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  • Source Publication: Journal of Climate, early online access, doi: 10.1175/JCLI-D-18- 0461.1. Authors: Seiler, C., Publication Date: Apr 2019

    Extratropical cyclones (ETCs) are known to intensify due to three vertically interacting positive potential vorticity perturbations that are associated with potential temperature anomalies close to the surface (θB), condensational heating in the lower-level atmosphere (qsat), and stratospheric intrusion in the upper-level atmosphere (qtr). This study presents the first climatological assessment of how much each of these three mechanisms contributes to the intensity of extreme ETCs. Using relative vorticity at 850 hPa as a measure of ETC intensity, results show that in about half of all cases the largest contributions during maximum ETC intensity are associated with qsat (53% of all ETCs), followed by qtr (36%) and θB (11%). The relative frequency of storms that are dominated by qsat is higher 1) during warmer months (61% of all ETCs during warmer months) compared to colder months (50%) and 2) in the Pacific (56% of all ETCs in the Pacific) compared to the Atlantic (46%). The relative frequency of ETCs that are dominated by θB is larger 1) during colder months (13%) compared to warmer months (3%), 2) in the Atlantic (15%) compared to the Pacific (8%), and 3) in western (11%–20%) compared to eastern ocean basins (4%–9%). These findings are based on piecewise potential vorticity inversion conducted for intense ETCs that occurred from 1980 to 2016 in the Northern Hemisphere (3273 events; top 7%). The results may serve as a baseline for evaluating ETC biases and uncertainties in global climate models.

  • Source Publication: Journal of Advances in Modeling Earth Systems, doi: 10.1029/2018MS001532. Authors: He, Y., N.A.McFarlane, and A.H. Monahan Publication Date: Mar 2019

    A new semi‐empirical turbulence parameterization is presented. Key features of the scheme include representation of turbulent diffusivities in terms of the turbulent kinetic energy (TKE) which is determined by solving a quasi‐equilibrium form of the equation representing the TKE budget. The new parameterization is innovative in the treatment of turbulent transfer in stably stratified conditions and the representation of non‐local contributions to the vertical transport of heat, moisture, and scalar prognostic variables in convectively active boundary layers. A key element in the modeling of turbulence in stably stratified conditions is the formulation of the turbulent Prandtl number based on results of recently published theoretical, modeling and observational studies of stratified turbulence in the atmospheric boundary layer. The new parameterization has been implemented in the CanAM4 single column model. Its performance in comparison with that of the operational CanAM4 turbulence parameterization is documented in terms of selected results from case studies for clear sky conditions based on meteorological observations from the KNMI‐mast at Cabauw, Netherlands, and the DYCOMS II case study of stratocumulus‐topped marine boundary layers. The performance of the new and operational schemes is qualitatively similar in clear sky conditions in both convective and stable boundary layer regimes. However, they perform differently for the extended simulations for the DYCOM‐II case study. The new scheme maintains an elevated stratocumulus layer throughout a 30‐hour simulation but peak liquid water contents are larger than LES simulations.

  • Source Publication: Hydrology and Earth System Sciences, 23, 811-828, doi:10.5194/hess-23-811-2019. Authors: Islam, S. Ul, C.L. Curry, S.J. Dery and F.W. Zwiers Publication Date: Feb 2019

    In response to ongoing and future-projected global warming, mid-latitude, nival river basins are expected to transition from a snowmelt-dominated flow regime to a nival–pluvial one with an earlier spring freshet of reduced magnitude. There is, however, a rich variation in responses that depends on factors such as the topographic complexity of the basin and the strength of maritime influences. We illustrate the potential effects of a strong maritime influence by studying future changes in cold season flow variability in the Fraser River Basin (FRB) of British Columbia, a large extratropical watershed extending from the Rocky Mountains to the Pacific Coast. We use a process-based hydrological model driven by an ensemble of 21 statistically downscaled simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), following the Representative Concentration Pathway 8.5 (RCP 8.5).

