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

    Two recently published articles explore how projected changes to climate and carbon dioxide in the atmosphere may affect grasslands in temperate regions and three crops in the United States. Addressing the first question in Nature Climate Change, Obermeier et al. (2017) find that the carbon dioxide fertilization effect in C3 grasslands is reduced when conditions are wetter, dryer or hotter than the conditions to which the grasses are adapted.

    Publishing in Nature Communications, Schauberger et al. (2017) examine the second question. They find that yields for wheat, soy and corn decline at projected temperatures greater than 30°C, with reductions in yield of 22% for wheat, 40% for soy and 49% for corn. While carbon fertilization does reduce the loss in yields, the effect is much smaller than that of irrigation, suggesting that water stress at higher temperatures may be largely responsible for losses.

  • Source Publication: Journal of Advances in Modeling Earth Systems, 9, 2, 1292-1306, doi:10.1002/2016MS000830 Authors: Ouali, D., F. Chebana and T.B.M.J. Ouarda Publication Date: Apr 2017

    The high complexity of hydrological systems has long been recognized. Despite the increasing number of statistical techniques that aim to estimate hydrological quantiles at ungauged sites, few approaches were designed to account for the possible nonlinear connections between hydrological variables and catchments characteristics. Recently, a number of nonlinear machine‐learning tools have received attention in regional frequency analysis (RFA) applications especially for estimation purposes. In this paper, the aim is to study nonlinearity‐related aspects in the RFA of hydrological variables using statistical and machine‐learning approaches. To this end, a variety of combinations of linear and nonlinear approaches are considered in the main RFA steps (delineation and estimation). Artificial neural networks (ANNs) and generalized additive models (GAMs) are combined to a nonlinear ANN‐based canonical correlation analysis (NLCCA) procedure to ensure an appropriate nonlinear modeling of the complex processes involved. A comparison is carried out between classical linear combinations (CCAs combined with linear regression (LR) model), semilinear combinations (e.g., NLCCA with LR) and fully nonlinear combinations (e.g., NLCCA with GAM). The considered models are applied to three different data sets located in North America. Results indicate that fully nonlinear models (in both RFA steps) are the most appropriate since they provide best performances and a more realistic description of the physical processes involved, even though they are relatively more complex than linear ones. On the other hand, semilinear models which consider nonlinearity either in the delineation or estimation steps showed little improvement over linear models. The linear approaches provided the lowest performances.

  • Source Publication: Nature Geoscience 10, 255–259, doi:10.1038/ngeo2911. Authors: Zhang, X., F.W. Zwiers, G.L. Hui Wan and A.J. Cannon Publication Date: Mar 2017

    Warming of the climate is now unequivocal. The water holding capacity of the atmosphere increases by about 7% per °C of warming, which in turn raises the expectation of more intense extreme rainfall events. Meeting the demand for robust projections for extreme short-duration rainfall is challenging, however, because of our poor understanding of its past and future behaviour. The characterization of past changes is severely limited by the availability of observational data. Climate models, including typical regional climate models, do not directly simulate all extreme rainfall producing processes, such as convection. Recently developed convection-permitting models better simulate extreme precipitation, but simulations are not yet widely available due to their computational cost, and they have their own uncertainties. Attention has thus been focused on precipitation–temperature relationships in the hope of obtaining more robust extreme precipitation projections that exploit higher confidence temperature projections. However, the observed precipitation–temperature scaling relationships have been established almost exclusively by linking precipitation extremes with day-to-day temperature variations. These scaling relationships do not appear to provide a reliable basis for projecting future precipitation extremes. Until better methods are available, the relationship of the atmosphere's water holding capacity with temperature provides better guidance for planners in the mid-latitudes, albeit with large uncertainties.

  • Source Publication: doi:10.1007/s00382-017-3634-9 Authors: C. Seiler, F. W. Zwiers, K. I. Hodges and J. F. Scinocca Publication Date: Mar 2017

