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  • 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.

  • Authors: Wilson, T. and Eco-Logical Resolutions Publication Date: Apr 2018

    The Fraser Valley Climate Adaptive Drainage Management Forum project was initiated to generate and share the best available precipitation projections for the Fraser Valley; research collaborative climate adaptive drainage management strategies adopted in comparable settings; and host a Forum between producers, local government and agency staff, researchers and agricultural association representatives to deliberate preferred drainage management strategies to address local runoff and drainage challenges.

  • Source Publication: Hydrology and Earth System Sciences, doi:10.5194/hess-2017-531 Authors: Curry, C.L. and F.W. Zwiers Publication Date: Apr 2018

    The Fraser River Basin (FRB) of British Columbia is one of the largest and most important watersheds in western North America, and home to a rich diversity of biological species and economic assets that depend implicitly upon its extensive riverine habitats. The hydrology of the FRB is dominated by snow accumulation and melt processes, leading to a prominent annual peak streamflow invariably occurring in May–July. Nevertheless, while annual peak daily streamflow (APF) during the spring freshet in the FRB is historically well correlated with basin-averaged, 1 April snow water equivalent (SWE), there are numerous occurrences of anomalously large APF in below- or near-normal SWE years, some of which have resulted in damaging floods in the region. An imperfect understanding of which other climatic factors contribute to these anomalously large APFs hinders robust projections of their magnitude and frequency. We employ the Variable Infiltration Capacity (VIC) process-based hydrological model driven by gridded observations to investigate the key controlling factors of anomalous APF events in the FRB and four of its subbasins that contribute nearly 70 % of the annual flow at Fraser-Hope. The relative influence of a set of predictors characterizing the interannual variability of rainfall, snowfall, snowpack (characterized by the annual maximum value, SWEmax), soil moisture and temperature on simulated APF at Hope (the main outlet of the FRB) and at the subbasin outlets is examined within a regression framework. The influence of large-scale climate modes of variability (the Pacific Decadal Oscillation (PDO) and the El Niño–Southern Oscillation – ENSO) on APF magnitude is also assessed, and placed in context with these more localized controls. The results indicate that next to SWEmax (univariate Spearman correlation with APF of ρˆ = 0.64; 0.70 (observations; VIC simulation)), the snowmelt rate (ρˆ = 0.43 in VIC), the ENSO and PDO indices (ρˆ = −0.40; −0.41) and (ρˆ = −0.35; −0.38), respectively, and rate of warming subsequent to the date of SWEmax (ρˆ = 0.26; 0.38), are the most influential predictors of APF magnitude in the FRB and its subbasins. The identification of these controls on annual peak flows in the region may be of use in understanding seas

  • Authors: M. Ek, T. Murdock, S. Sobie, B. Cavka, B. Coughlin and R. Wells Publication Date: Apr 2018

    Since local weather and climate greatly affect the construction and performance of buildings, reliable meteorological
    data is essential when simulating building performance. It is well understood that climate change will affect future
    weather and there is a growing interest in generating future weather files to support climate resilient building design.
    Weather files that account for climate change have not been widely used for the lower mainland region of British
    Columbia. In this study, hourly weather files for future climate conditions in Vancouver are created for three time periods
    using a “morphing” methodology. Morphing uses results from global climate models to adjust observed weather data
    at a specific location. In this study, daily data from climate simulations for the RCP8.5 emission scenario have been
    used. The weather variables that have been adjusted are dry-bulb temperature, relative humidity, solar radiation, cloud
    cover, wind speed and atmospheric pressure. The impact of climate change on the energy performance of a multi-unit
    residential building located on the University of BC campus is analyzed using the energy modelling software
    EnergyPlus. The simulation results indicate that the changing climate in Vancouver, following RCP8.5, would have a
    considerable effect on building energy performance and energy demand due to decrease in space heating and increase
    in cooling requirements.

