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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

Metadata

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