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Introduction:In July 2013, a train transporting oil derailed and exploded in Lac-Mégantic, causing major human, environmental, and economic impacts. A community-based survey of people aged 10-25, conducted in 2017, revealed that many young people suffer in silence and report feeling isolated. These observations led to the conclusion that we must make room for young people, and that opportunities for engagement and participation must be provided within the community.Aim:The Public Health Direction of Estrie aimed to identify strategies to promote health and wellbeing for young people living in and around Lac-Mégantic.Methods:A collective reflection half-day was hosted with sixty key stakeholders (school board, other education institutions, health and social services, community sector, municipal/political sector, parents, youth). Throughout the event, participants were invited to build on and learn from accomplishments and experiential knowledge, and develop a common vision of the solutions to be pursued or implemented. All qualitative data sources (verbal and written data from large- and sub-group activities) were analyzed through a content analysis.Results:Several themes (i.e. potential solutions) emerged from the analysis: common venue, diversified activities, communication, collaboration, involvement, support for at-risk youth, intergenerational component, etc. Participants agreed on four priorities for action: 1) creating a gathering place, 2) establishing a Youth Committee, 3) supporting adults working with youth, and 4) fostering a better flow of information.Discussion:Several positive outcomes of the collective reflection half-day were observed, including the mobilization of the participants who greatly appreciated the event, and many promising ideas launched by stakeholders. A social worker is now fully dedicated to supporting youth wellbeing and engagement in Lac-Mégantic. A Youth Committee has been established and projects by and for youth are being implemented. Bottom-up approaches to identify solutions to complex situations are not only effective but also respectful of the local culture.

On 15 March 2005, the Meteorological Service of Canada (MSC) proceeded to the implementation of a four-dimensional variational data assimilation (4DVAR) system, which led to significant improvements in the quality of global forecasts. This paper describes the different elements of MSC’s 4DVAR assimilation system, discusses some issues encountered during the development, and reports on the overall results from the 4DVAR implementation tests. The 4DVAR system adopted an incremental approach with two outer iterations. The simplified model used in the minimization has a horizontal resolution of 170 km and its simplified physics includes vertical diffusion, surface drag, orographic blocking, stratiform condensation, and convection. One important element of the design is its modularity, which has permitted continued progress on the three-dimensional variational data assimilation (3DVAR) component (e.g., addition of new observation types) and the model (e.g., computational and numerical changes). This paper discusses some numerical problems that occur in the vicinity of the Poles where the semi-Lagrangian scheme becomes unstable when there is a simultaneous occurrence of converging meridians and strong wind gradients. These could be removed by filtering the winds in the zonal direction before they are used to estimate the upstream position in the semi-Lagrangian scheme. The results show improvements in all aspects of the forecasts over all regions. The impact is particularly significant in the Southern Hemisphere where 4DVAR is able to extract more information from satellite data. In the Northern Hemisphere, 4DVAR accepts more asynoptic data, in particular coming from profilers and aircrafts. The impact noted is also positive and the short-term forecasts are particularly improved over the west coast of North America. Finally, the dynamical consistency of the 4DVAR global analyses leads to a significant impact on regional forecasts. Experimentation has shown that regional forecasts initiated directly from a 4DVAR global analysis are improved with respect to the regional forecasts resulting from the regional 3DVAR analysis.

In this study future flooding frequencies have been estimated for the Grand River catchment located in south - western Ontario, Canada. Historical and future climatic projections made by fifteen Coupled Model Inter - comparison Project - 3 climate models are bias - corrected and downscaled before they are used to obtain mid - and end of 21 st century streamflow projections. By comparing the future projected and historically observed precipitation and temperature record s it is found that the mean and extreme temperature events will intensify in future across the catchment. The increase is more drastic in the case of extreme events than the mean events. The sign of change in future precipitation is uncertain. Further flow extremes are expected to increase in magnitude and frequency in future across the catchment. The confidence in the projection is more for low return period (<10 years) extreme events than higher return period (10 - 100 years) events. It can be expected that increases in temperature will play a dominant role in increasing the magnitude of low return period flooding events while precipitation seems to play an important role in shaping the high return period events.

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada’s (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Quebec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Among natural-disaster risks, heat waves are responsible for a large number of deaths, diseases and economic losses around the world. As they will increase in severity, duration and frequency over the decades to come within the context of climate change, these extreme events constitute a genuine danger to human health, and heat-warning systems are strongly recommended by public health authorities to reduce this risk of diseases and of excessive mortality and morbidity. Thus, evidence-based public alerting criteria are needed to reduce impacts on human health before and during persistent hot weather conditions. The goal of this guide is to identify alert thresholds for heat waves in Canada based on evidence, and to propose an approach for better defining heat waves in the Canadian context in order to reduce the risks to human health and contribute to the well-being of Canadians. This guide is the result of the collaboration among various research and public institutions working on: 1) meteorological and climate aspects, i.e. the Meteorological Service of Canada (MSC, Environment and Climate Change Canada), and the ESCER centre at the Universite du Quebec a Montreal, and 2) public health, i.e. Health Canada and the Institut National de Sante Publique du Quebec.

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affected by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. These results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.

