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.
Research
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 deep learning methods, primarily neural networks, to further examine "window of opportunity" forecasts provided by features from stratosphere-troposphere coupled dynamics.
Presentations
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 of 2024. Please reach out to me with any questions.
Curriculum Vitae
I am pleased to announce that I have recently accepted a fellowship through the NOAA WPO Innovation for Next Generation Scientists (WINGS) program.
Last updated April of 2025.
Outreach
Beyond research, outreach and engagement for Atmospheric Science is a large aspect of my graduate career. I have served as the Department of Atmospheric and Environment Science's (DAES) Outreach Program Coordinator since 2021. 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.
Contact Me
If you have any questions or inquiries, please email me at emfernandez@albany.edu. Thank you!
Current Research Images
GPH - LRP
LRP Frequency for the 10% most confident (>90th percentile) and correct predictions of negative temperature anomalies over Europe using 4-day lagged GPH Anomaly @ 500hPa in a combined model with 14-day lagged PVU Anomaly @ 100hPa.
GPH - Composite
GPH @ 500hPa Anomaly Composites for the 10% most confident (>90th percentile) and correct predictions of negative temperature anomalies over Europe from my combined GPH and PVU model. Strong - NAO signal is present.
PVU - LRP
LRP Frequency for the 10% most confident (>90th percentile) and correct predictions of negative temperature anomalies over Europe using 14-day lagged PVU Anomaly @ 100hPa.
GPH + LRP
LRP Frequency for the 10% most confident (>90th percentile) and correct predictions of positive temperature anomalies over Europe using 4-day lagged GPH Anomaly @ 500hPa in a combined model with 14-day lagged PVU Anomaly @ 100hPa.
GPH + Composite
GPH @ 500hPa Anomaly Composites for the 10% most confident (>90th percentile) and correct predictions of positive temperature anomalies over Europe from my combined GPH and PVU model. Strong + NAO signal is present.
PVU + LRP
LRP Frequency for the 10% most confident (>90th percentile) and correct predictions of positive temperature anomalies over Europe using 14-day lagged PVU @100hPa.
Timeseries of SPVMD for Temperature Extremes
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.
SPVMD Evolution surrounding SSWs
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.