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Canada is a vast country with most of its population located along its southern border. Large areas are sparsely populated and/or heavily forested, and severe weather reports are rare when thunderstorms occur there. Thus, it has been difficult to accurately assess the true tornado climatology and risk. It is also important to establish a reliable baseline for tornado-related climate change studies. The Northern Tornadoes Project (NTP), led by Western University, is an ambitious multidisciplinary initiative aimed at detecting and documenting every tornado that occurs across Canada. A team of meteorologists and wind engineers collects research-quality data during each damage investigation via thorough ground surveys and high-resolution satellite, aircraft, and drone imaging. Crowdsourcing through social media is also key to tracking down events. In addition, NTP conducts research to improve our ability to detect and accurately assess tornadoes that affect forests, cropland, and grassland. An open data website allows sharing of resulting datasets and analyses. Pilot investigations were carried out during the warm seasons of 2017 and 2018, with the scope expanding from the detection of any tornadoes in heavily forested regions of central Canada in 2017 to the detection of all EF1+ tornadoes in Ontario plus all significant events outside of Ontario in 2018. The 2019 season was the first full campaign, systematically collecting research-quality tornado data across the entire country. To date, the project has found 89 tornadoes that otherwise would not have been identified, and increased the national tornado count in 2019 by 78%. [ABSTRACT FROM AUTHOR]

An object-based forecasting, nowcasting, and alerting system prototype was demonstrated during the summer 2015 Environment Canada Pan Am Science Showcase (ECPASS) in Toronto. Part of this demonstration involved the generation of experimental thunderstorm threat areas by both automated NWP postprocessing algorithms and by a pair of human forecasters. This paper first develops a rigorous verification methodology for the intercomparison of continuous as well as categorical probabilistic thunderstorm forecasts. The methodology is then applied to the intercomparison of thunderstorm forecasts made during ECPASS. Statistical postprocessing of forecasts by smoothing with optimal bandwidth followed by recalibration is found to improve the skill scores of all thunderstorm forecasts studied at all lead times between 6 and 48 h. In addition, the calibrated ensemble mean forecasts are found to be better than the calibrated deterministic thunderstorm forecasts for all lead times considered, though postprocessing of the convective rain-rate forecast gives results that are statistically comparable with the ensemble mean forecast. Thunderstorm threat areas that were automatically generated by thresholding the output of NWP-based postprocessed algorithms have better scores than those generated by human forecasters for most lead times beyond 9 h, indicating that they could be integrated as an automated tool for providing high-quality "first-guess" thunderstorm threat areas in an object-based forecasting, nowcasting, and alerting system. A unique contribution of this paper is a novel verification methodology for the fair comparison between continuous and categorical probabilistic forecasts, a methodology that could be used for other experiments involving human- and automatically generated object-based forecasts derived from probabilistic forecasts. [ABSTRACT FROM AUTHOR]

The distance transform (DT) (also known as distance map or distance field) is a fundamental tool of mathematical morphology. We introduce a generalized DT (GDT) that is smoother than the classical DT. This transform can be used to define a generalized Hausdorff metric that is shown to be more robust to noise while preserving all metric properties. It is also shown to lead to smoother level sets, allowing contour evolution without having to solve a partial differential equation. Two applications in weather analysis and forecasting demonstrate the usefulness of this proposed GDT. In particular, the dilation of sets according to the GDT allows the simplification of numerical weather forecasts and analysis into geometric objects, called MetObjects, and the generalized Hausdorff distance can be used as a forecast verification metric. [ABSTRACT FROM AUTHOR]

