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  • Authors: Christian Seiler, Francis W. Zwiers and Kevin I. Hodges Publication Date: Jun 2016
  • Authors: T. Q. MURDOCK, A. J. CANNON, AND S.R. SOBIE Publication Date: Jun 2016

    The need for future projections of extremes is growing, particularly as users planning to adapt to climate change continue to experience record-breaking events (Figure 1). Decision-making demands that such projections possess high spatial resolution. Downscaling has been carried out for Canada by the Pacic Climate Impacts Consortium for the newest Global Climate Model (GCM) and Regional Climate Model (RCM) projections.

  • Authors: G. Bürger, T. Q. Murdock, A. T. Werner, S. R. Sobie Publication Date: Jun 2016

    Empirical downscaling is based in a statistical analysis of present climatic conditions for an area, usually recorded by a number of variables from weather stations. The result of this analysis is a set of recipes (algorithms) and parameters from which the present climate, or at least some of its crucial aspects, such as extreme temperature values, can be recovered.

  • Authors: S.R. Sobie, A.J. Cannon, T.Q. Murdock Publication Date: Jun 2016

    For terrestrial British Columbia, precipitation averages and extremes can be simulated more accurately within individual regions by using gridded downscaling to increase the resolution of regional climate models. In locations where the difference between observations and RCMs is large, bias correction tends to inflate the magnitude of projected extremes. Differences in projections between the RCMs and downscaled simulations can be large enough to affect the PIEVC Risk Assessment process, leading to higher risk values. Future work will focus on correcting the inflation of extremes in the downscaling method and extending the analysis to additional regions.

  • Authors: S.R. Sobie, A.J. Cannon, T.Q. Murdock Publication Date: Jun 2016

    For terrestrial British Columbia, precipitation averages and extremes can be simulated more accurately within individual regions by using gridded downscaling to increase the resolution of both global and regional climate models. In locations where the difference between observations and model simulations is large, bias correction tends to inflate the magnitude of high resolution projected extremes. The effect is minimal for average indices but is statistically significant in a subset of models for projected changes of 10 and 20-year return periods. Future work will focus on correcting the inflation of extremes in the downscaling method and extending the analysis to additional regions.

  • Authors: T. Q. MURDOCK, S.R. SOBIE, A. J. CANNON, AND F.W. ZWIERS Publication Date: Jun 2016

    The main effect of statistical downscaling on projected change in extremes is due to correction of historical bias. is does not necessarily mean downscaling is adding value. e coarse scale projected change in annual precipitation is retained but heavy precipitation (R95ptot) is somewhat amplied and extreme precipitation change (RP10) is considerably altered. Since it is these extremes that are needed for planning, further work is needed. In next steps we will compare results at a coarser scale (e.g. 5°) to reduce the inuence of bias correction on results and also separate into small and large scale explicitly as in Di Luca et al. (2013). Finally, we plan to compare projected changes from RCMs to that of their driving models in the same ways. Statistical downscaling methods that are explicitly designed to preserve coarse scale projected changes including extremes would be a welcome development for regional decision-making.

  • Source Publication: Climate Dynamics, doi:0.1007/s00382-016-3239-8 Authors: Teufel, B., G.T. Diro, K. Whan, S.M. Milrad, D.I. Jeong, A. Ganji, O. Huziy, K. Winger, E. Montero, J.R. Gyakum, R. de Elia, F.W. Zwiers and L. Sushama Publication Date: Jun 2016

    During 19–21 June 2013 a heavy precipitation event affected southern Alberta and adjoining regions, leading to severe flood damage in numerous communities and resulting in the costliest natural disaster in Canadian history. This flood was caused by a combination of meteorological and hydrological factors, which are investigated from weather and climate perspectives with the fifth generation Canadian Regional Climate Model. Results show that the contribution of orographic ascent to precipitation was important, exceeding 30 % over the foothills of the Rocky Mountains. Another contributing factor was evapotranspiration from the land surface, which is found to have acted as an important moisture source and was likely enhanced by antecedent rainfall that increased soil moisture over the northern Great Plains. Event attribution analysis suggests that human induced greenhouse gas increases may also have contributed by causing evapotranspiration rates to be higher than they would have been under pre-industrial conditions. Frozen and snow-covered soils at high elevations are likely to have played an important role in generating record streamflows. Results point to a doubling of surface runoff due to the frozen conditions, while 25 % of the modelled runoff originated from snowmelt. The estimated return time of the 3-day precipitation event exceeds 50 years over a large region, and an increase in the occurrence of similar extreme precipitation events is projected by the end of the 21st century. Event attribution analysis suggests that greenhouse gas increases may have increased 1-day and 3-day return levels of May–June precipitation with respect to pre-industrial climate conditions. However, no anthropogenic influence can be detected for 1-day and 3-day surface runoff, as increases in extreme precipitation in the present-day climate are offset by decreased snow cover and lower frozen water content in soils during the May–June transition months, compared to pre-industrial climate.

