News Teaching Publications Group Research
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, multi-discipline collaboration, and stakeholder engagement.

group-photo

Fall 2022 group photo. Pictured from left to right: Jhayron Steven Perez Carrasquilla, 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.


Group

Maria Molina

Dr. Maria J. Molina

Assistant Professor

she/her

I am an Assistant Professor within the Department of Atmospheric and Oceanic Science at the University of Maryland and an Affiliate Faculty with the University of Maryland Institute for Advanced Computer Studies (UMIACS). I am also affiliated with the National Center for Atmospheric Research (NCAR) in Boulder, Colorado and am an Adjunct Assistant Professor within the Department of Marine, Earth, and Atmospheric Sciences at North Carolina State University. I am Vice-Chair of the AMS STAC Committee on Artificial Intelligence Applications to Environmental Science and am a member of the AMS Board on Representation, Accessibility, Inclusion, and Diversity (BRAID).

[CV]
Siddharth Cherukupalli

Siddharth Cherukupalli

CS Undergraduate

he/him

I am a second-year Computer Science major at the University of Maryland, College Park. I have previous research experience and also lead a STIC course in the CS department. I am interested in the application of Computer Science, specifically Machine Learning/NLP, to solve real-world issues related to climate. I think this is an intersection that has not been explored in-depth yet, so there is a lot of potential in terms of utilizing the most pivotal invention of our generation to solve a pressing issue. Outside of research, I like to spend a lot of my time keeping up with the stock market and watching basketball.

Alex Alvin Cheung

Alex Alvin Cheung

AOSC PhD Student

he/him

I am a Graduate Research Assistant within the Department of Atmospheric and Oceanic Science at the University of Maryland, College Park. I earned a B.S. in Meteorology and Atmospheric Science (w/ honors) at Penn State. My research interest involves studying tropical cyclones (TCs) and understanding the mechanisms that control their intensity and storm motion. My current research focuses on using machine learning (ML) techniques to study TCs (e.g., Secondary Eyewall Formations). At UMD, I will continue my studies in TCs with ML applications. Outside of research, I have a strong interest in teaching, especially in core science courses and helping students with coding.

Heather Fettke von Koeckritz

Heather Fettke von Koeckritz

AOSC/MechEng Undergraduate

she/her

I am an undergraduate student pursuing degrees in Mechanical Engineering and Atmospheric and Oceanic Sciences with a minor in Robotics and Autonomous Systems at the University of Maryland, College Park. My research interests involve renewable energy, coastal processes, and climate change. My current research will involve training ML models to analyze and further understand the impacts of stratospheric aerosol injection on climate patterns. I hope to be able to continue my research using ML after graduating and possibly pursue an advanced degree in engineering or computer science. Outside of the classroom, I enjoy hiking, skiing, and sailing.

Bhuvan Jammalamadaka

Bhuvan Jammalamadaka

CS Undergraduate

he/him

I am a second-year Computer Science student at the University of Maryland, College Park. I have gained valuable experience as an undergraduate research assistant and course instructor in the UMD STIC program. I am particularly interested in the intersection of Computer Science and Climate because of the critical role that technology can play in mitigating the effects of climate change and reducing our carbon footprint. By utilizing the advancements in computer science and technology, we have the potential to create more sustainable systems and solutions to address this global issue. In addition to my research pursuits, I enjoy staying informed about financial markets and engaging in chess as a leisure activity.

Jhayron Steven Perez Carrasquilla

Jhayron Steven Perez Carrasquilla

AOSC PhD Student

he/him

I am currently pursuing a Ph.D. degree in the Department of Atmospheric and Oceanic Science at the University of Maryland, College Park and am working as a Graduate Research Assistant. I earned a bachelor's and master's degree in engineering from the Universidad Nacional de Colombia. My main research interests are moist convection and extreme rainfall events. My work has focused on applying machine learning and numerical modeling to meteorology, hydrology, and air quality problems. I also love sports, movies and books.

Varun Vishnubhotla

Varun Vishnubhotla

CS Undergraduate

he/him

I'm an undergraduate student studying Computer Science with a minor in Statistics at the University of Maryland, College Park. My research interests lie in using Machine Learning (ML) to analyze the implications of climate misinformation. My current research involves using Natural Language Processing to conduct social media sentiment analysis and analyze prediction capabilities of specific climate patterns. I hope to continue researching in various ML subsets and use this experience for professional enrichment, while also providing exposure to graduate level practicums. Outside of the classroom, I enjoy drawing, keeping up with football and basketball, and listening to music.

