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UMD

Climate and Extremes Data Science

MRG

Welcome! Our research focuses on the application of machine learning tools (e.g. neural networks) and numerical modeling systems (e.g. CESM) to answer pressing questions in the domains of climate and extremes. Examples of problems that we are tackling include:

☁ extending Earth system prediction,
☁ understanding genesis of extremes, and
☁ uncovering multi-scale patterns in the climate system.

Our research also strives to incorporate open-source software and data, accessible communication, and multi-discipline collaboration.

group-photo

Fall 2023 group photo. Pictured from left to right: Jhayron Steven Perez Carrasquilla, Emily Faith Wisinski, Erin Elise Evans, Hannah Bao, Cumulus, and Assistant Professor Maria J. Molina. Learn more about our group [here].

If you are interested in joining our group as a graduate researcher, please note that all interested applicants must apply online to be considered.


Recent News

☁ [March] Emily Wisinski was selected to participate in the NOAA Women in Science Leadership Workshop to be held next month in Princeton, NJ. Congrats, Emily!

☁ [February] Maria J. Molina earned the NASA Early Career Investigator Program in Earth Science Award for the project titled, "Quantifying urban heat using satellite-based estimation with machine learning."

☁ [February] Congratulations to Jhayron Steven Perez Carrasquilla for winning the Dr. Richard Payne Graduate Fellowship from the College of Computer, Mathematical, and Natural Sciences (CMNS), made possible in partnership with the National Socio-Environmental Synthesis Center (SESYNC). We are so proud of you, Jhayron!

☁ [February] Congratulations to Jhayron Steven Perez Carrasquilla for winning the 2nd place Best Student Oral Presentation Award from the AMS 23rd Conference on Artificial Intelligence for Environmental Science for “An Earth-System-Oriented View of the S2S Predictability of Weather Regimes.” Amazing work, Jhayron!

More news available [here].

Recent Publications

☁ *Campbell, T., G. M. Lackmann, M. J. Molina, and M. D. Parker (2024). Severe Convective Storms in Limited Instability Organized by Pattern and Distribution. Weather and Forecasting. [Link]

☁ Shah, S. H., C. O'Lenick, A. Ramos Valle, J. Wan, O. Wilhelmi, K. Ash, C. M. Edgeley, M. J. Molina, J. Moulite, C. C. Pizzaro, K. Emard, O. Cameron, J. Done, C. W. Hazard, T. Hopson, M. Jones, F. Lacey, M. A. Lachaud, D. Lombardozzi, M. Mendez, R. Morss, K. Ricke, F. Tormos-Aponte, W. Wieder, and C. Williams (2023). Connecting Physical and Social Science Datasets: Challenges and Pathways Forward. Environmental Research Communications. [Link]

☁ DuVivier, A. K., M. J. Molina, A. L. Deppenmeier, M. M. Holland, L. Landrum, K. Krumhardt, and S. Jenouvrier (2023). Projections of Winter Polynyas and Their Biophysical Impacts in the Ross Sea Antarctica. Climate Dynamics. [Link]

More publications available [here].


Any opinions, findings and conclusions or recommendations expressed herein do not necessarily reflect the views of the University of Maryland.

MRG