  • Source Publication: Journal of Hydrometeorology, doi: 10.1175/JHM-D-17-0110.1 Authors: Ben Alaya, M.A., F.W. Zwiers and X. Zhang Publication Date: Apr 2018

    Probable maximum precipitation (PMP) is the key parameter used to estimate the probable maximum flood (PMF), both of which are important for dam safety and civil engineering purposes. The usual operational procedure for obtaining PMP values, which is based on a moisture maximization approach, produces a single PMP value without an estimate of its uncertainty. We therefore propose a probabilistic framework based on a bivariate extreme value distribution to aid in the interpretation of these PMP values. This 1) allows us to evaluate estimates from the operational procedure relative to an estimate of a plausible distribution of PMP values, 2) enables an evaluation of the uncertainty of these values, and 3) provides clarification of the impact of the assumption that a PMP event occurs under conditions of maximum moisture availability. Results based on a 50-yr Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) simulation over North America reveal that operational PMP estimates are highly uncertain and suggest that the assumption that PMP events have maximum moisture availability may not be valid. Specifically, in the climate simulated by CanRCM4, the operational approach applied to 50-yr data records produces a value that is similar to the value that is obtained in our approach when assuming complete dependence between extreme precipitation efficiency and extreme precipitable water. In contrast, our results suggest weaker than complete dependence. Estimates from the operational approach are 15% larger on average over North America than those obtained when accounting for the dependence between precipitation efficiency and precipitable water extremes realistically. A difference of this magnitude may have serious implications in engineering design.

  • Source Publication: Earth's Future, 6, doi: 10.1002/2018EF000813 Authors: Kharin, V.V., G.M. Flato, X. Zhang, N.P. Gillett, F.W. Zwiers and K. Anderson Publication Date: Apr 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: Anslow, F.S. Publication Date: Mar 2018

    Presented by Faron Anslow at the State of the Pacific Ocean meeting.

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

    Two recent articles in the journal Climatic Change examine some of the effects that climate change may have on agriculture in the Pacific Northwest.

    Focusing on specialty fruit production, Houston et al. (2018) find that overall warmer conditions and reduced water availability may reduce net returns on crops due to increasing farming costs, affecting yields and altering product quality. They suggest that management strategies currently employed in marginal production areas that moderate temperatures and offset mismatches between the needs of the plant at various growth stages and seasonal weather conditions may be useful adaptation strategies.

    Neibergs and colleagues (2018) review the impacts of climate change on beef cattle production. They find that changes to seasonal temperature and precipitation may affect the availability of the plants on which cattle forage. This in turn could affect the number of cattle that an area can support, and the dates at which cattle are "turned-out" to pasture and taken in from pasture.

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

    The March 2018 PCIC Update includes the following stories: 2017 in Climatological Context, Applying the Updated VIC Model to New Regions, Engagement with First Nations Communities and Engineers, New Projects, Staff Profile on Dr. Faron Anslow and the Pacific Climate Seminar Series, as well as staff changes and publications.

  • Source Publication: Agricultural and Forest Meteorology, 250–251, 226-242 doi:10.1016/j.agrformet.2017.12.253 Authors: Sgubin, G., D. Swingedouw, G. Dayon, I.G. de Cortázar-Atauri, N. Ollat, C. Pagé and , C. van Leeuwen Publication Date: Mar 2018

    Tardive frosts, i.e. frost events occurring after grapevine budburst, are a significant risk for viticultural practices, which have recently caused substantial yield losses over different winegrowing regions of France, e.g. in 2016 and 2017. So far, it is unclear whether the frequency of late frosts events is destined to increase or decrease under future climatic conditions. Here, we assess the risk of tardive frosts for the French vineyards throughout the 21st century by analyzing temperature projections from eight climate models and their statistical regional downscaling. Our approach consists in comparing the statistical occurrences of the last frost (day of the year) and the characteristic budburst date for nine grapevine varieties as simulated by three different phenological models. Climate models qualitatively agree in projecting a gradual increase in temperature all over the France, which generally produces both an earlier characteristic last frost day and an earlier characteristic budburst date. However, the latter notably depends on the specific phenological model, implying a large uncertainty in assessing the risk exposure. Overall, we identified Alsace, Burgundy and Champagne as the most vulnerable regions, where the probability of tardive frost is projected to significantly increase throughout the 21st century for two out of three phenological models. The third phenological model produces opposite results, but the comparison between simulated budburst dates and observed records over the last 60 years suggests its lower reliability. Nevertheless, for a more trustworthy risk assessment, the validity of the budburst models should be accurately tested also for warmer climate conditions, in order to narrow down the associated large uncertainty.

