Geos-Chem Data Analysis

Overview

This repository contains a Jupyter notebook for analyzing Geos-Chem model outputs. Geos-Chem is a global 3-D model of atmospheric chemistry and composition. This tool allows you to load, visualize, and analyze Geos-Chem data in both NetCDF and BPCH formats, making it easier to explore atmospheric chemistry data.

Key Features

• Support for Multiple Formats: Load and analyze Geos-Chem outputs in both NetCDF and BPCH formats.
• Interactive Visualizations: Generate static and interactive plots using matplotlib and cartopy.
• Custom Colormaps: Utilize the WhGrYlRd colormap for consistent and attractive visualizations.
• Automated Installation: Quick setup with an installation script for both conda and pip environments.
• Comprehensive Analysis: Explore variables, attributes, and coordinates with ease.

Getting Started

Prerequisites

• Python 3.6 or higher
• Conda or pip for environment management
• Jupyter Lab

Installation

Using the Install Script

• Conda:

  ./install.sh -e conda my_env

• Pip:

  ./install.sh -e pip

Manual Installation

• Conda:

  conda create -n my_env -f geoschem_data_analysis.yml

• Pip:

  pip install -r requirements.txt

Usage

• Conda:

  conda activate my_env
  jupyter-lab

• Pip:

  jupyter-lab

Project Structure

• analysis.ipynb: Main Jupyter notebook for data analysis.
• utils/: Contains utility scripts and data files.
  • gamap_colormap.py: Custom colormap for visualizations.
  • levs.csv: Level definitions for analysis.
• out/: Directory for output files and visualizations.
• requirements.txt: Python dependencies for pip installation.
• geoschem_data_analysis.yml: Conda environment file.
• install.sh: Automated installation script.

Customization

• Adapting to Other Outputs: Modify the file paths in analysis.ipynb to analyze different Geos-Chem outputs.
• Using Custom Levels: Adjust the levs.csv file to match your model's vertical levels.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

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

Acknowledgements

• Geos-Chem for the atmospheric chemistry model.
• xarray and xbpch for data handling.
• matplotlib and cartopy for visualizations.