    Warming under RCP 8.5 leads to reduced winter snowfall, shortening the average snow accumulation season by about one-third. Despite this, large increases in cold season rainfall lead to unprecedented cold season peak flows and increased overall runoff variability in the VIC simulations. Increased cold season rainfall is shown to be the dominant climatic driver in the Coast Mountains, contributing 60 % to mean cold season runoff changes in the 2080s. Cold season runoff at the outlet of the basin increases by 70 % by the 2080s, and its interannual variability more than doubles when compared to the 1990s, suggesting substantial challenges for operational flow forecasting in the region. Furthermore, almost half of the basin (45 %) transitions from a snow-dominated runoff regime in the 1990s to a primarily rain-dominated regime in the 2080s, according to a snowmelt pulse detection algorithm. While these projections are consistent with the anticipated transition from a nival to a nival–pluvial hydrologic regime, the marked increase in FRB cold season runoff is likely linked to more frequent landfalling atmospheric rivers in the region projected in the CMIP5 models, providing insights for other maritime-influenced extratropical basins.

  • Source Publication: Scientific Data, 6, 180299, doi:10.1038/sdata.2018.299 Authors: Werner, A.T., M.S. Schnorbus, R.R. Shrestha, A.J. Cannon, F.W. Zwiers, G. Dayon and F. Anslow, Publication Date: Jan 2019

    We describe a spatially contiguous, temporally consistent high-resolution gridded daily meteorological dataset for northwestern North America. This >4 million km2 region has high topographic relief, seasonal snowpack, permafrost and glaciers, crosses multiple jurisdictional boundaries and contains the entire Yukon, Mackenzie, Saskatchewan, Fraser and Columbia drainages. We interpolate daily station data to 1/16° spatial resolution using a high-resolution monthly 1971–2000 climatology as a predictor in a thin-plate spline interpolating algorithm. Only temporally consistent climate stations with at least 40 years of record are included. Our approach is designed to produce a dataset well suited for driving hydrological models and training statistical downscaling schemes. We compare our results to two commonly used datasets and show improved performance for climate means, extremes and variability. When used to drive a hydrologic model, our dataset also outperforms these datasets for runoff ratios and streamflow trends in several, high elevation, sub-basins of the Fraser River.

  • Source Publication: Nature Scientific Data, 6, 180299, doi:10.1038/sdata.2018.299. Authors: Werner, A.T., R.R. Shrestha, A.J. Cannon, M.S. Schnorbus, F.W. Zwiers, G. Dayon and F. Anslow Publication Date: Jan 2019

    We describe a spatially contiguous, temporally consistent high-resolution gridded daily meteorological dataset for northwestern North America. This >4 million km2 region has high topographic relief, seasonal snowpack, permafrost and glaciers, crosses multiple jurisdictional boundaries and contains the entire Yukon, Mackenzie, Saskatchewan, Fraser and Columbia drainages. We interpolate daily station data to 1/16° spatial resolution using a high-resolution monthly 1971–2000 climatology as a predictor in a thin-plate spline interpolating algorithm. Only temporally consistent climate stations with at least 40 years of record are included. Our approach is designed to produce a dataset well suited for driving hydrological models and training statistical downscaling schemes. We compare our results to two commonly used datasets and show improved performance for climate means, extremes and variability. When used to drive a hydrologic model, our dataset also outperforms these datasets for runoff ratios and streamflow trends in several, high elevation, sub-basins of the Fraser River.