Cumulus

Cumulus ☁️

Group Mascot

support animal

Struggling with research? Can't find the bug in your code? Questioning your life decisions? I am here to provide you with emotional support.


Publications

☁ Research In Progress (group members in bold)

[2.] Molina, M. J., T. A. O'Brien, G. Anderson, M. Ashfaq, K. E. Bennett, W. D. Collins, K. Dagon, J. M. Restrepo, and P. A. Ullrich (Under Review). Recent and Emerging Machine Learning Applications for Climate Variability and Weather Phenomena. Artificial Intelligence for the Earth Systems.

[1.] 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 (Under Review). 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.

☁ Peer-Reviewed Journal Publications

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

[14.] Dagon, K., J. Truesdale, J. C. Biard, K. E. Kunkel, G. A. Meehl, and M. J. Molina (2022). Machine learning-based detection of weather fronts and associated extreme precipitation in historical and future climates. Journal of Geophysical Research: Atmospheres. [Link]

[13.] Morales, A., L. Medina Luna, D. Zietlow, J. E. LeBeau, and M. J. Molina (2022). Testing the Impact of Culturally-Relevant Communication Style on Engagement with Hispanic and Latinx Adults. Journal of Geoscience Education. [Link]

[12.] Yeager, S. G., N. Rosenbloom, A. A. Glanville, X. Wu, I. Simpson, H. Li, M. J. Molina, K. Krumhardt, S. Mogen, K. Lindsay, D. Lombardozzi, W. Wieder, W. Kim, J. H. Richter, M. Long, G. Danabasoglu, D. Bailey, M. Holland, N. Lovenduski, W. G. Strand, and T. King (2022). The Seasonal-to-Multiyear Large Ensemble (SMYLE) Prediction System using the Community Earth System Model Version 2. Geoscientific Model Development. [Link]

[11.] Tye, M. R., K. Dagon, M. J. Molina, J. H. Richter, D. Visioni, B. Kravitz, C. Tebaldi, and S. Tilmes (2022). Indices of Extremes: Geographic patterns of change in extremes and associated vegetation impacts under climate intervention. Earth System Dynamics. [Link]

[10.] Molina, M. J., A. Hu, and G. A. Meehl (2022). Response of Global SSTs and ENSO to the Atlantic and Pacific Meridional Overturning Circulations. Journal of Climate. [Link]

[9.] Molina, M. J., D. J. Gagne, and A. F. Prein (2021). A benchmark to test generalization capabilities of deep learning methods to classify severe convective storms in a changing climate. Earth and Space Science. [Link]

[8.] Hu, A., G. A. Meehl, N. Rosenbloom, M. J. Molina, and W. G. Strand (2021). The influence of variability in meridional overturning on global ocean circulation. Journal of Climate. [Link]

[7.] Poujol, B., A. F. Prein, M. J. Molina, and C. Muller (2021). Dynamic and thermodynamic impacts of climate change on organized convection in Alaska. Climate Dynamics, 1-25. [Link]

[6.] Molina, M. J., J. T. Allen, and A. F. Prein (2020). Moisture Attribution and Sensitivity Analysis of a Winter Tornado Outbreak. Weather and Forecasting, 35(4), 1263-1288. [Link]

[5.] Molina, M. J., and J. T. Allen (2020). Regionally-stratified tornadoes: Moisture source physical reasoning and climate trends. Weather and Climate Extremes, 28, 100244. [Link]

[4.] Molina, M. J., and J. T. Allen (2019). On the moisture origins of tornadic thunderstorms. Journal of Climate, 32(14), 4321-4346. [Link]

[3.] Molina, M. J., J. T. Allen, and V. A. Gensini (2018). The Gulf of Mexico and ENSO influence on subseasonal and seasonal CONUS winter tornado variability. Journal of Applied Meteorology and Climatology, 57(10), 2439-2463. [Link]

[2.] Allen, J. T., M. J. Molina, and V. A. Gensini (2018). Modulation of annual cycle of tornadoes by El Niño–Southern Oscillation. Geophysical Research Letters, 45(11), 5708-5717. [Link]

