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Significant increase in wintertime air temperature, especially the reduced cold extremes under climate change, might be beneficial to the winter survival of perennial crops. However, climate warming could result in less snowfall, reduced snow cover, as well as changes in climate conditions for fall hardening and winter thaws. How these changes might impact the risks of winter damages to overwintering crops, such as perennial forage crops requires a comprehensive assessment for proactively adapting to climate change in the agricultural sector, especially the beef and dairy industries. Based on the most up-to-date climate projections from a set of global climate models, we used a snow model and a suite of agroclimatic indices for perennial forage crops to assess potential changes in the risks of winter injury to perennial forage crops across Canada in the near-term (2030s), the mid-term (2050s), and the distant future (2070s). Our results show that the risk of exposure to extremely low temperatures (daily Tmin ≤ −15 °C) without snow protection is projected to decrease across Canada with improved conditions for fall hardening. However, winter thaws and rainfall are projected to increase, and this would increase the risk of winter injury due to loss of hardiness together with potential soil heaving and ice encasement. [ABSTRACT FROM AUTHOR]

Current exterior wall assembly designs for new low-rise residential buildings targeting low-energy demand in heating dominated countries include split-insulation wall and thick-wall assembly designs. Both have been shown to result in thermal efficiency gains compared to building-code minimum assemblies, however long-term hygrothermal performance can vary depending on boundary conditions and the presence of construction deficiencies. Future climate scenarios estimate many heating-dominated climates will experience a reduction in heating-degree day hours and an increase in annual rainfall. Using validated assembly performance data from a Passive House certified facility, a sensitivity analysis is performed to determine the impact of rainwater wetting, air exfiltration and insulation material properties on the hygrothermal response of a thick-wall assembly. Results show that rainwater leakage values of 0.50% and greater of the adhering rainfall on the exterior surface of the assembly results in the greatest risk for failure. The hygrothermal response of the assembly is then examined under a global temperature rise scenario of 3.5°C for five geographic locations across Canada. Results show that an increase in average annual total rainfall does not directly result in an increase in the failure rate of the assembly when a rainwater leak is present. Additional climatic factors, including outdoor air temperature, driving rain and solar radiation received will influence the hygrothermal response of the assembly and need to be considered when modelling the performance under future climate change scenarios. [ABSTRACT FROM AUTHOR]

Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi‐day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short‐term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. Plain Language Summary: This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called "tree water deficit" to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. Key Points: A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causalitySoil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi‐days)Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit [ABSTRACT FROM AUTHOR]

Climate change is increasing global atmospheric temperatures, which can reduce abundance and cause range shifts in species that are sensitive to warming. However, fine‐scale thermal heterogeneity can drive highly variable local responses to climate change, especially in freshwater environments that differ in groundwater inputs and geomorphology.We used temperature data collected during 2012–2021 from 10 small, pristine streams in eastern Canada to characterise thermal variation at a small spatial scale (~25 km2). We then used relationships between daily air and stream temperatures to reconstruct stream temperature since 1980, and assessed how thermal variation influenced the phenology and growth of brook trout (Salvelinus fontinalis).Air–stream temperature relationships varied considerably among streams despite their close proximity, with predicted summer temperatures differing up to 9.5°C between warmer rainfall‐dominated streams and cooler groundwater‐dominated streams. Rainfall‐dominated streams warmed more than twice as fast as groundwater‐dominated streams across all seasons since 1980, with nearly four‐fold differences in rates of warming evident during summer months. Fine‐scale thermal heterogeneity also shaped brook trout phenology, as juveniles in rainfall‐dominated streams were estimated to hatch and emerge much later (~70 and 40 days, respectively) and experience faster phenological shifts than in groundwater‐dominated streams. Relationships between juvenile brook trout size and accumulated degree‐days were positive, but slopes differed over two‐fold and did not vary systematically based on stream hydrology, suggesting more idiosyncratic impacts of warming on early growth.Collectively, our study illustrates how species responses to climate change in freshwater environments can be consistent in direction but vary substantially in magnitude owing to the influence of groundwater. Future climate change is likely to increase the thermal stress experienced by brook trout populations in warmer rainfall‐dominated streams, while potentially benefiting those in groundwater‐dominated streams where current temperatures are often suboptimal.Observed differences in the rates and ecological impacts of warming among streams suggest that fine‐scale thermal variation must be considered when forecasting effects of future climate change on stream fish population dynamics. [ABSTRACT FROM AUTHOR]

El Niño is known to affect Arctic temperature. However, the robustness of the observed relationship between El Niño and Arctic temperature remains debated. Here we reexamine the impacts of El Niño on the Arctic temperature in boreal winter [December–February (DJF)] using reanalysis datasets and atmospheric model experiments. This study shows that extreme El Niño events are accompanied by significant boreal winter cooling over northeastern Canada and Greenland (NECG), while moderate eastern Pacific (MEP) El Niño events are accompanied by significant boreal winter warming in this region. For central Pacific (CP) El Niño events, a cold signal appears in NECG, but with no statistical significance. During extreme El Niño winters, a positive Pacific–North America (PNA)-like pattern is seen in the Pacific, and anomalously negative 200-hPa geopotential height (Z200) strengthening occurs over NECG, which is a response to anomalous strong wave activity originating in the tropical Pacific. El Niño–induced circulation anomalies can further induce NECG cooling via cold temperature advection and decreased downward longwave radiation. In contrast, for the MEP El Niño, the subtropical jet extends zonally from the North Pacific to the North Atlantic, which is accompanied by increased baroclinicity anomalies and favors the propagation of synoptic eddies into the Atlantic, leading to a negative North Atlantic Oscillation (NAO)-like pattern. This in turn could further enhance the positive Z200 anomalies over NECG, resulting in anomalous warming in NECG through warm temperature advection and enhanced downward longwave radiation. A series of atmospheric model experiments simulates the observed circulation changes and associated warming over NECG. Significance Statement: This work investigates the different impacts of the three El Niño types on regional Arctic wintertime temperature anomalies based on observations and model experiments. The impacts of El Niño events on northeastern Canada and Greenland temperatures during boreal winter show distinct differences between extreme El Niño and moderate EP El Niño events. These distinct differences can be attributed to the different atmospheric circulation patterns induced by different SST patterns, which can lead to warm (cold) temperature advection and enhanced (decreased) downward longwave radiation. These results highlight the different impacts of extreme and moderate EP El Niños on Arctic temperatures and provide an improved understanding of the impact of El Niños on the Arctic climate. [ABSTRACT FROM AUTHOR]

Canada has major sources of atmospheric methane (CH4), with the world second-largest boreal wetland and the world fourth-largest natural gas production. However, Canada's CH4 emissions remain uncertain among estimates. Better quantification and characterization of Canada's CH4 emissions are critical for climate mitigation strategies. To improve our understanding of Canada's CH4 emissions, we performed an ensemble regional inversion (2007–2017) constrained with the Environment and Climate Change Canada (ECCC) surface measurement network. The decadal CH4 estimates show no significant trend, unlike some studies that reported long-term trends. The total CH4 estimate is 17.4 (15.3–19.5) Tg CH4 year-1, partitioned into natural and anthropogenic sources, 10.8 (7.5–13.2) and 6.6 (6.2–7.8) Tg CH4 year-1, respectively. The estimated anthropogenic emission is higher than inventories, mainly in western Canada (with the fossil fuel industry). Furthermore, the results reveal notable spatiotemporal characteristics. First, the modelled gradients of atmospheric CH4 show improvement after inversion when compared to observations, implying the CH4 gradients could help verify the inversion results. Second, the seasonal variations show slow onset and late summer maximum, indicating wetland CH4 flux has hysteretic dependence on air temperature. Third, the boreal winter natural CH4 emissions, usually treated as negligible, appear quantifiable (≥ 20 % of annual emissions). Understanding winter emission is important for climate prediction, as the winter in Canada is warming faster than the summer. Fourth, the inter-annual variability in estimated CH4 emissions is positively correlated with summer air temperature anomalies. This could enhance Canada's natural CH4 emission in the warming climate. [ABSTRACT FROM AUTHOR]

