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A freezing rain event, in which the Meteorological Centre of Canada’s 2.5-km numerical weather prediction system significantly underpredicted the quantity of freezing rain, is examined. The prediction system models precipitation types explicitly, directly from the Milbrandt–Yau microphysics scheme. It was determined that the freezing rain underprediction for this case was due primarily to excessive refreezing of rain, originating from melting snow and graupel, in and under the temperature inversion of the advancing warm front ultimately depleting the supply of rain reaching the surface. The refreezing was caused from excessive collisional freezing between rain and graupel. Sensitivity experiments were conducted to examine the effects of a temperature threshold for collisional freezing and on varying the values of the collection efficiencies between rain and ice-phase hydrometeors. It was shown that by reducing the rain–graupel collection efficiency and by imposing a temperature threshold of −5°C, above which collisional freezing is not permitted, excessive rain–graupel collection and graupel formation can be controlled in the microphysics scheme, leading to an improved simulation of freezing rain at the surface.

This paper describes a numerical and observational study focused on ice-pellet formation and microphysical properties near 0 degrees C from an ice-pellet-dominated storm associated with an unusually warm and dry atmosphere on 10 April 2005, in Sapporo, Japan. A one-dimensional numerical model simulation indicated that precipitation particle temperatures were sensitive to environmental temperature and relative humidity and close to the wet-bulb temperature. The simulation demonstrated that completely melted snowflakes could refreeze by evaporative cooling. Moreover, initial freezing could be explained by contact ice nucleation at the height of the minimum wet-bulb temperature.Observations using a 2D video distrometer (2DVD) indicated that ice pellets exhibited two modes of fall velocities at surface temperatures near 0 degrees C during the same time period: slow falling and fast falling. The slow-falling ice pellets exhibited a velocity similar to the average terminal velocity of hail, whereas the velocities of the fast-falling ice pellets were closer to those of raindrops. Surface roundness and fracturing characteristics of ice pellets suggest that slow-falling ice pellets froze rapidly and uniformly in a relatively cold dry layer with a wet-bulb temperature near -4 degrees C. In contrast, the fast-falling ice pellets exhibited the properties of ice particles with a wet smooth surface, suggesting that they froze slowly in a relatively warm layer by contacting ice crystals or splinters generated by preceding slow-falling ice pellets.

This paper describes a numerical and observational study focused on ice-pellet formation and microphysical properties near 0 degrees C from an ice-pellet-dominated storm associated with an unusually warm and dry atmosphere on 10 April 2005, in Sapporo, Japan. A one-dimensional numerical model simulation indicated that precipitation particle temperatures were sensitive to environmental temperature and relative humidity and close to the wet-bulb temperature. The simulation demonstrated that completely melted snowflakes could refreeze by evaporative cooling. Moreover, initial freezing could be explained by contact ice nucleation at the height of the minimum wet-bulb temperature.Observations using a 2D video distrometer (2DVD) indicated that ice pellets exhibited two modes of fall velocities at surface temperatures near 0 degrees C during the same time period: slow falling and fast falling. The slow-falling ice pellets exhibited a velocity similar to the average terminal velocity of hail, whereas the velocities of the fast-falling ice pellets were closer to those of raindrops. Surface roundness and fracturing characteristics of ice pellets suggest that slow-falling ice pellets froze rapidly and uniformly in a relatively cold dry layer with a wet-bulb temperature near -4 degrees C. In contrast, the fast-falling ice pellets exhibited the properties of ice particles with a wet smooth surface, suggesting that they froze slowly in a relatively warm layer by contacting ice crystals or splinters generated by preceding slow-falling ice pellets.