  • Source Publication: Geophysical Research Letters, 46, 1651-1661, doi:10.1029/2018GL080720. Authors: Curry, C.L., S.U. Islam, F.W. Zwiers and S.J. Dery Publication Date: Jan 2019

    Snow‐dominated watersheds are bellwethers of climate change. Hydroclimate projections in such basins often find reductions in annual peak runoff due to decreased snowpack under global warming. British Columbia's Fraser River Basin (FRB) is a large, nival basin with exposure to moisture‐laden atmospheric rivers originating in the Pacific Ocean. Landfalling atmospheric rivers over the region in winter are projected to increase in both strength and frequency in Coupled Model Intercomparison Project Phase 5 climate models. We investigate future changes in hydrology and annual peak daily streamflow in the FRB using a hydrologic model driven by a bias‐corrected Coupled Model Intercomparison Project Phase 5 ensemble. Under Representative Concentration Pathway (8.5), the FRB evolves toward a nival‐pluvial regime featuring an increasing association of extreme rainfall with annual peak daily flow, a doubling in cold season peak discharge, and a decrease in the return period of the largest historical flow, from a 1‐in‐200‐year to 1‐in‐50‐year event by the late 21st century.

  • Source Publication: Earth's Future, doi:10.1029/2018EF001001. Authors: Li, C., F.W. Zwiers, X. Zhang and G. Li Publication Date: Jan 2019

    Global warming is expected to increase the amount of atmospheric moisture, resulting in heavier extreme precipitation. Various studies have used the historical relationship between extreme precipitation and temperature (temperature scaling) to provide guidance about precipitation extremes in a future warmer climate. Here we assess how much information is required to robustly identify temperature scaling relationships, and whether these relationships are equally effective at different times in the future in estimating precipitation extremes everywhere across North America. Using a large ensemble of 35 North American regional climate simulations of the period 1951–2100, we show that individual climate simulations of length comparable to that of typical instrumental records are unable to constrain temperature scaling relationships well enough to reliably estimate future extremes of local precipitation accumulation for hourly to daily durations in the model's climate. Hence, temperature scaling relationships estimated from the limited historical observations are unlikely to be able to provide reliable guidance for future adaptation planning at local spatial scales. In contrast, well‐constrained temperature scaling relations based on multiple regional climate simulations do provide a feasible basis for accurately projecting precipitation extremes of hourly to daily durations in different future periods over more than 90% of the North American land area.

  • Source Publication: Hydrological Processes, doi: 10.1002/hyp.13321. Authors: Tsuruta, K., M.A. Hassan, S.D. Donner and Y. Alila, Publication Date: Jan 2019

    Future sediment dynamics may be affected by changing climates or hydrological regimes because of the close link between hydrology and sediment erosion, deposition, and transport. Previously, investigations of these potential changes have been constrained by a combination of limited observational data, hydrological drivers, and appropriate mechanistic models. Additionally, there is often ambiguity regarding how to disentangle the impacts of climate and hydrology from direct human factors such as reservoirs and land‐use change, which often exert more control over sediment dynamics. In this study, we utilize a recently developed, large‐scale, distributed, mechanistic sediment transport model to project future sediment erosion, deposition, and transportation within the Fraser River Basin in British Columbia, Canada—a basin with historical water flux and sediment load observations and limited anthropogenic influences upstream of its delta. The sediment model is driven by synthetic land‐surface hydrology derived from Scenarios A1B, A2, and B1 of the Special Report on Emissions Scenarios, which were provided by the Pacific Climate Impacts Consortium. Resulting simulations of water flux and sediment load from 1965 to 1994 are first validated against observational data then compared with future projections. Future projections show an overall increase in annual hillslope erosion and in‐channel transportation, a shift towards earlier spring peak erosion and transportation, and longer persistence of the sediment signal through the year. These shifts in timing and annual yield may have deleterious effects on spawning sockeye salmon and are insufficient to counteract future coastal retreat caused by sea‐level rise.