[1.] Molina, M. J., R. P. Timmer, and J. T. Allen (2016). Importance of the Gulf of Mexico as a climate driver for US severe thunderstorm activity. Geophysical Research Letters, 43(23), 12-295. [Link]

☁ Other Technical and Concept Papers

[6.] Molina, M. J., T. A. O’Brien, G. Anderson, M. Ashfaq, K. E. Bennett, W. Collins, S. Collis, K. Dagon, S. Klein, J. M. Restrepo, and P. A. Ullrich (2022). DOE AI for Earth System Predictability Workshop Report, Chapter 8: Climate Variability and Extremes, 186-201. [Link]

[5.] Molina, M. J., J. Richter, J. Berner, A. A. Glanville, K. Dagon, A. Jaye, A. Hu, and G. Meehl (2022). Deep learning for subseasonal precipitation and temperature errors. Climate prediction S&T digest: NWS science & technology infusion climate bulletin supplement. [Link]

[4.] Dagon, K., M. J. Molina, G. A. Meehl, J. H. Richter, E. A. Barnes, J. Berner, J. M. Caron, W. Chapman, G. Danabasoglu, D. J. Gagne, S. Glanville, S. E. Haupt, A. Hu, Z. Martin, K. Mayer, K. Pegion, K. Raeder, I. Simpson, A. Subramanian, and S. Yeager (2021). Machine learning to extend and understand the sources and limits of water cycle predictability on subseasonal-to-decadal timescales in the Earth system. DOE Concept Papers to Advance an Integrative Artificial Intelligence Framework for Earth System Predictability: AI4ESP. [Link]

[3.] Ahmed, N., M. Slipski, I. Venzor-Cardenas, M. J. Molina, G. Senay, M. Cheung, C. Tillier, S. Edgington, and G. Renard (2020). Leveraging Lightning with Convolutional Recurrent AutoEncoder and ROCKET for Severe Weather Detection. Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), AI4EARTH. [Link]

[2.] Slipski, M, I. Venzor-Cardenas, M. J. Molina, N. Ahmed, M. Cheung, C. Tillier, S. Edgington, and G. Renard (2020). Predicting severe thunderstorms with machine learning and the Geostationary Lightning Mapper. Frontier Development Lab Technical Memorandum. [Link]

[1.] Molina, M. J., J. T. Allen, and V. A. Gensini (2018). Gulf of Mexico influence on sub-seasonal and seasonal severe thunderstorm frequency. NOAA Climate Prediction S&T Digest: National Weather Service science & technology infusion climate bulletin supplement, 42-45. [Link]


Teaching

Course offerings
Fall 2023: (AOSC400) Physical Meteorology

Group Training

In addition to research check-ins and discussions, our research group sets time aside for soft-skills training. Studies have shown that career success can be attributed to soft-skills. Biweekly meetings will be held to help address this critically important training, along with other needed skills for graduate school.

Fall Semester 2022
[Sep. 7] UMD graduate school path: what do you need to do to graduate?
[Sep. 21] Scholarship, grant, fellowship, and visiting opportunities
[Oct. 5] Open science (software and data practices)
[Oct. 19] Professional enrichment workshops and opportunities
[Nov. 2] Award winning presentations and posters
[Nov. 16] Importance of being kind in science
[Nov. 30] Building a website
Spring Semester 2023
[Feb. 1] Time management and productive procrastination
[Feb. 15] Your online professional presence and social media
[Mar. 1] Where to publish? And predatory journals
[Mar. 15] Surviving peer review
[Mar. 29] Formatting your CV
[Apr. 12] Importance of professional networks
[Apr. 26] Service in academia (UMD, AMS, AGU, and other opportunities)
[May 10] DEI and being an advocate and ally

News

☁ [January 2023] Current undergraduates in the Department of Computer Science, Varun Vishnubhotla, Bhuvan Jammalamadaka, and Siddharth Cherukupalli, have joined our research group. Welcome!

☁ [January 2023] Maria J. Molina will participate in the Convergence Research (CORE) Institute, which is funded by the NSF Convergence Accelerator. 2023 CORE Fellows will focus on "Tackling Climate-Induced Challenges with AI."