  • Source Publication: The Journal of Open Source Software. 3, 22, 360, doi:10.21105/joss.00360 Authors: Hiebert, J., A. Cannon, A. Schoeneberg, S. Sobie and T. Murdock Publication Date: Feb 2018

    The ClimDown R package publishes the routines and techniques of the Pacific Climate Impacts Consortium (PCIC) for downscaling coarse scale Global Climate Models (GCMs) to fine scale spatial resolution. PCIC’s overall downscaling algorithm is named Bias-corrected constructed analogues with quantile mapping reordering (BCCAQ) (Cannon, Sobie, and Murdock 2015; Werner and Cannon 2016). BCCAQ is a hybrid downscaling method that combines outputs from Constructed Analogues (CA) (Maurer et al. 2010) and quantile mapping at the fine-scale resolution. First, the CA and Climate Imprint (CI) (Hunter and Meentemeyer 2005) plus quantile delta mapping (QDM) (Cannon, Sobie, and Murdock 2015) algorithms are run independently. BCCAQ then combines outputs from the two by taking the daily QDM outputs at each fine-scale grid point and reordering them within a given month according to the daily CA ranks, i.e., using a form of Empirical Copula Coupling (Schefzik, Thorarinsdottir, and Gneiting 2013). The package exports high-level wrapper functions that perform each of three downscaling steps: CI, CA, and QDM, as well as one wrapper that runs the entire BCCAQ pipeline.

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

    Three recent journal articles examine the rate of sea level rise and the ability of models to accurately simulate sea level rise at a global and regional scale.

    Publishing in Geophysical Research Letters, Yi et al. (2017) examine the rate at which sea level rise is accelerating and find that the rate of acceleration over the 2005-2015 period is three times faster than it was over the 1993-2014 period and an order of magnitude larger than the acceleration over the 1920-2011 period. They also identify three primary contributors to this acceleration: the thermal expansion of sea water, reduced storage of water on land and the melting of ice on land.

    In a pair of articles published in the Journal of Climate, Slangen et al. (2017) and Meyssignac et al. (2017) analyze the of climate models to simulate both global and regional sea level rise. They find that simulations can only explain about half (50% ± 30%) of the observed sea level rise. After bias corrections are included for the Greenland ice sheet and the possibility that ice sheets and the deep ocean were not in equilibrium with the 20th Century climate, the models explain about three-quarters (75% ± 38%) of the observed 20th Century sea level rise and all (105% ± 35%) of the observed sea level rise over the period from 1993-1997 to 2011-2015 period. Regionally, climate models underestimate the amount of sea level rise that occured, but do show reasonable agreement for interannual and multidecadal variability. When the same bias corrections are applied, the models come into closer agreement with observations. In addition, they find that the spatial variability in regional sea level rise is largely due to the thermal expansion of sea water and ongoing isostatic adjustment resulting from the end of the last glacial period.

