Research

I study how reflecting sunlight back into space (a possible climate intervention) might affect crops that billions of people rely on. My research looks at staples like rice and wheat in India, as well as global favorites like coffee and chocolate. These studies help us see whether interventions could reduce crop stress from extremes under climate change—or what new risks might come along.

Climate models work best at the global scale, but farmers, city planners, and policymakers need local detail. I compare different methods — including machine learning — to “downscale” global climate projections into more usable, high-resolution maps. I test whether these methods can be trusted even under new conditions, like artificial cooling of the planet, to create reliable data for impact assessments worldwide.

Scientists and industry often use global climate datasets as a stand-in for observations, but these products aren't true ground observations and therefore don’t always agree. I worked with the Electric Power Research Institute to check how well leading datasets capture heatwaves and heavy rainfall in the U.S. Knowing where each product is strong — and where it falls short — helps everyone from farmers to energy companies make smarter decisions. It’s also important because the changes we expect from global warming depend on where we set our baseline.

Before focusing on agriculture and climate interventions, I studied how volcanic eruptions and Indian ocean temperature patterns influence the Indian monsoon. These natural “experiments” help us anticipate how the climate system might respond to human-made changes like solar geoengineering.