This paper describes a numerical and observational study focused on ice-pellet formation and microphysical properties near 0 degrees C from an ice-pellet-dominated storm associated with an unusually warm and dry atmosphere on 10 April 2005, in Sapporo, Japan. A one-dimensional numerical model simulation indicated that precipitation particle temperatures were sensitive to environmental temperature and relative humidity and close to the wet-bulb temperature. The simulation demonstrated that completely melted snowflakes could refreeze by evaporative cooling. Moreover, initial freezing could be explained by contact ice nucleation at the height of the minimum wet-bulb temperature.Observations using a 2D video distrometer (2DVD) indicated that ice pellets exhibited two modes of fall velocities at surface temperatures near 0 degrees C during the same time period: slow falling and fast falling. The slow-falling ice pellets exhibited a velocity similar to the average terminal velocity of hail, whereas the velocities of the fast-falling ice pellets were closer to those of raindrops. Surface roundness and fracturing characteristics of ice pellets suggest that slow-falling ice pellets froze rapidly and uniformly in a relatively cold dry layer with a wet-bulb temperature near -4 degrees C. In contrast, the fast-falling ice pellets exhibited the properties of ice particles with a wet smooth surface, suggesting that they froze slowly in a relatively warm layer by contacting ice crystals or splinters generated by preceding slow-falling ice pellets.

Several types of precipitation, such as freezing rain, ice pellets, and wet snow, are commonly observed during winter storms. The objective of this study is to better understand the formation of these winter precipitation types. To address this issue, detailed melting and refreezing of precipitation was added onto an existing bulk microphysics scheme. These modifications allow the formation of mixed-phase particles and these particles in turn lead to, or affect, the formation of many of the other types of precipitation. The precipitation type characteristics, such as the mass content, liquid fraction, and threshold diameters formed during a storm over St John’s, Newfoundland, Canada, are studied and compared with observations. Many of these features were reproduced by the model. Sensitivity experiments with the model were carried out to examine the dependence of precipitation characteristics in this event on thresholds of particle evolution in the new parameterization.

ELECTRONIC FILE CHARACTERISTICS: 2 text files; Adobe Acrobat (.PDF). PHYSICAL DESCRIPTION: 1 computer laser optical disc (CD-ROM); 4 3/4 in.; 121 MB. SYSTEMS DETAIL NOTE: IBM-clone PC-compatible. ABSTRACT: This technical note presents a back-to-basics approach to forecasting the stronger, more dynamic weather systems of winter. Although it is especially designed for new and inexperienced forecasters, it is also an excellent review for all forecasters. As winter approaches, the subtropical ridge begins to drift southeastward with its effects lessened. The polar jet shifts southward and results in drastic changes in weather conditions within as little as 24 hours as blasts of colder polar air become more frequent. This technical note presents synoptic patterns and regimes that routinely occur during the winter months. Synoptic pattern recognition remains one of the most important considerations when producing a forecast and will help in determining if forecast model guidance is "on track.", For individual articles, see

This technical note discusses three advection patterns favorable for freezing precipitation. Two graphs were developed based on 503 freezing precipitation occurrences during the past 11 years- a 1000- to 500-mb thickness graph and an 850-mb temperature graph. Two anticyclonic pressure patterns are discussed throughout the technical note. Relationships between inverted troughs and 850-mb lows are presented. Considerable discussion on synoptic patterns across the continental United States is included. This technical note is designed to help and train forecasters on various freezing precipitation scenarios.

The relationship between soil temperature and CO₂ flux from undisturbed soil cores was examined during freeze-up of arctic tundra. Three habitats which dominate tundra topography, polygon trough, ridge and basin, produced significantly different amounts of CO₂ when soil temperatures were above 0 C. A significant positive correlation between soil temperatures between 10 to -7 C and CO₂ flux from each habitat was established. Substantial quantities of CO₂ were produced during freeze-up period when soil temperatures remained near 0 C for an extended period, and the CO₂ production continued at reduced levels as the soil temperature dropped below 0 C. When soil temperatures reached -7 C and the study was terminated, the CO₂ flux was reduced to a low level, but did not reach extinction. A maximum CO₂ flux of 2925 mg CO₂/m²/day from the trough habitat was observed when the soil temperature was 10 C, and the minimum CO₂ flux of 131 mg/m²/day was observed when the soil temperature was -7 C. These data are consistant with the hypothesis that soil microorganisms in arctic tundra are capable of physiological activity in the range of 0 to -7 C.