The Hudson Plains, Canada, is one of the largest, undisturbed peatland regions (370,000 km2) in the world. Air temperature in the Hudson Plains is increasing rapidly leading to unprecedented permafrost thaw. The region's remoteness has hindered our knowledge of how permafrost thaw alters peatland land cover and hydrological response at multiple scales. To assess which landscapes in the Hudson Plains are vulnerable to such disturbances, we analysed latitudinal distributions of land cover over a 300‐km transect spanning the sporadic (<30% areal) to continuous (>80% areal) permafrost zone in northern Ontario and quantified land cover changes over 40 years using multiple remote sensing datasets (lidar, air photographs, and high‐resolution satellite imagery). We then evaluated these landscapes at a fundamental hydrological unit, the peatland complex, identified five peatland complex types, and conceptualized their potential hydrological response using circuitry analogues. Over four decades, we found that permafrost peatlands declined by 4%, 8.5%, and 2% areal in the sporadic, discontinuous, and continuous permafrost zones, respectively. Circuitry analogues partitioned peatland complexes into their component peatland forms (e.g., permafrost peatland, bog, and fen) and represented each component's hydrological function using an electrical equivalent (e.g., generator, switch, and conductor). When interpreted at the landscape scale, circuitry analogues demonstrated latitudinal patterns in landscape structure (i.e., circuitry wiring) and indicated where permafrost thaw will have the greatest impact on landscape structure (i.e., rewiring) and therefore hydrological response. Based on these analyses, we suggest a 60‐km latitudinal segment (54.5°N to 54.9°N) where peatland complexes are most vulnerable to permafrost‐thaw‐induced land cover and hydrological change and should therefore be the focus of future research and monitoring efforts. [ABSTRACT FROM AUTHOR]

Peatland pools are freshwater bodies that are highly dynamic aquatic ecosystems because of their small size and their development in organic‐rich sediments. However, our ability to understand and predict their contribution to both local and global biogeochemical cycles under rapidly occurring environmental change is limited because the spatiotemporal drivers of their biogeochemical patterns and processes are poorly understood. We used (1) pool biogeochemical data from 20 peatlands in eastern Canada, the United Kingdom, and southern Patagonia and (2) multi‐year data from an undisturbed peatland of eastern Canada, to determine how climate and terrain features drive the production, delivering and processing of carbon (C), nitrogen (N), and phosphorus (P) in peatland pools. Across sites, climate (24%) and terrain (13%) explained distinct portions of the variation in pool biogeochemistry, with climate driving spatial differences in pool dissolved organic C (DOC) concentration and aromaticity. Within the multi‐year dataset, DOC, carbon dioxide (CO2), total N concentrations, and DOC aromaticity were highest in the shallowest pools and at the end of the growing seasons, and increased gradually from 2016 to 2021 in relation to a combination of increases in summer precipitation, mean air temperature for the previous fall, and number of extreme summer heat days. Given the contrasting effects of terrain and climate, broad‐scale terrain characteristics may offer a baseline for the prediction of small‐scale pool biogeochemistry, while broad‐scale climate gradients and relatively small year‐to‐year variations in local climate induce a noticeable response in pool biogeochemistry. These findings emphasize the reactivity of peatland pools to both local and global environmental change and highlight their potential to act as widely distributed climate sentinels within historically relatively stable peatland ecosystems. [ABSTRACT FROM AUTHOR]

In the context of global warming, the Clausius–Clapeyron (CC) relationship has been widely used as an indicator of the evolution of the precipitation regime, including daily and sub-daily extremes. This study aims to verify the existence of links between precipitation extremes and 2 m air temperature for the Ottawa River Basin (ORB, Canada) over the period 1981–2010, applying an exponential relationship between the 99th percentile of precipitation and temperature characteristics. Three simulations of the Canadian Regional Climate Model version 5 (CRCM5), at three different resolutions (0.44°, 0.22°, and 0.11°), one simulation using the recent CRCM version 6 (CRCM6) at "convection-permitting" resolution (2.5 km), and two reanalysis products (ERA5 and ERA5-Land) were used to investigate the CC scaling hypothesis that precipitation increases at the same rate as the atmospheric moisture-holding capacity (i.e., 6.8%/°C). In general, daily precipitation follows a lower rate of change than the CC scaling with median values between 2 and 4%/°C for the ORB and with a level of statistical significance of 5%, while hourly precipitation increases faster with temperature, between 4 and 7%/°C. In the latter case, rates of change greater than the CC scaling were even up to 10.2%/°C for the simulation at 0.11°. A hook shape is observed in summer for CRCM5 simulations, near the 20–25 °C temperature threshold, where the 99th percentile of precipitation decreases with temperature, especially at higher resolution with the CRCM6 data. Beyond the threshold of 20 °C, it appears that the atmospheric moisture-holding capacity is not the only determining factor for generating precipitation extremes. Other factors need to be considered, such as the moisture availability at the time of the precipitation event, and the presence of dynamical mechanisms that increase, for example, upward vertical motion. As mentioned in previous studies, the applicability of the CC scaling should not be generalised in the study of precipitation extremes. The time and spatial scales and season are also dependent factors that must be taken into account. In fact, the evolution of precipitation extremes and temperature relationships should be identified and evaluated with very high spatial resolution simulations, knowing that local temperature and regional physiographic features play a major role in the occurrence and intensity of precipitation extremes. As precipitation extremes have important effects on the occurrence of floods with potential deleterious damages, further research needs to explore the sensitivity of projections to resolution with various air temperature and humidity thresholds, especially at the sub-daily scale, as these precipitation types seem to increase faster with temperature than with daily-scale values. This will help to develop decision-making and adaptation strategies based on improved physical knowledge or approaches and not on a single assumption based on CC scaling. [ABSTRACT FROM AUTHOR]

Aquatic invasive species (AIS) present major ecological and economic challenges globally, endangering ecosystems and human livelihoods. Managers and policy makers thus need tools to predict invasion risk and prioritize species and areas of concern, and they often use native range climate matching to determine whether a species could persist in a new location. However, climate matching for AIS often relies on air temperature rather than water temperature due to a lack of global water temperature data layers, and predictive power of models is seldom evaluated. We developed 12 global lake (water) temperature‐derived "BioLake" bioclimatic layers for distribution modeling of aquatic species and compared "climatch" climate matching predictions (from climatchR package) from BioLake with those based on BioClim temperature layers and with a null model. We did this for 73 established AIS in the United States, training the models on their ranges outside of the United States and Canada. Models using either set of climate layers outperformed the null expectation by a similar (but modest) amount on average, but some species were occasionally found in locations with low climatch scores. Mean US climatch scores were higher for most species when using air temperature. Including additional climate layers in models reduced mean climatch scores, indicating that commonly used climatch score thresholds are not absolute but can be context specific and may require calibration based upon climate data used. Although finer resolution global lake temperature data would likely improve predictions, our BioLake layers provide a starting point for aquatic species distribution modeling. Climate matching was most effective for some species that originated at low latitudes or had small ranges. Climatch scores remain useful but limited for predicting AIS risk, perhaps because current ranges seldom fully reflect climatic tolerances (fundamental niches). Managers could consider climate matching as one of a suite of tools that can be used in AIS prioritization. [ABSTRACT FROM AUTHOR]