  • Source Publication: Earth's Future, doi:10.1029/2018EF001050. Authors: M.C. Kirchmeier‐Young N.P. Gillett F.W. Zwiers A.J. Cannon F.S. Anslow Publication Date: Dec 2018

    A record 1.2 million ha burned in British Columbia, Canada's extreme wildfire season of 2017. Key factors in this unprecedented event were the extreme warm and dry conditions that prevailed at the time, which are also reflected in extreme fire weather and behavior metrics. Using an event attribution method and a large ensemble of regional climate model simulations, we show that the risk factors affecting the event, and the area burned itself, were made substantially greater by anthropogenic climate change. We show over 95% of the probability for the observed maximum temperature anomalies is due to anthropogenic factors, that the event's high fire weather/behavior metrics were made 2–4 times more likely, and that anthropogenic climate change increased the area burned by a factor of 7–11. This profound influence of climate change on forest fire extremes in British Columbia, which is likely reflected in other regions and expected to intensify in the future, will require increasing attention in forest management, public health, and infrastructure.

  • Source Publication: Earth's Future, doi:10.1029/2018EF001001. Authors: Li, C., F. Zwiers X. Zhang and G. Li Publication Date: Dec 2018

    Global warming is expected to increase the amount of atmospheric moisture, resulting in heavier extreme precipitation. Various studies have used the historical relationship between extreme precipitation and temperature (temperature scaling) to provide guidance about precipitation extremes in a future warmer climate. Here we assess how much information is required to robustly identify temperature scaling relationships, and whether these relationships are equally effective at different times in the future in estimating precipitation extremes everywhere across North America. Using a large ensemble of 35 North American regional climate simulations of the period 1951–2100, we show that individual climate simulations of length comparable to that of typical instrumental records are unable to constrain temperature scaling relationships well enough to reliably estimate future extremes of local precipitation accumulation for hourly to daily durations in the model's climate. Hence, temperature scaling relationships estimated from the limited historical observations are unlikely to be able to provide reliable guidance for future adaptation planning at local spatial scales. In contrast, well‐constrained temperature scaling relations based on multiple regional climate simulations do provide a feasible basis for accurately projecting precipitation extremes of hourly to daily durations in different future periods over more than 90% of the North American land area.

  • Authors: Zwiers, F., C. Li, X. Zhang and G. Li Publication Date: Dec 2018

    Poster presented at 2018 AGU Fall Meeting, Dec. 10th-14th in Washington, DC.

  • Source Publication: Journal of Climate, 31, 19, 7771-7787, doi:10.1175/JCLI-D-17-0552.1 Authors: Mueller, B.L., N.P. Gillett, A. Monahan and F.W. Zwiers Publication Date: Sep 2018

    The paper presents results from a climate change detection and attribution study on the decline of Arctic sea ice extent in September for the 1953–2012 period. For this period three independently derived observational datasets and simulations from multiple climate models are available to attribute observed changes in the sea ice extent to known climate forcings. Here we direct our attention to the combined cooling effect from other anthropogenic forcing agents (mainly aerosols), which has potentially masked a fraction of greenhouse gas–induced Arctic sea ice decline. The presented detection and attribution framework consists of a regression model, namely, regularized optimal fingerprinting, where observations are regressed onto model-simulated climate response patterns (i.e., fingerprints). We show that fingerprints from greenhouse gas, natural, and other anthropogenic forcings are detected in the three observed records of Arctic sea ice extent. Beyond that, our findings indicate that for the 1953–2012 period roughly 23% of the greenhouse gas–induced negative sea ice trend has been offset by a weak positive sea ice trend attributable to other anthropogenic forcing. We show that our detection and attribution results remain robust in the presence of emerging nonstationary internal climate variability acting upon sea ice using a perfect model experiment and data from two large ensembles of climate simulations.

  • Source Publication: Journal of Geophysical Research: Earth Surface, doi: 10.1029/2017JF004578. Authors: Tsuruta, K., M.A. Hassan, S.D. Donner and Y. Alila Publication Date: Sep 2018

