requests: about 5 hours
Past year issue authors: 13
Past year pull request authors: 2
Past year average comments per issue: 1.89
Past year average comments per pull request: 2.5
Past year merged pull request: 11
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- monocongo (163)
- crestedcaracaryn (6)
- bennyistanto (5)
- kikocorreoso (5)
- SouhailAB (4)
- aleccourt (4)
- WeatherGod (4)
- wewe-sst (3)
- itati01 (3)
- wsor330 (3)
- tommylees112 (3)
- Lixia0911 (3)
- s-m-t-c (3)
- jamaa (2)
- yheng0821 (2)
Top Pull Request Authors
- monocongo (209)
- WeatherGod (9)
- Seven-milk (7)
- dependabot[bot] (3)
- kikocorreoso (3)
- nnayda (2)
- dawiedotcom (1)
- go1me (1)
- ScottWales (1)
- Emmadd (1)
- oshin94 (1)
- cshields143 (1)
- itati01 (1)
- Daafip (1)
- Laura-Guillory (1)
Top Issue Labels
- enhancement (28)
- help wanted (19)
- bug (11)
- question (3)
- documentation (2)
Top Pull Request Labels
- dependencies (4)
- enhancement (1)
Package metadata
- Total packages: 2
-
Total downloads:
- pypi: 2,153 last-month
- Total dependent packages: 0 (may contain duplicates)
- Total dependent repositories: 0 (may contain duplicates)
- Total versions: 19
- Total maintainers: 2
pypi.org: climdex-kit
Tool for multi-scenario calculation, publishing, and analysis of indices from 3D time-series of climate projections.
- Homepage: https://gitlab.inf.unibz.it/earth_observation_public/cdr/climdex-kit
- Documentation: https://climdex-kit.readthedocs.io/
- Licenses: GNU General Public License v3 (GPLv3)
- Latest release: 1.0.1 (published 5 months ago)
- Last Synced: 2025-04-26T13:36:40.457Z (1 day ago)
- Versions: 4
- Dependent Packages: 0
- Dependent Repositories: 0
- Downloads: 196 Last month
-
Rankings:
- Dependent packages count: 6.633%
- Average: 18.622%
- Dependent repos count: 30.611%
- Maintainers (1)
pypi.org: climate_indices
Reference implementations of various climate indices typically used for drought monitoring
- Homepage:
- Documentation: https://climate_indices.readthedocs.io/
- Licenses: BSD License
- Latest release: 2.0.1 (published 7 months ago)
- Last Synced: 2025-04-26T13:36:40.828Z (1 day ago)
- Versions: 15
- Dependent Packages: 0
- Dependent Repositories: 0
- Downloads: 1,957 Last month
-
Rankings:
- Downloads: 8.718%
- Dependent packages count: 10.315%
- Average: 25.697%
- Dependent repos count: 58.056%
- Maintainers (1)
Dependencies
- actions/checkout v3 composite
- actions/setup-python v2 composite
- pytest * develop
- toml 0.10.2 develop
- cftime 1.6.2
- dask 2022.2.0
- h5netcdf 1.1.0
- python >=3.8,<3.12
- scipy 1.9.3
- xarray 2023.1.0
- toml >=0.10.2
Score: 16.776963967289845