  • Source Publication: International Journal of Climatology, 38, 2, 1041-1059, doi:10.1002/joc.5235 Authors: Pingree-Shippee, K., F.W. Zwiers and D. Atkinson Publication Date: Feb 2018

    Extratropical cyclones often produce extreme and hazardous weather conditions, such as high winds, heavy precipitation, blizzard conditions, and flooding, all of which have detrimental environmental/physical and socio‐economic impacts. Furthermore, storm interaction with the ocean produces additional hazards, with major local impacts, including inundation and coastal erosion. The North American west coast is influenced by the North Pacific storm track and by ‘atmospheric river’ events while the east coast is particularly influenced by winter storms that track along two favoured routes: the St. Lawrence Valley and the Eastern Seaboard. Reanalysis provides an invaluable tool for studying the characteristics of storm events that are identified as causing the most severe impacts. However, reanalysis products differ substantially in spatial resolution, model physics, assimilation approach, and the data that are assimilated. This study evaluates the representation of storm activity along the mid‐latitude North American coastlines by six global reanalyses: NCEP‐1, NCEP‐2, ERA‐Interim, Modern‐Era Retrospective analysis for Research and Applications (MERRA), Climate Forecast System Reanalysis (CFSR), and Twentieth Century Reanalysis Version 2 (20CR). Storm activity representation is evaluated at annual and seasonal timescales (JFM, AMJ, JAS, OND, and ‘extended winter’ ONDFM) during the 1979–2010 time period through comparison with selected meteorological stations using single‐point surface pressure‐based proxies of extratropical storm activity. Stations are selected on the basis of record length, reporting frequency, coastal proximity, and relatively uniform spatial distribution. Comparisons are made using data extracted from the reanalysis grid box centre that is closest to each selected station. All reanalyses are found to successfully represent most aspects of mid‐latitude North American coastal strong storm activity, annually and seasonally, along both coasts. Nevertheless, ERA‐Interim, MERRA, and CFSR provide the better representations of mid‐latitude North American coastal strong storm activity, with ERA‐Interim performing best overall.

  • Authors: Seiler, C. Publication Date: Jan 2018

    Extratropical cyclones (ETCs) intensify due to three vertically interacting positive potential vorticity anomalies that are associated with warm temperature anomalies at the surface, condensational heating in the lower-level atmosphere, and stratospheric intrusion in the upper-level atmosphere. It remains unclear how much each mechanism contributes to ETC intensification, as results from case studies are conflicting and a climatological assessment has not yet been done. Such a climatology would be useful for identifying sources of ETC biases and uncertainties in global climate models (GCMs). To fill this gap, this study presents the first climatology of mechanisms that generate intense ETCs in the Northern Hemisphere for the period 1980 to 2016 (3273 ETCs). Using piecewise potential vorticity inversion, I show that the lower level contributes most to maximum ETC intensification (52%), followed by the upper level (26%), and the surface (22%). These values vary during the last 36 hours prior to maximum ETC intensity, with decreasing surface contributions (from 35% to 22%) and increasing upper-level contributions (from 13% to 26%). The dominance of the lower level applies to 74% of ETCs, followed by the upper level (18% of ETCs) and the surface (8% of ETCs). Upper-level contributions are stronger in eastern than in western ocean basins, while the opposite applies to surface and lower-level contributions. This is consistent with regional patterns of potential vorticity anomalies, which, as discussed, may be associated with Rossby wave breaking and western boundary currents. The ability of GCMs to reproduce the mechanisms quantified in this study remains to be assessed.

  • Source Publication: Journal of Climate, doi:10.1175/JCLI-D-16-0752.1 Authors: Naveau, P., A. Ribes, F.W. Zwiers, A. Hannart, A. Tuel and P. Yiou Publication Date: Jan 2018

    Both climate and statistical models play an essential role in the process of demonstrating that the distribution of some atmospheric variable has changed over time and in establishing the most likely causes for the detected change. One statistical difficulty in the research field of Detection and Attribution resides in defining events that can be easily compared and accurately inferred from reasonable sample sizes. As many impacts studies focus on extreme events, the inference of small probabilities and the computation of their associated uncertainties quickly become challenging. In the particular context of event attribution, we address the question of how to compare records between the so-called world as “it might have been been without anthropogenic forcings” and the “world that is”. Records are often the most important events in terms of impact and get much media attention. We will show how to efficiently estimate the ratio of two small probability of records. The inferential gain is particularly substantial when a simple hypothesis testing procedure is implemented. The theoretical justification of such a proposed scheme can be found in Extreme Value Theory. To illustrate our approach, classical indicators in event attribution studies like the Risk Ratio or the Fraction of Attributable Risk, are modified and tailored to handle records. We illustrate the advantages of our method through theoretical results, simulation studies, temperature records in Paris and outputs from a numerical climate model.