Longwave radiation (LR) is one of the energy balance components responsible for warming and cooling water during hot summers. Both downward incoming LR, emitted by the atmosphere, and outgoing LR emitted by the land surface are not widely measured. The influence of clouds on the LR heat budget makes it even harder to establish reliable formulations for all-sky conditions. This paper uses air temperature and cloud cover from the ERA5 reanalysis database to compare 20 models for the downward longwave irradiance (DLI) at Earth's surface and compare them with ERA5's DLI product. Our work uses long-time continuous DLI measured data at three stations over Canada, and ERA5 reanalysis, a reliable source for data-scarce regions, such as central British Columbia (Canada). The results show the feasibility of the local calibration of different formulations using ERA5 reanalysis data for all-sky conditions with RMSE metrics ranging from 37.1 to 267.3 W m−2, which is comparable with ERA5 reanalysis data and can easily be applied at broader scales by implementing it into hydrological models. Moreover, it is shown that ERA5 gridded data for DLI shows the best results with RMSE = 31.7 W m−2. This higher performance suggests using ERA5 data directly as input data for hydrological and ecological models. [ABSTRACT FROM AUTHOR]

Accurate simulations of snow emission in surface-sensitive microwave channels are needed to separate snow from atmospheric information essential for numerical weather prediction. Measurements from a field campaign in Trail Valley Creek, Inuvik, Canada during March 2018 were used to evaluate the Snow Microwave Radiative Transfer (SMRT) Model at 89 GHz and, for the first time, frequencies between 118 and 243 GHz. In situ data from 29 snow pits, including snow specific surface area, were used to calculate exponential correlation lengths to represent the snow microstructure and to initialize snowpacks for simulation with SMRT. Measured variability in snowpack properties was used to estimate uncertainty in the simulations. SMRT was coupled with the Atmospheric Radiative Transfer Simulator to account for the directionally-dependent emission and attenuation of radiation by the atmosphere. This is a major developmental step needed for top-of-atmosphere simulations of microwave brightness temperature at atmosphere-sensitive frequencies with SMRT. Nadir simulated brightness temperatures at 89, 118, 157, 183 and 243 GHz were compared with airborne measurements and with ground-based measurements at 89 GHz. Inclusion of an anisotropic atmosphere in SMRT had the greatest impact on brightness temperature simulations at 183 GHz and the least at 89 GHz. Simulations compared well with observations, with a root mean squared error of 14 K, although snowpit measurements did not capture the observed variability fully as simulations and airborne observations formed statistically different distributions. Topographical differences in simulated brightness temperature between sloped, valley and plateau areas diminished with increasing frequency as the penetration depth within the snow decreased and less emission from the underlying ground contributed to the airborne observations. Observed brightness temperature differences between flights were attributed to the deposition of a thin layer of very low density snow. This illustrates the need to account for both temporal and spatial variability in surface snow microstructure at these frequencies. Sensitivity to snow properties and the ability to reflect changes in observed brightness temperature across the frequency range for different landscapes, as demonstrated by SMRT, is a necessary condition for inclusion of atmospheric measurements at surface-sensitive frequencies in numerical weather prediction. [ABSTRACT FROM AUTHOR]

Monarch butterflies (Danaus plexippus) undergo an iconic multi‐generational migration, traveling thousands of kilometers from the summer breeding grounds in southern Canada to overwintering sites in central Mexico. This migration phenomena can be affected by climate change, which may have important implications on fitness and ultimately populations status. We investigated the long‐term trends in fall migration phenology of monarchs using a 25‐year dataset collected along the coast of Lake Erie in Ontario, Canada. We also investigated local long‐term trends in weather covariates that have the potential to influence migration phenology at this site. Patterns in standardized daily counts of monarchs were compared with local weather covariates using two methods (i.e., monthly averages and moving windows) to assess difference in outputs between analytical approaches. Our results suggest that monarch migration timing (migration midpoint, average peak, first peak, and late passage) and weather covariates have been consistent over time, in direct contrast to a similar study in Cape May, New Jersey, which showed a significant increase in both fall temperature and a 16‐ to 19‐day shift in monarch migration timing. Furthermore, our results differed between analytical approaches. With respect to annual variability in air temperature, our monthly average analysis suggested that for each degree increase in September air temperature, late season passage would advance 4.71 days (±1.59 SE, p =.01). However, the moving window analysis suggested that this result is likely spurious and found no significant correlations between migration timing and any weather covariates. Importantly, our results caution against extrapolating the effects of climate change on the migration phenology of the monarch across study regions and the need for more long‐term monitoring efforts to better understand regional drivers of variability in migration timing. [ABSTRACT FROM AUTHOR]

Temperatures near 0°C represent a critical threshold for many environmental processes and socio‐economic activities. This study examines surface air temperatures (T) near 0°C (−2°C ≤ T ≤ 2°C) across much of southern Canada over a 13 year period (October 2000–September 2013). It utilized hourly data from 39 weather stations and from 4‐km resolution Weather Research and Forecasting model simulations that were both a retrospective simulation as well as a pseudo‐global warming simulation applicable near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% from 985 hr in the current climate to 1,035 hr within the future one. Near‐0°C occurrences with precipitation vary from <5% to approximately 50% of these values. Near‐0°C occurrences are sometimes higher than values of neighboring temperatures. These near‐0°C peaks in temperature distributions can occur in both the current and future climate, in only one, or in neither. Only 4.3% of southern Canada is not associated with a near‐0°C peak and 65.8% is associated with a near‐0°C peak in both climates. It is inferred that latent heat exchanges from the melting and freezing of, for example, precipitation and the snowpack contribute significantly to some of these findings. Plain Language Summary: Our changing climate is spurring the development of huge efforts to improve resiliency. For many regions of the world, these efforts must account for potential changes in near‐0°C conditions within which both melting and freezing can occur and the accompanying latent heat exchanges can push air temperature toward 0°C. This article focuses on the occurrence of near‐0°C surface temperatures across southern Canada through an examination of observational and model information including projections in a future warmer (average 6.1°C increase) climate near the end of the 21st century. Average annual occurrences of near‐0°C conditions increase by a relatively small amount of 5.1% in the future climate and highest values continue to be along the Pacific coast or within the Western Cordillera and lowest values continue to be within central and northern areas. Near‐0°C occurrences are often higher than those of neighboring temperatures in the present climate and some of these elevated occurrences persist into the future one despite dramatic warming. It is inferred that latent heat exchanges from the melting and freezing of precipitation and snowcover contribute to these findings. Key Points: Near‐0°C surface air temperatures were examined over southern Canada using retrospective and pseudo‐global warming simulationsOverall average occurrences increase slightly and their spatial patterns are largely maintained in the warmer climateNear‐0°C occurrences sometimes exceed those of neighboring temperatures and this feature often persists despite dramatic warming [ABSTRACT FROM AUTHOR]

Increasing river water temperature in response to the warming climate is concerning for water quality and ecosystem health of rivers. This study provides an assessment of the spatio‐temporal variability of the ongoing and potential future river water temperature (Tw) change in western Canada. We use the air2stream model to reconstruct historical Tw dataset for 17 stations across six rivers, and employ the reconstructed Tw to analyze hydro‐climatic controls, trends, and sensitivities in relation to air temperature (Ta) and discharge. Results provide insights on the contrasting summer (July and August) Tw responses. While Tw is primarily Ta controlled for the northern rivers, discharge exerts increasing influence that approaches Ta control for the southern rivers. Trends in Tw are increasing and spatially varied, with significant increases and occurrences above the critical 18 and 20°C thresholds for the southern Fraser and Similkameen Rivers. A sensitivity analysis indicated 0.5–1.5°C Tw increases for a 2.0°C Ta increase, and 0.2–0.6°C Tw increases for a 20% summer discharge decline. Overall, the results provide critical information for understanding the river ecosystem health, such as cold‐water species habitat. [ABSTRACT FROM AUTHOR]

The increasing amount of operational data in buildings opens up new methods for improving building performance through advanced controls. Although predictive control has been widely investigated in the literature, field demonstrations still remain rare. Alternatively, model-based controls can provide similar improvement while being easier to implement in real buildings. This paper investigates three data-driven model-based control strategies to improve the cooling performance of commercial and institutional buildings: (a) chiller sequencing, (b) free cooling, and (c) supply air temperature reset. These energy efficiency measures are applied to an existing commercial building in Canada with data from summer 2020 and 2021. The impact of each measure is individually assessed, as well as their combined effects. The results show that all three of the measures together reduce building cooling energy by 12% and cooling system electric energy by 33%. [ABSTRACT FROM AUTHOR]

