Maggie Powell

Ph.D. Student · Earth & Environmental Engineering
Columbia University · DOE CSGF Fellow

I'm a PhD student, co-advised by Prof. Robert Pincus and Prof. Pierre Gentine, and a researcher with the NSF LEAP (Learning the Earth with Artificial Intelligence and Physics) Science and Technology Center. My research is funded by the Department of Energy Computational Science Graduate Fellowship.

My research combines atmospheric physics and scientific computing to better understand cloud processes and improve how they are represented in Earth System Models. Current projects include understanding how the 1D treatment of radiative transfer in models introduces errors in surface sunlight for cloudy atmospheres, and investigating how cloud shadows drive boundary layer turbulence using large-eddy simulation and DOE ARM observations.

Previously I was a Climate Impact Data Scientist at Gro Intelligence and a Research Analyst at Industrial Economics, Inc. I received my A.B. in Earth and Planetary Sciences from Harvard College in 2019.

m.powell@columbia.edu GitHub ORCID Scholar

News

Mar 2026 New preprint: Cloud geometry and solar zenith angle control 3D radiative effects . Submitted to Journal of the Atmospheric Sciences.
Jan 2026 New paper in JAMES: Perspectives on systematic cloud microphysics scheme development with machine learning (Lamb, Singer, Loftus, Morrison, Powell et al.).
Aug 2025 Attended the hpc4climate Summer School in Lauenburg, Germany, an eleven-day program on high-performance computing for climate science.
2024 Awarded the Department of Energy Computational Science Graduate Fellowship and the Columbia University Presidential Fellowship.

Research

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3D Cloud Radiative Effects

Atmospheric models treat radiative transfer as a 1D process, introducing systematic errors. We show these errors are primarily controlled by cloud geometry and solar angle, with cloud cover, aspect ratio, and transmissivity governing the sign and magnitude of the bias.

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NSF LEAP Center

As part of the NSF LEAP (Learning the Earth with Artificial Intelligence and Physics) Science and Technology Center, I collaborate on developing machine learning approaches that respect physical constraints for improving Earth System Model representations of clouds and climate.

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Shallow Cumulus–Surface Feedbacks

Exploring how cloud shadows alter the surface energy budget and feed back on cloud formation, depth, and organization using large-eddy simulation.

Publications

Peer-Reviewed Articles & Preprints

Cloud geometry and solar zenith angle control 3D radiative effects Preprint

Powell, M., van Heerwaarden, C., Gentine, P., & Pincus, R.

Submitted to Journal of the Atmospheric Sciences, 2026 · ESSOAr
Perspectives on systematic cloud microphysics scheme development with machine learning JAMES 2026

Lamb, K. D., Singer, C. E., Loftus, K., Morrison, H., Powell, M., Ko, J., Buch, J., Hu, A., van Lier Walqui, M., & Gentine, P.

Journal of Advances in Modeling Earth Systems, 18(1), e2025MS005341 · DOI
Scaling waterbody carbon dioxide and methane fluxes in the arctic using an integrated terrestrial-aquatic approach ERL 2023

Ludwig, S. M., Natali, S. M., Schade, J. D., Powell, M., Fiske, G., Schiferl, L. D., & Commane, R.

Environmental Research Letters, 18(6), 064019 · DOI
Using machine learning to predict inland aquatic CO₂ and CH₄ concentrations and the effects of wildfires in the Yukon-Kuskokwim Delta, Alaska GBC 2022

Ludwig, S. M., Natali, S. M., Mann, P. J., Schade, J. D., Holmes, R. M., Powell, M., Fiske, G., & Commane, R.

Global Biogeochemical Cycles, 36(4), e2021GB007146 · DOI
Using radon to quantify groundwater discharge and methane fluxes to a shallow, tundra lake on the Yukon-Kuskokwim Delta, Alaska Biogeochem. 2020

Dabrowski, J. S., Charette, M. A., Mann, P. J., Ludwig, S. M., Natali, S. M., Holmes, R. M., Schade, J. D., Powell, M., & Henderson, P. B.

Biogeochemistry, 148(1), pp. 69–89 · DOI

Conference Presentations

Leveraging subgrid-scale spatial organization and variability for improved cloud fraction parametrization using PINACLES simulations AGU 2024

Powell, M., Kaul, C., Pressel, K. G., Shpund, J., Ma, P.-L., & Gentine, P.

AGU Fall Meeting Abstracts, A21C-1701
Global calculations of tropical cyclone return periods and an ACE-like risk metric AGU 2022

Russotto, R. D., Caffrey, M., Powell, M., Lepore, C., Schneider, E., Dwyer, J. G., Qaddoumi, A., Dinh, L., & Simonetti, M.

AGU Fall Meeting Abstracts, A22G-1762
Integration of ground-based and airborne measurements shows substantial methane emissions from freshwater ecosystems in the Yukon-Kuskokwim Delta, Alaska AGU 2018

Powell, M., Commane, R., Ludwig, S., Mann, P. J., Schade, J. D., Natali, S., Wofsy, S. C., & Fiske, G.

AGU Fall Meeting Abstracts, B31F-2547