    Explosive extratropical cyclones (EETCs) are rapidly intensifying low pressure systems that generate severe weather along North America’s Atlantic coast. Global climate models (GCMs) tend to simulate too few EETCs, perhaps partly due to their coarse horizontal resolution and poorly resolved moist diabatic processes. This study explores whether dynamical downscaling can reduce EETC frequency biases, and whether this affects future projections of storms along North America’s Atlantic coast. A regional climate model (CanRCM4) is forced with the CanESM2 GCM for the periods 1981 to 2000 and 2081 to 2100. EETCs are tracked from relative vorticity using an objective feature tracking algorithm. CanESM2 simulates 38% fewer EETC tracks compared to reanalysis data, which is consistent with a negative Eady growth rate bias (−0.1 day−1). Downscaling CanESM2 with CanRCM4 increases EETC frequency by one third, which reduces the frequency bias to −22%, and increases maximum EETC precipitation by 22%. Anthropogenic greenhouse gas forcing is projected to decrease EETC frequency (−15%, −18%) and Eady growth rate (−0.2 day−1, −0.2 day−1), and increase maximum EETC precipitation (46%, 52%) in CanESM2 and CanRCM4, respectively. The limited effect of dynamical downscaling on EETC frequency projections is consistent with the lack of impact on the maximum Eady growth rate. The coarse spatial resolution of GCMs presents an important limitation for simulating extreme ETCs, but Eady growth rate biases are likely just as relevant. Further bias reductions could be achieved by addressing processes that lead to an underestimation of lower tropospheric meridional temperature gradients.

  • Authors: Zwiers, F. Publication Date: Jan 2017
  • Authors: The Pacific Climate Impacts Consortium Publication Date: Jan 2017

    This Science Brief covers recent research by Mao et al. (2016) published in Nature Climate Change. The authors find that the observed greening of the land surface between 30-75° north over the 1982-2011 period is largely due to anthropogenic greenhouse gas emissions.

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

    This newsletter contains articles on the following: 2016 as a record-warm year for the province, recent PCIC research on Fraser River Basin climate impacts, recent Data Portal upgrades, Director Francis Zwiers's keynote at the Wildland Fire Canada Meeting and recognition as a highly-cited researcher, a staff profile on Megan Kirchmeier-Young, our Pacific Climate Seminar Series, PCIC's contributions to the AGU Fall Meeting and Northwest Climate Conference, the most recent Science Brief, staff changes and recent papers by PCIC staff and affiliates.

  • Authors: Norman J. Shippee, Christian Seiler and Francis Zwiers Publication Date: Jan 2017

    Presented by Norman Shippee at the American Meteorological Society's 97th Annual Meeting in January, 2017:  CanSIPS reproduces the overall spatial pattern of cyclone track density found in ERA-Interim. Individual models of CanCM3 and CanCM4 over and under-represent the observed storm track, respectively. CanSIPS mean storm track and spread of track density is well represented, though an overall overprediction of storm track density is evident across the North Pacific, particularly from 45 - 60 deg N. This overprediction of storm track density is present in all components of the CanSIPS system. Moderate to strong correlation between CanSIPS mean storm track density and ERA-Interim track density are found across the primary storm track in the North Pacific and in the primary formation regions for Atlantic cyclones affecting North America (Gulf of Mexico and Cape Hatteras) Most CanSIPS bias in the North Pacific is centralized in the exit regions of the Pacific storm track, localized to Gulf of Alaska and coastal BC.

  • Source Publication: Geoscientific Model Development, 9, 3751-3777 doi:10.5194/gmd-2016-78 Authors: Boer, G.J., D.M. Smith, C. Cassou, F. Doblas-Reyes, G. Danabasoglu, B. Kirtman, Y. Kushnir, M. Kimoto, G.A. Meehl, R. Msadek, W.A. Mueller, K. Taylor and F.W. Zwiers Publication Date: Jan 2017

    The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Prediction (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-toend decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours.

    Groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them. The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society

  • Authors: Schoeneberg (née Werner), A.T., M.A. Schnorbus and M.R. Najafi Publication Date: Dec 2016

    Understanding future climate change impacts on hydro-climatic extremes in British Columbia, Canada requires hydrologic models that can accurately represent the cryospheric processes specific to mountainous regions in higher latitudes. Consequently, hydrologic simulations are conducted using a newly modified version of the Variable Infiltration Capacity (VIC) hydrologic model that couples to a dynamic glacier model. Using this coupled model, we project changes to streamflow extremes in the Columbia and Peace River basins based on a selection of CMIP5 models, run under two representative concentration pathways, statistically downscaled with multiple methods. The modified version of VIC is calibrated against daily streamflow and monthly evaporation using recently developed gridded climate observations, and the dynamic glacier model is evaluated with observed glacier mass balance and coverage data. We analyze changes in the frequency and intensity of peak and low flow events and compare these to previous simulations, which used a simpler version of VIC driven by statistically downscaled CMIP3 outputs.