Northern peatlands cover approximately four million km 2 , and about half of these peatlands are estimated to contain permafrost and periglacial landforms, like palsas and peat plateaus. In northeastern Canada, peatland permafrost is predicted to be concentrated in the western interior of Labrador but is assumed to be largely absent along the Labrador Sea coastline. However, the paucity of observations of peatland permafrost in the interior, coupled with traditional and ongoing use of perennially frozen peatlands along the coast by Labrador Inuit and Innu, suggests a need for re-evaluation of the reliability of existing peatland permafrost distribution estimates for the region. In this study, we develop a multi-stage consensus-based point inventory of peatland permafrost complexes in coastal Labrador and adjacent parts of Quebec using high-resolution satellite imagery, and we validate it with extensive field visits and low-altitude aerial photography and videography. A subset of 2092 wetland complexes that potentially contained peatland permafrost were inventoried, of which 1119 were classified as likely containing peatland permafrost. Likely peatland permafrost complexes were mostly found in lowlands within 22 km of the coastline, where mean annual air temperatures often exceed +1 ∘ C. A clear gradient in peatland permafrost distribution exists from the outer coasts, where peatland permafrost is more abundant, to inland peatlands, where permafrost is generally absent. This coastal gradient may be attributed to a combination of climatic and geomorphological influences which lead to lower insolation, thinner snowpacks, and poorly drained, frost-susceptible materials along the coast. The results of this study suggest that existing estimates of permafrost distribution for southeastern Labrador require adjustments to better reflect the abundance of peatland permafrost complexes to the south of the regional sporadic discontinuous permafrost limit. This study constitutes the first dedicated peatland permafrost inventory for Labrador and provides an important baseline for future mapping, modelling, and climate change adaptation strategy development in the region. [ABSTRACT FROM AUTHOR]

Hydrological processes within the alpine tundra of the Taiga Cordillera ecozone in northwestern Canada are poorly understood, yet these areas receive more precipitation per unit area than lowlands and sustain late summer and winter flow in large river systems when contributions from other areas are reduced. The objective of this study was to quantify the spatial and temporal variability in streamflow and groundwater recharge within an alpine tundra basin with discontinuous permafrost and explore the potential impacts of climate change on the timing and intensity of these hydrological processes. Hydrometric and remote sensing methods were used to complete a water balance assessment of the study basin and compare spatial and seasonal differences in inputs, outputs, runoff ratio, and runoff–recharge partitioning during the 2019 open water season. During the freshet, the basin received large daily melt volumes and responded with highly efficient runoff. Evapotranspiration became the primary means of water loss in the early summer but declined as the summer progressed. During the summer, groundwater discharge exceeded precipitation inputs and sustained headwater subbasin streamflow. Groundwater recharge occurred primarily via glaciofluvial upland infiltration during the freshet and channel bed infiltration during the summer. The partitioning of basin outputs between runoff and groundwater recharge was highly seasonal, with a freshet ratio favoring runoff (0.83) while the early and late summer favored recharge (0.28 and 0.17, respectively). As climate change continues, higher air temperatures and greater precipitation are expected for the study basin. Longer open water seasons and declining permafrost extent within the study basin will result in a greater proportion of input water routed to storage and/or groundwater recharge instead of runoff. Shrubification and treeline expansion may also increase evaporative losses from alpine tundra areas, reducing both rapid runoff and delayed aquifer recharge contributions important for larger rivers at lower elevation. [ABSTRACT FROM AUTHOR]

Northern high latitudes are experiencing some of the greatest increases in air temperatures on Earth. Air temperatures (along with other modulating variables including precipitation and the onset of snowmelt) are influenced by atmospheric–oceanic circulation patterns, some of which are persistent and recurrent. One pattern in particular, the Arctic Dipole (AD) anomaly, is a persistent sea‐level pressure teleconnection pattern between the Canadian Archipelago and Barents Sea that has unknown impacts on local climate variability. These patterns may be important, especially in hydro‐ecologically sensitive areas such as Northwest Territories (NWT), Canada where permafrost thaw and ecosystem changes are influenced by interannual climate variability. The goal of this research is to determine the impacts of the AD on local climate (air temperature, precipitation, snowmelt) for a 66‐year period (1950–2015) spanning both latitudinal and longitudinal gradients across NWT from north to south and foothills to plains. Deviations during strong positive and negative modes of the AD index were calculated in reference to the complete 66‐year record. Results showed considerable year‐to‐year variability in the AD pattern, with more frequent strong negative modes during the 2000s. During 1950–2015, there were 64 and 56 occurrences of strong positive and strong negative AD modes, respectively, across all seasons. Spring and summer strong AD modes led to local air temperature anomalies of greater than 0.8°C compared with the long‐term (66 years) mean. Earlier onset of snowmelt, by an average of 3–5 days, was also noted during positive AD modes. Despite strong connectivity between the AD and local air temperature, we found less correspondence between the AD and seasonal precipitation. These findings improve understanding of the impacts of the AD on local weather and climate in NWT and suggest implications for ecosystem change, such as drying and shrubification of northern boreal peatlands and possible connectivity to teleconnection impacts on wildland fire. [ABSTRACT FROM AUTHOR]

In mountains, the precipitation phase greatly varies in space and time and affects the evolution of the snow cover. Snowpack models usually rely on precipitation‐phase partitioning methods (PPMs) that use near‐surface variables. These PPMs ignore conditions above the surface thus limiting their ability to predict the precipitation phase at the surface. In this study, the impact on snowpack simulations of atmospheric‐based PPMs, incorporating upper atmospheric information, is tested using the snowpack scheme Crocus. Crocus is run at 2.5‐km grid spacing over the mountains of southwestern Canada and northwestern United States and is driven by meteorological fields from an atmospheric model at the same resolution. Two atmospheric‐based PPMs were considered from the atmospheric model: the output from a detailed microphysics scheme and a post‐processing algorithm determining the snow level and the associated precipitation phase. Two ground‐based PPMs were also included as lower and upper benchmarks: a single air temperature threshold at 0°C and a PPM using wet‐bulb temperature. Compared to the upper benchmark, the snow‐level based PPM improved the estimation of snowfall occurrence by 5% and the simulation of snow water equivalent (SWE) by 9% during the snow melting season. In contrast, due to missing processes, the microphysics scheme decreased performances in phase estimate and SWE simulations compared to the upper benchmark. These results highlight the need for detailed evaluation of the precipitation phase from atmospheric models and the benefit for mountain snow hydrology of the post‐processed snow level. The limitations to drive snowpack models at slope scale are also discussed. Plain Language Summary: The partitioning of precipitation between rainfall and snowfall is a crucial component of the evolution of the snowpack in mountains. Most snowpack models use the air temperature and humidity near the surface to derive the precipitation phase. However, the phase at the surface is strongly influenced by processes such as melting and refreezing of falling hydrometeors that occur above the surface. Atmospheric models simulate these processes and the corresponding phase at the surface. However, snowpack models rarely use this information. In this study, we considered two estimates of precipitation phase from an atmospheric model and tested them with a physically‐based snow model over the mountains of southwestern Canada and northwestern United States. The results were compared with traditional approaches using the air temperature and humidity near the surface to derive the precipitation phase. Our results showed that the precipitation phase associated with the snow level obtained from the atmospheric model improved snowfall estimate and snowpack prediction compared to the traditional approaches. In contrast, the cloud/precipitation scheme of the atmospheric model decreased performance in phase estimate and snow simulations due to missing physical processes. Our study highlights that snowpack predictions in the mountains can be improved if valuable information is obtained from atmospheric models. Key Points: Estimates of precipitation phase from an atmospheric model were used to drive snow simulations with a detailed snowpack modelSnowfall prediction and snowpack modeling are improved by using the snow level from post‐processing of the atmospheric modelDirect precipitation phase from the microphysics scheme does not improve snow simulations compared to simpler rain‐snow partitioning schemes [ABSTRACT FROM AUTHOR]

