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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 2022 group photo. Pictured from left to right: Jhayron Steven Perez Carrasquilla, Cumulus, Assistant Prof. Maria J. Molina, Heather Fettke von Koeckritz, Alex Alvin Cheung, and Malcolm Maas. Malcolm is a first year AOSC student sitting in on research group meetings to observe and learn. 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

☁ [May] Congratulations to Alex Alvin Cheung for receiving the 2023 Unidata Users Workshop Student Travel Support to attend the in-person workshop in Boulder, Colorado this summer. Excellent work, Alvin!

☁ [May] Maria J. Molina will serve as a member of the Scientific Steering Group (SSG) of the World Climate Research Programme (WCRP) for the Earth System Modelling and Observations (ESMO) Core Project starting this June.

☁ [April] Congratulations to Jhayron Steven Perez Carrasquilla for making it to the finals of the Annual AOSC Ping Pong Championship!

More news available [here].

Recent Publications

☁ Morales, A., M. J. Molina, J. E. Trujillo-Falcón, K. M. Nuñez Ocasio, A. L. Lang, E. Murillo, C. Bieri, B. S. Barrett, L. B. Avilés, and S. J. Camargo (In Press). Commitment to Active Allyship is Required to Address the Lack of Hispanic and Latinx Representation in the Earth and Atmospheric Sciences. Bulletin of the American Meteorological Society. [Link]

Molina, M. J., E. Smith, T. Washington, D. Schvartzman, A. Morrison, C. Brinkworth, K. Aponte, K. Goebbert, M. Augustyniak, and K. Putsavage (2023). The AMS Early Career Leadership Academy: Training Leaders for a more Equitable and Inclusive Future, Bulletin of the American Meteorological Society, 45Beacon, EIJ Column. [Link]

Molina, M. J., J. H. Richter, A. A. Glanville, K. Dagon, J. Berner, A. Hu, and G. A. Meehl (2023). Subseasonal Representation and Predictability of North American Weather Regimes using Cluster Analysis. Artificial Intelligence for the Earth Systems. [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