  • Source Publication: Journal of Climate, 30, 553-571, doi:10.1175/JCLI-D-16-0412.1 Authors: Kirchmeier-Young, M.C., F.W. Zwiers and N.P. Gillett Publication Date: Dec 2016

    Arctic sea ice extent (SIE) has decreased over recent decades, with record-setting minimum events in 2007 and again in 2012. A question of interest across many disciplines concerns the extent to which such extreme events can be attributed to anthropogenic influences. First, a detection and attribution analysis is performed for trends in SIE anomalies over the observed period. The main objective of this study is an event attribution analysis for extreme minimum events in Arctic SIE. Although focus is placed on the 2012 event, the results are generalized to extreme events of other magnitudes, including both past and potential future extremes. Several ensembles of model responses are used, including two single-model large ensembles. Using several different metrics to define the events in question, it is shown that an extreme SIE minimum of the magnitude seen in 2012 is consistent with a scenario including anthropogenic influence and is extremely unlikely in a scenario excluding anthropogenic influence. Hence, the 2012 Arctic sea ice minimum provides a counterexample to the often-quoted idea that individual extreme events cannot be attributed to human influence.

  • Source Publication: Delivered at the Fall Meeting of the American Geophysical Union, December 2016 Authors: Sobie, S.R. and T.Q. Murdock Publication Date: Dec 2016

    Regional and local governments in British Columbia are recognizing the need to obtain detailed information about the effects of future climate change in their communities. The Pacific Climate Impacts Consortium (PCIC) has been a source for relevant analysis and information focussed on climate projections and impacts in BC since 2005. Recently, PCIC has moved away from preparing reports directly for users and instead worked in a more collaborative framework with several communities. In this new format, PCIC supplies climate projection information and assistance with interpretation, while allowing users to develop assessments tailored to their individual needs. This new structure allows PCIC to be more relevant in informing adaption practices. Our goal is to describe the process and outcomes from several collaborative climate change assessment projects.

  • Source Publication: Presented at the 2016 Fall Meeting of the American Geophysical Union Authors: Curry, C.L. and F.W. Zwiers Publication Date: Dec 2016

    The Fraser River basin (FRB) of British Columbia is one of the largest and most important watersheds in Western North America, and is 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 June-July. However, while annual peak daily streamflow (APDF) during the spring freshet in the FRB is historically well correlated with basin-averaged, annual maximum snow water equivalent (SWEmax), there are numerous occurrences of anomalously large APDF in below- or near-normal SWEmax 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 APDFs complicates future projections of streamflow magnitude and frequency.

    We employ the Variable Infiltration Capacity (VIC) process-based hydrological model driven by both observations and an ensemble of CMIP3 climate models in an attempt to discover the proximate causes of anomalous APDF events in the FRB. At several hydrometric stations representing a range of elevations, the relative importance of a set of predictors characterizing the magnitude and timing of rainfall, snowfall, and temperature is examined within a regression framework. The results indicate that next to the magnitude of SWEmax, the rate of warming subsequent to the date of SWEmax is the most influential variable for predicting APDF magnitudes in the lower FRB. Finally, the role of large-scale climate modes of variability for APDF magnitude and timing in the basin will be briefly discussed.

  • Authors: Pingree-Shippee, K.A., F,W. Zwiers and D.E. Atkinson Publication Date: Dec 2016

    Extratropical cyclones (ETCs) often produce extreme hazardous weather conditions, such as high winds, blizzard conditions, heavy precipitation, and flooding, all of which can have detrimental socio-economic impacts. The North American east and west coastal regions are both strongly influenced by ETCs and, subsequently, land-based, coastal, and maritime economic sectors in Canada and the USA all experience strong adverse impacts from extratropical storm activity from time to time. Society would benefit if risks associated with ETCs and storm activity variability could be reliably predicted for the upcoming season. Skillful prediction would enable affected sectors to better anticipate, prepare for, manage, and respond to storm activity variability and the associated risks and impacts. In this study, the potential predictability of seasonal variations in extratropical storm activity is investigated using analysis of variance to provide quantitative and geographical observational evidence indicative of whether it may be possible to predict storm activity on the seasonal timescale. This investigation will also identify origins of the potential predictability using composite analysis and large-scale teleconnections (Southern Oscillation, Pacific Decadal Oscillation, and North Atlantic Oscillation), providing the basis upon which seasonal predictions can be developed. Seasonal potential predictability and its origins are investigated for the cold seasons (OND, NDJ, DJF, JFM) during the 1979-2015 time period using daily mean sea level pressure, absolute pressure tendency, and 10-m wind speed from the ECMWF ERA-Interim reanalysis as proxies for extratropical storm activity. Results indicate potential predictability of seasonal variations in storm activity in areas strongly influenced by ETCs and with origins in the investigated teleconnections. For instance, the North Pacific storm track has considerable potential predictability and with notable origins in the SO and PDO.