  • Source Publication: Nature Scientific Reports, 8, 1007, doi:10.1038/s41598-018-19288- Authors: Li, C., Y. Fang, K. Calderia, X. Zhang, N.S. Diffenbaugh, and A.M. Michalak Publication Date: Jan 2018

    A critical question for climate mitigation and adaptation is to understand when and where the signal of changes to climate extremes have persistently emerged or will emerge from the background noise of climate variability. Here we show observational evidence that such persistent changes to temperature extremes have already occurred over large parts of the Earth. We further show that climate models forced with natural and anthropogenic historical forcings underestimate these changes. In particular, persistent changes have emerged in observations earlier and over a larger spatial extent than predicted by models. The delayed emergence in the models is linked to a combination of simulated change (‘signal’) that is weaker than observed, and simulated variability (‘noise’) that is greater than observed. Over regions where persistent changes had not occurred by the year 2000, we find that most of the observed signal-to-noise ratios lie within the 16–84% range of those simulated. Examination of simulations with and without anthropogenic forcings provides evidence that the observed changes are more likely to be anthropogenic than nature in origin. Our findings suggest that further changes to temperature extremes over parts of the Earth are likely to occur earlier than projected by the current climate models.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Dec 2017
  • Authors: The Pacific Climate Impacts Consortium Publication Date: Dec 2017

    This newsletter discusses the publishing of rivers climate change indicators for the British Columbia (BC) Ministry of Environment and Climate Change Strategy, engineering design values for Island Health, progress on the development of the Climate Tool for Engineers, new partnerships with the Blueberry Council of BC and the Comox Valley Regional District, a paper on projected changes to summer mean wet bulb globe temperatures led by Chao Li, a Canadian Meteorological and Oceanographic Society article on extreme wildfire risk in the Fort McMurray area by Megan Kirchmeier-Young, a staff profile on Dr. Gildas Dayon, the PCIC Climate Seminar Series, a welcome to doctoral student Yaheng Tan, the release of PCIC's 2016-2017 Corporate Report, the release of a Science Brief on snowmelt and drought, the publishing of Climate Change Projections for the Cowichan Valley Regional District and State of the Physical, Biological and Selected Fishery Resources of Pacific Canadian Marine Ecosystems in 2016, as well as peer-reviewed publications since the last newsletter.

  • Source Publication: Weather and Climate Extremes, 18, 65-74,doi:10.1016/j.wace.2017.10.003 Authors: Sillmann, J., T.L. Thoranisdottir, N. Schaller, L. Alexander, G.C. Hegerl, S.I. Seneviratne, R. Vautard, X. Zhang and F.W. Zwiers Publication Date: Dec 2017

    Weather and climate extremes are identified as major areas necessitating further progress in climate research and have thus been selected as one of the World Climate Research Programme (WCRP) Grand Challenges. Here, we provide an overview of current challenges and opportunities for scientific progress and cross-community collaboration on the topic of understanding, modeling and predicting extreme events based on an expert workshop organized as part of the implementation of the WCRP Grand Challenge on Weather and Climate Extremes. In general, the development of an extreme event depends on a favorable initial state, the presence of large-scale drivers, and positive local feedbacks, as well as stochastic processes. We, therefore, elaborate on the scientific challenges related to large-scale drivers and local-to-regional feedback processes leading to extreme events. A better understanding of the drivers and processes will improve the prediction of extremes and will support process-based evaluation of the representation of weather and climate extremes in climate model simulations. Further, we discuss how to address these challenges by focusing on short-duration (less than three days) and long-duration (weeks to months) extreme events, their underlying mechanisms and approaches for their evaluation and prediction.