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Secondary ice production improves simulations of freezing rain

Mélissa Cholette, Jason A. Milbrandt, Hugh Morrison, Sabrina Kirk and Louis-Émile Lalonde

Article (2024)

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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.

Subjects: 3100 Physics > 3100 Physics
Department: Department of Engineering Physics
PolyPublie URL: https://publications.polymtl.ca/58183/
Journal Title: Geophysical research letters (vol. 51, no. 8)
Publisher: Wiley
DOI: 10.1029/2024gl108490
Official URL: https://doi.org/10.1029/2024gl108490
Date Deposited: 22 May 2024 10:10
Last Modified: 23 May 2024 12:43
Cite in 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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