The warm Arctic–cold continent pattern (WACC) of near-surface air temperature variability has often been associated with the connection between Arctic sea ice reduction and cold weather over the midlatitude continents. Whether the existence of this pattern is due to variability of sea ice or is caused by atmospheric internal dynamics is subject to debate. Based on a long integration of a primitive equation atmospheric model (SGCM), this study examines the origin of the warm Arctic–cold North American pattern (WACNA), which is characterized by a pair of opposite surface air temperature anomalies over the high-latitude Chukchi–Bering Sea region and the North American continent, in boreal winter on the intraseasonal time scale. The model atmosphere is maintained by a time-independent forcing, so that atmospheric internal dynamics is the only source of variability. It is found that the SGCM model simulates well the behavior of the observed WACNA pattern. The WACNA pattern develops by interacting with the time-mean flow and synoptic-scale transient eddies. Two pathways of Rossby wave propagation are associated with WACNA. The northern pathway originates from eastern Siberia moving eastward across the Bering Strait to Canada, and the southern pathway is rooted in the subtropical waveguide propagating across the eastern North Pacific. Our simulation of this pattern implies that tropospheric dynamics alone can generate the WACNA, and the predictability associated with this pattern is likely limited by its internal dynamics nature. Significance Statement: The warm Arctic–cold continent pattern of temperature variability has often been associated with the connection between Arctic sea ice reduction and cold weather over the midlatitude continents, which implies possible impacts of polar warming on midlatitude climate. There has been debate on whether the existence of this pattern depends on variability of sea ice or can be caused by processes within the atmosphere. In this study, we use a simple atmospheric model, which has a constant forcing; thus, atmospheric internal dynamics is the only source of variability. We show that atmospheric internal dynamics alone can generate the warm Arctic–cold North American pattern. The result has implications for our understanding of the impact of global warming. [ABSTRACT FROM AUTHOR]

The Bayesian model averaging (BMA) method has been widely used for generating probabilistic climate projections. However, the averaging weights used in BMA can only reflect the spatially‐ and temporally‐averaged performance of each ensemble member, without the ability to address the spatiotemporal variations of model biases. This can lead to inevitable exaggeration or understatement of the contributions of individual members to the ensemble mean, thus reducing the robustness of the resulting probabilistic projections. Here we propose a new method to help address the neglected spatiotemporal variations of model biases. Through the proposed method, the BMA weights are used as prior distributions to drive the Bayesian discriminant analysis in order to generate refined weights for individual ensemble models according to their spatially‐ and temporally‐clustered performance. Through applying the proposed method to Canada, we demonstrate its effectiveness in generating robust probabilistic climate projections (e.g., the average R2 increases from 0.82 to 0.89). Plain Language Summary: Since no climate model is superior to others under all conditions, taking the advantages of multiple models is desired for robust climate projections. However, there exist significant spatial and temporal variations regarding the model performances. For example, an overall poorly‐performed model can still show promising results over a specific region or during a specific time period, while an overall well‐performed model does not necessarily perform well over all regions or in all years. Here we propose a new method to robustly address the spatiotemporal variations in the modeling performance of each ensemble member. Then we apply the proposed method to generate the probabilistic temperature projections over Canada. The proposed method can improve both the accuracy and reliability in ensemble‐based climate projections. Key Points: A discriminant‐BMA ensemble modeling approach is developed to synthesize the spatiotemporal variations of model biasesThe accuracy and reliability of probabilistic projections are both improved (e.g., the average R2 increases from 0.82 to 0.89)The temperature probabilistic projections based on regional climate models in three future periods are generated over Canada [ABSTRACT FROM AUTHOR]

Glacier mass balance models are needed at sites with scarce long-term observations to reconstruct past glacier mass balance and assess its sensitivity to future climate change. In this study, North American Regional Reanalysis (NARR) data were used to force a physically based, distributed glacier mass balance model of Saskatchewan Glacier for the historical period 1979–2016 and assess its sensitivity to climate change. A 2-year record (2014–2016) from an on-glacier automatic weather station (AWS) and historical precipitation records from nearby permanent weather stations were used to downscale air temperature, relative humidity, wind speed, incoming solar radiation and precipitation from the NARR to the station sites. The model was run with fixed (1979, 2010) and time-varying (dynamic) geometry using a multitemporal digital elevation model dataset. The model showed a good performance against recent (2012–2016) direct glaciological mass balance observations as well as with cumulative geodetic mass balance estimates. The simulated mass balance was not very sensitive to the NARR spatial interpolation method, as long as station data were used for bias correction. The simulated mass balance was however sensitive to the biases in NARR precipitation and air temperature, as well as to the prescribed precipitation lapse rate and ice aerodynamic roughness lengths, showing the importance of constraining these two parameters with ancillary data. The glacier-wide simulated energy balance regime showed a large contribution (57 %) of turbulent (sensible and latent) heat fluxes to melting in summer, higher than typical mid-latitude glaciers in continental climates, which reflects the local humid "icefield weather" of the Columbia Icefield. The static mass balance sensitivity to climate was assessed for prescribed changes in regional mean air temperature between 0 and 7 ∘ C and precipitation between -20 % and + 20 %, which comprise the spread of ensemble Representative Concentration Pathway (RCP) climate scenarios for the mid (2041–2070) and late (2071–2100) 21st century. The climate sensitivity experiments showed that future changes in precipitation would have a small impact on glacier mass balance, while the temperature sensitivity increases with warming, from -0.65 to -0.93 m w.e. a -1 ∘ C -1. The mass balance response to warming was driven by a positive albedo feedback (44 %), followed by direct atmospheric warming impacts (24 %), a positive air humidity feedback (22 %) and a positive precipitation phase feedback (10 %). Our study underlines the key role of albedo and air humidity in modulating the response of winter-accumulation type mountain glaciers and upland icefield-outlet glacier settings to climate. [ABSTRACT FROM AUTHOR]

Canada's climate is warming at a rate about double the global average, leading to potential negative impacts on public infrastructures such as jointed plain concrete pavement (JPCP). In light of this reality of changing climate, the work contained in this paper is aimed at evaluating JPCP's early-age behaviour in response to environmental conditions. HIPERPAV® software and the associated models developed by the U.S. Federal Highway Administration (FHWA) were used to identify cracking potential. A sensitivity analysis was performed to assess the effect of different levels of air temperature, mix temperature, base layer temperature, wind speed, and relative humidity. Additionally, projected extreme temperatures predicted by the Canadian Regional Climate Model (CanRCM) were used to determine the relative impact of climate change on cracking risk. The results demonstrated the increased cracking risk under changing climate in several Canadian cities by mid-century and highlighted the importance of developing a pathway forward for climate adaptation. [ABSTRACT FROM AUTHOR]

In light of the recent climate warming, monitoring of lake ice in Arctic and sub-Arctic regions is becoming increasingly important. Many shallow arctic lakes and ponds of thermokarst origin freeze to bed in the winter months, maintaining the underlying permafrost in its frozen state. However, as air temperatures rise and precipitation increases, less lakes are expected to develop bedfast ice. In this work, we propose a novel temporal deep learning approach to lake ice regime mapping from synthetic aperture radar (SAR) and employ it to study lake ice dynamics in the Old Crow Flats (OCF), Yukon, Canada over the 1993 to 2021 period. We utilized a combination of Sentinel-1, ERS-1 and 2, and RADARSAT-1 to create an extensive annotated dataset of SAR time-series labeled as either bedfast ice, floating ice, or land, used to train a temporal convolutional neural network (TempCNN). The trained TempCNN, in turn, allowed to automatically map lake ice regimes. The classified maps aligned well with the available field measurements and ice thickness simulations obtained with a thermodynamic lake ice model. Reaching a mean overall classification accuracy of 95 %, the TempCNN was determined to be suitable for automated lake ice regime classification. The fraction of bedfast ice in the OCF increased by 11 % over the 29-year period of analysis. Findings suggest that the OCF lake ice dynamics is dominated by lake drainage events, brought on by thermokarst processes accelerated by climate warming, as well as fluctuations in water level and winter snowfall. Catastrophic drainage, and lowered water levels cause surface water area and lake depth to decrease and lake ice to often transition from floating to bedfast ice, while a reduction in snowfall allows for the growth of thicker ice. [ABSTRACT FROM AUTHOR]