  • Authors: Rajesh R. Shrestha, Alex J. Cannon, Markus A. Schnorbus and Francis W. Zwiers Publication Date: Jun 2016

    Historically high extreme streamflow on the lower Fraser River has the potential to cause significant damage due the high concentration of infrastructure and human activity in the region. Using a combination of process-based and statistical modelling, we project that small (e.g. 2-20 year return period) extreme streamflow events will decrease in intensity, that the intensity of intermediate events (e.g. 40-60 year return period) will remain essentially unchanged, and that events of historic intensity (e.g. 100-200 year return period) will intensify modestly. [Extreme streamflow on the Fraser typically occurs in late spring/ early summer and is dependent on snow storage in the basin. Projected increases in winter precipitation would, all else being equal, increase the snow storage. Warming, however, tends to moderate this impact by reducing the fraction of winter precipitation stored as snow and shortening the period of snow storage]. The analysis in this paper is performed using an extreme value analysis technique that allows for nonstationarity in annual extreme streamflow by relating extreme streamflow with antecedent winter and spring precipitation and temperature. The study uses an extensive suite of existing simulations with the Variable Infiltration Capacity (VIC) hydrologic model driven by Coupled Model Intercomparison Project Phase 3 (CMIP3) climate simulations to train and evaluate the nonlinear and nonstationary Generalized Extreme Value conditional density network (GEVcdn) model of Fraser River streamflow extremes, and subsequently applies the model to project changes in Fraser River extremes under CMIP5 based climate change scenarios.

  • Authors: Krosby, M., Michalak, J., Robbins, T.O., Morgan, H., Norheim, R., Mauger, G., and T. Murdock Publication Date: Jun 2016

    Plant and animal species have historically used movement to adapt to changes in the Earth’s climate, shifting their ranges across landscapes to stay within climatically suitable habitat. Species are using this strategy to adapt to present day climate change, but the current rate of change is so rapid that many species will have difficulty keeping pace. In addition, human land use (e.g., highways, cities, farms) presents significant barriers to wildlife movement across today’s landscapes. For this reason, enhancing habitat connectivity – the ability of species to move across the landscape – is a leading strategy for helping wildlife respond to climate change. And yet, significant challenges remain in translating this high-level strategy into specific, on-the-ground actions. The Washington-British Columbia Transboundary Climate-Connectivity Project was initiated to help address these challenges. The region spanning the border of Washington state, USA, and British Columbia, Canada, faces increasing development pressure and limited transboundary coordination of land and wildlife management, both of which may threaten habitat connectivity and limit the potential for wildlife movement in response to change. In addition, the effects of climate change may further reduce habitat connectivity, and species may need novel types of habitat connectivity to complete adaptive range shifts. This project paired scientists and practitioners from both sides of the border to collaboratively identify potential climate impacts and adaptation actions for transboundary habitat connectivity, using a diverse suite of case study species, a vegetation system, and a region. Case study assessments revealed that climate change is likely to have significant implications for transboundary habitat connectivity. The adaptation actions identified to address potential impacts varied by case study, but fell into two general categories: those addressing potential climate impacts on existing habitat connectivity and those addressing novel habitat connectivity needs for climate-induced shifts in species ranges. In addition, project partners identified priority spatial locations for implementing these actions, as well as additional research needed to improve assessment of climate impacts and adaptation actions for habitat connectivity. The project resulted in a suite of products designed in collaboration with project partners to ensure their relevance and ease of application to decision-making. These products include this project overview report, which describes the project’s rationale, partnerships, approach, key findings, lessons learned, and remaining needs; detailed, stand-alone appendices for each case study, which describe the assessment process and key findings for each, and include all materials used in the assessment; and an interactive project gallery on the online mapping platform, Data Basin, which includes project reports and associated assessment materials, including interactive and downloadable connectivity and climate datasets. In addition, project participants emerged with enhanced capacity and a transboundary community of practice for addressing climate change and habitat connectivity in their decisionmaking. However, ongoing support for transboundary capacity building, collaboration, and research will be needed to promote the future resilience of our shared species and ecosystems.

