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Polar lows (PLs), which are intense maritime polar mesoscale cyclones, are associated with severe weather conditions. Due to their small size and rapid development, PL forecasting remains a challenge. Convection-permitting models are adequate to forecast PLs since, compared to coarser models, they provide a better representation of convection as well as surface and near-surface processes. A PL that formed over the Norwegian Sea on 25 March 2019 was simulated using the convection-permitting Canadian Regional Climate Model version 6 (CRCM6/GEM4, using a grid mesh of 2.5 km) driven by the reanalysis ERA5. The objectives of this study were to quantify the impact of the initial conditions on the simulation of the PL, and to assess the skill of the CRCM6/GEM4 at reproducing the PL. The results show that the skill of the CRCM6/GEM4 at reproducing the PL strongly depends on the initial conditions. Although in all simulations the synoptic environment is favourable for PL development, with a strong low-level temperature gradient and an upper-level through, only the low-level atmospheric fields of three of the simulations lead to PL development through baroclinic instability. The two simulations that best captured the PL represent a PL deeper than the observed one, and they show higher temperature mean bias compared to the other simulations, indicating that the ocean surface fluxes may be too strong. In general, ERA5 has more skill than the simulations at reproducing the observed PL, but the CRCM6/GEM4 simulation with initialisation time closer to the genesis time of the PL reproduces quite well small scale features as low-level baroclinic instability during the PL development phase.

Polar lows (PLs) are maritime mesoscale cyclones associated with severe weather. They develop during marine cold air outbreaks near coastlines and the sea ice edge. Unfortunately, our knowledge about the mechanisms leading to PL development is still incomplete. This study aims to provide a detailed analysis of the development mechanisms of a PL that formed over the Norwegian Sea on 25 March 2019 using the output of a simulation with the sixth version of the Canadian Regional Climate Model (CRCM6/GEM4), a convection-permitting model. First, the life cycle of the PL is described and the vertical wind shear environment is analysed. Then, the horizontal wind divergence and the baroclinic conversion term are computed, and a surface pressure tendency equation is developed. In addition, the roles of atmospheric static stability, latent heat release, and surface heat and moisture fluxes are explored. The results show that the PL developed in a forward-shear environment and that moist baroclinic instability played a major role in its genesis and intensification. Baroclinic instability was initially only present at low levels of the atmosphere, but later extended upward until it reached the mid-troposphere. Whereas the latent heat of condensation and the surface heat fluxes also contributed to the development of the PL, convective available potential energy and barotropic conversion do not seem to have played a major role in its intensification. In conclusion, this study shows that a convection-permitting model simulation is a powerful tool to study the details of the structure of PLs, as well as their development mechanisms.

Abstract The contraction of species range is one of the most significant symptoms of biodiversity loss worldwide. While anthropogenic activities and habitat alteration are major threats for several species, climate change should also be considered. For species at risk, differentiating the effects of human disturbances and climate change on past and current range transformations is an important step towards improved conservation strategies. We paired historical range maps with global atmospheric reanalyses from different sources to assess the potential effects of recent climate change on the observed northward contraction of the range of boreal populations of woodland caribou ( Rangifer tarandus caribou ) in Quebec (Canada) since 1850. We quantified these effects by highlighting the discrepancies between different southern limits of the caribou's range (used as references) observed in the past and reconstitutions obtained through the hindcasting of the climate conditions within which caribou are currently found. Hindcasted southern limits moved ~105 km north over time under all reanalysis datasets, a trend drastically different from the ~620 km reported for observed southern limits since 1850. The differences in latitudinal shift through time between the observed and hindcasted southern limits of distribution suggest that caribou range recession should have been only 17% of what has been observed since 1850 if recent climate change had been the only disturbance driver. This relatively limited impact of climate reinforces the scientific consensus stating that caribou range recession in Quebec is mainly caused by anthropogenic drivers (i.e. logging, development of the road network, agriculture, urbanization) that have modified the structure and composition of the forest over the past 160 years, paving the way for habitat‐mediated apparent competition and overharvesting. Our results also call for a reconsideration of past ranges in models aiming at projecting future distributions, especially for endangered species.

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981–2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal ‘seriality’, as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water—PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately.

Empirical relationships are derived for the expected sampling error of quantile estimations using Monte Carlo experiments for two frequency distributions frequently encountered in climate sciences. The relationships found are expressed as a scaling factor times the standard error of the mean; these give a quick tool to estimate the uncertainty of quantiles for a given finite sample size.

An urban heat island (UHI) is a relative measure defined as a metropolitan area that is warmer than the surrounding suburban or rural areas. The UHI nomenclature includes a surface urban heat island (SUHI) definition that describes the land surface temperature (LST) differences between urban and suburban areas. The complexity involved in selecting an urban core and external thermal reference for estimating the magnitude of a UHI led us to develop a new definition of SUHIs that excludes any rural comparison. The thermal reference of these newly defined surface intra-urban heat islands (SIUHIs) is based on various temperature thresholds above the spatial average of LSTs within the city’s administrative limits. A time series of images from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) from 1984 to 2011 was used to estimate the LST over the warm season in Montreal, Québec, Canada. Different SIUHI categories were analyzed in consideration of the global solar radiation (GSR) conditions that prevailed before each acquisition date of the Landsat images. The results show that the cumulative GSR observed 24 to 48 h prior to the satellite overpass is significantly linked with the occurrence of the highest SIUHI categories (thresholds of +3 to +7 °C above the mean spatial LST within Montreal city). The highest correlation (≈0.8) is obtained between a pixel-based temperature that is 6 °C hotter than the city’s mean LST (SIUHI + 6) after only 24 h of cumulative GSR. SIUHI + 6 can then be used as a thermal threshold that characterizes hotspots within the city. This identification approach can be viewed as a useful criterion or as an initial step toward the development of heat health watch and warning system (HHWWS), especially during the occurrence of severe heat spells across urban areas.