In Canada, flood analysis and water resource management, in general, are tasks conducted at the provincial level; therefore, unified national-scale approaches to water-related problems are uncommon. In this study, a national-scale flood risk assessment approach is proposed and developed. The study focuses on using global and national datasets available with various resolutions to create flood risk maps. First, a flood hazard map of Canada is developed using topography-based parameters derived from digital elevation models, namely, elevation above nearest drainage (EAND) and distance from nearest drainage (DFND). This flood hazard mapping method is tested on a smaller area around the city of Calgary, Alberta, against a flood inundation map produced by the city using hydraulic modelling. Second, a flood exposure map of Canada is developed using a land-use map and the satellite-based nightlight luminosity data as two exposure parameters. Third, an economic flood risk map is produced, and subsequently overlaid with population density information to produce a socioeconomic flood risk map for Canada. All three maps of hazard, exposure, and risk are classified into five classes, ranging from very low to severe. A simple way to include flood protection measures in hazard estimation is also demonstrated using the example of the city of Winnipeg, Manitoba. This could be done for the entire country if information on flood protection across Canada were available. The evaluation of the flood hazard map shows that the topography-based method adopted in this study is both practical and reliable for large-scale analysis. Sensitivity analysis regarding the resolution of the digital elevation model is needed to identify the resolution that is fine enough for reliable hazard mapping, but coarse enough for computational tractability. The nightlight data are found to be useful for exposure and risk mapping in Canada; however, uncertainty analysis should be conducted to investigate the effect of the overglow phenomenon on flood risk mapping.

Flood events in Canada result in larger costs, in terms of property damage, than any other natural disaster. Changes in land use, and more recently the impacts of climate change, can lead to changes in the flood regime. This paper describes research examining changes in the flood regime for watersheds across Canada. To distinguish between changes resulting from land-use changes and those occurring due to changes in climate, the analysis of flood data is conducted only on watersheds that are either part of a formal Reference Hydrologic Network (RHN), or which exhibit RHN-like characteristics. A total of 280 gauging stations have been analyzed for changes to a number of attributes of the flood regime. Changes in the magnitude and timing of flood events as well as the frequency and duration of high-flow events are examined for all 280 sites. Using all 280 sites and different groupings of the sites, based on timing of floods, drainage area and the RHN designation, changes were determined in the annual number ...

Abstract. This study presents an analysis of the observed inter-annual variability and inter-decadal trends in river discharge across northern Canada for 1964–2013. The 42 rivers chosen for this study span a combined gauged area of 5.26×106km2 and are selected based on data availability and quality, gauged area and record length. Inter-annual variability in river discharge is greatest for the eastern Arctic Ocean (coefficient of variation, CV=16%) due to the Caniapiscau River diversion into the La Grande Riviere system for enhanced hydropower production. Variability is lowest for the study area as a whole (CV=7%). Based on the Mann–Kendall test (MKT), no significant (p>0.05) trend in annual discharge from 1964 to 2013 is observed in the Bering Sea, western Arctic Ocean, western Hudson and James Bay, and Labrador Sea; for northern Canada as a whole, however, a statistically significant (p

The objective of this study is to use two hydrological indices (coefficients of variation and immoderation) to analyze the impacts of dam management methods on seasonal daily flow rate change downstream of three dams: Manouane (diversion-type management method), Ouareau (natural-type management method) and Matawin (inversion-type management method). The results show that this change is far greater downstream of the Matawin dam (characterized by an inversion-type management method) than downstream of the two other dams. Moreover, downstream of the Matawin dam, this daily flow rate change increases significantly over time, while decreasing downstream of the two other dams and in natural rivers. Lastly, this change is better correlated with climate downstream of the Ouareau dam than downstream of the two other dams. It is positively correlated with winter and spring temperatures as well as summer and fall rain. Contrary commonly accepted hypothesis, this study shows that the impacts of dams generally result in an increase of the seasonal flow rate change in Quebec.

Abstract River ice breakup has extensive implications on cold-region hydrological, ecological and river morphological systems. However, spatial and temporal breakup patterns under the changing climate are not well explored on large scale. This study discusses the spatial-temporal variations of breakup timing over terrestrial ecozones and five selected river basins of Canada based on long-term (1950–2016) data record. The link between the discovered patterns and climatic drivers (including air temperature, snowfall and rainfall), as well as elevation and anthropogenic activities are analyzed. An overall earlier breakup trend is observed across Canada and the spring air temperature is found to be the main driver behind it. However, the most pronounced warming trends across Canada is observed in winter. Spring warming trend is not as strong as winter warming and even becomes weak as period changes from 1950–2016 to 1970–2016, resulting in more stations showing later and significant later breakup during 1970–2016. Breakup pattern also displays evident spatial differences. Significant earlier breakup trends are mainly seen in western Canada (e.g. the Nelson River basin) and Arctic where spring warming trends are evident. Later and mixed breakup trends are generally identified in regions with weak warming or even cooling trends, such as Atlantic Canada and the St. Lawrence River basin. Spring snowfall generally delays breakup. Spring rainfall usually advances breakup dates while winter-rainfall can also delay breakup through refreezing. The increased snowfall in the north and increased rainfall in the south may be the reason why breakup timing is more sensitive to climatic warming in lower latitude regions than in higher latitude regions. Additionally, breakup timing in main streams and large rivers appears to be less sensitive to the warming trend than the headwaters and small tributaries. Elevation and flow regulation are also found to be contributing factors to the changes in breakup timing.