Historical tornado events from 1982 to 2020 were documented within Canada's forested regions using high-resolution satellite imagery. Tornado forest disturbances were identified using a three-step process: 1) detecting, 2) assessing, and 3) dating each event. A grid of 120 km × 120 km boxes was created covering Canada (excluding the extreme north). Of the 484 boxes, 367 were manually searched. Once a long, narrow region of tree damage was detected, it was first cross-referenced with known tornado databases to ensure it was a unique event. Once events were classified as either tornadic or downburst, the coordinates of the start, worst damage, and end locations were documented, as well as the direction of motion, damage indicators, degree of damage, estimated maximum wind speed, and F/EF-scale rating. In total, 231 previously unknown tornadoes were identified. In Ontario, 103 events were discovered, followed by 98 in Quebec, 9 in Manitoba, 6 in Saskatchewan, 9 in Alberta, 5 in British Columbia, and 1 in New Brunswick. The largest number of discovered tornadoes occurred in 2015, and the largest number of strong F2 tornadoes occurred in 2005. Most of the discovered tornadoes occurred in July for both F/EF1 and F/EF2 ratings. Most tornado tracks had widths between 200 and 400 m, and more than 50% of the tornadoes had a pathlength of less than 10 km. Of all the events that were discovered, 125 events could be fully dated, 19 were dated only by month, 41 were dated only by year, and 46 remained undated. [ABSTRACT FROM AUTHOR]

The current study develops a variant of the VAD method to retrieve thunderstorm peak event velocities using low-elevation WSR-88D radar scans. The main challenge pertains to the localized nature of thunderstorm winds, which complicates single-Doppler retrievals as it dictates the use of a limited spatial scale. Since VAD methods assume constant velocity in the fitted section, it is important that retrieved sections do not contain background flow. Accordingly, the current study proposes an image processing method to partition scans into regions, representing events and the background flows, that can be retrieved independently. The study compares the retrieved peak velocities to retrievals using another VAD method. The proposed technique is found to estimate peak event velocities that are closer to measured ASOS readings, making it more suitable for historical analysis. The study also compares the results of retrievals from over 2600 thunderstorm events from 19 radar–ASOS station combinations that are less than 10 km away from the radar. Comparisons of probability distributions of peak event velocities for ASOS readings and radar retrievals showed good agreement for stations within 4 km from the radar while more distant stations had a higher bias toward retrieved velocities compared to ASOS velocities. The mean absolute error for velocity magnitude increases with height ranging between 1.5 and 4.5 m s−1. A proposed correction based on the exponential trend of mean errors was shown to improve the probability distribution comparisons, especially for higher velocity magnitudes. [ABSTRACT FROM AUTHOR]

Severe thunderstorms are a common occurrence in summer on the Canadian prairies, with a large number originating along the Alberta, Canada, foothills, just east of the Rocky Mountains. Most of these storms move eastward to affect the Edmonton-Calgary corridor, one of the most densely populated and fastest-growing regions in Canada. Previous studies in the United States, Europe, and Canada have stressed the importance of mesoscale features in thunderstorm development. However, such processes cannot be adequately resolved using operational observation networks in many parts of Canada. Current conceptual models for severe storm outbreaks in Alberta were developed almost 20 years ago and do not focus explicitly on mesoscale boundaries that are now known to be important for thunderstorm development. The Understanding Severe Thunderstorms and Alber ta Boundary Layers Experiment (UNSTABLE) is a field and modeling study aiming to improve our understanding of the processes associated with the initiation of severe thunderstorms, to refine associated conceptual models, and to assess the ability of convectivescale NWP models to simulate relevant physical processes. As part of UNSTABLE in 2008, Environment Canada and university scientists conducted a pilot field experiment over the Alberta foothills to investigate mesoscale processes associated with the development of severe thunderstorms. Networks of fixed and mobile surface and upper-air instrumentation provided observations of the atmospheric boundary layer at a level of detail never before seen in this region. Preliminary results include the most complete documentation of a dryline in Canada and an analysis of variability in boundary layer evolution across adjacent forest and crop vegetation areas. Convective-scale NWP simulations suggest that although additional information on convective mode may be provided, there is limited benefit overall to downscaling to smaller grid spacing without assimilation of mesoscale observations. [ABSTRACT FROM AUTHOR]