Since the 1980s, populations of the Asian tiger mosquito Aedes albopictus have become established in south-eastern, eastern and central United States, extending to approximately 40°N. Ae. albopictus is a vector of a wide range of human pathogens including dengue and chikungunya viruses, which are currently emerging in the Caribbean and Central America and posing a threat to North America.

Background: Although floods may have important respiratory health impacts, few studies have examined this issue. This study aims to document the long-term impacts of the spring floods of 2019 in Quebec by (1) describing the population affected by the floods; (2) assessing the impacts on the respiratory system according to levels of exposure; and (3) determining the association between stressors and respiratory health. Methods: A population health survey was carried out across the six most affected regions 8–10 months post-floods. Data were collected on self-reported otolaryngology (ENT) and respiratory symptoms, along with primary and secondary stressors. Three levels of exposure were examined: flooded, disrupted and unaffected. Results: One in ten respondents declared being flooded and 31.4% being disrupted by the floods. Flooded and disrupted participants reported significantly more ENT symptoms (adjusted odds ratio (aOR): 3.18; 95% CI: 2.45–4.14; aOR: 1.76; 95% CI: 1.45–2.14) and respiratory symptoms (aOR: 3.41; 95% CI: 2.45–4.75; aOR: 1.45; 95% CI: 1.10–1.91) than the unaffected participants. All primary stressors and certain secondary stressors assessed were significantly associated with both ENT and respiratory symptoms, but no “dose–response” gradient could be observed. Conclusion: This study highlights the long-term adverse effects of flood exposure on respiratory health.

Dans le contexte du réchauffement planétaire, la relation de Clausius Clapeyron (CC) est utilisée comme un indicateur de l’évolution des précipitations extrêmes. Parmi les théories proposées, nous utilisons dans notre recherche une relation exponentielle qui fait le lien entre l’évolution des centiles les plus extrêmes des précipitations et le changement de la température ΔT dans le climat actuel. Selon cette théorie, les précipitations augmentent au même rythme que la capacité de rétention d'humidité dans l’atmosphère, expliquée par la relation de CC, avec un taux de changement d'environ 7 % par degré Celsius pour des valeurs de température et de pression près de la surface. Ainsi, le présent travail vise à vérifier l’existence de liens physiquement plausibles dans la relation entre les précipitations extrêmes et la température de l’air pour la région du Bassin Versant de la Rivière des Outaouais (BVRO) sur la période 1981-2010, à l’aide des simulations du Modèle Régional Canadien du Climat (MRCC) (versions 5 et 6), développé au centre ESCER, et de deux produits de réanalyses du Centre Européen pour les prévisions météorologiques à moyen terme (CEPMMT) à différentes résolutions spatiales. En général, les précipitations quotidiennes suivent un taux de changement inférieur à celui de CC ; tandis que les précipitations horaires augmentent plus rapidement avec la température. Dans ce dernier cas, pour la simulation du MRCC5 à plus haute résolution spatiale, des taux de changement supérieurs à CC ont même été produits, jusqu’à 10,2 %/°C. Ce travail a également mis en évidence qu’au-delà du seuil de 20°C, la capacité de rétention d'humidité de l’atmosphère n’est pas le seul facteur déterminant pour générer des précipitations extrêmes, et que d’autres facteurs sont à considérer, comme la disponibilité de l'humidité au moment de l'événement de précipitation et la présence de mécanismes dynamiques qui favorisent les mouvements verticaux ascendants. Un comportement sous forme de crochet, qui décrit une augmentation des précipitations jusqu'à un seuil de température, est observé dans la saison estivale avec le MRCC5, mais il a disparu avec les simulations du MRCC6, ce qui pourrait être une conséquence d’avoir seulement une année de simulation disponible ou bien d’une conséquence de la très haute résolution du modèle sur les intervalles de température et sur les effets locaux. En conclusion, l'applicabilité de la relation de CC ne doit pas être généralisée quant à l’étude des précipitations extrêmes, il est également important de considérer l'échelle temporelle, la résolution du modèle utilisé et la saison de l'année. L’évolution de cette relation de CC devrait être évaluée avec des simulations à très haute résolution spatiale (version en développement au centre ESCER), et pour d’autres zones climatiques, sachant que les intervalles de températures et les effets locaux exercent un rôle majeur sur les occurrences et les intensités des fortes précipitations. Ces éléments sont essentiels à intégrer dans le contexte des changements climatiques, en raison des conséquences associées aux fortes précipitations, notamment sur l’occurrence des inondations. _____________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Clausius-Clapeyron, évènements extrêmes, aléas météorologiques, risques d’inondation, changements climatiques

La pandémie transforme la manière avec laquelle la sécurité civile a l’habitude de procéder devant les aléas. Nos réseaux de soutien communautaire seront mis à rude épreuve s’il y a des inondations.

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.