Accurate snowfall measurements are necessary for meteorology, hydrology, and climate research. Typical uses include creating and calibrating gridded precipitation products, the verification of model simulations, driving hydrologic models, input into aircraft deicing processes, and estimating streamflow runoff in the spring. These applications are significantly impacted by errors in solid precipitation measurements. The recent WMO Solid Precipitation Intercomparison Experiment (SPICE) attempted to characterize and reduce some of the measurement uncertainties through an international effort involving 15 countries utilizing over 20 types and models of precipitation gauges from various manufacturers. Key results from WMO-SPICE are presented herein. Recent work and future research opportunities that build on the results of WMO-SPICE are also highlighted.

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.

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 l

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.

Given their potentially severe impacts, understanding how freezing rain events may change as the climate changes is of great importance to stakeholders including electrical utility companies and local governments. Identification of freezing rain in climate models requires the use of precipitation-type algorithms, and differences between algorithms may lead to differences in the types of precipitation identified for a given thermodynamic profile. We explore the uncertainty associated with algorithm selection by applying four algorithms (Cantin and Bachand, Baldwin, Ramer, and Bourgouin) offline to an ensemble of simulations of the fifth-generation Canadian Regional Climate Model (CRCM5) at 0.22° grid spacing. First, we examine results for the CRCM5 driven by ERA-Interim reanalysis to analyze how well the algorithms reproduce the recent climatology of freezing rain and how results vary depending on algorithm parameters and the characteristics of available model output. We find that while the Ramer and Baldwin algorithms tend to be better correlated with observations than Cantin and Bachand or Bourgouin, their results are highly sensitive to algorithm parameters and to the number of pressure levels used. We also apply the algorithms to four CRCM5 simulations driven by different global climate models (GCMs) and find that the uncertainty associated with algorithm selection is generally similar to or greater than that associated with choice of driving GCM for the recent past climate. Our results provide guidance for future studies on freezing rain in climate simulations and demonstrate the importance of accounting for uncertainty between algorithms when identifying precipitation type from climate model output. Significance Statement Freezing rain events and ice storms can have major consequences, including power outages and dangerous road conditions. It is therefore important to understand how climate change might affect the frequency and severity of these events. One sou

A freezing rain event, in which the Meteorological Centre of Canada’s 2.5-km numerical weather prediction system significantly underpredicted the quantity of freezing rain, is examined. The prediction system models precipitation types explicitly, directly from the Milbrandt–Yau microphysics scheme. It was determined that the freezing rain underprediction for this case was due primarily to excessive refreezing of rain, originating from melting snow and graupel, in and under the temperature inversion of the advancing warm front ultimately depleting the supply of rain reaching the surface. The refreezing was caused from excessive collisional freezing between rain and graupel. Sensitivity experiments were conducted to examine the effects of a temperature threshold for collisional freezing and on varying the values of the collection efficiencies between rain and ice-phase hydrometeors. It was shown that by reducing the rain–graupel collection efficiency and by imposing a temperature threshold of −5°C, above which collisional freezing is not permitted, excessive rain–graupel collection and graupel formation can be controlled in the microphysics scheme, leading to an improved simulation of freezing rain at the surface.

Several types of precipitation, such as freezing rain, ice pellets, and wet snow, are commonly observed during winter storms. The objective of this study is to better understand the formation of these winter precipitation types. To address this issue, detailed melting and refreezing of precipitation was added onto an existing bulk microphysics scheme. These modifications allow the formation of mixed-phase particles and these particles in turn lead to, or affect, the formation of many of the other types of precipitation. The precipitation type characteristics, such as the mass content, liquid fraction, and threshold diameters formed during a storm over St John’s, Newfoundland, Canada, are studied and compared with observations. Many of these features were reproduced by the model. Sensitivity experiments with the model were carried out to examine the dependence of precipitation characteristics in this event on thresholds of particle evolution in the new parameterization.