About the Zarzycki MEWAC lab

Real-time 7-day CESM forecasts

Housed within Penn State University's Department of Meteorology and Atmospheric Science, our group's research is broadly centered around understanding and quantifying weather and climate risk, using next-generation modeling tools and data science to connect atmospheric dynamics to real-world impacts. We develop and apply cutting-edge models to simulate high-impact weather phenomena, from tropical cyclones and atmospheric rivers to winter storms and freezing rain, and use storyline approaches to assess and communicate what extreme event risk looks like and how it is changing. Our group investigates tropical cyclone dynamics, asking questions about their internal structure and how they interact with the broader atmosphere and ocean on longer timescales that go beyond just "where is it headed in 3 days?" We also develop objective algorithms to detect and track weather extremes across large climate datasets, a challenge that grows as models increase in resolution and complexity. Increasingly, we leverage machine learning and artificial intelligence (ML/AI) to complement these physics-based approaches: using unsupervised techniques such as self-organizing maps to link large-scale circulation patterns to regional extremes, building neural network emulators for expensive model components, and curating AI-ready climate datasets to support data-driven research across the community.