A thermal metric developed using the day-to-day temperature variability framework that was previously applied to the east coast of China has been adapted for Canadian climate station data. The same metric, based on the variability of the minimum temperature of the day, was able to distinguish between coastal and inland stations, especially when the winter months of December, January and February, were removed from the analysis. While the threshold of the metric that distinguished between the two groups was different than that developed for the east coast of China, it was nonetheless unambiguous. The range of latitudes in the Canadian setting was sufficiently narrow that a latitude correction, as was performed for the China climate stations, was not required. A comparison with a more traditional measure of continentality suggests that the thermal variability measure performs better at identifying the coastal/continental nature of the climate station data. This work also suggests that a more nuanced treatment of winter months should be considered for all such measures in colder climates. [ABSTRACT FROM AUTHOR]

Conventional green roofs have been widely accepted as a climate change adaptation strategy. However, little is known about the potential of blue–green roofs and rooftop farms to control urban stormwater and improve microclimates. This study evaluates a farmed blue–green roof's hydrologic and thermal performance over an entire growing season in Toronto, Ontario, Canada. The runoff discharge from three plots planted with various crops was monitored. The substrate and air temperatures at two elevations of different cultivated and self-sowing plant species were collected and compared to a control roof. Results indicate that planting and harvesting activities impacted the hydrologic performance. Mean values for retention ranged from 85–88%, peak attenuation ranged from 82–85%, and peak delay ranged from 7.7 to 8 h. At the lower elevation, the mean air temperature difference above okra, tobacco, and beet was 2.5 °C, whereas, above squash, potato, and milkweed, it was 1.4 °C. Maximum and moderate air-cooling effects were observed in the afternoon and evening, but a warming effect was observed in the early morning. Farmed blue–green roof evaluated in this study provides a runoff control and microclimate improvement comparable to or better than conventional green roofs, in addition to other benefits such as improving food security. [ABSTRACT FROM AUTHOR]

• Paired multi-year eddy covariance measurements at the forest-tundra ecotone in western Canada. • A mixed-layer slab model and radiosonde observations to understand atmospheric boundary layer dynamics. • Similar latent heat flux but higher sensible heat flux at woodland compared to tundra. • Deeper, warmer, and drier (spring only) atmospheric boundary layer at woodland compared to tundra. • Vegetation shifts in the forest-tundra ecotone will modify local surface climate. The circumpolar forest-tundra ecotone is experiencing rapid changes in vegetation composition and structure. Collectively, these changes modify surface-atmosphere energy exchanges and thus characteristics of the atmospheric boundary layer (ABL). Here, we characterize differences in bulk surface properties and resulting energy balance components using multi-year eddy covariance and supporting measurements made at a mineral upland tundra and a nearby subarctic woodland site between 2013 and 2022. The two sites are characteristic of the forest-tundra ecotone of northwestern Canada. A mixed-layer slab model, in combination with radiosonde observations, was used to gain more insights into differences in ABL characteristics. Compared to the tundra, the tree cover of the woodland led to an enhanced ability to transfer heat into the atmosphere, a higher resistance to evapotranspiration and a stronger coupling between surface and atmosphere. Sensible heat flux (H) was generally higher at the woodland than at the tundra. The largest difference in daily mean H was observed in late winter and spring when the albedo of the snow-covered landscape at the woodland was reduced by 45% compared to the tundra. Both sites experienced similar latent heat flux throughout the year. At the woodland, modelled afternoon air temperature in the mixed layer was up to 9 °C higher in spring and up to 3 °C higher in summer compared to the tundra. In accordance with model results, radiosonde observations indicated a deeper ABL and higher air temperature at the woodland. The presence of trees in the southern part of the forest-tundra ecotone increases air temperature throughout the year and has a drying effect in spring. Consequently, vegetation shifts in the forest-tundra ecotone can be expected to modify local surface climate change patterns, which must be considered when assessing climate change impacts in the region. [ABSTRACT FROM AUTHOR]

• May minimum temperature is the primary driver of budburst in boreal conifers. • P. mariana showed the highest response to warmer springs and P. glauca the lowest. • Precipitation's effect on budburst is limited when compared to temperature. • Changes in bud phenology may disrupt host-insect interactions. • Budburst timing correlates with latitude and ecological provinces. Budburst is a pivotal event in plant life, representing a crucial response to seasonal meteorological shifts. Boreal tree species exhibit species-specific phenologies, and the rate of phenological changes under warming conditions may differ among these species. In this study we aim to investigate the timing of budburst in three coniferous species [Balsam fir (Abies balsamea), black spruce (Picea mariana) and white spruce (Picea glauca) (Pinaceae)]; identify the main drivers of budburst, its rate of advance and the spatiotemporal patterns of budburst in relation to climate across Canada using a time period of 1980–2021. The timing of budburst was observed at 2839 locations stretching from Alberta to Newfoundland. We developed response functions between budburst and climate (air temperature, precipitation and solar radiation) and used the strongest correlations to test their effect on budburst using species, time and the ecoclimatic framework of Canadian ecoprovinces. We applied spatially constrained multivariate clustering and identified natural budburst clustering across Canada. We found a baseline difference of 17 days in the budburst of black spruce relative to that of balsam fir and white spruce. Mean minimum temperature of May was negatively correlated with budburst date. Black spruce advanced budburst at a rate of change per degree of temperature (−3.33 days °C−1), twice that of balsam fir and white spruce (−1.53 and −1.27 days °C−1, respectively). Cluster distribution of budburst timing matched well with the distribution of Canadian ecoprovinces. Budburst within the clusters followed clinal patterns in temperature across Canada. Mean minimum temperature in May is the main factor driving budburst in northern tree species. Under a warmer spring, we project an earlier budburst, with black spruce being the species expected to show the greatest rate of change. The identified clustering patterns did not vary with precipitation, which represents the primary longitudinal gradient across Canada. [ABSTRACT FROM AUTHOR]

Unexpected observations of strong radiowave scatter at a ~85–90 km altitude with very high frequency radars were explained in the early 1990s, when it was demonstrated that these were due to special turbulent and small-scale scatterers with high Schmidt number. Studies of these phenomena have primarily been concentrated in polar regions, and the events seem most prominent in regions of very cold air (below 140 K). Such radar echoes are referred to as polar mesosphere summer echoes (PMSE), and are rare at lower latitudes. In this paper we report observations of similar scatterers at sites below 50° latitude. The nature of these scatterers is discussed and results are compared to observations at the polar site of Eureka, Canada. Mid-latitude observations at frequencies of 48.92 and 45.47 MHz were made, respectively, at Abitibi Canyon (49.9° N latitude) and Markstay (46.5° N latitude) in Ontario, Canada. In particular, we look at the relationship of these scatterers to geophysical parameters, especially the Ap index. Our results suggest that mesospheric air with temperatures less than 140 K now exists below 50° latitude. This may be an indication of an equator-ward creep of global mesospheric cooling (which is associated with the well-known tropospheric global warming), but the scatterers at lower latitudes also demonstrate correlation with the Ap index. On the other hand, the polar scatterers at Eureka demonstrated no correlation of any significance with Ap. The importance of these results in regard to the global distribution of mesospheric temperatures is discussed, and comparisons to other measurements are made. [ABSTRACT FROM AUTHOR]

