Changes in snow, ice, and permafrost across Canada

Derksen, Chris; Burgess, David; Duguay, Claude R.; Howell, S.; Murdyk, L; Smith, S L; Thackeray, Chad W.; Kirchmeier‐Young, Megan C.

doi:10.4095/308279

Cited by 37 publications

(39 citation statements)

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“…It is predicted that, without taking action to reduce global warming, the Arctic will be ice-free each summer before 2050 (Hwang et al, 2020). The Canadian Arctic is warming at a rate three times the global average (Flato et al, 2019) and the greatest reductions of sea ice cover duration and concentration have been observed there (Stammerjohn et al, 2012;Mudryk et al, 2018;Derksen et al, 2019). The Eastern Canadian Arctic has been highlighted as lacking historical baseline data generally (Archambault et al, 2010) and for kelps, specifically (Krumhansl et al, 2016), with sampling efforts for the latter only recently increasing through documentation of kelp forests along Arctic and subarctic coastlines between Ellesmere Island and Labrador and along coasts in Lancaster Sound, Ungava Bay, Hudson Bay, Baffin Bay, and Resolute Bay (Lee, 1973;Adey and Hayek, 2011;Filbee-Dexter et al, 2019;Bringloe et al, 2020;Starko et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Kelp in the Eastern Canadian Arctic: Current and Future Predictions of Habitat Suitability and Cover

et al. 2021

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Climate change is transforming marine ecosystems through the expansion and contraction of species’ ranges. Sea ice loss and warming temperatures are expected to expand habitat availability for macroalgae along long stretches of Arctic coastlines. To better understand the current distribution of kelp forests in the Eastern Canadian Arctic, kelps were sampled along the coasts for species identifications and percent cover. The sampling effort was supplemented with occurrence records from global biodiversity databases, searches in the literature, and museum records. Environmental information and occurrence records were used to develop ensemble models for predicting habitat suitability and a Random Forest model to predict kelp cover for the dominant kelp species in the region – Agarum clathratum, Alaria esculenta, and Laminariaceae species (Laminaria solidungula and Saccharina latissima). Ice thickness, sea temperature and salinity explained the highest percentage of kelp distribution. Both modeling approaches showed that the current extent of arctic kelps is potentially much greater than the available records suggest. These modeling approaches were projected into the future using predicted environmental data for 2050 and 2100 based on the most extreme emission scenario (RCP 8.5). The models agreed that predicted distribution of kelp in the Eastern Canadian Arctic is likely to expand to more northern locations under future emissions scenarios, with the exception of the endemic arctic kelp L. solidungula, which is more likely to lose a significant proportion of suitable habitat. However, there were differences among species regarding predicted cover for both current and future projections. Notwithstanding model-specific variation, it is evident that kelps are widespread throughout the area and likely contribute significantly to the functioning of current Arctic ecosystems. Our results emphasize the importance of kelp in Arctic ecosystems and the underestimation of their potential distribution there.

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Section: Introductionmentioning

confidence: 99%

Kelp in the Eastern Canadian Arctic: Current and Future Predictions of Habitat Suitability and Cover

et al. 2021

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“…Particularly, enhanced warming in the northern latitudes (which is almost twice the global average temperature increase [1][2][3]) and amplified poleward moisture transport to the region [4,5] (which propagates into increased precipitation) are affecting different components of the regional hydro-climatic systems. Prominent changes include reductions in the magnitude, duration and extent of snow cover [6][7][8], enhanced permafrost thaw [9,10] and changes in the snowfall-rainfall balance [11], all with the potential to alter the mean and extreme streamflow conditions across the permafrost region.…”

Section: Introductionmentioning

confidence: 99%

Climatic Controls on Mean and Extreme Streamflow Changes Across the Permafrost Region of Canada

