The Fire and Implications for Resilient Environments (FIRE) team specializes in the coupled interaction between multiple physical, chemical, ecological, and hydrologic processes and feedbacks across a range of spatiotemporal scales, ranging from sub-meter processes to global scales and sub-seconds to decades. We develop and apply both high-fidelity and fast-running coupled fire-atmosphere behavior models to link critical fire processes with environmental feedbacks to predict fire response.

The FIRE team comprises experts in combustion, fluid dynamics, heat transfer, turbulence, ecology, hydrology, computational science and machine learning to reveal process linkages and provide answers in the interest of national security, ecosystems and public health.

What We Do

Team capabilities include multi-fidelity coupled fire/atmosphere and smoke modeling, wildland fire- ecosystem interactions and impacts on hydrology. Our multidisciplinary team leverages numerical modeling capabilities to address interactions between natural and engineered systems such as those associated with prescribed fire and the multi-scale feedbacks between atmosphere and wind farms.

Primary Expertise

High-fidelity HPC-based model development
Fast-running decision support tools
Fundamental fire behavior research
Prescribed fire science
Large fire conflagrations in urban settings

Influences of heterogeneous vegetation structure
Wind turbine/atmosphere feedbacks
Wind turbine array flow fields
Transport and dispersion of gases and particulates
Turbulence in the atmospheric boundary layer; biosphere atmosphere interaction

Watershed response to fire disturbance and fire structure management
Ecosystem sustainability
Influences of three-dimensional vegetation structure
Fire as an ecosystem process
Fire effects modeling

Fire-environment dependent emissions modeling
Smoke Chemistry modeling
Global plume evolution and dispersion

Research Themes

Proactive Fire: Developing and using a suite of multi-fidelity simulation tools and data streams to improve the science basis and decision support tools to support a more active approach to wildland fire.
Fundamental wildland fire research: Improving our understanding of fire behavior and its response to variations in surrounding conditions. This work is essential to assuring that fire behavior prediction tools are able to capture the influences of heterogeneous environments and are appropriate as fire environments shift due to climate change and fire exclusion.
Fire’s role in ecosystem and hydrology system dynamics: Creating and integrating tools that will allow us to better understand the implications of wildland fire for ecosystem sustainability, watershed security and terrestrial carbon stability.
Urban Fire Modeling: Investigate behaviors and impacts of large conflagrations in urban environment (e.g., a variety of national security applications) that can develop firestorms.
Fire Feedback Modeling: Developing technologies to measure fire progress to be returned to fast running surrogate models informed by machine learning to predict short-term fire behavior between measurements.