The active layer thickness (ALT) is a key parameter for permafrost studies. Changes in the ALT are affected mainly by air and ground temperatures, physical and thermal properties of the surface and subsurface materials, soil moisture, vegetation, and the duration and thickness of snow cover. Ground penetrating radar (GPR) and electrical resistivity tomography (ERT) were employed across a snow fence during the thawing season to delineate and monitor the active layer of permafrost in Cambridge Bay, Nunavut, Canada. The variation of the ALT is well captured by the high-resolution time-lapse radargram. At the position of the fence, the active layer thickens over the thawing period from 0.5 m depth at the beginning to 1.0 m depth at the end. The active layer is thicker in the pre-fence area (C zone) than in the post-fence area (H zone). As the air temperature increases with time, the difference in thickness between the two zones decreases, eventually becoming almost equal. Changes in the ALT are represented in the ERT by low resistivities (< 200 Ωm), which decrease gradually with time. This occurs most significantly in the H zone due to the rapidly increasing temperature in the absence of snow cover. The electrical resistivity structure of the active layer is well correlated with the vegetation activity, as measured by the normalized difference vegetation index, air/ground temperatures, soil moisture, snow cover, and snow accumulation controlled by the fence. Geophysical data interpretation and correlation schemes with vegetation and meteorological data explored in this paper can be applied to monitor the active layer, which is expected to thin during the freezing season. [ABSTRACT FROM AUTHOR]

Groundwater recharge (GWR) is a strategic hydrologic variable, and its estimate is necessary to implement sustainable groundwater management. This is especially true in a global warming context that highly impacts key winter conditions in cold and humid climates. For this reason, long-term simulations are particularly useful for understanding past changes in GWR associated with changing climatic conditions. However, GWR simulation at the regional scale and for long-term conditions is challenging, especially due to the limited availability of spatially distributed calibration data and due to generally short observed time series. The objective of this study is to demonstrate the relevance of using a water budget model to understand long-term transient and regional-scale GWR in cold and humid climates where groundwater observations are scarce. The HydroBudget model was specifically developed for regional-scale simulations in cold and humid climate conditions. The model uses commonly available data such as runoff curve numbers to describe the study area, precipitation and temperature time series to run the model, and river flow rates and baseflow estimates for its automatic calibration. A typical case study is presented for the southern portion of the Province of Quebec (Canada, 36 000 km 2). With the model simultaneously calibrated on 51 gauging stations, the first GWR estimate for the region was simulated between 1961 and 2017 with very little uncertainty (≤ 10 mm/yr). The simulated water budget was divided into 41 % runoff (444 mm/yr), 47 % evapotranspiration (501 mm/yr), and 12 % GWR (139 mm/yr), with preferential GWR periods during spring and winter (44 % and 32 % of the annual GWR, respectively), values that are typical of other cold and humid climates. Snowpack evolution and soil frost were shown to be a key feature for GWR simulation in these environments. One of the contributions of the study was to show that the model sensitivity to its parameters was correlated with the average air temperature, with colder watersheds more sensitive to snow-related parameters than warmer watersheds. Interestingly, the results showed that the significant increase in precipitation and temperature since the early 1960s did not lead to significant changes in the annual GWR but resulted in increased runoff and evapotranspiration. In contrast to previous studies of past GWR trends in cold and humid climates, this work has shown that changes in past climatic conditions have not yet produced significant changes in annual GWR. Because of their relative ease of use, water budget models are a useful approach for scientists, modelers, and stakeholders alike to understand regional-scale groundwater renewal rates in cold and humid climates, especially if they can be easily adapted to specific study needs and environments. [ABSTRACT FROM AUTHOR]

To assess the potential change in agroclimatic indices in western Canada, this study used a convection-permitting Weather Research Forecasting (WRF) model to conduct simulations for the current climate (CTL, 2000-2015) and future climate under the RCP8.5 scenario based on a pseudo-global-warming (PGW) approach. Both CTL and PGW simulations were bias-corrected to the GEM-CaPA dataset using a multivariate quantile mapping method. An evaluation of the CTL simulation of daily maximum and minimum temperatures and precipitation during the growing season against the gridded observations has been performed, indicating good agreements in the spatial patterns of air temperature and precipitation in western Canada. The PGW-CTL differences in several selected agroclimatic indices were then examined. Due to rising temperatures, substantial increases in growing degree-days (GDD) by 800-1,200◦ days and reductions in frost days by 10 to 20 days, favouring regional crop production, are found in southern Alberta and Saskatchewan. However, globalwarming also poses great risks to Canadian agriculture by modifying heat accumulations and water availability during the growing season. Plant heat stress will substantially increase by ∼50◦ days in southern Alberta and Saskatchewan, offsetting the positive effects caused by the reduction in frost days and increase in GDD. The southern Canadian Prairies will experience statistically significant increases in the number of dry days and precipitation deficit, suggesting an exacerbation of water stress on the Canadian Prairies by global warming. [ABSTRACT FROM AUTHOR]

• New high air temperature records were established over a large domain over a few days. • Changes to streamflow coincided with the air temperature extremes. • The hydrologic regime determined the type of response to the heatwave. • Hydrological responses were conditioned by the existing snowpack. The 2021 Western North America heatwave resulted in record high air temperatures over a large area of Canada west of 100°. The heatwave persisted from mid-June into July, depending upon the threshold used to define the heatwave. The heatwave was a weather event that was short lived but had a widespread transient impact on hydrology in this single year. These impacts were more evident in nival systems because of the prominent role of snowmelt. In normal years, the timing of hydrological processes, particularly snowmelt, is a function of latitude and elevation; in 2021 the heatwave resulted in simultaneous high rates of snowmelt across rivers where a snowpack existed at the time of the event, and strong diurnal melt signal was a diagnostic. In 2021, rivers throughout Canada west of 100°W responded strongly to the heatwave, but the response depended on three factors: location relative to the heat dome, the hydrologic regime, and the amount of snow present at the time. The melt signal was strongest in those basins that had not reached their annual peak often having discharges in the highest 5 % of historical observations for that day of the year. Discharges rapidly declined in basins already in recession indicating the rapid depletion of the snowpack. In basins with little or no remaining snow, streamflow often declined during the same period often to levels in the lowest 5 % of historical observations for that day of the year. [ABSTRACT FROM AUTHOR]

This article presents the results of a 182 day implementation of a model predictive controller (MPC) in a test house in Ottawa, Canada. The MPC controls the timing of hydronic floor heating and cooling within the highly glazed house (13.5% south-facing window-to-floor ratio). The objectives of the MPC are to optimally control the on/off times of active heating and cooling to minimize energy use while also minimizing air temperature violations outside of a prescribed range. It was found that 71% of the days in the experimental period saw successful operation of the MPC towards these goals. Days that experienced overheating were found to be concentrated in January–February and days that experienced overcooling were found to be concentrated in March–May. Problematic decision making by the MPC was found to be rooted in 4 main issues: (1) global horizontal irradiance (GHI) is a bad indicator of passive solar on its own; (2) weather forecasting (specifically GHI forecasting) is critical to MPC success in highly glazed buildings; (3) the GHI history regressor used in the prediction model regularly influenced predictions illogically; and (4) the MPC lacked decision-making logic on the timing of hydronic floor cooling. • A model predictive controller was implemented in a highly glazed, full-scale, test house. • Performance of the model predictive controller was evaluated over 7 months. • The design of the MPC is simple and practical for implementation in a real building. • A recommendation is made on what a model predictive controller could look like for a highly glazed house. [ABSTRACT FROM AUTHOR]