The Meteorological Service of Canada held a series of three Forecasters Forum meetings between 2003 and 2005 to seek input from the meteorological community on the best ways to implement a restructuring strategy and to develop a common vision related to the provision of weather forecasts. The meeting provided significant insight into a number of topics related to operational forecasting in Canada and have added to the larger discussion on these issues in the international meteorological community. During the course of the three forums, several themes emerged as overarching concerns. Foremost among them was the future role of the human forecaster. Most forum participants believed that human forecasters should be the "heart of weather prediction," with an increased emphasis on the analysis/ diagnosis/prognosis paradigm, and recommended developing the sophisticated tools required to facilitate that role. Using results from the forums, it is suggested here that the primary role of the future forecaster should be to develop and maintain a sequence of plan-view composite depictions evolving through time to best represent the current and future states of the atmosphere. This would be accomplished using an area-based, object-oriented analysis/forecast system, with a toolbox of numerical weather prediction guidance and carefully designed artificial intelligence assistants. The forecaster's work would be focused on high-impact weather events, mainly in the short term but also in the longer term when necessary. Products would be automatically generated from the weather object database, allowing the forecast team to focus on "hands on" meteorology and maintaining shared situational awareness at all times. [ABSTRACT FROM AUTHOR]

Several severe thunderstorms, including a tornadic supercell, developed on the afternoon of 3 November 2000, during the Sydney 2000 Forecast Demonstration Project. Severe weather included three tornadoes, damaging wind gusts, hail to 7-cm diameter, and heavy rain causing flash flooding. A unique dataset was collected including data from two Doppler radars, a surface mesonet, enhanced upper-air profiling, storm photography, and a storm damage survey. Synoptic-scale forcing was weak and mesoscale factors were central to the development of severe weather. In particular, low-level boundaries such as gust fronts and the sea-breeze front played critical roles in the initiation and enhancement of storms, the motion of storms, and the generation of rotation at low levels. The complex and often subtle boundary interactions that led to the development of the tornadic supercell in this case highlight the need for advanced detection and prediction tools to improve the warning capacity for such events. [ABSTRACT FROM AUTHOR]

Observations from the 2015 Environment and Climate Change Canada Pan/Parapan American Science Showcase (ECPASS) and real-case, cloud-resolving numerical simulations with the Weather Research and Forecasting (WRF) Model are used to investigate two cases of moist convection forced by lake-breeze convergence over southern Ontario (18 July and 15 August 2015). The two cases shared several characteristics, including high pressure conditions, similar morning soundings, and isolated afternoon convection along a line of lake-breeze convergence between Lakes Erie and Ontario. However, the convection was significantly stronger in the August case, with robustly deeper clouds and larger radar reflectivities than in the July case. Synoptic and mesoscale analyses of these events reveal that the key difference between them was their large-scale forcing. The July event exhibited a combination of strong warm advection and large-scale descent at midlevels (850–650 hPa), which created an inversion layer that capped cloud tops at 4–6 km. The August case exhibited similar features (large-scale descent and warm advection), but these were focused at higher levels (700–400 hPa) and weaker. As a consequence, the convection in the August case was less suppressed at midlevels and ascended deeper (reaching over 8 km). Although the subcloud updraft along the lake-breeze convergence zone was also found to be stronger in the August case, this difference was found to be an effect, rather than a cause, of stronger moist convection within the cloud layer. [ABSTRACT FROM AUTHOR]

Given the impracticality of attempting to directly measure wind speeds in tornadoes, wind speed estimation typically relies on the assessment of damage to structures and vegetation using classifications described in the Enhanced Fujita (EF) Scale. The advent of technology enabling the collection of large amounts of data, including detailed ground, drone, and aerial imagery, has led to a growth in research on non-conventional approaches for estimating tornado wind speeds. Research methods focused on defining the tornadic wind field based on forensic analysis of damage observations have shown promise for improving tornado assessments in a quantitative manner. In this study, novel methods for collecting forensic data following tornadoes are presented. Data from the Alonsa, MB tornado are applied to estimating the wind field along the damage path using treefall pattern analysis and threshold debris flight speed calculations. Comparison of the resulting wind speed estimates show reasonable agreement, with maximum speeds from both methods in the EF5 range. These research methods yield higher wind speeds than the maximum value obtained from the conventional EF-Scale assessment, which is in the low-end of the EF4 range based on a wood-frame house with sub-standard construction that was swept entirely from its foundation. Further work is still needed to make these methods operational for routine tornado intensity estimates. • New data collection methods can enhance level of detail obtained in damage surveys. • Unconventional wind speed estimation methods are useful in analyzing tornadoes. • Research methods yield higher wind speeds than conventional EF-scale assessment. • Treefall patterns can capture greater wind field detail than typical assessments. • Debris flight analysis has large uncertainties but could be developed in the future. [ABSTRACT FROM AUTHOR]

