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Freezing rain can cause severe impacts, particularly when it persists for many hours. In this paper, we present the climatology of long-duration (6 or more hours) freezing rain events in the United States and Canada from 1979 to 2016. We identify three focus regions from this climatology and examine the archetypal thermodynamic evolution of events in each region using surface and radiosonde observations. Long-duration events occur most frequently in the northeastern United States and southeastern Canada, where freezing rain typically begins as lower-tropospheric warm-air advection develops the warm layer aloft. This warm-air advection and the latent heat of fusion released when rain freezes at the surface erode the cold layer, and freezing rain transitions to rain once the surface temperature reaches 0°C. In the southeastern United States, a larger percentage of events are of long duration than elsewhere in North America. Weak surface cold-air advection and evaporative cooling in the particularly dry onset cold layers there prevent surface temperatures from rising substantially during events. Finally, the south-central United States has a regional maximum in the occurrence of the top 1% of events by duration (18 or more hours), despite the relative rarity of freezing rain there. These events are associated with particularly warm/deep onset warm layers, with persistent low-level cold-air advection maintaining the cold layer. The thermodynamic evolutions we have identified highlight characteristics that are key to supporting persistent freezing rain in each region and may warrant particular attention from forecasters tasked with predicting these events. [ABSTRACT FROM AUTHOR]

In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results reveal statistically significant positive trends for most extreme precipitation indices, which means that extreme precipitation of Canada has generally become more severe since the mid-twentieth century. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominated the central Canadian Prairies. In addition, strong teleconnections are found between extreme precipitation and climate indices, but the effects of climate patterns differ from region to region. Furthermore, complex interactions of climate patterns with synoptic atmospheric circulations can also affect precipitation variability, and changes to the summer and winter extreme precipitation could be explained more by the thermodynamic impact and the combined thermodynamic and dynamic effects, respectively. The seasonal CAPE, specific humidity, and temperature are correlated to Canadian extreme precipitation, but the correlations are season dependent, which could be positive or negative. [ABSTRACT FROM AUTHOR]

The Western Arctic Linkage Experiment (WALE) is aimed at understanding the role of high-latitude terrestrial ecosystems in the response of the Arctic system to global change through collection and comparison of climate datasets and model results. In this paper, a spatiotemporal approach is taken to compare and validate model results from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) with commonly used analysis and reanalysis datasets for monthly averages of temperature and precipitation in 1992–2000 and for a study area at 55°–65°N, 160°–110°W in northwestern Canada and Alaska. Objectives include a quantitative assessment of similarity between datasets and climate model fields, and identification of geographic areas and seasons that are problematic in modeling, with potential causes that may aid in model improvement. These are achieved by application of algebraic similarity mapping, a simple yet effective method for synoptic analysis of many (here, 45) different spatial datasets, maps, and models. Results indicate a dependence of model–data similarity on seasonality, on climate variable, and on geographic location. In summary, 1) similarity of data and models is better for temperature than for precipitation; and 2) modeling of summer precipitation fields, and to a lesser extent, temperature fields, appears more problematic than that of winter fields. The geographic distribution of areas with best and worst agreement shifts throughout the year, with generally better agreement between maps and models in the northeastern and northern inland areas than in topographically complex and near-coastal areas. The study contributes to an understanding of the geographic complexity of the Arctic system and modeling its diverse climate. [ABSTRACT FROM AUTHOR]

In the present paper, a 5-yr baseline integration for the period 1987–91 was carried out over a Pan-Canadian domain to validate the performance of the third-generation Canadian Regional Climate Model (CRCM). The CRCM simulated the large-scale circulation over North America well; it also correctly captured the seasonal variability of surface temperature and reproduced the winter precipitation over North America realistically. However, the CRCM systematically overestimated the summer precipitation over the continent when compared with the observed values. Extensive experiments have been conducted to trace down the sources of error of summer precipitation. Particular attention has been given to the water-vapor-related physical parameterization processes such as the mass flux convection scheme in the CRCM. Experiments involving spectral nudging of the specific humidity toward the values of large-scale driving data enabled the authors to link overestimation with abundant water vapor accumulated in the lower boundary layer resulting from an excessive amount of moisture stored in the soil. A strong boundary layer mixing process from the third generation of the Canadian Atmospheric General Circulation Model was then implemented into the CRCM along with an adjustment to the soil water holding capacity. A final analysis of a 14-month experiment showed that these modifications significantly improved the simulation of summer precipitation over North America without adversely affecting the simulation of winter precipitation. [ABSTRACT FROM AUTHOR]