Worldwide, approximately 1900 people die by suicide daily. Daily elevations in air pollution and temperature have previously been linked to a higher risk of death from suicide. To date, there have been relatively few studies of air pollution and suicide, particularly at a national level. National analyses play an important role in shaping health policy to mitigate against adverse health outcomes. We used a time-stratified case-crossover study design to investigate the influence of short-term (i.e., day to day) interquartile range (IQR) increases in air pollutants (nitrogen dioxide [NO 2 ], ozone [O 3 ], and fine particulate matter [PM 2.5 ]) and temperature on suicide mortality in Canada between 2002 and 2015. For air pollution models, odds ratios (ORs) derived from conditional logistic regression models were adjusted for average daily temperature, and holidays. For temperature models, ORs were adjusted for holidays. Stratified analyses were undertaken by suicide type (non-violent and violent), sex, age, and season. Analyses are based on 50,800 suicide deaths. Overall, temperature effects were stronger than those for air pollution. A same day IQR increase in temperature (9.6 °C) was associated with a 10.1% increase (95% confidence interval (CI): 9.0%–11.2%) of death from suicide. For 3-day average increase of O 3 (IQR = 14.1 ppb), PM 2.5 (IQR = 5.6 μg/m3) and NO 2 (IQR = 9.7 ppb) the corresponding risks were 4.7% (95% CI: 3.9, 5.6), 3.4% (95% CI: 3.0, 3.8), and 2.0% (95% CI: 1.1, 2.8), respectively. All pollutants showed stronger associations with suicide during the warmer season (April–September). Stratified analyses revealed stronger associations for both temperature and air pollution in women. Daily increases in air pollution and temperature were found to increase the risk of death from suicide. Females, particularly during warmer season, were most vulnerable to these exposures. Policy decisions related to air pollution and climate change should consider effects on mental health. • Daily increases in NO 2 , PM 2.5 and O 3 were associated with higher suicide mortality. • Those associations were strongest in women and during the warmer season. • A same day increase in temperature was associated with the highest risk of suicide. • Higher levels of PM 2.5 and O 3 may amplify the temperature-suicide association. [ABSTRACT FROM AUTHOR]

• A framework is developed to assess overheating in existing building in whole summer. • Calibration simulation model is used using field measurements of indoor temperature. • Overheating risk in existing school building is assessed. • Climate change effect is studied using current and future extreme RSWY years. • Effective passive mitigation measures are provided for future extreme climates. Canadian buildings have been primarily designed to withstand cold and long winters, not hot summers. With climate change and the increase in the intensity and severity of heatwaves, it has become important to investigate overheating in buildings. However, there are limited studies on assessing and mitigating the overheating risk in existing buildings that house vulnerable populations in cold climates, especially in Canada. This paper provides a framework for the systematic assessment of overheating risks and the development of passive mitigation strategies to reduce the overheating risks without increasing cooling energy consumption under current and future climates with simulation models that are calibrated based on measured indoor air temperatures and outdoor weather conditions. The framework is applied to a school building built in 1958. The calibrated building model achieved an RMSE of less than 0.6 °C compared with measurements, a Maximum-Absolute-Difference of less than 1.9 °C, and a 1 °C Percentage-Error of less than 10 %. The simulation results from the calibrated model predicted 110 overheating hours during the year 2020. The use of exterior blind roll or a combination of night cooling and other mitigation measures that reduce solar heat gain can achieve acceptable thermal conditions. In 2044 (the future extreme midterm year), night cooling with the exterior blind roll shading would be required during extreme heat events. Whereas during 2090 (the future long-term extreme year), additional mitigation measures such as a cool roof may be required to achieve an acceptable level of thermal conditions in the school. [ABSTRACT FROM AUTHOR]

To provide some design references for ships and offshore structures to operate in the Arctic waters, we assessed the spatial distributions of design air temperatures (DATs) in the Arctic Ocean using a 40-year MERRA-2 air temperature reanalysis data (1981–2020). The DATs studied included the design temperature (t D), polar service temperature (PST), lowest anticipated service temperature (LAST), and record lowest temperature (RLT). Higher DATs were observed in the Atlantic Arctic sector than Pacific Arctic sector. The lowest DATs were mainly in the Central Arctic Ocean near Canada. Moreover, the PST was generally lower than the RLT in the summer months. The lowest yearly (summer) t D for the Northeast Passage, the Transpolar Sea Route, and the Northwest Passage were −34.2 °C (−8.7 °C), −33.4 °C (−16.2 °C), and −32.0 °C (−13.2 °C). They are used to determine the steel grade requirements for ships. Not all regions in the Arctic Ocean had a rising trend in the yearly extreme low temperature under Arctic warming, especially in some nearshore areas. Furthermore, a strategy was provided for LAST uncertainties caused by climate change. These results and treatments provided references for future polar engineering designs. [ABSTRACT FROM AUTHOR]

Global climatic changes have been observed for all natural biomes, with the greatest impact in the permafrost zone. The short series of direct observations of air temperature and precipitation from meteorological stations for this territory make it difficult to use them in studies of the impact of climate change on forest and forest-tundra ecosystems, but only longer series of gridded data expand the temporal-spatial resolution of this analysis. We compared local and gridded air temperature, precipitation and vapor pressure deficit (VPD) data, analyzed the trends of their changes over the last century for three sites in the permafrost zone (YAK and TAY in Russia, and CAN in Canada), and estimated the effect of their variability on oxygen isotopes in the tree-ring cellulose (δ18Ocell) of three different species (Larix cajanderi Mayr, Larix gmelinii Rupr. Rupr and Piceaglauca (Moench) Voss). Climate trend analysis showed strong changes after the 1980s, and even more pronounced from 2000 to 2020. We revealed that δ18Ocell-YAK showed mixed signals of the July temperature (r = 0.49; p = 0.001), precipitation (r = −0.37; p = 0.02) and vapor pressure deficit (VPD) (r = 0.31; p = 0.02), while δ18Ocell-CAN captured longer March–May (r = 0.37, p = 0.001) and July (r = 0.32, p < 0.05) temperature signals as well as spring VPD (r = 0.54, p = 0.001). The δ18Ocell-TAY showed a significant correlation with air temperature in July (r = 0.23, p = 0.04) and VPD in March (r = −0.26, p = 0.03). The obtained eco-hydrological relationships indicate the importance of temperature and moisture to varying degrees, which can be explained by site- and species-specific differences. [ABSTRACT FROM AUTHOR]

This study examined heat flux from 15 Canadian northern rivers that drain to the Arctic Ocean and the Hudson/James Bay. Based on statistical analysis of available water temperature and discharge data, we determined patterns and characteristics of discharge, water temperature, and heat flux in relation to seasonal air temperature and precipitation. We found similar seasonal cycles of discharge and water temperature across the study region, i.e. most rivers experiencing maximum discharge in June/July and highest water temperatures in July/August. The mean flows during the open water season (May to Oct.) vary from west to east along the Arctic Coast (with higher yield from the Mackenzie and Peel rivers), while river flows are higher with warmer water temperatures in western and southern Hudson Bay. The summed heat flux for the studied rivers was about 10.0 × 1012 MJ along the Arctic Coast and 2.0x1012MJ around the Hudson Bay. Among the 9 rivers flowing directly into the Arctic Ocean, the Mackenzie River with the highest flow and warmest water temperature delivered the highest heat flux, i.e. average 9.5 × 1012 MJ over the open water season during 1960–2015. These observed patterns in discharge, water temperature and heat flux were generally consistent with CHANGE model simulations for most rivers in northern Canada. The outcomes of our study provide critical knowledge of river thermal condition and heat transport to the northern seas, which will be useful for large-scale climate and ocean model development and validation, and climate/hydrology change investigations in the broader northern regions. • Determined patterns of discharge (Q), water temperature (WT), and heat flux (HF) for 15 northern rivers in Canada. • Similar seasonal cycles of Q, WT and HF for the rivers, most rivers with max Q in June/July and highest WT in July/August. • Total warm season HF of 10.0x1012 MJ from the 9 rivers along Arctic Coast and 2.0x1012MJ for the 6 rivers into Hudson Bay. • Mackenzie River with highest Q and warmest WT delivered highest HF, 9.5x1012 MJ in open water season during 1960-2015. • Observations and CHANGE model HF simulations were generally consistent for most rivers in northern Canada. [ABSTRACT FROM AUTHOR]