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 investigates the formation and chemical composition of atmospheric aerosol particles, particularly secondary organic aerosols formed through oxidation of organic gases. Using a large controlled atmospheric chamber, the work studies how environmental conditions influence aerosol chemistry, improving understanding of air pollution, climate impacts, cloud formation, and human health effects.

This research improves climate prediction models by developing advanced computational methods for simulating cloud microphysics. By tracking more detailed information about cloud droplets and aerosol interactions, the work enhances understanding of how clouds influence Earth’s energy balance, rainfall, and climate change, helping reduce uncertainty in long-term global climate projections.

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 improves weather and climate forecasting by studying how dry air mixes into thunderstorm clouds, a process called entrainment. Using satellite observations, radar data, and interpretable machine learning, the work refines outdated cloud physics models, helping scientists better predict severe weather, hurricanes, and long-term climate behavior.

This research compares Earth’s energy balance to a personal budget and examines how aerosols—especially black carbon—disturb that balance. By simulating how black carbon interacts with cloud droplets and light, the study helps improve understanding of climate impacts. The goal is better climate modeling and reducing harmful atmospheric pollution.

This research uses computer simulations to predict how Greenland’s ice mélange—the icy “cork” stabilizing glaciers—will melt under climate warming. Results show ocean temperatures drive melting twice as strongly as air temperatures. A new equation from this work helps improve climate models and reduce uncertainty in future sea-level rise.

The researcher studies how clouds on distant exoplanets affect their climates and potential for life. Working with NASA, they model how exotic materials—like iron or sapphire clouds—absorb and reflect light. They found particle shape greatly influences temperature and habitability, helping determine whether alien worlds could support liquid water and life.