Remote Sensing and Applied Meteorology听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听 听
Office: Burnside Hall 810
Tel.: (514) 398-3652
frederic.fabry [at] mcgill.ca (Email)
Research interests
Between technological breakthroughs and our increasing awareness of impacts of climate change, meteorology is undergoing a rapid transformation, and so is our group's focus: Understanding and forecasting the changing threats from severe storms remain a focus, but we lack data and understanding; in parallel, weather and climate impact our society in an increasing number of ways that we do not fully appreciate, from warming cities to our increasing reliance on weather-affected renewable energy.
Our group's research hence follows two axes. One more traditional axis deals with improving our understanding of severe storms and our ability to probe atmospheric conditions with remote sensors such as radars and radiometers: For example, we recently worked on understanding the effect of hilly terrain on thunderstorm occurrence; we also devised new approaches to assimilate storms in numerical models. A new axis focuses more on using meteorological knowledge to improve our resilience and adaptation to climate change and its threats. For example, we are seeking ways to take advantage of meteorological patterns to determine where to deploy solar and wind energy production assets.
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To learn more
For details on publications made by my students, co-workers, and I, consult the .
I also wrote a textbook, 听that introduces readers to radar and how to use it in both the operational meteorology and research context.
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Some recent publications
Fabry, F., J. Samuel, and V. Meunier, 2023. Weather driven complementarity between daily energy demand at one location and renewable supply at another. Journal of Applied Meteorology and Climatology, 62, 1115鈥�1127, .
Minder, J., N. Bassill, F. Fabry, J. R. French, K. Friedrich, I. Gultepe, J. Gyakum, D. E. Kingsmill, K. Kosiba, M. Lachapelle, D. Michelson, L. Nichman, C. Nguyen, J. M. Theriault, 虂A. C. Winters, M. Wolde, J. Wurman, 2023. P-type processes and predictability: The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX). Bulletin of the American Meteorological Society, 104, E1469鈥揈1492, .
Sodhi, J.S., and F. Fabry, 2022. Benefits of smoothing backgrounds and radar reflectivity observations for multiscale data assimilation with an ensemble Kalman filter at convective scales: A proof of concept study. Monthly Weather Review, 150, 589鈥�601, .
Fabry, F., and V. Meunier, 2020. Why are radar data so difficult to assimilate skillfully? Monthly Weather Review, 148 (7), 2819鈥�2836,.
For a complete list of publications for all our faculty, please visit听our publications page.