  • Authors: T. Q. MURDOCK, D. NYLAND, S. SOBIE, AND J. WOLF Publication Date: Jun 2016

    Large scale infrastructure projects have long lifespans so planning them considers the long term. Highways in British Columbia are already experiencing extreme events beyond design capacity (see: photos at left). In 2008, the BC MOTI identied a pair of adaptation case studies, the results of which informed four streams of subsequent work (see timeline and other text boxes). A best practices summary of four years of adaptation work recommended MOTI produce a policy document. Following stakeholder and expert review, a ”Technical Circular” was published in 2015, requiring all projects for MOTI to consider climate. To assist with implementation, the Association of Professional Engineers and Geoscientists of BC is developing comprehensive guidelines for engineers to mainstream adaptation into their practice.

  • Authors: M. Kirchmeier-Young, F. Zwiers and N. Gillett Publication Date: May 2016

    An anthropogenic signal is detected in Arctic Sea Ice Extent (SIE) with all ensembles for the annual time series and also for September and March separately. All forcings (anthropogenic and natural, ALL) are necessary to explain the occurrence of SIE events more extreme than the current record minima (2012 for Sep., 2015 for Mar.), but not yet sufficient. If the current trends continue, ALL forcing will become sufficient for the occurrence of such events. Arctic SIE presents a counterexample to the statement that individual extreme events cannot be attributed to human influence.

  • Authors: Francis Zwiers Publication Date: May 2016

    Material includes: detection and attribution of long term changes and event attribution.

  • Source Publication: Climate Dynamics, doi:10.1007/s00382-016-3079-6 Authors: Ribes, A, F.W. Zwiers, Jean-Marc Azaïs and P. Naveau Publication Date: Apr 2016

    We propose here a new statistical approach to climate change detection and attribution that is based on additive decomposition and simple hypothesis testing. Most current statistical methods for detection and attribution rely on linear regression models where the observations are regressed onto expected response patterns to different external forcings. These methods do not use physical information provided by climate models regarding the expected response magnitudes to constrain the estimated responses to the forcings. Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly. As an alternative to this approach, our statistical model is only based on the additivity assumption; the proposed method does not regress observations onto expected response patterns. We introduce estimation and testing procedures based on likelihood maximization, and show that climate modelling uncertainty can easily be accounted for. Some discussion is provided on how to practically estimate the climate modelling uncertainty based on an ensemble of opportunity. Our approach is based on the “models are statistically indistinguishable from the truth” paradigm, where the difference between any given model and the truth has the same distribution as the difference between any pair of models, but other choices might also be considered. The properties of this approach are illustrated and discussed based on synthetic data. Lastly, the method is applied to the linear trend in global mean temperature over the period 1951–2010. Consistent with the last IPCC assessment report, we find that most of the observed warming over this period (+0.65 K) is attributable to anthropogenic forcings (+0.67 ±± 0.12 K, 90 % confidence range), with a very limited contribution from natural forcings (−0.01±0.02−0.01±0.02 K).

  • Authors: Francis Zwiers Publication Date: Apr 2016

    Topics include observations of precipitation extremes, detection and attribution work on precipitation extremes and projected changes to precipitation extremes. Key points include that the understanding of the impact of anthropogenic forcing on extremes remains limited, but it is safe to conclude that stationarity is dead. Projected changes are large and depend ont the emissions scenario, time horizon and model used. We do not yet know much about accumulation periods shorter than 1-day. If we could produce robust, complete future IDF
    curves, we still must determine what to design for.

  • Authors: Francis Zwiers Publication Date: Apr 2016

    Our understanding of the impact of anthropogenic forcing on extremes remains limited. While we have relatively high confidence for temperature extremes and some confidence in precipitation extremes, as yet we can say relatively little about storms, droughts and floods. We are often very limited by data and, while models and methods can be improved, improving historical data is much harder. To progress, we need further methodological development and improved process understanding. Event attribution is increasingly being undertaken, but there is still much work to do to develop methods and capabilities, understand the implications of framing choices, and develop objective evaluation techniques.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Apr 2016

    The City of Vancouver is warming. Global climate models project annual average temperature to increase by 1.7°C to 4.0°C, and indicate an average increase of 2.9°C between the 1971-2000 baseline and the 2050s. This fact sheet provides specific information intended to facilitate adaptation as the climate changes. All values in the summary are for the 2050s relative to the 1971-2000 baseline. Additional variables, seasons, projections for the 2080s, and maps were also produced and provided to the City of Vancouver.

