Joey Knisely

Department of Atmospheric and Oceanic Sciences

University of Maryland


About Me

I'm Joey, a third year graduate student at the Department of Atmospheric and Oceanic Sciences at the University of Maryland, College Park. I currently work with Dr. Jon Poterjoy in the Weather-Chaos Research Group.

I have a B.S. in Physics with a minor in Mathematics from the Pennsylvania State University . I have also spent two years at Eurofins Lancaster Laboratories Environmental before starting grad school.

I love listening to electronic music, hip hop, and jazz fusion, and wish to go to travel and eat cuisines from around the world. You can generally find me playing Civilization VI, Witcher III, The Elder Scrolls games, or retro N64 games on weekends. I enjoy drinking craft beers (IPAs mostly) and have recently developed an interest in red wines. I also enjoy cooking, reading political theory, biking, hiking, running cross country and petting kitties .

Download CV (coming soon)


The Hurricane Analysis and Forecasting System (HAFS) is the next generation tropical cyclone (TC) forecasting system, built within the Unified Forecasting System. Although HAFS has already shown improvement over older models, it lacks the ability to accurately forecast TC intensity. This is likely due to a lack of measurement data assimilation (DA), particularly around the inner eyewall of the vortex. Current observation networks of this area are sparse and low resolution. Furthermore, the DA methodologies for assimilating these measurements are not sufficient, mostly due to highly nonlinear dynamical processes that dominate in this area.


My current work proposes the integration of satellite all-sky radiance measurements collected from the Advanced Baseline Imager (ABI) aboard the GOES-16 weather satellite into a fully cycling HAFS DA framework. These measurements have high temporal and spatial resolution and can provide detailed information about atmospheric temperatures, moisture, and wind profiles.

We also propose a novel DA methodology that combines an experimental local Particle Filter (PF) with a traditional Ensemble Kalman Filter (EnKF) technique. This local PF/EnKF hybrid circumvents the issues EnKFs have with non-Gaussian error statistics.



I have been a TA for AOSC 200 (Weather and Climate) for Dr. Tim Canty and taught AOSC 201 (Weather and Climate Lab) for three semesters (Fall 2019, Spring 2020, Fall 2020). For more information about these classes, visit my class website

I also help organise weekly AOSC departmental seminars and lead the "Meet the Speaker" sessions.





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