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Abstract A devastating, flood-producing rainstorm occurred over southern Alberta, Canada, from 19 to 22 June 2013. The long-lived, heavy rainfall event was a result of complex interplays between topographic, synoptic, and convective processes that rendered an accurate simulation of this event a challenging task. In this study, the Weather Research and Forecasting (WRF) Model was used to simulate this event and was validated against several observation datasets. Both the timing and location of the model precipitation agree closely with the observations, indicating that the WRF Model is capable of reproducing this type of severe event. Sensitivity tests with different microphysics schemes were conducted and evaluated using equitable threat and bias frequency scores. The WRF double-moment 6-class microphysics scheme (WDM6) generally performed better when compared with other schemes. The application of a conventional convective/stratiform separation algorithm shows that convective activity was dominant during the early stages, then evolved into predominantly stratiform precipitation later in the event. The HYSPLIT back-trajectory analysis and regional water budget assessments using WRF simulation output suggest that the moisture for the precipitation was mainly from recycling antecedent soil moisture through evaporation and evapotranspiration over the Canadian Prairies and the U.S. Great Plains. This analysis also shows that a small fraction of the moisture can be traced back to the northeastern Pacific, and direct uptake from the Gulf of Mexico was not a significant source in this event.

Abstract 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.

Abstract. Precipitation events that bring rain and snow to the Banff–Calgary area of Alberta are a critical aspect of the region's water cycle and can lead to major flooding events such as the June 2013 event that was the second most costly natural disaster in Canadian history. Because no special atmospheric-oriented observations of these events have been made, a field experiment was conducted in March and April 2015 in Kananaskis, Alberta, to begin to fill this gap. The goal was to characterize and better understand the formation of the precipitation at the surface during spring 2015 at a specific location in the Kananaskis Valley. Within the experiment, detailed measurements of precipitation and weather conditions were obtained, a vertically pointing Doppler radar was deployed and weather balloons were released. Although 17 precipitation events occurred, this period was associated with much less precipitation than normal (−35 %) and above-normal temperatures (2.5 ∘C). Of the 133 h of observed precipitation, solid precipitation occurred 71 % of the time, mixed precipitation occurred 9 % and rain occurred 20 %. An analysis of 17 504 precipitation particles from 1181 images showed that a wide variety of crystals and aggregates occurred and approximately 63 % showed signs of riming. This was largely independent of whether flows aloft were upslope (easterly) or downslope (westerly). In the often sub-saturated surface conditions, hydrometeors containing ice occurred at temperatures as high as 9 ∘C. Radar structures aloft were highly variable with reflectivity sometimes >30 dBZe and Doppler velocity up to −1 m s−1, which indicates upward motion of particles within ascending air masses. Precipitation was formed in this region within cloud fields sometimes having variable structures and within which supercooled water at least sometimes existed to produce accreted particles massive enough to reach the surface through the relatively dry sub-cloud region.

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.

Abstract. The phase of precipitation and its distribution at the surface can affect water resources and the regional water cycle of a region. A field project was held in March–April 2015 on the eastern slope of the Canadian Rockies to document precipitation characteristics and associated atmospheric conditions. During the project, 60 % of the particles documented were rimed in relatively warm and dry conditions. Rain–snow transitions also occurred aloft and at the surface in sub-saturated conditions. Ice-phase precipitation falling through a saturated atmospheric layer with temperatures > 0 ∘C will start melting. In contrast, if the melting layer is sub-saturated, the ice-phase precipitation undergoes sublimation, which increases the depth of the rain–snow transition. In this context, this study investigates the role of sublimation and riming in precipitation intensity and type reaching the surface in the Kananaskis Valley, Alberta, during March–April 2015. To address this, a set of numerical simulations of an event of mixed precipitation observed at the surface was conducted. This event on 31 March 2015 was documented with a set of devices at the main observation site (Kananaskis Emergency Services, KES), including a precipitation gauge, disdrometer, and micro rain radar. Sensitivity experiments were performed to assess the impacts of temperature changes from sublimation and the role of the production of graupel (riming) aloft in the surface precipitation evolution. A warmer environment associated with no temperature changes from sublimation leads to a peak in the intensity of graupel at the surface. When the formation of graupel is not considered, the maximum snowfall rate occurred at later times. Results suggest that unrimed snow reaching the surface is formed on the western flank and is advected eastward. In contrast, graupel would form aloft in the Kananaskis Valley. The cooling from sublimation and melting by rimed particles increases the vertical shear near KES. Overall, this study illustrated that the presence of graupel influenced the surface evolution of precipitation type in the valley due to the horizontal transport of precipitation particles.

