Elena M. Fernández
Ph.D. Candidate in Atmospheric Science University at Albany, SUNY
Welcome — my research explores Stratosphere-Troposphere Dynamic Coupling, Subseasonal-to-Seasonal (S2S) Forecasting, and Machine Learning.
I am currently working under the advisement of Drs. Andrea Lopez Lang and Zheng Wu. One of my current research objectives is to examine how features of the stratospheric polar vortex (SPVMD) can be used as model diagnostics for forecasting wintertime temperature extremes. Funded by NOAA, my SPVMD work can be found on GitHub.
I am also using machine learning methods and artificial intelligence to examine "window of opportunity" forecasts provided by features from stratosphere-troposphere coupled dynamics.
A full list of my presentations can be found on my CV. Please feel free to view the materials from my most recent presentation from December 2024. Please reach out to me with any questions.
I am pleased to announce that I accepted a fellowship through the NOAA WPO Innovation for Next Generation Scientists (WINGS) program.
Last updated September 2025.
Beyond research, outreach and engagement for Atmospheric Science is a large aspect of my graduate career. I served as the Department of Atmospheric and Environmental Science's (DAES) Outreach Program Coordinator for the 2021/2022 through 2024/2025 academic years. As of September 2025, I am very honored to announce that I was awarded the 2025/2026 DAES Distinguished Service Award.
I am also very involved with the American Meteorological Society — serving on multiple student volunteer committees since 2019.
If you are interested in organizing an education outreach event with DAES, please email daesoutreach@albany.edu.
If you have any questions or inquiries, please email me at emfernandez@albany.edu. Thank you!
Mean SHAP feature values for the negative temperature class when making predictions for the European forecast region at +14 days.
ACC Scores for the 90th percentile of confidence predictions (light blue) compared to all predictions (dark blue) for the Europe forecast region at 14-day leadtime.
Composites of European surface temperature anomalies for the most confident 14-day predictions.
10-hPa GPH anomalies (shading) and composites (contours) for the most confident 14-day predictions during True Positive/Negative and False Positive/Negative outcomes. Plots are also separated by whether a temperature anomaly greater than 1.5 standard deviations (top row) or within a normal range (bottom row) occurred.
A visualization the average evolution of the stratospheric polar vortex moment diagnostics (SPVMD) in the 10 days prior to the onset of an event in four quantile classifications.
From my Master's Thesis, this visualizes the average profiles for the SPVMDs surrounding the onset of major SSW events in the wintertime periods between 1979 and 2019.