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A0725
Title: Modeling the impacts of climate factors across the distribution of wildfires Authors:  Adam Diaz - Clemson University (United States) [presenting]
Abstract: Climate change is widely expected to affect the behavior of wildland fires. However, the question of which climate factors are the most meaningful in the spread and sustenance of fires is not very straightforward to answer. The behavior of fire is dependent on terrain and geographic location, among many other non-climate factors. Additionally, the climate conditions that are ideal for ignition do not necessarily coincide with those that allow for a fire to grow completely out of control. We use a historical data set of California wildfires and ERA5 climate reanalysis data to model how this relationship differs between run-of-the-mill fires and extensive wildfires. Using a Bayesian Hierarchical framework, we attempt to relate wildfire characteristics with a set of climate covariates. Applying Integrated Nested Laplace Approximation (INLA) allows us to efficiently fit highly complex SPDE models and perform inference on our large data set. We utilize a spatial mixture model to account for the rich spatial dependence structure of the data, employ techniques from extreme value theory to analyze the most extreme fire events effectively.