Biography
Liran Peng, Ph.D., is Assistant Project Scientist in the Department of Earth System Sciences at the University of California, Irvine. A climate scientist specializing in Arctic climate change, cloud microphysics, and multi-scale climate modeling, Peng has contributed to advancing understanding of atmospheric processes through high-resolution modeling frameworks and machine learning applications in climate science.
Peng received a Ph.D. in Arctic climate change from the University of Alaska, Fairbanks in 2019, an M.S. in cloud microphysics from the University of Wyoming in 2013, and a Bachelor's degree from Nanjing University in 2008. His research has focused on Arctic storm impacts on sea ice, cloud feedback mechanisms, and the development of innovative multi-scale modeling approaches. He has authored numerous peer-reviewed publications in journals including the Journal of Advances in Modeling Earth Systems, Geophysical Research Letters, and Atmospheric Chemistry and Physics, with recent work on improving stratocumulus cloud representation in climate models and climate-invariant machine learning.
Peng has extensive field research experience, having participated in three Arctic Ocean expeditions aboard the research vessel Araon between 2016 and 2018. He serves as a reviewer for multiple atmospheric science journals and has received computational support grants from the National Center for Atmospheric Research and the University of Illinois. Prior to his current position, he worked as a Postdoctoral Associate at UC Irvine from 2020 to 2023 and has presented his research at numerous international conferences and institutions.
Return to topEducation
- Ph.D. in Arctic climate change, University of Alaska, Fairbanks, 2019
- M.S. in Cloud microphysics, University of Wyoming, 2013
- Bachelor in Tropical typhoon structure study, Nanjing University, 2008
Distinctions
- Thesis/Dissertation Completion Fellowship, University of Alaska Fairbanks, 2018
Areas of Expertise
- Climate Modeling Systems
- Arctic Sea Ice Dynamics
- Cloud Microphysics Processes
- Atmospheric Storm Analysis
- Multi-scale Modeling Frameworks
- Machine Learning Climate Parameterization
- High-Resolution Computational Methods
- Hybrid Physics-ML Emulation
- Load Balancing Algorithms
- Tropical Typhoon Structure
Recent Publications
- Jerry Lin, Sungduk Yu, Liran Peng, Tom Beucler, Eliot Wong-Toi, Zeyuan Hu, Pierre Gentine, Margarita Geleta, Mike Pritchard, “Navigating the Noise: Bringing Clarity to ML Parameterization Design With O(100) Ensembles” (opens in new tab), Journal of Advances in Modeling Earth Systems, vol. 17, 2025.
- Peng, L., Blossey, P.N., Hannah, W.M., Bretherton, C.S., Terai, C.R., Jenney, A.M., Pritchard, M., “Improving stratocumulus cloud amounts in a 200-m resolution multi-scale modeling framework through tuning of its interior physics” (opens in new tab), Journal of Advances in Modeling Earth Systems, vol. 16, 2024.
- Beucler, T., Pritchard, M., Yuval, J., Gupta, A., Peng, L., Rasp, S., Ahmed, F., O'Gorman, P., Neelin, J., Lutsko, N., Gentine, P., “Climate-invariant machine learning” (opens in new tab), Science Advances, vol. 10, no. 6, 2024.
- Griffin Mooers, Mike Pritchard, Tom Beucler, Prakhar Srivastava, Harshini Mangipudi, Liran Peng, Pierre Gentine, Stephan Mandt, “Correction to: Comparing storm resolving models and climates via unsupervised machine learning (Scientific Reports, (2023), 13, 1, (22365), 10.1038/s41598-023-49455-w)” (opens in new tab), Scientific Reports, vol. 14, 2024.
- Yu, S., Hannah, W., Peng, L., Lin, J., Bhouri, M. A., Gupta, R., Pritchard, M., “ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation”, Advances in Neural Information Processing Systems, vol. 36, 2023. Presented at 37th Conference on Neural Information Processing Systems.
- Mooers, G., Pritchard, M., Beucler, T., Srivastava, P., Mangipudi, H., Peng, L., Mandt, S., “Comparing storm resolving models and climates via unsupervised machine learning” (opens in new tab), Scientific Reports, vol. 13, no. 1, pp. 22365, 2023.
- Bhouri, M. A., Peng, L., Pritchard, M. S., Gentine, P., “Multi-fidelity climate model parameterization for better generalization and extrapolation”, 2023.
- Peng, L., Pritchard, M., Hannah, W., Blossey, P., Worley, P., Bretherton, C., “Load balancing intense physics calculations to embed regionalized high-resolution cloud resolving models in the E3SM and CESM climate models” (opens in new tab), Journal of Advances in Modeling Earth Systems, vol. 14, 2022.
- Peng, L., Zhang, X., Kim, J.-H., Cho, K.-H., Kim, B.-M., Wang, Z., Tang, H., “Role of intense Arctic storm in accelerating summer sea ice melt: An in situ observational study”, Geophysical Research Letters, vol. 48, 2021.
- Peng, L., Snider, J. R., Wang, Z., “Ice crystal concentrations in wave clouds: dependencies on temperature, D > 0.5 µm aerosol particle concentration, and duration of cloud processing”, Atmospheric Chemistry and Physics, vol. 15, pp. 6113-6125, 2015.
- Wang, Z., French, J., Vali, G., Wechsler, P., Haimov, S., Rodi, A., Deng, M., Leon, D., Snider, J. R., Peng, L., Pazmany, A. L., “Single Aircraft Integration of Remote Sensing and In Situ Sampling for the Study of Cloud Microphysics and Dynamics”, Bulletin of the American Meteorological Society, vol. 93, pp. 653-668, 2012.
- Shu, S., Peng, L., Pazmany, A. L., “Analysis on structure of typhoon Longwang based on GPS dropsonde data”, Journal of Tropical Meteorology, vol. 17, no. 3, 2011.
Contact Information
Website: https://liranpeng.github.io
Email: liranp@uci.edu
Address: 3 Stanford Ct, Irvine CA
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Last updated on 7/24/2025.