The concurrent occurrence of extreme events can significantly impact societies and infrastructure systems, especially when the instructions provided to the exposed communities demand conflicting responses. In this study, a probabilistic assessment of concurrent tornado and storm‐related flash flood (TORFF) events is performed across southern Canada. We quantify the interdependencies between tornadoes and flash floods (extreme precipitation as proxy) using ground‐based and reanalysis datasets. Windspeed values corresponding to tornado events, categorized based on the recorded Fujita rating, are derived through a resampling approach. The TORFF events are clustered and the corresponding bivariate probability distributions of the resampled windspeed and associated precipitation are characterized based on Copula framework. The individual and joint return periods of concurrent tornadoes and flash floods are then assessed under the AND (when both variables exceed predefined thresholds), OR (when either one of the two variables exceeds predefined thresholds), and conditional hazard scenarios across Canada. Results show positive strong dependencies between resampled windspeed and associated precipitation in Saskatchewan, and weaker dependencies followed by Alberta, Manitoba, Ontario, and Quebec. The Saskatchewan region shows the highest risk underestimation considering the independence scenario compared to the other regions. Higher precipitation is also expected during extreme windspeed, as observed in the conditional assessment of precipitation given windspeed. This study provides insights for more robust recurrence interval estimation for tornadoes and flash floods to aid in emergency planning of evacuation decision‐making process. [ABSTRACT FROM AUTHOR]

Presents an obituary for Hans Zeisel, a public opinion analyst, a sociologist, a statistician, a historian of Austrian socialism and a law professor.

The article presents information on the book "International Encyclopedia of the Social Sciences," edited by David L. Sills. A fair assessment of the degree to which the new encyclopedia meets its goals, as well as other criteria one might apply to a work of this nature, requires the talents of erudite scholars whose contributions and orientations to social science penetrate the boundaries of disciplines other than their own. The selections which follow certainly confirm this orientation among our reviewers, each of whom has contributed not only an evaluation of the encyclopedia, but an assessment of the state of the art and speculation on possible future directions as well. The stimulus for this new feature, which will be repeated only as publications of special significance to the several social sciences are forthcoming, is nothing less than the 17-volume encyclopedia which has as its goal to reflect and encourage the rapid development of the social sciences throughout the world.

Urban-scale Numerical Weather Prediction (NWP) systems will be important tools for decision-making in and around large cities in a changing climate exposed to more extreme weather events. Such a state-of-the-art real-time system down to 250-m grid spacing was implemented in the context of the Toronto 2015 Panamerican games, Canada (PanAm). Combined with the Global Environmental Multiscale (GEM) model, attention was brought to the representation of the detailed urban landscape, and to the inclusion of sub-daily variation of the Great Lakes surface temperature. Results show a refined representation of the urban coastal environment micro-meteorology with a strong anisotropy of the urban heat island reaching about 2 °C on average for the summer season, coastal upwelling, and mesoscale features such as cumulus clouds and lake-breeze flow. Objective evaluation at the surface with a dense observational network reveals an overall good performance of the system and a clear improvement in comparison to reference forecasts at 2.5-km grid spacing in particular for standard deviation errors in urban areas up to 0.3 °C for temperature and dew point temperature, and up to 0.5 m s − 1 for the wind speed, as well as for precipitation with an increased Equitable Threat Score (ETS) by up to 0.3 for the evening accumulation. The study provides confidence in the capacity of the new system to improve weather forecasts to be delivered to urban dwellers although further investigation of the initialization methods in urban areas is needed. [ABSTRACT FROM AUTHOR]

