Skip to main content

ECmean4 Global Climate Model lightweight evaluation tool

Project description

Maintenance Documentation Status PyTest Coverage Status PyPI version DOI

ECmean4

A lightweight climate model evaluation tool

ECmean4 is a lightweight parallelized tool for evaluation of basic properties of Global Climate Models, such as global mean and climate model performance indices.

It builds on the original ECmean which has been used for EC-Earth2 and EC-Earth3 evaluation, but it uses Python3 as a scripting language to perform lazy calls with Xarray+Dask and makes use of YML configuration files, with parallelization support with Multiprocess. It works both on raw EC-Earth4 output and on CMOR model output from CMIP5 and CMIP6.

ECmean4 is under development, so please use it with caution!

A complete ReadTheDocs Documentation is available, please refer to this.

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

ecmean4-0.1.15.tar.gz (21.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ecmean4-0.1.15-py3-none-any.whl (20.7 MB view details)

Uploaded Python 3

File details

Details for the file ecmean4-0.1.15.tar.gz.

File metadata

  • Download URL: ecmean4-0.1.15.tar.gz
  • Upload date:
  • Size: 21.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for ecmean4-0.1.15.tar.gz
Algorithm Hash digest
SHA256 b7323656d3be8de7082300189939bfd3d5f7b721ac5918d1aa3692dcf65eec00
MD5 d201ed594e648c5b72921753d736a0ec
BLAKE2b-256 a56a5d0815a707856bf8d6d105c3c4df4a7f775367dd195ed1b7b9badb0bbe62

See more details on using hashes here.

File details

Details for the file ecmean4-0.1.15-py3-none-any.whl.

File metadata

  • Download URL: ecmean4-0.1.15-py3-none-any.whl
  • Upload date:
  • Size: 20.7 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for ecmean4-0.1.15-py3-none-any.whl
Algorithm Hash digest
SHA256 9194bd7cb15f977a8131f969862b0fb07e341a27293cc03f0a181d1d6aeb917a
MD5 6af33d9ac8ff5a97107bf2ec5f478ad4
BLAKE2b-256 89bb2e6e9e454e20d612a9bebfebffaa5eb98a7c18bc9a1b677a318c133909e1

See more details on using hashes here.

Supported by

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