Welcome to the Interdisciplinary Approaches to Modeling Extreme Wildfire Events repository, part of the Environmental Data Science Innovation and Inclusion Lab (ESIIL). This repository serves as the central hub for our working group, hosting our project description, proposals, member bios, codebase, and more.
Extreme wildfire events are increasing, driven by the expansion of urban communities closer to forests, land management practices which suppressed wildfire, and climate change. These events have a low probability of occurring, but they exhibit exceptional fire behavior characteristics and produce severe consequences for forests and humans. While the media and field studies focus on extreme wildfire events like the Lahaina wildfire in Hawaii and the Paradise fire in California, most estimates of wildfire risk report averages, but not extreme events, and they often underestimate the effects of climate change. Our workshops will form a cohesive, interdisciplinary research team to: 1) synthesize our current understanding of extreme fire behavior, 2) isolate the current gaps in our understanding of the social and biophysical drivers that cause extreme wildfire events and risk to communities, 3) develop a roadmap for improving the representation of extreme events into models that represent social and biophysical processes, and 4) integrate a widely-used model of forest change into High Performance Computers to generate improved predictions of wildfire risk and the probability of extreme wildfire events. We will initially investigate extreme fires in the Sierra Nevada Mountains of California, interior Alaska, and the Southern Appalachians.
Here, you will find the accepted project proposal, including project goals, timeline and more.
- Member 1: Melissa Lucash, PI.
- Member 2: James Lamping, Co-PI and tech lead.
- Member 3: Rob Scheller, Co-PI.
- Member 4: Branda Nowell, Co-PI.
- Member 5: Sam Flake, Co-PI.
- Analysis Code: Scripts for data analysis, statistical modeling, etc.
- Data Processing: Scripts for cleaning, merging, and managing datasets.
- Visualization: Code for creating figures, charts, and interactive visualizations.
- Regular updates to keep all group members informed and engaged with the project's progress and direction.
- Contributions from all group members are welcome.
- Please adhere to these guidelines:
- Ensure commits have clear and concise messages.
- Document major changes in the meeting notes.
- Review and merge changes through pull requests for oversight.
- If you encounter any issues or have questions, please refer to the ESIIL Support Page or contact the repository maintainers directly.
- Edit This Readme: Update with information specific to your project.
- Update Group Member Bios: Add detailed information about each group member's expertise and role.
- Organize Your Code: Use logical structure and clear naming conventions.
- Document Your Data: Include a data directory with README files for datasets.
- Outline Your Methods: Create a METHODS.md file for methodologies and tools.
- Set Up Project Management: Use 'Issues' and 'Projects' for task tracking.
- Add a License: Include an appropriate open-source license.
- Create Contribution Guidelines: Establish a CONTRIBUTING.md file.
- Review and Merge Workflow: Document your process for reviewing and merging changes.
- Establish Communication Channels: Set up channels like Slack or Discord for discussions.
Remember, the goal is to make your repository clear, accessible, and useful for all current and future members of your working group. Happy researching!