Temperature in the North American boreal forest is rising 2.5 times faster than the global average. Warming has caused boreal wildfires to become more frequent, larger, and severe than at any point in the last 10,000 years, which is eroding the resilience of forests, causing abrupt ecological change. Fires also increasingly threaten people, including Alaska Native and Canadian First-Nations communities. With climate change, the risk of fire and potential for forest degradation will only accelerate in the future. Advanced predictive modeling to evaluate and prioritize conservation and adaptation strategies hold great potential for mitigating the impact of increased fire by reducing risk, cost, and damage. My team develops advanced simulation models of boreal forests and fire. We use these models to identify leverage points that could alter trajectories toward sustainable social, economic, and ecological outcomes.
The purpose of this project is to deploy a state-of-the-art process-based simulation model of forests and the necessary dependencies in an HPC environment at Rensselaer Polytechnic Institute. Tasks will include compiling the model on "bare metal", optimizing and benchmarking performance, and developing a workflow for managing 100s of replicate runs. The key to project success will be replicable workflows that are well documented so a non CS expert can repeat the processes.