Pedro DiNezio

I use computer models to improve climate predictions on timescales from weeks to decades. My research bridges the gap between global climate change and decision-relevant scales by developing simulations that better capture variability and extremes. By advancing the representation of physical processes and feedback loops, I aim to produce robust projections to guide adaptation strategies. To achieve these goals, I have pioneered the integration of models with geological archives, improving our ability to predict long-term drought. Currently, I use high-resolution models to investigate how small-scale processes, often missing from conventional models, shape large-scale ocean-atmosphere responses important for prediction. Looking ahead, a central goal at ATLAS is to merge climate models, machine learning, and mapping platforms to make climate information more accessible and actionable.

The New York Times: The West’s Megadrought Might Not Let Up for Decades, Study Suggests
CU Boulder Today: Climate scientist reflects on year of disastrous weather—and what’s to come
The Conversation: Climate models reveal how human activity may be locking the Southwest into permanent drough
The Conversation: La Niña is coming, raising the chances of a dangerous Atlantic hurricane season – an atmospheric scientist explains this climate phenomenon