Skip to main content

Analysis ready CMIP6 data the easy way

Project description

Documentation Status Anaconda Cloud conda-forge Pypi Build Status Full Archive CI codecov License:MIT DOI

BLM

Science is not immune to racism. Academia is an elitist system with numerous gatekeepers that has mostly allowed a very limited spectrum of people to pursue a career. I believe we need to change that.

Open source development and reproducible science are a great way to democratize the means for scientific analysis. But you can't git clone software if you are being murdered by the police for being Black!

Free access to software and hollow diversity statements are hardly enough to crush the systemic and institutionalized racism in our society and academia.

If you are using this package, I ask you to go beyond just speaking out and donate here to Data for Black Lives and Black Lives Matter Action.

I explicitly welcome suggestions regarding the wording of this statement and for additional organizations to support. Please raise an issue for suggestions.

cmip6_preprocessing

Are you interested in CMIP6 data, but find that is is not quite analysis ready? Do you just want to run a simple (or complicated) analysis on various models and end up having to write logic for each seperate case, because various datasets still require fixes to names, coordinates, etc.? Then this package is for you.

Developed during the cmip6-hackathon this package provides utility functions that play nicely with intake-esm.

We currently support the following functions

  1. Preprocessing CMIP6 data (Please check out the tutorial for some examples using the pangeo cloud). The preprocessig includes: a. Fix inconsistent naming of dimensions and coordinates b. Fix inconsistent values,shape and dataset location of coordinates c. Homogenize longitude conventions d. Fix inconsistent units
  2. Creating large scale ocean basin masks for arbitrary model output

The following issues are under development:

  1. Reconstruct/find grid metrics
  2. Arrange different variables on their respective staggered grid, so they can work seamlessly with xgcm

Check out this recent Earthcube notebook (cite via doi: 10.1002/essoar.10504241.1) for a high level demo of cmip6_preprocessing and xgcm.

Installation

Install cmip6_preprocessing via pip:

pip install cmip6_preprocessing

or conda:

conda install -c conda-forge cmip6_preprocessing

To install the newest master from github you can use pip aswell:

pip install git+pip install git+https://github.com/jbusecke/cmip6_preprocessing.git

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

cmip6_preprocessing-0.6.0.tar.gz (8.0 MB view details)

Uploaded Source

Built Distribution

cmip6_preprocessing-0.6.0-py3-none-any.whl (55.5 kB view details)

Uploaded Python 3

File details

Details for the file cmip6_preprocessing-0.6.0.tar.gz.

File metadata

  • Download URL: cmip6_preprocessing-0.6.0.tar.gz
  • Upload date:
  • Size: 8.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for cmip6_preprocessing-0.6.0.tar.gz
Algorithm Hash digest
SHA256 bf5680d7382e06ce4a3b7fd47b788d8a130abac8580a801935915cae320268bf
MD5 7ed03a1eb270628900909e692a45c02d
BLAKE2b-256 69af57fcdc5c98a988ab362c6d0e67c3040ca86a82db4ac35943e7d6b30b7cfc

See more details on using hashes here.

File details

Details for the file cmip6_preprocessing-0.6.0-py3-none-any.whl.

File metadata

File hashes

Hashes for cmip6_preprocessing-0.6.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4401805b583b44da9de3ca05688005ee080684950860b7e1c50ce47f995e1829
MD5 e375d73e8b6aace4c11517990a8f3799
BLAKE2b-256 69dc59f19dea8ba363b99569acced3eb12a920590440578399a357fee865418e

See more details on using hashes here.

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