Destruction and fatalities from recent tornado outbreaks in North America have raised considerable concerns regarding their climatic and geographic variability. However, regional characterization of tornado activity in relation to large-scale climatic processes remains highly uncertain. Here, a novel Bayesian hierarchical framework is developed for elucidating the spatiotemporal variability of the factors underlying tornado occurrence in North America. It is demonstrated that regional variability of tornado activity can be characterized using a hierarchical parameterization of convective available potential energy, storm relative helicity, and vertical wind shear quantities. It is shown that the spatial variability of tornado occurrence during the warm summer season can be explained by convective available potential energy and storm relative helicity alone, while vertical wind shear is clearly better at capturing the spatial variability of the cool season tornado activity. The results suggest that the Bayesian hierarchical modeling approach is effective for understanding the regional tornadic environment and in forming the basis for establishing tornado prognostic tools in North America. [ABSTRACT FROM AUTHOR]

The number of tornado observations in Canada is believed to be significantly lower than the actual occurrences. To account for this bias, the authors propose a Bayesian modeling approach founded upon the explicit consideration of the population sampling bias in tornado observations and the predictive relationship between cloud-to-ground (CG) lightning flash climatology and tornado occurrence. The latter variable was used as an indicator for quantifying convective storm activity, which is generally a precursor to tornado occurrence. The CG lightning data were generated from an 11-yr lightning climatology survey (1999-2009) from the Canadian Lightning Detection Network. The results suggest that the predictions of tornado occurrence in populated areas are fairly reliable with no profound underestimation bias. In sparsely populated areas, the analysis shows that the probability of tornado occurrence is significantly higher than what is represented in the 30-yr data record. Areas with low population density but high lightning flash density demonstrate the greatest discrepancy between predicted and observed tornado occurrence. A sensitivity analysis with various grid sizes was also conducted. It was found that the predictive statements supported by the model are fairly robust to the grid configuration, but the population density per grid cell is more representative to the actual population density at smaller resolution and therefore more accurately depicts the probability of tornado occurrence. Finally, a tornado probability map is calculated for Canada based on the frequency of tornado occurrence derived from the model and the estimated damage area of individual tornado events. [ABSTRACT FROM AUTHOR]

Flood forecasting is essential to minimize the impacts and costs of floods, especially in urbanized watersheds. Radar rainfall estimates are becoming increasingly popular in flood forecasting because they provide the much-needed realtime spatially distributed precipitation information. The current study evaluates the use of radar quantitative precipitation estimates (QPEs) in hydrological model calibration for streamflow simulation and flood mapping in an urban setting. First, S-band and C-band radar QPEs were integrated into event-based hydrological models to improve the calibration of model parameters. Second, rain gauge and radar precipitation estimates' performances were compared for hydrological modeling in an urban watershed to assess radar QPE's effects on streamflow simulation accuracy. Third, flood extent maps were produced using coupled hydrological--hydraulic models integrated within the Hydrologic Engineering Center Real-Time Simulation (HEC-RTS) framework. It is shown that the bias correction of radar QPEs can enhance the hydrological model calibration. The radar--gauge merging obtained a Kling--Gupta efficiency, modified peak flow criterion, Nash--Sutcliffe efficiency, and volume error improvement of about +0.42, +0.12, +0.78, and -0.23, respectively, for S-band and +0.64, +0.36, +1.12, and -0.34, respectively, for C-band radar QPEs. Merged radar QPEs are also helpful in running hydrological models calibrated using gauge data. The HEC-RTS framework can be used to produce flood forecast maps using the bias-corrected radar QPEs. Therefore, radar rainfall estimates could be efficiently used to forecast floods in urbanized areas for effective flood management and mitigation. Canadian flood forecasting systems could be efficiently updated by integrating bias-corrected radar QPEs to simulate streamflow and produce flood inundation maps. [ABSTRACT FROM AUTHOR]

