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Abstract Investigations into the melting layer (ML) of winter storms have revealed small-scale fluctuations in the horizontal wind that could significantly affect the surface precipitation type (p-type) and the evolution of the ML. Despite previous evidence of such fluctuations, essential questions remain concerning their characteristics and the forces driving them. Therefore, this study characterizes small-scale horizontal wind fluctuations (<1 km in length with perturbation magnitudes < 3 m s⁻¹) and their environments within the ML of winter storms. This analysis uses data from a scanning X-band Doppler radar collected during the Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX), conducted during February and March 2022. We present three case studies where small-scale horizontal wind fluctuations are identified using along-radial and along-azimuthal radial velocity perturbations. These cases cover the range of environmental conditions observed during WINTRE-MIX, including (i) a descending ML with change in surface p-type from snow to rain, (ii) a steady ML with a surface p-type transition from freezing rain to rain due to surface cold air erosion, and (iii) a steady ML with a surface p-type transition from freezing rain to ice pellets due to surface cold air advection. Forcing mechanisms for small-scale wind fluctuations during each case are attributed to static instability, vertically trapped gravity waves, and/or shear instability inferred from rawinsonde data, HRRR analysis, and radar data. Our findings suggest that static instability, gravity waves, and shear instability drive the ML’s small-scale wind fluctuations and may influence surface precipitation-type transitions. Significance StatementThis research aims to enhance our understanding of horizontal motions (<1 km in length) within melting layers (MLs) of winter storms and their underlying causes. This study uses radar data to detect differences in horizontal motion within the ML of three different winter storms. Weather balloon observations and output from computer weather forecasts are then used to distinguish between horizontal motions generated by convection, vertically trapped gravity waves, or shear. Our findings reveal that horizontal motions within the ML are generated by different forcing mechanisms within different storms and that horizontal motions may influence the surface p-type. 

Abstract During freezing rain, secondary ice produced by the fragmentation of freezing drops (FFD) can initiate a chain reaction, potentially transitioning freezing rain into ice pellets. Including this process in numerical weather prediction models is challenging due to the uncertainty of this mechanism. To bridge this gap, this study aims to evaluate the efficiency of the FFD process during ice pellet precipitation using measurements collected onboard the National Research Council Canada (NRC) Convair-580 research aircraft during the 2022 Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX). Below the supercooled raindrops freezing altitude, in situ probes measured a bimodal particle size distribution. Observations from imaging and optical-array probes show that most particles smaller than 500μm in diameter were nonspherical ice crystals, in the concentration of ∼500 L⁻¹. In contrast, most particles larger than 500μm were identified as fractured ice pellets and ice pellets with bulges, which suggested the occurrence of the FFD process. A conceptual model is then developed to show that five–eight fragments of ice were produced for each freezing drop. Two existing parameterizations of the FFD process are also tested. It is shown that one parameterization would result in less ice crystals than the measured number concentration, while the second one would result in too many ice crystals. Adjustments to these parameterizations are computed based on the collected observations. This analysis will be valuable for including the FFD process into simulations of freezing rain, ice pellets, and other weather phenomena where this process plays a significant role. Significance StatementThis study presents unique measurements from a winter storm recorded by state-of-the-art instruments onboard a research aircraft at the altitude where ice pellets are formed. The collected data suggest that the freezing of a few initial raindrops at an altitude of around 250 m above the ground resulted in the production of ice crystals. These ice crystals led to the freezing of additional raindrops in a feedback loop that can be referred to as ice multiplication. This process is quantified in the current study. The results will be valuable in improving the representation of ice pellets and freezing rain in computer simulations of winter storms. 

Abstract The St. Lawrence River Valley experiences a variety of precipitation types (p-types) during the cold season, such as rain, freezing rain, ice pellets, and snow. These varied precipitation types exert considerable impacts on aviation, road transportation, power generation and distribution, and winter recreation and are shaped by diverse multiscale processes that interact with the region’s complex topography. This study utilizes ERA5 reanalysis data, surface cyclone climatology, and hourly station observations from Montréal, Québec, and Burlington, Vermont, during October–April 2000–18 to investigate the spectrum of synoptic-scale weather regimes that induce cold-season precipitation across the St. Lawrence River Valley. In particular,k-means clustering and self-organizing maps (SOMs) are used to classify cyclone tracks passing near the St. Lawrence River Valley, and their accompanying thermodynamic profiles, into a set of event types that include a U.S. East Coast track, a central U.S. track, and two Canadian clipper tracks. Composite analyses are subsequently performed to reveal the synoptic-scale environments and the characteristic p-types that most frequently accompany each event type. Global Ensemble Forecast System version 12 (GEFSv12) reforecasts are then used to examine the relative predictability of cyclone characteristics and the local thermodynamic profile associated with each event type at 0–5-day forecast lead times. The analysis suggests that forecasted cyclones near the St. Lawrence River Valley develop too quickly and are located left-of-track relative to the reanalysis on average, which has implications for forecasts of the local thermodynamic profile and p-type across the region when the temperature is near 0°C. Significance StatementDiverse precipitation types are observed when near-surface temperatures approach 0°C during the cold season, especially across the St. Lawrence River Valley in southern Québec. This study classifies cold-season precipitation events impacting the St. Lawrence River Valley based on the track of storm systems across the region and quantifies the average meteorological characteristics and predictability of each track. Our analysis reveals that forecasted low pressure systems develop too quickly and are left of their observed track 0–5 days prior to an event on average, which has implications for forecasted temperatures and the type of precipitation observed across the region. Our results can inform future operational forecasts of cold-season precipitation events by providing a storm-focused perspective on forecast errors during these impactful events. 