Abstract. The 0 ∘C temperature threshold is critical for many meteorological and hydrological processes driven by melting and freezing in the atmosphere, surface, and sub-surface and by the associated precipitation varying between rain, freezing rain, wet snow, and snow. This threshold is especially important in cold regions such as Canada, because it is linked with freeze–thaw, snowmelt, and permafrost. This study develops a Canada-wide perspective on near-0 ∘C conditions using hourly surface temperature and precipitation type observations from 92 climate stations for the period from 1981 to 2011. In addition, nine stations from various climatic regions are selected for further analysis. Near-0 ∘C conditions are defined as periods when the surface temperature is between −2 and 2 ∘C. Near-0 ∘C conditions occur often across all regions of the country, although the annual number of days and hours and the duration of these events varies dramatically. Various types of precipitation (e.g., rain, freezing rain, wet snow, and ice pellets) sometimes occur with these temperatures. Near-0 ∘C conditions and the reported precipitation type occurrences tend to be higher in Atlantic Canada, although high values also occur in other regions. Trends of most temperature-based and precipitation-based indicators show little or no change despite a systematic warming in annual surface temperatures over Canada. Over the annual cycle, near-0 ∘C temperatures and precipitation often exhibit a pattern: short durations occur around summer, driven by the diurnal cycle, and a tendency toward longer durations around winter, associated with storms. There is also a tendency for near-0 ∘C surface temperatures to occur more often than expected relative to other temperature windows at some stations due, at least in part, to diabatic cooling and heating that take place with melting and freezing, respectively, in the atmosphere and at the surface.

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. The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society yet limited by lack of understanding of changes in cold-region process responses and interactions, along with their representation in most current-generation land-surface and hydrological models. It is essential to consider the underlying processes and base predictive models on the proper physics, especially under conditions of non-stationarity where the past is no longer a reliable guide to the future and system trajectories can be unexpected. These challenges were forefront in the recently completed Changing Cold Regions Network (CCRN), which assembled and focused a wide range of multi-disciplinary expertise to improve the understanding, diagnosis, and prediction of change over the cold interior of western Canada. CCRN advanced knowledge of fundamental cold-region ecological and hydrological processes through observation and experimentation across a network of highly instrumented research basins and other sites. Significant efforts were made to improve the functionality and process representation, based on this improved understanding, within the fine-scale Cold Regions Hydrological Modelling (CRHM) platform and the large-scale Modélisation Environmentale Communautaire (MEC) – Surface and Hydrology (MESH) model. These models were, and continue to be, applied under past and projected future climates and under current and expected future land and vegetation cover configurations to diagnose historical change and predict possible future hydrological responses. This second of two articles synthesizes the nature and understanding of cold-region processes and Earth system responses to future climate, as advanced by CCRN. These include changing precipitation and moisture feedbacks to the atmosphere; altered snow regimes, changing balance of snowfall and rainfall, and glacier loss; vegetation responses to climate and the loss of ecosystem resilience to wildfire and disturbance; thawing permafrost and its influence on landscapes and hydrology; groundwater storage and cycling and its connections to surface water; and stream and river discharge as influenced by the various drivers of hydrological change. Collective insights, expert elicitation, and model application are used to provide a synthesis of this change over the CCRN region for the late 21st century.

Abstract 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. , Key Points The major 1998 Ice Storm was simulated with the Weather Research and Forecasting model, with and without a pseudo‐global warming A higher melting layer in warmer conditions led to more riming aloft, larger drops, and higher maximum amounts of rain and freezing rain The precipitation type transition region is wider in the warmer conditions over the geographical areas of both southern Quebec and Maine

Abstract. The continental divide along the spine of the Canadian Rockies in southwestern Canada is a critical headwater region for hydrological drainages to the Pacific, Arctic, and Atlantic oceans. Major flooding events are typically attributed to heavy precipitation on its eastern side due to upslope (easterly) flows. Precipitation can also occur on the western side of the divide when moisture originating from the Pacific Ocean encounters the west-facing slopes of the Canadian Rockies. Often, storms propagating across the divide result in significant precipitation on both sides. Meteorological data over this critical region are sparse, with few stations located at high elevations. Given the importance of all these types of events, the Storms and Precipitation Across the continental Divide Experiment (SPADE) was initiated to enhance our knowledge of the atmospheric processes leading to storms and precipitation on either side of the continental divide. This was accomplished by installing specialized meteorological instrumentation on both sides of the continental divide and carrying out manual observations during an intensive field campaign from 24 April–26 June 2019. On the eastern side, there were two field sites: (i) at Fortress Mountain Powerline (2076 m a.s.l.) and (ii) at Fortress Junction Service, located in a high-elevation valley (1580 m a.s.l.). On the western side, Nipika Mountain Resort, also located in a valley (1087 m a.s.l.), was chosen as a field site. Various meteorological instruments were deployed including two Doppler light detection and ranging instruments (lidars), three vertically pointing micro rain radars, and three optical disdrometers. The three main sites were nearly identically instrumented, and observers were on site at Fortress Mountain Powerline and Nipika Mountain Resort during precipitation events to take manual observations of precipitation type and microphotographs of solid particles. The objective of the field campaign was to gather high-temporal-frequency meteorological data and to compare the different conditions on either side of the divide to study the precipitation processes that can lead to catastrophic flooding in the region. Details on field sites, instrumentation used, and collection methods are discussed. Data from the study are publicly accessible from the Federated Research Data Repository at https://doi.org/10.20383/101.0221 (Thériault et al., 2020). This dataset will be used to study atmospheric conditions associated with precipitation events documented simultaneously on either side of a continental divide. This paper also provides a sample of the data gathered during a precipitation event.