  • Authors: Shumlich, M.J. and T.Q. Murdock Publication Date: Nov 2016

    Regional climate service providers such as the Pacific Climate Impacts Consortium (PCIC) have often produced “grey literature” scientific project reports and impact assessments for the regional stakeholders they serve. These reports are suitable for those with some experience in adaptation and climate science. However, for the broader audience of policymakers, planners and the general public these reports are often too technical to be of use. To address the inaccessibility of these reports and provide usable information for decision making, PCIC has taken three main approaches. The first of these approaches is producing high-level summary reports to accompany some of PCIC’s more technical project reports. It is challenging to provide plain language summaries of the important findings without misleading readers or glossing over the subtleties of climate change impacts. However, anecdotal feedback from users indicates that the availability of summary reports dramatically increases the usability of the information provided to them. The second approach is collaborating and co-writing project reports directly with our users. This approach fosters constant learning, improved understanding and strengthens two-way communication between PCIC and regional stakeholders. The third approach is to develop short, high-level extension notes called science briefs. These cover regionally-relevant findings from the scientific community, contextualizing them and discussing what they mean for the users PCIC serves. They also serve as a way for PCIC to address frequently-asked questions in an in-depth manner. This poster discusses the methods and communication principles PCIC employs in the development of these projects and some of the lessons that have been learned along the way.

    (Delivered at the 7th Annual Northwest Climate Conference in Stevenson, Washington, November 14-16, 2016.)

  • Source Publication: Presented at the Northwest Climate Conference, November 14-16, 2016 Authors: Anslow, F. Publication Date: Nov 2016
  • Authors: The Pacific Climate Impacts Consortium Publication Date: Oct 2016

    The September 2016 PCIC Update covered: a recent data homogenization pilot project that PCIC undertook; the release of the 2015-2016 Corporate Report; hydrologic modelling work on peak flows on the Fraser River; the new ClimDown downscaling package; a recent Science Brief on storm surges and atmospheric river events; the resuming of the Pacific Climate Seminar Series; staff changes and recent papers authored by PCIC staff.

  • Source Publication: Bulletin of the American Meteorological Society, doi:10.1175/BAMS-D-16-0019.1 Authors: Myhre, G., P.M. Forster, B.H. Samset, O. Hodnebrog, J. Sillmann, O. Boucher, G. Faluvegi, D. Flaschner, T. Iversen, M. Kasoar, V. Kharin, A. Kirkevag, J.-F. Lamarque, D. Olivie, T. Richardson, D. Shindell, K.P. Shine, C. Weum Stiern, T. Takemura, A. Voulg Publication Date: Oct 2016

    PDRMIP investigates the role of various drivers of climate change for mean and extreme precipitation changes, based on multiple climate model output and energy budget analyses.

    As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of inter-model differences unaccounted for. Individual drivers of climate change initially alter the energy budget of the atmosphere leading to distinct rapid adjustments involving changes in precipitation. Differences in how these rapid adjustment processes manifest themselves within models are likely to explain a large fraction of the present model spread and needs better quantifications to improve precipitation predictions. Here, we introduce the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where a set of idealized experiments designed to understand the role of different climate forcing mechanisms were performed by a large set of climate models. PDRMIP focuses on understanding how precipitation changes relating to rapid adjustments and slower responses to climate forcings are represented across models. Initial results show that rapid adjustments account for large regional differences in hydrological sensitivity across multiple drivers. The PDRMIP results are expected to dramatically improve our understanding of the causes of the present diversity in future climate projections.

  • Authors: Metro Vancouver, the Pacific Climate Impacts Consortium, Pinna Sustainability Publication Date: Sep 2016

    Temperatures in Metro Vancouver are warming. Global climate models project an average increase of about 3°C in our region by the 2050s. Metro Vancouver’s ability to adapt to climate change requires specific information on how changes in temperature and precipitation will play out locally, how expected changes may vary throughout the seasons, and about new climate extremes. Work has been completed by the Pacific Climate Impacts Consortium (PCIC) to understand the details of how our climate may change by the 2050s and 2080s.

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

    This is the Pacific Climate Impacts Constortium's 2015-2016 Corporate Report.