Geostationary Operational Environmental Satellite (GOES) imagery is used to demonstrate the development of lake-breeze boundaries in southern Ontario under different synoptic conditions. The orientation of the gradient wind with respect to the shorelines is important in determining the location of such lines. When moderate winds (5–10 m s[sup -1] ) are parallel to straight sections of coastlines, cloud lines can extend well inland. In the region between Lakes Huron and Erie lake-breeze lines merge frequently, sometimes resulting in long-lasting stationary storms and attendant heavy rain and flooding. The influence of the lakes is apparent in the tornado climatology for the region: tornadoes appear to be suppressed in regions visited by lake-modified air and enhanced in regions favored by lake-breeze convergence lines. The cloud patterns in the case of a cold front interacting with merging lake-breeze boundaries are shown to be similar to those on a major tornado outbreak day. Two of the cases discussed are used as conceptual models to explain many of the features in the patterns of tornado touchdown locations. In general, it appears that the lakes suppress tornadoes in southern Ontario, compared with neighboring states and in particular in areas where southwest winds are onshore, but enhance tornado likelihood locally in areas of frequent lake-breeze activity. [ABSTRACT FROM AUTHOR]

Weather radar provides real-time, spatially distributed precipitation estimates, whereas traditional gauge data are restricted in space. The use of radar quantitative precipitation estimates (QPEs) as an input of hydrological models for hydrometeorological applications has increased with the development of weather radar worldwide. New dual-polarization technology and algorithms are showing improvements to radar QPEs. This study evaluates radar QPEs from C-band radar at King City, Canada (WKR), and NEXRAD S-band radar at Buffalo, New York (KBUF), to verify the reliability and accuracy for operational use in the Humber River (semiurban) and Don River (urban) watersheds in the Greater Toronto Area (GTA), Canada. Twenty rainfall events that occurred from 2011 to 2017 were determined from hourly gauge measurements and compared with nine radar QPEs. Rain rates were estimated with different algorithms using three dualpolarized reflectivity values: horizontal reflectivity Z, differential reflectivity ZDR, and specific differential phase KDP. The correlation coefficient, bias, detection, and root-mean-square error were calculated and averaged over all events for each gauge station to show the spatial distribution and in a similar pattern to represent the variation by the event. The quality of the results in terms of accuracy and reliability indicates that the radar QPEs from KBUF S-band and WKR C-band multiparameter rain rate estimators can be effectively used as precipitation forcing of hydrological models for hydrometeorological applications. The high spatiotemporal resolution, long-term data archive, and good percent detection of radar QPEs can facilitate hydrometeorological applications by providing a continuous time series for hydrological models. [ABSTRACT FROM AUTHOR]

Canadian Global Environmental Multiscale (GEM) numerical model output was compared with the meteorological data from an enhanced observational network to investigate the model's ability to predict Lake Ontario lake breezes and their characteristics for two cases in the Greater Toronto Area--one in which the large-scale wind opposed the lake breeze and one in which it was in the same direction as the lake breeze. An enhanced observational network of surface meteorological stations, a C-band radar, and two Doppler wind lidars were deployed among other sensors during the 2015 Pan and Parapan American Games in Toronto. The GEM model was run for three nested domains with grid spacings of 2.5, 1, and 0.25 km. Comparisons between the model predictions and ground-based observations showed that the model successfully predicted lake breezes for the two events. The results indicated that using GEM 1 and 0.25 km increased the forecast accuracy of the lake-breeze location, updraft intensity, and depth. The accuracy of the modeled lake breeze timing was approximately 6135min. The model underpredicted the surface cooling caused by the lake breeze. The GEM 0.25-km model significantly improved the temperature forecast accuracy during the lake-breeze circulations, reducing the bias by up to 72%, but it mainly underpredicted the moisture and overpredicted the surface wind speed. Root-mean-square errors of wind direction forecasts were generally high because of large biases and high variability of errors. [ABSTRACT FROM AUTHOR]

