ACCESS-Visualisation-Recipes 1.0.0 is now available!
Climate data analysis with intuitive and advanced visualisation tools.
The ACCESS-Visualisation-Recipes repository hosts a collection of recipes developed to simplify and enhance the visualisation of ACCESS climate model data. Designed as part of the Model Evaluation and Diagnostics (MED) team’s efforts at ACCESS-NRI, these recipes enable researchers to explore climate data using Python-based tools interactively.
ACCESS-Visualisation-Recipes 1.0.0 is now available to use on Gadi via the Australian Research Environment (ARE). Researchers can also explore the recipes on their local machines using the accessvis Python package.
Key Features
Supported by the ACCESS-Vis (accessvis) package for seamless rendering of climate data, including outputs from ACCESS-ESM models and CMIP6 datasets.
Comprehensive visualisation examples, including ozone concentration plots, global temperature visualisations, and bathymetry explorations.
Interactive Earth visualisation with dynamic features such as ice cover changes, seasons, and sun positioning using orbital information from Astropy.
Advanced animation capabilities, enabling researchers to create engaging 3D visualisation sequences.
Simple Regional plotting to focus on specific areas of interest.
How to Use
Running on Gadi (ARE)
- Log in to ARE:
- Go to the Australian Research Environment and start a JupyterLab session as per the instructions provided in the repository.
- Clone the ACCESS-Visualisation-Recipes" repository
git clone https://github.com/ACCESS-NRI/ACCESS-Visualisation-Recipes.git - Access Examples:
- Open the example notebooks to explore and interact with climate data.
Running Locally
- Install
accessvis:- Use
pip install accessvisto install the required Python package.
- Use
- Download the Recipes:
- Clone the repository and start using the recipes in your Python environment.
For detailed instructions, visit the ACCESS-Visualisation-Recipes GitHub repository.
Showcased Examples
- Sun and Seasons: Simulate Earth’s changing seasons and position the sun dynamically.
- Bathymetry: Exaggerate and explore ocean depths and mountain heights.
- Global Temperature Data: Plot high-resolution historical temperature data with custom colour schemes.
- Overlay Images: Integrate satellite imagery of clouds or ice cover on the Earth’s surface.
- Animations: Create zooms, rotations, and other 3D animations.
Acknowledgements
The visualisation recipes were developed by Owen Kaluza and the MED team at ACCESS-NRI. These tools aim to support the climate research community by simplifying complex data visualisation tasks.
Please tag @rbeucher and/or @OwKal for questions!
We welcome contributions and suggestions!!