ABSTRACT A devastating storm struck southern Manitoba, Canada on 10–13 October 2019, producing a large region of mainly sticky and wet snow. Accumulations reached 75 cm, wind gusts exceeded 100 km h−1, and surface temperature (T) remained near 0°C (−1°C ≤ T ≤ 1°C) for up to 88 h. It produced the largest October snowfall and was the earliest to produce at least 20 cm since 1872 in Winnipeg. These factors led to unparalleled damage and power restoration challenges for Manitoba Hydro and, with leaves still largely on vegetation, the most damaging storm to Winnipeg’s trees ever recorded. The storm’s track was uncommon, and produced elevated convection related to buoyancy-driven instability and conditional symmetric instability (CSI), with a moist absolutely unstable layer (MAUL) near 500 hPa. Instabilities were released via lift through lower-tropospheric warm advection and frontogenesis, differential cyclonic vorticity advection, and jet streak dynamics. Precipitation bands, elevated convection, and lake effect snow bands enhanced local snowfall. Snow adhering to structures was not always wet but, when present, it sometimes occurred because of incomplete freezing of particles partially melted aloft in a near-surface (<100 m deep) inversion. Although other storms over the historical record have produced a similar combination of severe precipitation, temperature and wind conditions, none have done this for such a long period.

Abstract Winter precipitation is the source of many inconveniences in many regions of North America, for both infrastructure and the economy. The ice storm that hit the Canadian Maritime Provinces on 24–26 January 2017 remains one of the most expensive in history for the province of New Brunswick. Up to 50 mm of freezing rain caused power outages across the province, depriving up to one-third of New Brunswick residences of electricity, with some outages lasting 2 weeks. This study aims to use high-resolution atmospheric modeling to investigate the meteorological conditions during this severe storm and their contribution to major power outages. The persistence of a deep warm layer aloft, coupled with the slow movement of the associated low pressure system, contributed to widespread ice accumulation. When combined with the strong winds observed, extensive damage to electricity networks was inevitable. A 2-m temperature cold bias was identified between the simulation and the observations, in particular during periods of freezing rain. In the northern part of New Brunswick, cold-air advection helped keep temperatures below 0°C, while in southern regions, the 2-m temperature increased rapidly to slightly above 0°C because of radiational heating. The knowledge gained in this study on the processes associated with either maintaining or stopping freezing rain will enhance the ability to forecast and, in turn, to mitigate the hazards associated with those extreme events. Significance Statement A slow-moving low pressure system produced up to 50 mm of freezing rain for 31 h along the east coast of New Brunswick, Canada, on 24–26 January 2017, causing unprecedented power outages. Warm-air advection aloft, along with a combination of higher wind speeds and large amounts of ice accumulation, created ideal conditions for severe freezing rain. The storm began with freezing rain along the entire north–south cross section of eastern New Brunswick and changed to rain only in the south, when local temperatures increased to >0°C. Near-surface cold-air advection kept temperatures below 0°C in the north. Warming from the latent heat produced by freezing contributed to persistent near-0°C conditions during freezing rain.

Abstract Winter precipitation is the source of many inconveniences in many regions of North America, for both infrastructure and the economy. The ice storm that hit the Canadian Maritime Provinces on 24–26 January 2017 remains one of the most expensive in history for the province of New Brunswick. Up to 50 mm of freezing rain caused power outages across the province, depriving up to one-third of New Brunswick residences of electricity, with some outages lasting 2 weeks. This study aims to use high-resolution atmospheric modeling to investigate the meteorological conditions during this severe storm and their contribution to major power outages. The persistence of a deep warm layer aloft, coupled with the slow movement of the associated low pressure system, contributed to widespread ice accumulation. When combined with the strong winds observed, extensive damage to electricity networks was inevitable. A 2-m temperature cold bias was identified between the simulation and the observations, in particular during periods of freezing rain. In the northern part of New Brunswick, cold-air advection helped keep temperatures below 0°C, while in southern regions, the 2-m temperature increased rapidly to slightly above 0°C because of radiational heating. The knowledge gained in this study on the processes associated with either maintaining or stopping freezing rain will enhance the ability to forecast and, in turn, to mitigate the hazards associated with those extreme events. Significance Statement A slow-moving low pressure system produced up to 50 mm of freezing rain for 31 h along the east coast of New Brunswick, Canada, on 24–26 January 2017, causing unprecedented power outages. Warm-air advection aloft, along with a combination of higher wind speeds and large amounts of ice accumulation, created ideal conditions for severe freezing rain. The storm began with freezing rain along the entire north–south cross section of eastern New Brunswick and changed to rain only in the south, when local temperatures increased to >0°C. Near-surface cold-air advection kept temperatures below 0°C in the north. Warming from the latent heat produced by freezing contributed to persistent near-0°C conditions during freezing rain.