There is growing interest in government and industry to use numerical simulations for the Certification by Analysis of aircraft ice protection systems as a cheaper and more sustainable alternative to wind-tunnel and flight testing. The ice accretion on a cylindrical test article mounted under the wing of the National Research Council of Canada’s Convair-580 research aircraft during a flight test in Appendix O icing conditions was simulated using Ansys FENSAP-ICE™. A multishot simulation with input parameters averaged over the full icing period led to an increased level of liquid catch and ice accretion (by mass), and a broader ice profile when compared to a simulation with shot-averaged input parameters. An additional simulation using Ansys’ proprietary “extended icing data with vapor solution” method for calculating heat fluxes at the icing surface resulted in a broader ice profile in comparison to the classical technique, which produced a similar amount of accretion by mass. No combination of simulation settings, input parameters, and multishot methods tested in this study generated the same level of surface detail observed during flight testing, however, the amount of ice accretion, general location of ice features, and formation processes were in good agreement with the experimental results. 

Abstract During near-0°C surface conditions, diverse precipitation types (p-types) are possible, including rain, drizzle, freezing rain, freezing drizzle, ice pellets, wet snow, snow, and snow pellets. Near-0°C precipitation affects wide swaths of the United States and Canada, impacting aviation, road transportation, power generation and distribution, winter recreation, ecology, and hydrology. Fundamental challenges remain in observing, diagnosing, simulating, and forecasting near-0°C p-types, particularly during transitions and within complex terrain. Motivated by these challenges, the field phase of the Winter Precipitation Type Research Multi-scale Experiment (WINTRE-MIX) was conducted from 1 February – 15 March 2022 to better understand how multiscale processes influence the variability and predictability of p-type and amount under near-0°C surface conditions. WINTRE-MIX took place near the US / Canadian border, in northern New York and southern Quebec, a region with plentiful near-0°C precipitation influenced by terrain. During WINTRE-MIX, existing advanced mesonets in New York and Quebec were complemented by deployment of: (1) surface instruments, (2) the National Research Council Convair-580 research aircraft with W- and X-band Doppler radars and in situ cloud and aerosol instrumentation, (3) two X-band dual-polarization Doppler radars and a C-band dual-polarization Doppler radar from University of Illinois, and (4) teams collecting manual hydrometeor observations and radiosonde measurements. Eleven intensive observing periods (IOPs) were coordinated. Analysis of these WINTRE-MIX IOPs is illuminating how synoptic dynamics, mesoscale dynamics, and microscale processes combine to determine p-type and its predictability under near-0°C conditions. WINTRE-MIX research will contribute to improving nowcasts and forecasts of near-0°C precipitation through evaluation and refinement of observational diagnostics and numerical forecast models. 

Hazardous atmospheric icing conditions occur at sub-zero temperatures when droplets come into contact with aircraft and freeze, degrading aircraft performance and handling, introducing bias into some of the vital measurements needed for aircraft operation (e.g., air speed). Nonetheless, government regulations allow certified aircraft to fly in limited icing environments. The capability of aircraft sensors to identify all hazardous icing environments is limited. To address the current challenges in aircraft icing detection and protection, we present herein a platform designed for in-flight testing of ice protection solutions and icing detection technologies. The recently developed Platform for Ice-accretion and Coatings Tests with Ultrasonic Readings (PICTUR) was evaluated using CFD simulations and installed on the National Research Council Canada (NRC) Convair-580 aircraft that has flown in icing conditions over North East USA, during February 2022. This aircraft is a flying laboratory, equipped with more than 40 sensors providing a comprehensive characterization of the flight environment including measurements of temperature, pressure, wind speed and direction, water droplet size and number distribution, and hydrometeor habits imagery. The flight tests of the platform included assessment of passive icephobic coatings as well as heat-assisted tests. Monitoring tools included visual high resolution, real-time inspection of the surface as well as detection of surface ice using NRC’s Ultrasonic Ice Accretion Sensors (UIAS). In this paper, we present the new platform and show some preliminary commissioning results of PICTUR, collected inflight under, predominantly, supercooled small droplets and supercooled large drops (SLD) icing conditions. The combination of the platform and the complementary sensors on the aircraft demonstrated an effective and unique technique for icing studies in a natural environment.