☁ [January 2023] Alex Alvin Cheung and Maria J. Molina presented at the AMS Conference in Denver on January 8-12.
Alvin's talk was:
11.5 - Documenting the Progressions of Secondary Eyewall Formations
Maria's talks were:
JointJ8.1 - The AMS Early Career Leadership Academy
13A.3 - Defying Chaos Theory: Using Machine Learning to Extend Earth System Prediction

☁ [January 2023] Maria J. Molina was elected to the AMS Artificial Intelligence Applications to Environmental Science STAC (Scientific and Technological Activities Commission) Committee.

☁ [December 2022] Alex Alvin Cheung received the Jacob K. Goldhaber Travel Grant from The Graduate School of the University of Maryland. Way to go, Alvin!

☁ [December 2022] Maria J. Molina received an NCAR Education, Engagement, and Early-Career Development (EdEC) Special Recognition Award for "outstanding work in support of the NCAR Explorer Series."

☁ [December 2022] Jhayron Steven Perez Carrasquilla and Maria J. Molina will be presenting at the AGU Fall Meeting in Chicago on December 12-16.
Jhayron's talks are:
A55L-1261 - Back-trajectories analysis for characterizing the origin and spatio-temporal variability of precipitation in Colombia, and the implications for the local electrical energy markets
A34C-06 - Use of two operational ML models for forecasting 24-hours-average PM2.5 concentration in the Aburrá Valley, Colombia, using global forecasts and satellite information
Maria's talks are:
A45H-05 - Classification and Detection of Organized Convection using Deep Learning (Invited)
GC16C-03 - Defying Chaos Theory: Using Machine Learning to Extend Earth System Prediction (Invited)

☁ [December 2022] Alex Alvin Cheung was awarded a graduate student small-allocation by NCAR for the project titled, "A Spatially-Aware Tropical Cyclogenesis Index using Machine Learning."

☁ [November 2022] Maria J. Molina is now an Affiliate Faculty with the University of Maryland Institute for Advanced Computer Studies (UMIACS).

☁ [November 2022] Alex Alvin Cheung was awarded a 2023 AMS Annual Meeting Travel Award to attend the conference in Denver, Colorado this coming January 2023. Way to go, Alvin!

☁ [October 2022] A partnership between the state of Maryland and the University of Maryland to build and operate a network of 75 weather-observing towers (the Maryland Mesonet) has been announced. Our group will contribute analysis with Prof. Poterjoy, Prof. Nigam, and State Climatologist Dr. Alfredo Ruiz-Barradas that will help with the siting analysis in collaboration with the Maryland Department of Emergency Management. [Link]

☁ [September 2022] Jhayron Steven Perez Carrasquilla was awarded a graduate student small-allocation by NCAR for the project titled, "Using deep learning for subseasonal predictability of weather regimes over North America in CESM2."

☁ [September 2022] Maria J. Molina was featured in Maryland Today, "Flipping the Channel: New Professor Left Cable News for Climate Data Science." [Link]

☁ [August 2022] Rising UMD senior, Heather Fettke von Koeckritz, has joined our research group. Heather is pursuing dual degrees in mechanical engineering and AOSC. Welcome, Heather!

☁ [August 2022] Maria J. Molina will be presented the AMS Editor's Award (Weather and Forecasting/Journal of Applied Meteorology and Climatology) at the 2023 AMS Annual meeting in Denver, Colorado in January. The award citation reads "For multiple high-quality, thorough, and rapid reviews."

☁ [July 2022] Incoming UMD AOSC PhD student, Alex Alvin Cheung, earned the second place oral presentation award at the NOAA Cooperative Research Programs Symposium!

☁ [March 2022] Incoming UMD AOSC PhD student, Alex Alvin Cheung, has been awarded the prestigious UMD Flagship Fellowship. Congratulations, Alvin! Very well deserved. [Link]

☁ [March 2022] Current Penn State student, Alex Alvin Cheung, will be joining our research group this coming Fall 2022 as a PhD student within UMD AOSC. Welcome, Alvin!

☁ [February 2022] Early access to the NCAR Derecho Supercomputer awarded via the NCAR Accelerated Scientific Discovery proposal. Large allocation of GPU resources will be used for the project, "Deep Learning-based Large Ensemble for Subseasonal Prediction of Global Precipitation," led by Maria J. Molina and co-led with Katie Dagon.

☁ [January 2022] UMD AOSC PhD student, Jhayron Steven Perez Carrasquilla, will be joining our research group this coming Fall 2022. Welcome, Jhayron!


We recognize that our campus rests on land first stolen from the Piscataway Tribe and later used as a slave plantation.

MRG