LorenzCycleToolkit

Overview

The LorenzCycleToolkit is a tool for calculating the Lorenz Energy Cycle (LEC) in specific atmospheric regions. Introduced by Edward Lorenz in 1965, the LEC estimates atmospheric energy, including zonal and eddy components of Kinetic and Available Potential Energy, and the conversions between these forms.

Importance

• Climate Studies: Improves understanding of energy exchanges, aiding climate predictions.
• Weather Prediction: Comparison tool for weather models and forecasts.
• Research and Education: Provides a structured approach for analyzing atmospheric energy flows.
• Environmental Diagnostics: Serves as a diagnostic tool for atmospheric dynamics.

Applications

• Synoptic-Scale Phenomena: Study extratropical cyclones and convergence zones.
• Mesoscale Phenomena: Analyze energy transformations in tropical cyclones.
• Model Comparison: Compare model dynamics with reanalysis data.

Features

• Flexible Frameworks: Analyze fixed regions using Eulerian or Semi-Lagrangian frameworks.
• User-Friendly: Simple command-line interface without needing to program scripts.
• Customizable Inputs: Define custom domains and variable configurations.
• Visualization Options: Generate detailed plots to visualize the energy cycle components.

Documentation

For detailed documentation and usage instructions, visit the LorenzCycleToolkit Documentation.

Installation

To install the required dependencies, use the provided requirements.txt file:

pip install -r requirements.txt

Basic Usage

Run the toolkit with a sample NetCDF file:

python lorenzcycletoolkit.py samples/testdata_ERA5.nc -r -f

For more detailed usage instructions, including configuration options and examples, please refer to the documentation.

Contributing

Contributions are welcome! Please see the contributing guide for more details.

Continuous Integration and Deployment

This project uses GitHub Actions for Continuous Integration (CI) and Continuous Deployment (CD).

• CI Pipeline: The CI pipeline is triggered on each push and pull request to the repository. It runs the following steps:

  • Sets up the Python environment.
  • Installs dependencies.
  • Formats code using autopep8.
  • Sorts imports using isort.
  • Lints code using flake8.
  • Runs tests using pytest.

• CD Pipeline: The CD pipeline deploys the documentation to GitHub Pages whenever changes are pushed to the main branch.

You can view the CI/CD configuration in the following files:

• python-app.yml
• deploy-docs.yml

License

This project is licensed under the MIT License. See the LICENSE file for details.