This paper investigates the large-scale flow and thermodynamic structures associated with barrier jets along the Alaskan coast using the National Centers for Environmental Prediction (NCEP) reanalysis, as well as the average wind, moisture, and thermodynamic soundings at Yakutat, Alaska (YAK), and Whitehorse, Yukon Territory, Canada (YXY). Large-scale and sounding composites are constructed for all barrier jets objectively identified around YAK using synthetic aperture radar (SAR) imagery during the cool and warm seasons of 1998–2003. During the cool season the jet events are separated into those with sharp upstream wind gradients (shock jets), highly variable (“gustlike”) surface winds (variable jets), and the other jet events (other jets). Those cool season barrier jets without shock or variable characteristics are associated with an anomalously deep upper-level trough approaching the Gulf of Alaska and an anomalous ridge over western Canada and interior Alaska. The associated surface cyclone and surface ridging result in strong low-level southerlies over southeast Alaska and the advection of 850-mb warm anomalies northward from the subtropics to Alaska. In contrast, the shock events have significant cold anomalies at 850 mb over the interior, while both the shock and variable jets have less upper-level ridging over the interior. The warm season other-jet composite is similar to that for the cool season, except that an 850-mb cool anomaly develops near the coast and the approaching upper-level trough is not significantly deeper than climatology. The sounding composite at YAK of the other-jet type during the cool season is more stable, moist, and slightly cooler at lower levels than the nonjet events. The largest low-level cool, dry, and high stability anomalies are for the shock events at YAK and YXY, which suggests that this cold and dry air source over the interior is an important ingredient for the development of sharp frontlike boundaries to the barrier jet. In contrast, the variable jets have weaker low-level stability, which favors the subsequent mixing of higher momentum to the surface in localized areas. The warm season jets also have cooler lower levels than those for the nonjet events, but the lower levels are nearly well mixed with little stratification, especially over the interior. [ABSTRACT FROM AUTHOR]

Lake-effect snowstorms are an important source of severe winter weather over the Great Lakes region and are often triggered by the passage of synoptic-scale low pressure systems. In this paper, a climatology of lake-effect snowstorms over southern Ontario, Canada, for the period 1992–99 is developed. The distinguishing characteristics of the synoptic-scale environment associated with intense lake-effect snowstorms in the region are identified through the study of individual events and through composite analysis. In particular, it is found that a low pressure and a cold-temperature anomaly situated over Hudson Bay, north of the Great Lakes, is a favorable environment for the development of intense lake-effect snowstorms over southern Ontario. It is also found that the track of the low pressure system can have a significant impact on the development or lack thereof of lake-effect snowstorms over southern Ontario. It is found that the low pressure systems that trigger intense lake-effect snowstorms tend to have an anomalous northeastward track as compared to the eastward track of most low pressure systems that transit the region. [ABSTRACT FROM AUTHOR]

The relative operating characteristic (ROC) is a measure of the quality of probability forecasts that relates the hit rate to the corresponding false-alarm rate. This paper examines some aspects of the ROC curve for probability forecasts of three equiprobable categories (below normal, near normal, and above normal) in the framework of a simple analog of a climate forecasting system. The insensitivity of the ROC score to some types of forecast biases is discussed and the link to deterministic potential predictability is established in the context of the simple forecasting system. The findings are illustrated with a collection of 24-member ensemble hindcasts of seasonal mean 700-hPa temperature produced with the second-generation general circulation model of the Canadian Centre for Climate Modelling and Analysis. [ABSTRACT FROM AUTHOR]

Soil quality models developed for ecodistrict polygons (EDP) and the polygons of the soil landscapes of Canada (SLC) to monitor the concentration of soil organic matter require daily climate data as an important input. The objectives of this paper are (i) to provide a method that interpolates the daily station data onto the 894 SLC polygons and 150 EDP in the province of Alberta, Canada, so that the interpolated data fit not only climate mean but also climate variability, especially for the precipitation field, and hence can be used as realistic climate input to soil quality models and (ii) to understand the variability of the Alberta daily climate, such as precipitation frequency. The procedure interpolates the station data onto a dense network of grid points and then averages the gridpoint values inside polygons. The procedure and results for maximum temperature, minimum temperature, and precipitation are reported in detail. The interpolation uses the observed daily data for the period 1 January 1961-31 December 1997 (13 514 days) within the latitude-longitude box (45°-64°N, 116°-124°W). Because the precipitation field can have a short spatial correlation length scale and large variability, a hybrid of the methods of inverse-distance weight and nearest-station assignment is developed for interpolating the precipitation data. This method can reliably calculate not only the number of precipitation days per month, but also the precipitation amount for a day. The temperature field has a long spatial correlation scale, and its data are interpolated by the inverse-distance-weight method. Cross-validation shows that the interpolated results on polygons are accurate and appropriate for soil quality models. The computing algorithm uses all the daily observed climate data; despite that, some stations have a very short time record or only summer records. [ABSTRACT FROM AUTHOR]