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Precipitation and temperature are among major climatic variables that are used to characterize extreme weather events, which can have profound impacts on ecosystems and society. Accurate simulation of these variables at the local scale is essential to adapt urban systems and policies to future climatic changes. However, accurate simulation of these climatic variables is difficult due to possible interdependence and feedbacks among them. In this paper, the concept of copulas was used to model seasonal interdependence between precipitation and temperature. Five copula functions were fitted to grid (approximately 10 km × 10 km) climate data from 1960 to 2013 in southern Ontario, Canada. Theoretical and empirical copulas were then compared with each other to select the most appropriate copula family for this region. Results showed that, of the tested copulas, none of them consistently performed the best over the entire region during all seasons. However, Gumbel copula was the best performer during the winter season, and Clayton performed best in the summer. More variability in terms of best copula was found in spring and fall seasons. By examining the likelihoods of concurrent extreme temperature and precipitation periods including wet/cool in the winter and dry/hot in the summer, we found that ignoring the joint distribution and confounding impacts of precipitation and temperature lead to the underestimation of occurrence of probabilities for these two concurrent extreme modes. This underestimation can also lead to incorrect conclusions and flawed decisions in terms of the severity of these extreme events.

Extreme events are widely studied across the world because of their major implications for many aspects of society and especially floods. These events are generally studied in terms of precipitation or temperature extreme indices that are often not adapted for regions affected by floods caused by snowmelt. The rain on snow index has been widely used, but it neglects rain-only events which are expected to be more frequent in the future. In this study, we identified a new winter compound index and assessed how large-scale atmospheric circulation controls the past and future evolution of these events in the Great Lakes region. The future evolution of this index was projected using temperature and precipitation from the Canadian Regional Climate Model large ensemble (CRCM5-LE). These climate data were used as input in Precipitation Runoff Modelling System (PRMS) hydrological model to simulate the future evolution of high flows in three watersheds in southern Ontario. We also used five recurrent large-scale atmospheric circulation patterns in north-eastern North America and identified how they control the past and future variability of the newly created index and high flows. The results show that daily precipitation higher than 10 mm and temperature higher than 5 ∘C were necessary historical conditions to produce high flows in these three watersheds. In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated with two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (HP regime) and the Atlantic Ocean (South regime). These hydrometeorological extreme events will still be associated with the same atmospheric patterns in the near future. The future evolution of the index will be modulated by the internal variability of the climate system, as higher Z500 on the east coast will amplify the increase in the number of events, especially the warm events. The relationship between the extreme weather index and high flows will be modified in the future as the snowpack reduces and rain becomes the main component of high-flow generation. This study shows the value of the CRCM5-LE dataset in simulating hydrometeorological extreme events in eastern Canada and better understanding the uncertainties associated with internal variability of climate.

Abstract In a rapidly changing world, what is today an unprecedented extreme may soon become the norm. As a result, extreme‐related disasters are expected to become more frequent and intense. This will have widespread socio‐economic consequences and affect the ability of different societal groups to recover from and adapt to rapidly changing environmental conditions. Therefore, there is the need to decipher the relation between genesis of unprecedented events, accumulation and distribution of risk, and recovery trajectories across different societal groups. Here, we develop an analytical approach to unravel the complexity of future extremes and multiscalar societal responses—from households to national governments and from immediate impacts to longer term recovery. This requires creating new forms of knowledge that integrate analyses of the past—that is, structural causes and political processes of risk accumulation and differentiated recovery trajectories—with plausible scenarios of future environmental extremes grounded in the event‐specific literature. We specifically seek to combine the physical characteristics of the extremes with examinations of how culture, politics, power, and policy visions shape societal responses to unprecedented events, and interpret the events as social‐environmental extremes. This new approach, at the nexus between social and natural sciences, has the concrete advantage of providing an impact‐focused vision of future social‐environmental risks, beyond what is achievable within conventional disciplinary boundaries. In this paper, we focus on extreme flooding events and the societal responses they elicit. However, our approach is flexible and applicable to a wide range of extreme events. We see it as the first building block of a new field of research, allowing for novel and integrated theoretical explanations and forecasting of social‐environmental extremes. , Key Points We conceptualize unprecedented extremes as social‐environmental processes shaped by institutional, political, and economic change As social‐environmental extremes become more frequent, there is an urgency to unravel their genesis and the possible societal responses This approach is the first building block of a new field of research in social‐environmental extreme event forecasts , Plain Language Summary The world is seeing increases in a range of extreme events, and this increase may continue or even accelerate in the future, due to anthropogenic climate change. Furthermore, it is often those who are already vulnerable that experience the biggest impacts from these extremes. Yet, there is little understanding of the possible societal responses to unprecedented events. This underscores the urgency of creating innovative approaches to develop plausible scenarios of societal responses and, in turn, mitigate hazards and reduce vulnerability and exposure to extreme events. In this commentary, we develop a truly interdisciplinary conceptual approach to better understand how different societal groups might interact with and respond to future unprecedented extreme events. We combine social science theories describing how different societal groups are affected by, and recover from, extreme events with projections from the literature identifying plausible areas at risk of unprecedented occurrences and local analyses of past extreme events. We see this as the first building block of a new field of research in forecasting social‐environmental extremes that could support governments, civil protection agencies, and civil society organizations to ensure a fairer, improved response to future events.