    Modeling sediment transport through large basins presents a challenging problem. The relation between water flux and sediment load is complex, and substantial erosion and transport can occur over small spatial and temporal scales. Analysis of large‐scale basins often relies on lumped empirical models that do not consider spatial or subannual variability. In this study, we adapt a small‐scale, mechanistic, distributed suspended sediment transport model for application to large basins. The model is integrated into the Terrestrial Hydrology Model with Biochemistry to make use of the Terrestrial Hydrology Model with Biochemistry's dynamic water routing. The coupled model is applied to the 230,000‐km2 Fraser River Basin in British Columbia, Canada, using climatic and hydrological inputs provided by a historical run of the Variable Infiltration Capacity model. Hourly simulations are aggregated into monthly and long‐term averages which are compared against observations. Simulated long‐term lake sedimentation values are within an order of magnitude of observations, and monthly load simulations have an average R2 of 0.70 across the five study stations with available data. Model results indicate that sediment loads from tributaries do not heavily influence dynamics along the main stem and suggest the importance of network connectivity. Sensitivity analysis indicates that models may benefit from characterizing bed load irrespective of its contribution to total sediment load. Historical simulations over the 1965–2004 period reveal important changes in sediment dynamics that could not be captured with a lumped model, including a decrease in basin sediment load interannual variability driven by changes in runoff and load variability within a key subbasin.

  • Source Publication: Climate Dynamics, doi:10.1007/s00382-018-4375-0. Authors: Teufel, B., L. Sushama, O. Huzly, G.T. Diro, D.I. Jeong, K. Winger, C. Garnaud, R. de Elia, F.W. Zwiers, J.R. Gyakum, D. Matthews and V.-T.-V. Nguyen Publication Date: Sep 2018

    Significant flood damage occurred near Montreal in May 2017, as flow from the upstream Ottawa River basin (ORB) reached its highest levels in over 50 years. Analysis of observations and experiments performed with the fifth generation Canadian Regional Climate Model (CRCM5) show that much above average April precipitation over the ORB, a large fraction of which fell as rain on an existing snowpack, increased streamflow to near record-high levels. Subsequently, two heavy rainfall events affected the ORB in the first week of May, ultimately resulting in flooding. This heavy precipitation during April and May was linked to large-scale atmospheric features. Results from sensitivity experiments with CRCM5 suggest that the mass and distribution of the snowpack have a major influence on spring streamflow in the ORB. Furthermore, the importance of using an appropriate frozen soil parameterization when modelling spring streamflows in cold regions was confirmed. Event attribution using CRCM5 showed that events such as the heavy April 2017 precipitation accumulation over the ORB are between two and three times as likely to occur in the present-day climate as in the pre-industrial climate. This increase in the risk of heavy precipitation is linked to increased atmospheric moisture due to warmer temperatures in the present-day climate, a direct consequence of anthropogenic emissions, rather than changes in rain-generating mechanisms or circulation patterns. Warmer temperatures in the present-day climate also reduce early-spring snowpack in the ORB, offsetting the increase in rainfall and resulting in no discernible change to the likelihood of extreme surface runoff.

  • Source Publication: Earth's Future, 6, 5, 704-715, doi:10.1002/2018EF000813. Authors: Kharin, V.V., G.M. Flato, X. Zhang, N.P. Gillett, F.W. Zwiers and K. Anderson Publication Date: Sep 2018

    Parties to the United Nations Framework Convention on Climate Change have agreed to hold the “increase in global average temperature to well below 2°C above preindustrial levels and to pursue efforts to limit the temperature increase to 1.5°C.” Comparison of the costs and benefits for different warming limits requires an understanding of how risks vary between warming limits. As changes in risk are often associated with changes in exposure due to projected changes in local or regional climate extremes, we analyze differences in the risks of extreme daily temperatures and extreme daily precipitation amounts under different warming limits. We show that global warming of 2°C would result in substantially larger changes in the probabilities of the extreme events than global warming of 1.5°C. For example, over the global land area, the probability of a warm extreme that occurs once every 20 years on average in the current climate is projected to increase 130% and 340% at the 1.5°C and 2.0°C warming levels, respectively (median values). Moreover, the relative changes in probability are larger for rarer, more extreme events, implying that risk assessments need to carefully consider the extreme event thresholds at which vulnerabilities occur.