In the future, the intensity, phases, and frequency of precipitation are expected to change due to global warming, in particular during colder seasons when temperatures are near 0°C. To investigate the impacts of warmer atmospheric conditions on the microphysical processes that lead to several precipitation types, the extreme 1998 Ice Storm was simulated using the Weather Research and Forecasting (WRF) model, with and without a pseudo-global warming. The pseudo-global warming approach simulates similar large-scale conditions but in warmer conditions, which allows for the assessment of thermodynamic feedback from cloud and precipitation microphysics. For both simulations, WRF was coupled with the Predicted Particle Properties (P3) bulk microphysics scheme that predicts the liquid fraction of mixed-phase particles. Results of the pseudo-global warming simulation show an increase of ∼828 m in the upper 0°C level and a northeastward migration (∼60 km) of the rain-snow transition region. The results also show a 20% decrease in domain-averaged freezing rain amounts, but with an increased maximum amount of 50%. The horizontal distance associated with a melting aloft and a refreezing layer near the surface is 105 km longer in southern Quebec due to the combined effects of the pseudo-warming and the presence of the Appalachian Mountains. The microphysical processes that lead to precipitation are impacted as well; the increased ice mass and riming conditions aloft in warmer temperatures result in higher liquid precipitation rates. This study contributes to our understanding of the changes in the fine-scale processes of an extreme storm, simulated with pseudo-global warming conditions.

Abstract A prognostic equation for the liquid fraction of mixed-phase particles has been recently added to the Predicted Particle Properties (P3) bulk microphysics scheme. Mixed-phase particles are necessary to simulate key microphysical processes leading to various winter precipitation types, such as ice pellets and freezing rain. To illustrate the impacts of predicting the bulk liquid fraction, the 1998 North American Ice Storm is simulated using the Weather Research and Forecasting (WRF) Model with the modified P3 scheme. It is found that simulating partial melting by predicting the bulk liquid fraction produces higher mass and number mixing ratios of rain. This leads to smaller rain sizes reaching the refreezing layer as well as a decrease in the freezing rain accumulation at the surface by up to 30% in some locations compared to when no liquid fraction is predicted. The increase in fall speed and density and decrease of particle diameter during partial melting combined with an improved representation of the refreezing process in the modified P3 leads to generally higher total solid surface precipitation rates than using the original P3 scheme. There is also an increase of solid precipitation in regions of ice pellet accumulation. Overall, the simulation of mixed-phase particles notably impacts the vertical and spatial distributions of precipitation properties.

Abstract Bulk microphysics parameterizations that are used to represent clouds and precipitation usually allow only solid and liquid hydrometeors. Predicting the bulk liquid fraction on ice allows an explicit representation of mixed-phase particles and various precipitation types, such as wet snow and ice pellets. In this paper, an approach for the representation of the bulk liquid fraction into the predicted particle properties (P3) microphysics scheme is proposed and described. Solid-phase microphysical processes, such as melting and sublimation, have been modified to account for the liquid component. New processes, such as refreezing and condensation of the liquid portion of mixed-phase particles, have been added to the parameterization. Idealized simulations using a one-dimensional framework illustrate the overall behavior of the modified scheme. The proposed approach compares well to a Lagrangian benchmark model. Temperatures required for populations of ice crystals to melt completely also agree well with previous studies. The new processes of refreezing and condensation impact both the surface precipitation type and feedback between the temperature and the phase changes. Overall, prediction of the bulk liquid fraction allows an explicit description of new precipitation types, such as wet snow and ice pellets, and improves the representation of hydrometeor properties when the temperature is near 0°C.