Afin de mieux comprendre la distribution géographique des facilitateurs et des obstacles à la participation sociale des Québécois âgés, cette étude visait à documenter l’Indice du potentiel de participation sociale (IPPS) selon les zones métropolitaines, urbaines et rurales. Des analyses de données secondaires, dont l’Enquête transversale sur la santé des collectivités canadiennes, ont permis de développer et de cartographier un indice composé de facteurs environnementaux associés à la participation sociale, pondérés par une analyse factorielle. En zones métropolitaines, l’IPPS était supérieur au centre qu’en périphérie, compte tenu d’une concentration accrue d’aînés et des transports. Bien qu’atténuée, la configuration était similaire en zones urbaines. En zone rurale, un IPPS élevé était associé à une concentration d’aînés et un accès aux ressources accru, sans configuration spatiale. Pour favoriser la participation sociale, l’IPPS soutient que les transports et l’accès aux ressources doivent respectivement être améliorés en périphérie des métropoles et en zone rurale., AbstractTo better understand the geographic distribution of facilitators of, and barriers to, social participation among older Quebecers, this study aimed to document the Social Participation Potential Index (SPPI; Indice du potentiel de participation sociale) in metropolitan, urban and rural areas. Secondary data analyses, including the Canadian Community Health Survey, were used to develop and map a composite index of environmental factors associated with social participation, weighted by factor analysis. In metropolitan areas, the SPPI was higher in the center than in the periphery, due to an increased concentration of seniors and transportation. Although reduced, the pattern was similar in urban areas. In rural areas, a higher SPPI was associated with an increased concentration of older adults and access to resources, showing no spatial pattern. To promote social participation, the SPPI suggests that transportation and access to resources must be improved in the periphery of metropolitan areas and in rural areas, respectively.

Abstract Background Evidence continues to demonstrate that certain marginalised populations are disproportionately affected by COVID-19. While many studies document the impacts of COVID-19 on social inequalities in health, none has examined how public health responses to the pandemic have unfolded to address these inequities in Canada. The purpose of our study was to assess how social inequalities in health were considered in the design and planning of large-scale COVID-19 testing programs in Montréal (Québec, Canada). Methods Part of the multicountry study HoSPiCOVID, this article reports on a qualitative case study of large-scale testing for COVID-19 in Montréal. We conducted semi-structured interviews with 19 stakeholders involved in planning large-scale testing or working with vulnerable populations during the pandemic. We developed interview guides and a codebook using existing literature on policy design and planning, and analysed data deductively and inductively using thematic analysis in NVivo. Results Our findings suggest that large-scale COVID-19 testing in Montréal did not initially consider social inequalities in health in its design and planning phases. Considering the sense of urgency brought by the pandemic, participants noted the challenges linked to the uptake of an intersectoral approach and of a unified vision of social inequalities in health. However, adaptations were gradually made to large-scale testing to improve its accessibility, acceptability, and availability. Actors from the community sector, among others, played an important role in supporting the health sector to address the needs of specific subgroups of the population. Conclusions These findings contribute to the reflections on the lessons learned from COVID-19, highlighting that public health programs must tackle structural barriers to accessing healthcare services during health crises. This will be necessary to ensure that pandemic preparedness and response, including large-scale testing, do not further increase social inequalities in health.