  • Source Publication: Atmospheric Chemistry and Physics, 18, 10133-10156, doi:10.5194/acp-18-10133-2018. Authors: Ji, D., S. Fang, C.L. Curry, H. Kashimura, S. Watanabe, J.N.S. Cole, A. Lenton, H. Muri, B. Kravitz and J.C. Moore. Publication Date: Jul 2018

    We examine extreme temperature and precipitation under two potential geoengineering methods forming part of the Geoengineering Model Intercomparison Project (GeoMIP). The solar dimming experiment G1 is designed to completely offset the global mean radiative forcing due to a CO2-quadrupling experiment (abrupt4 × CO2), while in GeoMIP experiment G4, the radiative forcing due to the representative concentration pathway 4.5 (RCP4.5) scenario is partly offset by a simulated layer of aerosols in the stratosphere. Both G1 and G4 geoengineering simulations lead to lower minimum temperatures (TNn) at higher latitudes and on land, primarily through feedback effects involving high-latitude processes such as snow cover, sea ice and soil moisture. There is larger cooling of TNn and maximum temperatures (TXx) over land compared with oceans, and the land–sea cooling contrast is larger for TXx than TNn. Maximum 5-day precipitation (Rx5day) increases over subtropical oceans, whereas warm spells (WSDI) decrease markedly in the tropics, and the number of consecutive dry days (CDDs) decreases in most deserts. The precipitation during the tropical cyclone (hurricane) seasons becomes less intense, whilst the remainder of the year becomes wetter. Stratospheric aerosol injection is more effective than solar dimming in moderating extreme precipitation (and flooding). Despite the magnitude of the radiative forcing applied in G1 being ∼ 7.7 times larger than in G4 and despite differences in the aerosol chemistry and transport schemes amongst the models, the two types of geoengineering show similar spatial patterns in normalized differences in extreme temperatures changes. Large differences mainly occur at northern high latitudes, where stratospheric aerosol injection more effectively reduces TNn and TXx. While the pattern of normalized differences in extreme precipitation is more complex than that of extreme temperatures, generally stratospheric aerosol injection is more effective in reducing tropical Rx5day, while solar dimming is more effective over extra-tropical regions.

  • Source Publication: Atmospheric Chemistry and Physics, 18, 10133-10156, doi:10.5194/acp-18-10133-2018. Authors: Ji, D., S. Fang, C.L. Curry, H. Kashimura, S. Watanabe, J.N.S. Cole, A. Lenton, H. Muri, B. Kravitz and J.C. Moore Publication Date: Jul 2018

    We examine extreme temperature and precipitation under two potential geoengineering methods forming part of the Geoengineering Model Intercomparison Project (GeoMIP). The solar dimming experiment G1 is designed to completely offset the global mean radiative forcing due to a CO2-quadrupling experiment (abrupt4 × CO2), while in GeoMIP experiment G4, the radiative forcing due to the representative concentration pathway 4.5 (RCP4.5) scenario is partly offset by a simulated layer of aerosols in the stratosphere. Both G1 and G4 geoengineering simulations lead to lower minimum temperatures (TNn) at higher latitudes and on land, primarily through feedback effects involving high-latitude processes such as snow cover, sea ice and soil moisture. There is larger cooling of TNn and maximum temperatures (TXx) over land compared with oceans, and the land–sea cooling contrast is larger for TXx than TNn. Maximum 5-day precipitation (Rx5day) increases over subtropical oceans, whereas warm spells (WSDI) decrease markedly in the tropics, and the number of consecutive dry days (CDDs) decreases in most deserts. The precipitation during the tropical cyclone (hurricane) seasons becomes less intense, whilst the remainder of the year becomes wetter. Stratospheric aerosol injection is more effective than solar dimming in moderating extreme precipitation (and flooding). Despite the magnitude of the radiative forcing applied in G1 being ∼ 7.7 times larger than in G4 and despite differences in the aerosol chemistry and transport schemes amongst the models, the two types of geoengineering show similar spatial patterns in normalized differences in extreme temperatures changes. Large differences mainly occur at northern high latitudes, where stratospheric aerosol injection more effectively reduces TNn and TXx. While the pattern of normalized differences in extreme precipitation is more complex than that of extreme temperatures, generally stratospheric aerosol injection is more effective in reducing tropical Rx5day, while solar dimming is more effective over extra-tropical regions.

