Jhayron S. Pérez-Carrasquilla

Contact: jhayron@umd.edu

Ph.D. Student - Atmospheric and Oceanic Science Department at the University of Maryland - Research Assistant at the PARETO Group

About Me

I'm currently studying atmospheric predictability and climate dynamics by leveraging machine learning techniques while pursuing a Ph.D. with Dr. Maria Molina at the Atmospheric and Oceanic Science Department at the University of Maryland 🇺🇸. Currently, I am part of the Fresh Eyes on CMIP initiative, working with the Data Analysis group focusing on multi-model ensembles. I recently visited NCAR at Boulder, CO, as part of the Graduate Visitor Program. I focused on evaluating long-term changes on the large-scale mid-latitude circulation and the impacts on surface weather.

I earned a bachelor's degree in engineering and a master's degree in water resources from the Universidad Nacional de Colombia 🇨🇴. My main research interests are large-scale atmospheric dynamics, variability, and predictability, moist convection, extreme weather events, and climate change 🌦️⛈️🌪️. My work has mainly aimed at applying machine learning and numerical modeling to gain a physical understanding of climatology, meteorology, hydrology, and air quality problems 💻🌎. I also enjoy playing and watching sports, watching movies, reading, music, and beer-brewing ⚽🎾🏓🍿📚🎵🍻.

Research Interests

I'm currently deepening my knowledge of atmospheric dynamics and machine learning to use new computational and data-driven methods to understand better the processes that affect people's everyday lives, including extreme weather events, climate variability, and climate change 🤓. My Ph.D. research is focused on using artificial intelligence to study the characteristics and potential future changes of the different Earth system processes that contribute to the S2S predictability of large-scale atmospheric patterns, while also studying their causal pathways 🌎.

My master thesis was mainly about how the internal dynamics of tropical cyclones behave when the storm is intensifying 🌀, and my undergraduate thesis was about how the origin of air parcels affected the characteristics of extreme precipitation events over the Colombian Andean region ⛰️. Additionally, I have some experience with idealized modeling and empirical forecasts of air quality, meteorological and hydrological variables. I have mostly used Python during my career to handle data from satellite, reanalysis, ground-based stations, radar, and model outputs 🐍.

Additional links

Public manuscripts

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