Risk and Impact Assessment of Extreme Precipitation and Flooding Using High-Resolution Numerical Weather Simulations
Extreme weather events—including intense rainfall, flash flooding, and severe lightning—pose growing threats to communities and critical infrastructure. In our lab, we run high-resolution regional weather simulations using the Weather Research and Forecasting (WRF) model to capture the fine-scale atmospheric dynamics driving these storms. The goal of this project is to translate these complex physics-based model outputs into actionable impact and risk assessments.
Students will work directly with multi-dimensional WRF simulation outputs alongside observational datasets, such as lightning detection networks, flood inundation records, and historical storm damage logs. Depending on their experience level and interests, students can contribute across several tracks:
- Data Extraction & Validation: Processing raw WRF outputs (e.g., precipitation rates, wind and cloud fields) and benchmarking them against ground observations and RADAR/satellite records.
- Hazard & Correlation Analysis: Investigating physical relationships within the model data, such as how lightning activity or urban land-use features correlate with extreme rainfall intensity and flash flood susceptibility.
- Risk Modeling & Machine Learning: Developing statistical models or machine learning pipelines to predict damaging weather impacts and map regional vulnerability.
Students will be paired with PhD and postdoctoral researchers, as well as a faculty mentor to scope a self-contained sub-project matched to their coding and analytical background.
You will learn how to work with massive, real-world numerical weather prediction output from state-of-the-art regional climate model and turn them into practical risk insights for disaster resilience.
Our group (the Atmospheric Modeling Group) works at the intersection of atmospheric physics, environmental engineering, high-performance computing, and applied machine learning. Because we maintain an active suite of regional simulations, students can jump straight into analysis without waiting weeks to generate data. Beyond extreme precipitation and flood risk, ongoing research in our lab includes coupled meso-to-microscale wind energy modeling, urban air quality and aerosol dynamics, and transboundary pollution exposure, offering a collaborative environment where computational methods are applied to high-impact environmental challenges.