Shrestha

Pesklevits

Yang

et al. 2021

Water

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Climatic change is affecting streamflow regimes of the permafrost region, altering mean and extreme streamflow conditions. In this study, we analyzed historical trends in annual mean flow (Qmean), minimum flow (Qmin), maximum flow (Qmax) and Qmax timing across 84 hydrometric stations in the permafrost region of Canada. Furthermore, we related streamflow trends with temperature and precipitation trends, and used a multiple linear regression (MLR) framework to evaluate climatic controls on streamflow components. The results revealed spatially varied trends across the region, with significantly increasing (at 10% level) Qmin for 43% of stations as the most prominent trend, and a relatively smaller number of stations with significant Qmean, Qmax and Qmax timing trends. Temperatures over both the cold and warm seasons showed significant warming for >70% of basin areas upstream of the hydrometric stations, while precipitation exhibited increases for >15% of the basins. Comparisons of the 1976 to 2005 basin-averaged climatological means of streamflow variables with precipitation and temperature revealed a positive correlation between Qmean and seasonal precipitation, and a negative correlation between Qmean and seasonal temperature. The basin-averaged streamflow, precipitation and temperature trends showed weak correlations that included a positive correlation between Qmin and October to March precipitation trends, and negative correlations of Qmax timing with October to March and April to September temperature trends. The MLR-based variable importance analysis revealed the dominant controls of precipitation on Qmean and Qmax, and temperature on Qmin. Overall, this study contributes towards an enhanced understanding of ongoing changes in streamflow regimes and their climatic controls across the Canadian permafrost region, which could be generalized for the broader pan-Arctic regions.

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“…There is strong scientific consensus that temperatures in Canada will continue to increase into the future, and the warming rate is expected to be about twice that of global mean (Zhang et al, 2019, Stadnyk and. Certain oceanic processes within Hudson Bay itself, such as summer sea ice coverage, are particularly sensitive to temperature and show a declining trend in many oceans surrounding Canada over 1968-2016 (Derksen et al, 2019). Analysis of global climate model (GCM) sea surface temperature (SST) in Greenan et al (2019) suggests that future projected increases in summer SST exceed winter SST, largely due to the absence of ice cover in summer, which allows for greater heat gains.…”

Section: Introductionmentioning

confidence: 99%

Representing climate evolution in ensembles of GCM simulations for the Hudson Bay System

Braun

Thiombiano

Vieira

et al. 2021

Elementa: Science of the Anthropocene

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Climate impact studies often require a reduction of the ensembles of opportunity from the Coupled Model Intercomparison Project when the simulations are used to drive impact models. An impact model’s nature limits the number of feasible realizations based on complexity and computational requirements or capacities. For the purpose of driving a hydrological model and an ocean model in the BaySys research program, two hierarchical, differently sized simulation ensembles were produced to represent climate evolution for the region of the Hudson Bay Drainage Basin. We compare a 19-member ensemble to a 5-member subset to demonstrate comparability of the driving climate used to produce model results. Ten extreme climate indicators and their changes are compared for the full study region and seven sub regions, on an annual and seasonal basis and for two future climate horizons. Results indicate stronger warming in the North and for cold temperatures and an East-West gradient in precipitation with larger absolute increases to the East and South of the Hudson Bay. Generally, the smaller ensemble is sufficient to adequately reproduce the mean and spread in the indicators found for the larger ensemble. The analysis of extreme climate indicators ensures that the tails of the distribution of temperature and precipitation are addressed. We conclude that joint analysis at the interface of the hydrological and ocean model domains are not limited by the application of differently sized climate simulation ensembles as driving input for the two different modeling exercises of the BaySys project environmental studies, yet acknowledging that impact model output may be dependent on other factors.

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Changes in snow, ice, and permafrost across Canada

Cited by 37 publications

References 0 publications

Kelp in the Eastern Canadian Arctic: Current and Future Predictions of Habitat Suitability and Cover

Kelp in the Eastern Canadian Arctic: Current and Future Predictions of Habitat Suitability and Cover

Climatic Controls on Mean and Extreme Streamflow Changes Across the Permafrost Region of Canada

Representing climate evolution in ensembles of GCM simulations for the Hudson Bay System

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