Troy Arcomano
Research
My research focuses on the applications of machine learning for weather prediction and climate simulation. My current work is incorporating machine learning into numerical weather prediction models to improve forecasts and reduce biases.
Selected Publications
- Arcomano, T., Szunyogh, I., Wikner, A., Pathak, J., Hunt, B. R., & Ott, E. (2022). A hybrid approach to atmospheric modeling that combines machine learning with a physics-based numerical model. Journal of Advances in Modeling Earth System, 14, e2021MS002712. https://doi.org/10.1029/2021MS002712
- Arcomano, T., Szunyogh, I., Pathak, J., Wikner, A., Hunt, B. R., & Ott, E. (2020). A machine learning-based global atmospheric forecast model. Geophysical Research Letters, 47, e2020GL087776 https://doi.org/10.1029/2020GL087776
- Wikner, A., Pathak, J., Hunt, B., Girvan, M., Arcomano, T., Szunyogh, I., ... Ott, E. (2020). Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systems. Chaos, 30 (5), 053111
Education
B.S. in Atmospheric and Oceanic Science, University of Maryland - May 2018
Minor in Physics, University of Maryland - May 2018
Additional Information
Advisor: Istvan Szunyogh
