Geeta Persad Came Back to Austin to Build a Climate Group That Actually Talks to Policy

Most academic climate scientists will tell you they care about policy and then publish a paper that no policymaker is ever going to read. Geeta Persad spent four years working at the Union of Concerned Scientists translating climate models for water managers, and she came back to academia knowing exactly what the gap looks like.

Author: Koutian Wu; GitHub: ktwu01

Geeta’s chronicle: ut01.github.io/geeta-persad-chronicle. It is one of a directory of chronicles forked from the Sean Xiang chronicle template, all built by UT Austin colleagues and me. The full directory: Ashley Matheny, Chen Ning Yang, Daniella Rempe, Eric C. Greene, Geeta Persad, Gengchen Mai, Juan Santiago, Kehan Dong, Marc Hesse, Sean Xiang, Zong-Liang Yang.

Geeta grew up in Austin, Texas. Her family is from Trinidad and Tobago, an economy shaped by petrochemicals, which is the kind of biographical detail that I think actually matters for how she thinks about climate. She did her undergraduate at Stanford in Geophysics, finishing in 2010, then worked as a Physical Scientist at NOAA before going to Princeton for her PhD in Atmospheric and Oceanic Sciences, which she finished in 2016. She held an NSF Graduate Research Fellowship, the HMEI-STEP fellowship, and the Ford STEP fellowship, with Michael Oppenheimer as her STEP adviser. She also picked up consecutive Outstanding Student Paper Awards at AGU during the PhD.

Her dissertation focused on atmospheric aerosols, the small particles produced by transportation, fossil fuel combustion, and agricultural burning. The reason aerosols are interesting and irritating in equal measure is that they have a significant climate effect that is regional, fast, and short-lived, while CO2 is global, slow, and long-lived. So a country can change its aerosol emissions and see climate consequences within a few years, in places that are not necessarily its own. The political economy of aerosols is therefore very different from CO2, and most public climate discussion ignores this entirely.

After Princeton she did a joint postdoc-y position from 2016 to 2020. She was a Research Associate at the Carnegie Institution for Science with Ken Caldeira at Stanford, while simultaneously serving as a Senior Climate Scientist at the Union of Concerned Scientists in their Western Water and Climate Program. The Carnegie work was global climate modeling. The UCS work was applying climate models to water resource decisions in California, advocating that planners use future climate projections rather than historical hydrology when designing infrastructure. That second job is where the policy translation muscle got built.

In 2020 she joined UT Austin’s Jackson School of Geosciences as Assistant Professor of Climate Science, returning to her hometown after fourteen years away. She founded the Persad Aero-Climate Group. The group’s research thread is the same one that runs through her career, who experiences the impacts of climate and air quality changes, and how do you translate climate model output into something that a regional policymaker, a water manager, or a public health official can act on.

The reason I am writing about her is partly that she is the climate-science neighbor of my Earth-system-modeling work at Jackson School, and partly because of how she frames the field. Climate justice in her hands is not a slogan. It is a research methodology. If your climate model resolves the global mean temperature beautifully but cannot tell a person in Houston what the next decade of summer heat is going to look like for their specific neighborhood, you have produced a Nature paper, not a useful science. She works on closing that gap.

The aerosol piece is also genuinely interesting from a modeling standpoint. Aerosol-climate interactions are still one of the largest sources of uncertainty in climate sensitivity estimates. The cloud microphysics is hard. The regional pattern of emissions has shifted dramatically in the last two decades, with declining aerosols in North America and Europe and growing aerosols in parts of Asia and Africa. This shift has fingerprints on regional precipitation that are only just starting to be quantified. Anyone who does land surface modeling on the same continents has to take aerosol forcing seriously, and her work is one of the cleaner sources for this.

Two things I take from watching her career. First, the postdoc-at-Carnegie-while-also-at-UCS structure was not a side hustle. It was a deliberate choice to learn how to write for two audiences at the same time, and I think it shows in everything she has published since. Second, she is open about the family-from-Trinidad piece informing her science, which sounds soft but actually disciplines the work. If you grew up watching how an oil and gas economy shapes a society, you do not write breezy papers about energy transitions.

For a PhD student doing AI for land surface models, the meta-lesson is that the model output is not the product. Someone has to be able to use it. I am still figuring out what that means for my own work, but the question I now ask is, if my Noah-MP results land on the desk of someone trying to plan a reservoir in 2040, can they actually use what I produced. If not, I have not finished the job.