Abstract Freezing rain events have caused severe socioeconomic and ecosystem impacts. An understanding of how these events may evolve as the Earth warms is necessary to adequately adapt infrastructure to these changes. We present an analysis of projected changes to freezing rain events over North America relative to the 1980–2009 recent past climate for the periods during which +2, +3, and +4°C of global warming is attained. We diagnose freezing rain using four precipitation‐type algorithms (Cantin and Bachand, Bourgouin, Ramer, and Baldwin) applied to four simulations of the fifth‐generation Canadian Regional Climate Model (CRCM5) driven by four global climate models (GCMs). We find that the choice of driving GCM strongly influences the spatial pattern of projected change. The choice of algorithm has a comparatively smaller impact, and primarily affects the magnitude but not the sign of projected change. We identify several regions where all simulations and algorithms agree on the sign of change, with increases projected over portions of western Canada and decreases over the central, eastern, and southern United States. However, we also find large regions of disagreement on the sign of change depending on driving GCM and even ensemble member of the same GCM, highlighting the importance of examining freezing rain events in a multi‐member ensemble of simulations driven by multiple GCMs to sufficiently account for uncertainty in projections of these hazardous events. , Plain Language Summary Freezing rain events, or ice storms, can have major impacts on electrical infrastructure, agriculture, and road and air travel. Despite these impacts, relatively little research has been done on how these events may change as the Earth warms. We therefore examine several climate model simulations to determine how the frequency of freezing rain may change at different levels of future global warming. We focus in particular on how sensitive the projected changes are to the method used to identify freezing rain in the model output, as well as to the choice of climate model used to produce the projections. We find strong agreement among methods and models on a decrease in freezing rain frequency over much of the United States (from Texas northeastward to Maine) and an increase in freezing rain frequency over portions of western Canada (Alberta, Saskatchewan, Manitoba). In many other areas, however, the different methods and simulations disagree on the direction of projected change. Our findings highlight the importance of using many different climate models, rather than single simulations, to paint a clearer picture of the level of certainty in projections of freezing rain in the context of global warming. , Key Points Freezing rain is projected to increase in frequency over portions of western and central Canada and decrease over most of the United States The sign of projected changes is not highly sensitive to the precipitation‐type algorithm used to diagnose freezing rain The choice of driving global climate model is a key source of uncertainty in both the sign and magnitude of projected changes

Abstract In mountains, the precipitation phase greatly varies in space and time and affects the evolution of the snow cover. Snowpack models usually rely on precipitation‐phase partitioning methods (PPMs) that use near‐surface variables. These PPMs ignore conditions above the surface thus limiting their ability to predict the precipitation phase at the surface. In this study, the impact on snowpack simulations of atmospheric‐based PPMs, incorporating upper atmospheric information, is tested using the snowpack scheme Crocus. Crocus is run at 2.5‐km grid spacing over the mountains of southwestern Canada and northwestern United States and is driven by meteorological fields from an atmospheric model at the same resolution. Two atmospheric‐based PPMs were considered from the atmospheric model: the output from a detailed microphysics scheme and a post‐processing algorithm determining the snow level and the associated precipitation phase. Two ground‐based PPMs were also included as lower and upper benchmarks: a single air temperature threshold at 0°C and a PPM using wet‐bulb temperature. Compared to the upper benchmark, the snow‐level based PPM improved the estimation of snowfall occurrence by 5% and the simulation of snow water equivalent (SWE) by 9% during the snow melting season. In contrast, due to missing processes, the microphysics scheme decreased performances in phase estimate and SWE simulations compared to the upper benchmark. These results highlight the need for detailed evaluation of the precipitation phase from atmospheric models and the benefit for mountain snow hydrology of the post‐processed snow level. The limitations to drive snowpack models at slope scale are also discussed. , Plain Language Summary The partitioning of precipitation between rainfall and snowfall is a crucial component of the evolution of the snowpack in mountains. Most snowpack models use the air temperature and humidity near the surface to derive the precipitation phase. However, the phase at the surface is strongly influenced by processes such as melting and refreezing of falling hydrometeors that occur above the surface. Atmospheric models simulate these processes and the corresponding phase at the surface. However, snowpack models rarely use this information. In this study, we considered two estimates of precipitation phase from an atmospheric model and tested them with a physically‐based snow model over the mountains of southwestern Canada and northwestern United States. The results were compared with traditional approaches using the air temperature and humidity near the surface to derive the precipitation phase. Our results showed that the precipitation phase associated with the snow level obtained from the atmospheric model improved snowfall estimate and snowpack prediction compared to the traditional approaches. In contrast, the cloud/precipitation scheme of the atmospheric model decreased performance in phase estimate and snow simulations due to missing physical processes. Our study highlights that snowpack predictions in the mountains can be improved if valuable information is obtained from atmospheric models. , Key Points Estimates of precipitation phase from an atmospheric model were used to drive snow simulations with a detailed snowpack model Snowfall prediction and snowpack modeling are improved by using the snow level from post‐processing of the atmospheric model Direct precipitation phase from the microphysics scheme does not improve snow simulations compared to simpler rain‐snow partitioning schemes

