Mélissa Cholette, Jason A. Milbrandt, Hugh Morrison, Sabrina Kirk et Louis-Émile Lalonde
Article de revue (2024)
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Abstract
Weather forecasts and climate projections of precipitation phase and type in winter storms are challenging due to the complicated underlying microphysical and dynamical processes. In the Canadian numerical weather prediction model, explicit freezing rain (FR) at the surface is often overestimated during the winter season for situations in which snow is observed. For a case study simulated using this model with the Predicted Particle Properties (P3) microphysics scheme, the secondary ice production (SIP) process has a major impact on the surface precipitation type. Parameterized SIP substantially reduces FR due to increased collection of supercooled drops with ice particles formed by rime splintering. Hindcast simulations of 40 winter cases show that these results are systematic, and the decreased frequency of FR leads to improved forecast skill relative to observations. Thus, accounting for SIP in the model is critical for accurately simulating precipitation types.
Sujet(s): | 3100 Physique > 3100 Physique |
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Département: | Département de génie physique |
URL de PolyPublie: | https://publications.polymtl.ca/58183/ |
Titre de la revue: | Geophysical research letters (vol. 51, no 8) |
Maison d'édition: | Wiley |
DOI: | 10.1029/2024gl108490 |
URL officielle: | https://doi.org/10.1029/2024gl108490 |
Date du dépôt: | 22 mai 2024 10:10 |
Dernière modification: | 28 sept. 2024 07:40 |
Citer en APA 7: | Cholette, M., Milbrandt, J. A., Morrison, H., Kirk, S., & Lalonde, L.-É. (2024). Secondary ice production improves simulations of freezing rain. Geophysical research letters, 51(8), 108490 (11 pages). https://doi.org/10.1029/2024gl108490 |
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