I'm currently studying subseasonal-to-seasonal (S2S) atmospheric predictability while pursuing a Ph.D. at the Atmospheric and Oceanic Science Department at the University of Maryland 🇺🇸. 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, and extreme weather events 🌦️⛈️🌪️. My work has mainly focused on applying machine learning and numerical modeling to gain a physical understanding of climatology, meteorology, hydrology, and air quality problems 💻🌎. I also love playing and watching sports, watching movies, reading, and brewing beer ⚽🎾🏓🍿📚🍻.
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 🌎. 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 🐍.
- J., Pérez-Carrasquilla, Montoya P., Sánchez J. M., Ramírez M., Forecasting 24-hour-averaged PM2.5 concentration in the Aburrá Valley using tree-based ML models, global forecasts, and satellite information. Advances in Statistical Climatology, Meteorology and Oceanography (currently under review).
- Hoyos, C. D., Ceballos, L. I., Pérez-Carrasquilla, J. S., Sepúlveda, J., López-Zapata, S. M., Zuluaga, M. D., ... & Zapata, M. (2019). Meteorological conditions leading to the 2015 Salgar flash flood: lessons for vulnerable regions in tropical complex terrain. Natural Hazards and Earth System Sciences, 19(11), 2635-2665.
Presentations and Posters
- (Poster) J., Pérez-Carrasquilla, Montoya P., Sánchez J. M., Ramírez M. (2022, Dec). 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. AGU Fall Meeting, 2022.
- (Poster) J., Pérez-Carrasquilla, Betancur A., Hoyos C., Herrera L., Gómez L.A., Hernández-Mendoza D. A. (2022, Dec). Back-trajectories analysis for characterizing the origin and spatio-temporal variability of precipitation in Colombia, and the implications for the local electrical energy markets. AGU Fall Meeting, 2022.
- (Poster) Sepúlveda, J., Pérez-Carrasquilla, J. S., Zapata, M., & Hoyos, C. D. (2021, May). Climatology of the Internal Structure of Tropical Cyclones at Different Life Cycle Stages: CloudSat and Airborne Reflectivity Data. In 34th Conference on Hurricanes and Tropical Meteorology. AMS. View poster
- (Pesentation) Pérez-Carrasquilla, J. S., & Hoyos, C. D. (2021, May). Characterization of the Thermodynamics, Life Cycle and Influence Over the Mean Flow of Inner Core Processes in Tropical Cyclones: Observational and Idealized Modelling Approach. In 34th Conference on Hurricanes and Tropical Meteorology. AMS. View presentation
- (Pesentation) Zapata, M., Sepúlveda, J., Pérez-Carrasquilla, J. S., & Hoyos, C. D. (2021, May). Climatology of Cloud Population in Tropical Cyclones. In 34th Conference on Hurricanes and Tropical Meteorology. AMS. View presentation
- (Pesentation) J., Pérez-Carrasquilla & Hoyos, C. D. (2021, March). Convección e intensificación rápida en ciclones tropicales: Casos de estudio usando información de Infrarrojo de GOES-R y GLM. In Congreso Internacional de Variabilidad y Cambio Climático, Bogotá, Colombia.
- (Poster) Perez, J. S., & Hoyos, C. D. (2020, January). Tropical Cyclones Internal Dynamics and its Influence over the Intensity Changes: WRF Idealized Simulation in a Quiescent Environment and GOES-R IR and GLM Data Analysis. In 100th American Meteorological Society Annual Meeting. AMS.