  • Source Publication: Stochastic Environmental Research and Risk Assessment</em>, <b>32</b>, 10, 2821–2836, doi:/10.1007/s00477-018-1564-7. Authors: Ouali, D. and A.J. Cannon Publication Date: May 2018

    Intensity–duration–frequency (IDF) curves of extreme rainfall are used extensively in infrastructure design and water resources management. In this study, a novel regional framework based on quantile regression (QR) is used to estimate rainfall IDF curves at ungauged locations. Unlike standard regional approaches, such as index-storm and at-site ordinary least-squares regression, which are dependent on parametric distributional assumptions, the non-parametric QR approach directly estimates rainfall quantiles as a function of physiographic characteristics. Linear and nonlinear methods are evaluated for both the regional delineation and IDF curve estimation steps. Specifically, delineation by canonical correlation analysis (CCA) and nonlinear CCA (NLCCA) is combined, in turn, with linear QR and nonlinear QR estimation in a regional modelling framework. An exhaustive comparative study is conducted between standard regional methods and the proposed QR framework at sites across Canada. Overall, the fully nonlinear QR framework, which uses NLCCA for delineation and nonlinear QR for estimation of IDF curves at ungauged sites, leads to the best results.

  • Source Publication: Climate Dynamics, doi:10.1007/s00382-018-4145-z. Authors: Wan, H., X. Zhang and F. Zwiers Publication Date: May 2018

    Canada has experienced some of the most rapid warming on Earth over the past few decades with a warming rate about twice that of the global mean temperature since 1948. Long-term warming is observed in Canada’s annual, winter and summer mean temperatures, and in the annual coldest and hottest daytime and nighttime temperatures. The causes of these changes are assessed by comparing observed changes with climate model simulated responses to anthropogenic and natural (solar and volcanic) external forcings. Most of the observed warming of 1.7 °C increase in annual mean temperature during 1948–2012 [90% confidence interval (1.1°, 2.2 °C)] can only be explained by external forcing on the climate system, with anthropogenic influence being the dominant factor. It is estimated that anthropogenic forcing has contributed 1.0 °C (0.6°, 1.5 °C) and natural external forcing has contributed 0.2 °C (0.1°, 0.3 °C) to the observed warming. Up to 0.5 °C of the observed warming trend may be associated with low frequency variability of the climate such as that represented by the Pacific decadal oscillation (PDO) and North Atlantic oscillation (NAO). Overall, the influence of both anthropogenic and natural external forcing is clearly evident in Canada-wide mean and extreme temperatures, and can also be detected regionally over much of the country.

  • Source Publication: Comptes Rendus Geoscience, 350, 4, 41-153, https://doi.org/10.1016/j.crte.2018.03.001 Authors: Dayon G., J. Boé, É. Martin and J. Gailhard Publication Date: May 2018

    This study deals with the evolution of the hydrological cycle over France during the 21st century. A large multi-member, multi-scenario, and multi-model ensemble of climate projections is downscaled with a new statistical method to drive a physically-based hydrological model with recent improvements. For a business-as-usual scenario, annual precipitation changes generally remain small, except over southern France, where decreases close to 20% are projected. Annual streamflows roughly decrease by 10% (±20%) on the Seine, by 20% (±20%) on the Loire, by 20% (±15%) on the Rhone and by 40% (±15%) on the Garonne. Attenuation measures, as implied by the other scenarios analyzed, lead to less severe changes. However, even with a scenario generally compatible with a limitation of global warming to two degrees, some notable impacts may still occur, with for example a decrease in summer river flows close to 25% for the Garonne.

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