Enhanced meteorological observations were made during the 2015 Pan and Parapan American Games in Toronto in order to measure the vertical and horizontal structure of lake-breeze events. Two scanning Doppler lidars (one fixed and one mobile), a C-band radar, and a network including 53 surface meteorological stations (mesonet) provided pressure, temperature, humidity, and wind speed and direction measurements over Lake Ontario and urban areas. These observations captured the full evolution (prior, during, and after) of 27 lake-breeze events (73% of observation days) in order to characterize the convective and dynamic processes driving lake breezes at the local scale and mesoscale. The dominant signal of a passing lake-breeze front (LBF) was an increase in dew-point temperature of $$2.3 \pm 0.3 \,^{\circ }\hbox {C}$$ , coinciding with a $$180^{\circ }$$ shift in wind direction and a decrease in air temperature of $$2.1 \pm 0.2 \,^{\circ }\hbox {C}$$ . Doppler lidar observations over the lake detected lake breezes 1 hour (on average) before detection by radar and mesonet. On days with the synoptic flow in the offshore direction, the lidars observed wedge-shaped LBFs with shallow depths, which inhibited the radar's ability to detect the lake breeze. The LBF's ground speed and inland penetration distance were found to be well-correlated ( $$r = 0.78$$ ), with larger inland penetration distances occurring on days with non-opposing (non-offshore) synoptic flow. The observed enhanced vertical motion $$({>} 1\hbox { m s}^{-1})$$ at the LBF, observed by the lidar on 54% of lake-breeze days, was greater (at times $${>} 2.5\hbox { m s}^{-1}$$ ) than that observed in previous studies and longer-lasting over the lake than over land. The weaker and less pronounced lake-breeze structure over land is illustrated in two case studies highlighting the lifetime of the lake-breeze circulation and the impact of propagation distance on lake-breeze intensity. [ABSTRACT FROM AUTHOR]

The 'Effects of Lake Breezes on Weather in Manitoba' project was conducted during 6-24 July 2013 to better understand local lake-breeze characteristics. Data were collected using a variety of platforms including Doppler wind lidar, rawinsondes, Doppler radar, surface meteorological stations, and a mobile weather station. The spatial and temporal variability of thermodynamic and kinematic characteristics of lake-breeze fronts are presented for three cases. Lake-breeze frontal passages were characterized by an average increase in dew point of 2.5 $$^{\circ }$$ C and decrease in temperature of 0.5 $$^{\circ }$$ C. The lake-breeze front width varied significantly over multiple measurements and cases, ranging between 50 and 800 m. The depth of the lake-breeze circulation varied between 100 and 700 m. Vertical velocities were measured at the lake-breeze front using lidar, with upward velocities of 2-3 m s $$^{-1}$$ and small downward velocities of magnitude 0.5 m s $$^{-1}$$ behind the front. These observations of lake-breeze fronts in southern Manitoba contribute both to the local and broader understanding of the variability (temporally and spatially) of inland shallow lake breezes. [ABSTRACT FROM AUTHOR]

A tornado occurred in Angus, Ontario, during the late afternoon hours of 17 June 2014. The authors conducted a damage investigation on the morning following the storm. The damage indicators support the classification of the tornado as an EF-2 on the Enhanced Fujita Scale, including the observation of several complete roof failures of recently-constructed, wood-frame houses. Most of the damage to residential homes was contained along two streets, with the tornado appearing to have gone down the backyards between the two. In total, 101 houses were observed to have sustained some level of damage. The evidence suggests that the quality of construction likely affected the performance of failed roofs. A detailed fragility analysis was conducted to assess wind speeds associated with these failures of the roof-to-wall connections. An overturned and lofted box truck provided the opportunity to correlate this failure with adjacent, repetitive failures of roof sheathing, shingles, and garage doors. [ABSTRACT FROM AUTHOR]

