This code uses a causal discovery and causal inference methods to analyse linkages among ENSO, circulation fields, and the summer monsoon precipitation over the Himalayas.
Main requirements
- Python >= 3.9
- Tigramite >= 5.0
The rest of requirements can be installed by using 'requirements_file.txt' by creating a virtual environment as follows:
$ conda create --name <env> --file <this file>
The code has been tested on platform: osx-64.
To run the code you can use a jupyter notebook: 'Causal analysis of climate dynamics.ipynb'. The notebook uses 'config.yml' with the basic setup for:
- preprocessing of climate indices
- plotting maps
- statistical testing
- lagged cross-correlation
- causal discovery using PCMCI algorithm and causal inference implemented in Tigramite
- plotting causal graphs
- bootstrapping