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  • Source Publication: 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: 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.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Dec 2018

    This is the Pacific Climate Impacts Consortium's 2017-2018 Corporate Report.

  • 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.

  • Authors: Murdock, T. Publication Date: Nov 2018

    Presentation for Getting Climate Ready – Adaptation Tools for Northwest Communities, in Terrace, BC on 29 November 2018.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Oct 2018

    This newsletter discusses the IPCC's Special Report on a global warming of 1.5 °C, the summer of 2018 in BC, supporting agriculture in the Fraser Valley, PCIC's new Seasonal Maps Portal, Columbia Basin Trust workshops and Dr. Jana Sillmann's visit. The newsletter also has a staff spotlight on Matthew Benstead, covers talks delivered by Drs. Jana Sillmann and Whitney Huang, the most recent PCIC Science Brief on Paris Accord emissions and temperature limits, as well as PCIC publications and staff changes.

  • 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.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Aug 2018

    The 2015 Paris Climate Accord aims to limit global warming to at most 2°C and ideally 1.5°C relative to the preindustrial climate, to limit the impacts of anthropogenic climate change. In this Science Brief, we discuss greenhouse gas emissions budgets and pathways consistent with these warming limits.

    Three recent papers in Nature Climate Change examine different aspects of these budgets and pathways:

    Tokarska and Gillett (2018) use global climate model projections to calculate a new carbon budget for future emissions, relative to the 2006-2015 period, that is consistent with keeping warming to 1.5°C. They find a median remaining carbon budget of 208 billion tonnes from January 2016.

    Tanaka and O'Neill (2018) use an integrated assessment model to test whether the Paris temperature limits of 2°C and 1.5°C require zero greenhouse gas emissions, whether a zero net greenhouse emissions limit implies that the temperature limits will be met and what the effect of imposing both emissions and temperature limits are. Their results suggest that meeting the  temperature limits doesn't require reducing net greenhouse gas emissions to zero, that reducing emissions to zero doesn't necessarily result in keeping temperatures under the Paris temperature limits by the end of the century, and that the effect of imposing both temperature and emissions limits is that temperatures decline after meeting the initial temperature limit.

    Van Vuuren et al. also use an integrated assessment model, to develop alternative emissions scenarios that examine how the need for negative emissions may be reduced through implementing other strategies, such as making large-scale lifestyle changes, shifting to renewable energy and switching to more efficient technologies for the production of energy and materials. They find that these strategies can reduce to a small degree, but not eliminate, the need for negative emissions. They also find that these measures have co-benefits such as helping to meet other United Nations sustainability goals.

  • 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.

  • Authors: Anslow, F.S., S. Tam, J. Lussier Publication Date: Jun 2018

    Presented by Faron Anslow at the Canadian Meteorological and Oceanographic Society’s 52nd Congress.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Jun 2018

    The June 2018 PCIC Update includes the following stories: New on the Data Portal from the Hydrologic Impacts Theme: Gridded Meteorological Datasets, Updated Guidance for the Engineering Community, Climate Data for the Northwest Territories and Yukon, Agricultural Data Network Analysis, Renewed Climate Related Monitoring Program Agreement, Regional Assessment for Northeastern BC, Fraser Valley Extremes, New Projects, Staff Profile on Stephen Sobie and the Pacific Climate Seminar Series, as well as staff changes and publications.

  • 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, 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.

  • Source Publication: Climatic Change, 148, 1-2, 249-263, doi: 10.1007/s10584-018-2199-x Authors: Zhang, X., G. Li, A. Cannon, T. Murdock, S. Sobie, F.W. Zwiers, K. Anderson and B. Qian Publication Date: May 2018

    This study evaluates regional-scale projections of climate indices that are relevant to climate change impacts in Canada. We consider indices of relevance to different sectors including those that describe heat conditions for different crop types, temperature threshold exceedances relevant for human beings and ecological ecosystems such as the number of days temperatures are above certain thresholds, utility relevant indices that indicate levels of energy demand for cooling or heating, and indices that represent precipitation conditions. Results are based on an ensemble of high-resolution statistically downscaled climate change projections from 24 global climate models (GCMs) under the RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. The statistical downscaling approach includes a bias-correction procedure, resulting in more realistic indices than those computed from the original GCM data. We find that the level of projected changes in the indices scales well with the projected increase in the global mean temperature and is insensitive to the emission scenarios. At the global warming level about 2.1 °C above pre-industrial (corresponding to the multi-model ensemble mean for 2031–2050 under the RCP8.5 scenario), there is almost complete model agreement on the sign of projected changes in temperature indices for every region in Canada. This includes projected increases in extreme high temperatures and cooling demand, growing season length, and decrease in heating demand. Models project much larger changes in temperature indices at the higher 4.5 °C global warming level (corresponding to 2081–2100 under the RCP8.5 scenario). Models also project an increase in total precipitation, in the frequency and intensity of precipitation, and in extreme precipitation. Uncertainty is high in precipitation projections, with the result that models do not fully agree on the sign of changes in most regions even at the 4.5 °C global warming level.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: May 2018

    In this Science Brief we consider two aspects of climate change that are of direct interest to Canadians—the warming of the Canadian climate and changes in high water events that affect our coasts. Two articles recently published in the peer reviewed literature discuss the contribution of waves to coastal sea level rise and the roles of human and natural influences in Canada's warming climate.

    Publishing in Nature Climate Change, Melet et al. (2018) study the effect of atmospheric surges, tides and waves on total water level rise at the coast. Using a mixture of model output and observations from the 1993-2015 period, they find that the size of wave contributions from several processes varies regionally. These processes can strengthen, offset or, as is the case for locations on the west coast of North America, entirely dominate sea level rise due to thermal expansion and land ice melting. In their article in Climate Dynamics,

    Wan, Zhang and Zwiers (2018) examine the roles that human and natural influences have played in Canada's warming climate from 1948 to 2012, both nationally and regionally. Comparing observations to climate model simulations, they find that about 1.0°C of the 1.7°C warming that Canada experienced over that period can be attributed to anthropogenic influences, while natural external influences (the sun and volcanic eruptions) contributed only about 0.2°C. For the region comprised of British Columbia and Yukon, which has experienced a 1.6°C warming, they find that about 0.8°C is attributable to anthropogenic influences and about 0.2°C to natural influences. They also find that, in most cases, anthropogenic influences can be detected in changes to the annual hottest and coldest daytime and nighttime temperatures for Canada as a whole and at the regional level. Natural influences can generally only be detected in changes to the coldest winter nighttime and daytime temperatures, both nationally and regionally.