A heavy rainfall event over a 2-h period on 8 July 2013 caused significant flash flooding in the city of Toronto and produced 126 mm of rain accumulation at a gauge located near the Toronto Pearson International Airport. This paper evaluates the quantitative precipitation estimates from the nearby King City C-band dual-polarized radar (WKR). Horizontal reflectivity Z and differential reflectivity ZDR were corrected for attenuation using a modified ZPHI rain profiling algorithm, and rain rates R were calculated from R( Z) and R( Z, ZDR) algorithms. Specific differential phase KDP was used to compute rain rates from three R( KDP) algorithms, one modified to use positive and negative KDP, and an R( KDP, ZDR) algorithm. Additionally, specific attenuation at horizontal polarization A was used to calculate rates from the R( A) algorithm. High-temporal-resolution rain gauge data at 44 locations measured the surface rainfall every 5 min and produced total rainfall accumulations over the affected area. The nearby NEXRAD S-band dual-polarized radar at Buffalo, New York, provided rain-rate and storm accumulation estimates from R( Z) and S-band dual-polarimetric algorithm. These two datasets were used as references to evaluate the C-band estimates. Significant radome attenuation at WKR overshadowed the attenuation correction techniques and resulted in poor rainfall estimates from the R( Z) and R( Z, ZDR) algorithms. Rainfall estimation from the Brandes et al. R( KDP) and R( A) algorithms were superior to the other methods, and the derived storm total accumulation gave biases of 2.1 and −6.1 mm, respectively, with correlations of 0.94. The C-band estimates from the Brandes et al. R( KDP) and R( A) algorithms were comparable to the NEXRAD S-band estimates. [ABSTRACT FROM AUTHOR]

One of the principal aims of the Sydney 2000 Forecast Demonstration Project was to assess the utility of advanced nowcasting systems to operational severe weather forecasters. This paper describes the application of the products of a variety of systems by forecasters during a severe weather event in Sydney, Australia, on 3 November 2000. During this day a severe storm developed to the south of the metropolitan area and tracked north producing large, damaging hail, heavy rainfall, and at least three tornadoes. A number of severe weather warnings were issued by the Australian Bureau of Meteorology to a variety of customers throughout the day. This paper investigates how the novel nowcast products were used by the forecasters and the impact they had on the forecast and warning dissemination procedure. The products used are contrasted with those that were available or could have been made available at various stages of the storm development and the efficiency of use of these products is discussed. The severe weather forecasters expressed their satisfaction with the systems and believed that the additional information enhanced the quality and timeliness of the warnings issued during the event. [ABSTRACT FROM AUTHOR]

Surface-level ozone (O3) continues to be a significant health risk in the Greater Toronto Hamilton Area (GTHA) of Canada even though precursor emissions in the area have decreased significantly over the past two decades. In July 2015, Environment and Climate Change Canada (ECCC) led an intensive field study coincident with Toronto hosting the 2015 Pan American Games. During the field study, the daily 1-h maximum O3 standard (80 ppbv) was exceeded twice at a measurement site in North Toronto, once on July 12 and again on July 28. In this study, ECCC's 2.5-km configuration of the Global Environmental Multi-scale (GEM) meteorological model was combined with the Modelling Air-quality and CHemistry (MACH) on-line atmospheric chemistry model and the Town Energy Balance (TEB) urban surface parameterization to create a new urban air quality modelling system. In general, the model results showed that the nested 2.5-km grid-spaced urban air quality model performed better in statistical scores compared to the piloting 10-km grid-spaced GEM-MACH model without TEB. Model analyses were performed with GEM-MACH-TEB for the two exceedance periods. The local meteorology for both cases consisted of light winds with the highest O3 predictions situated along lake-breeze fronts. For the July 28 case, O3 production sensitivity analysis along the trajectory of the lake-breeze circulation showed that the region of most efficient O3 production occurred in the updraft region of the lake-breeze front, as the precursors to O3 formation underwent vertical mixing. In this updraft region, the ozone production switches from volatile organic compound (VOC)-sensitive to NOx-sensitive, and the local net O3 production rate reaches a maximum. This transition in the chemical regime is a previously unidentified factor for why O3 surface-level mixing ratios maximize along the lake-breeze front. For the July 12 case, differences between the model and observed Lake Ontario water temperature and the strength of lake-breeze opposing wind flow play a role in differences in the timing of the lake-breeze, which impacts the predicted location of the O3 maximum north of Toronto. [ABSTRACT FROM AUTHOR]