This research investigates tropical atmospheric waves that influence rainfall, storms, and seasonal weather patterns. Using satellite observations and machine learning, the study shows that wave propagation depends on geographic location, upper-level winds, and topography. The findings can improve weather forecasting models and help communities better prepare for extreme rainfall events.

This research develops a high-resolution chemical method for analyzing tree rings to reconstruct past climates and ecosystem responses. By measuring atomic-scale chemical variations within cellulose molecules, the study separates environmental signals from biological responses, enabling more detailed understanding of historical climate change, plant physiology, and long-term ecosystem adaptation.

This research develops a machine-learning and data-assimilation framework that combines idealized and operational Earth systems models into a high-resolution, physically realistic “bridging model.” Applied to the El Niño–Southern Oscillation, the approach improves climate simulation accuracy while enabling exploration of alternative climate regimes and physically consistent what-if scenarios.

This research examines how atmospheric aerosols influence cloud formation and rainfall, particularly under turbulent conditions. Using a laboratory cloud chamber and computer modeling, the study investigates how particle size and concentration affect droplet growth. The findings aim to improve climate models and weather forecasting in both polluted and clean environments.

This research examined Antarctic soils for microplastics and found contamination near human activity at Scott Base and Cape Evans, but none in the remote McMurdo Dry Valleys. The findings reveal one of the last microplastic-free environments and highlight how clothing choices and human presence influence even Earth’s most pristine ecosystems.

The Arctic is no longer pristine. “Forever chemicals” like OPEs and PFAS are accumulating in wildlife and ecosystems, threatening Inuit food sources. By studying Arctic seabirds as early-warning indicators, this research provides critical evidence to inform regulation and protect vulnerable environments and communities.

This research develops stable-isotope tools to measure how microbes—the Earth’s “lungs”—breathe CO₂ in and out. Microbes are massively abundant and shape global climate. Findings show deep subsurface environments slowly emit CO₂, a process that may influence future climate dynamics as human-driven environmental changes accelerate.