  • Authors: T. Q. Murdock, S. R. Sobie, H. D. Eckstrand, E. Jackson Publication Date: Apr 2016

    Climate change projections have been provided in this report for Metro Vancouver and the Capital Regional District from several difference sources: Global Climate Models (GCMs) directly, high resolution elevation-corrected projections from GCMs, and Regional Climate Models. Historical climate information at selected stations of interest throughout the region is also provided for comparison.
    Projected annual warming by the 2050s (compared to 1961-1990) for the two regions is similar, according to a set of 30 commonly used Global Climate Models (GCMs). Projections are given for both the 2050s and 2080s periods. For the 2050s, the range of projected change in Metro Vancouver is +1.4°C to +2.8°C in summer, +0.8°C to +2.7°C in winter, -5% to +16% in winter precipitation, and -25% to +5% in summer precipitation. For the 2050s, the range of projected change in the Capital Regional District (CRD) is +1.3°C to +2.6°C in summer, +0.8°C to +2.4°C in winter, -5% to +17% in winter precipitation, and -30% to +1% in summer precipitation. Compared to the ranges, the projected differences between regions are minor.
    Maps of high resolution projections of change are provided for several variables of interest. Projections mid-century show changes in variables related to temperature: increased growing degree days, cooling degree days, and frost free period along with decreased heating degree days and precipitation as snow. The projected 2080s maps illustrate a future climate that does not resemble the present-day for most of these variables.
    Regional Climate Models projections are used to provide projections of changes in temperature, precipitation, and indices of extremes. Extreme temperatures so warm that in the past they would be exceeded on average once every ten years (corresponding to about 32°C to 35°C) are projected to occur on average over twice as often in future in Metro Vancouver and almost four times as often in future in the CRD.
    The amount of precipitation falling during very wet days is projected to increase by 21% in Metro Vancouver and 20% in CRD, while precipitation during extremely wet days is projected to increase by 28% in Metro Vancouver and 25% in CRD. More extreme precipitation events (with 3-hour duration) so intense than in the past they would be exceeded on average only once every 10 years are projected to occur on average three times as often in future in Metro Vancouver and about three and a half times as often in future in CRD.
    The implications of these projected changes are briefly discussed for physical, social, economic, and ecological systems, and the ICLEI Canada climate adaptation planning methodology is described. This process, outlined in Changing Climate, Changing Communities: Guide and Workbook for Municipal Climate Adaptation is currently being undertaken by communities in Metro Vancouver and CRD. The information contained within this report supports Milestone Two of that process as is intended to assist with adaptation planning.

  • Source Publication: Environmental Research Letters, 11, 4, doi:10.1088/1748-9326/11/4/044011 Authors: B. Mueller, X. Zhang and F.W. Zwiers Publication Date: Apr 2016

    e project that within the next two decades, half of the world's population will regularly (every second summer on average) experience regional summer mean temperatures that exceed those of the historically hottest summer, even under the moderate RCP4.5 emissions pathway. This frequency threshold for hot temperatures over land, which have adverse effects on human health, society and economy, might be broached in little more than a decade under the RCP8.5 emissions pathway. These hot summer frequency projections are based on adjusted RCP4.5 and 8.5 temperature projections, where the adjustments are performed with scaling factors determined by regularized optimal fingerprinting analyzes that compare historical model simulations with observations over the period 1950–2012. A temperature reconstruction technique is then used to simulate a multitude of possible past and future temperature evolutions, from which the probability of a hot summer is determined for each region, with a hot summer being defined as the historically warmest summer on record in that region. Probabilities with and without external forcing show that hot summers are now about ten times more likely (fraction of attributable risk 0.9) in many regions of the world than they would have been in the absence of past greenhouse gas increases. The adjusted future projections suggest that the Mediterranean, Sahara, large parts of Asia and the Western US and Canada will be among the first regions for which hot summers will become the norm (i.e. occur on average every other year), and that this will occur within the next 1–2 decades.

  • Authors: Francis Zwiers Publication Date: Apr 2016

    China’s observing system records temperatures that are broadly influenced by urban warming

    Thus the warming of the Chinese land-mass is likely overestimated. Comparison between urban and rural stations appears to lead to an underestimate of the strength of the urbanization influence. A detection and attribution formalism allows decomposition of China’s temperature record into externally forced, urbanization induced and internal variability induced components of change

    Results suggest about 1/3rd of the recorded warming is due to urbanization

    Anthropogenic and natural external forcing combined are estimated to have caused 0.93°C [0.61-1.24], consistent with the observed global land mean warming 1.09°C [0.86-1.31

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Apr 2016

    This memo summarizes some of the key information required for adaptation in the Whistler area. Projected changes include: increases to the intensity and frequency of heavy rain events; longer, hotter, drier summers and milder winters with reduced snowpack at lower elevations.