Abstract Freezing precipitation has major consequences for ground and air transportation, the health of citizens, and power networks. Previous studies using coarse resolution climate models have shown a northward migration of freezing rain in the future. Increased model resolution can better define local topography leading to improved representation of conditions that are favorable for freezing rain. The goal of this study is to examine the climatology and characteristics of future freezing rain events using very-high resolution climate simulations. Historical and pseudo-global warming simulations with a 4-km horizontal grid length were used and compared with available observations. Simulations revealed a northerly shift of freezing rain occurrence, and an increase in the winter. Freezing rain was still shown to occur in the Saint-Lawrence River Valley in a warmer climate, primarily due to stronger wind channeling. Up to 50% of the future freezing rain events also occurred in present day climate within 12 h of each other. In northern Maine, they are typically shorter than 6 h in current climate and longer than 6 h in warmer conditions due to the onset of precipitation during low-pressure systems occurrences. The occurrence of freezing rain also locally increases slightly north of Québec City in a warmer climate because of freezing rain that is produced by warm rain processes. Overall, the study shows that high-resolution regional climate simulations are needed to study freezing rain events in warmer climate conditions, because high horizontal resolutions better define small-scale topographic features and local physical mechanisms that have an influence on these events.

Abstract Temperatures near 0°C represent a critical threshold for many environmental processes and socio‐economic activities. This study examines surface air temperatures ( T ) near 0°C (−2°C ≤  T  ≤ 2°C) across much of southern Canada over a 13 year period (October 2000–September 2013). It utilized hourly data from 39 weather stations and from 4‐km resolution Weather Research and Forecasting model simulations that were both a retrospective simulation as well as a pseudo‐global warming simulation applicable near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% from 985 hr in the current climate to 1,035 hr within the future one. Near‐0°C occurrences with precipitation vary from <5% to approximately 50% of these values. Near‐0°C occurrences are sometimes higher than values of neighboring temperatures. These near‐0°C peaks in temperature distributions can occur in both the current and future climate, in only one, or in neither. Only 4.3% of southern Canada is not associated with a near‐0°C peak and 65.8% is associated with a near‐0°C peak in both climates. It is inferred that latent heat exchanges from the melting and freezing of, for example, precipitation and the snowpack contribute significantly to some of these findings. , Plain Language Summary Our changing climate is spurring the development of huge efforts to improve resiliency. For many regions of the world, these efforts must account for potential changes in near‐0°C conditions within which both melting and freezing can occur and the accompanying latent heat exchanges can push air temperature toward 0°C. This article focuses on the occurrence of near‐0°C surface temperatures across southern Canada through an examination of observational and model information including projections in a future warmer (average 6.1°C increase) climate near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% in the future climate and highest values continue to be along the Pacific coast or within the Western Cordillera and lowest values continue to be within central and northern areas. Near‐0°C occurrences are often higher than those of neighboring temperatures in the present climate and some of these elevated occurrences persist into the future one despite dramatic warming. It is inferred that latent heat exchanges from the melting and freezing of precipitation and snowcover contribute to these findings. , Key Points Near‐0°C surface air temperatures were examined over southern Canada using retrospective and pseudo‐global warming simulations Overall average occurrences increase slightly and their spatial patterns are largely maintained in the warmer climate Near‐0°C occurrences sometimes exceed those of neighboring temperatures and this feature often persists despite dramatic warming