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  • 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: eather 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.

  • Source Publication: Geophysical Research Letters, 44, 21, 11012-11020, doi:10.1002/2017GL075016 Authors: Najafi, M.R., F.W. Zwiers and N.P. Gillett Publication Date: Oct 2017

    We study the observed decline in summer streamflow in four key river basins in British Columbia (BC), Canada, using a formal detection and attribution (D&A) analysis procedure. Reconstructed and simulated streamflow is generated using the semidistributed variable infiltration capacity hydrologic model, which is driven by 1/16° gridded observations and downscaled climate model data from the Coupled Model Intercomparison Project phase 5 (CMIP5), respectively. The internal variability of the regional hydrologic components using ~5100 years of streamflow was simulated using CMIP5 preindustrial control runs. Results show that the observed changes in summer streamflow are inconsistent with simulations representing the responses to natural forcing factors alone, while the response to anthropogenic and natural forcing factors combined is detected in these changes. A two‐signal D&A analysis indicates that the effects of anthropogenic (ANT) forcing factors are discernable from natural forcing in BC, albeit with large uncertainties.

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

    Two articles recently published in the peer reviewed literature examine how the rate of snowmelt may change as the Earth's climate changes, and how droughts can evolve and move over time.

    Publishing in Nature Climate Change, Musselman et al. (2017) examine the effect that global warming may have on snowmelt. They find that the portion of snow melt occurring at moderate and high melt rates in Western North America is projected to decrease, while the portion occurring at low melt rates is projected to increase. Total meltwater volume is projected to decrease.

    In recent research published in Geophysical Research Letters, Herrera-Estrada et al. (2017) explore how droughts evolve in space and time across six continents. They find that clusters of droughts can travel hundreds to thousands of kilometers across each continent. In addition, the authors find that longer-lasting droughts tend to travel farther, as well as be more severe.

  • Source Publication: Climatic Change, 145, 289303, doi:10.1007/s10584-017-2098-6 Authors: Shrestha, R., A.J. Cannon, M.A. Schnorbus and F.W. Zwiers Publication Date: Oct 2017

    We describe an efficient and flexible statistical modeling framework for projecting nonstationary streamflow extremes for the Fraser River basin in Canada, which is dominated by nival flow regime. The framework is based on an extreme value analysis technique that allows for nonstationarity in annual extreme streamflow by relating it to antecedent winter and spring precipitation and temperature. We used a representative suite of existing Variable Infiltration Capacity hydrologic model simulations driven by Coupled Model Intercomparison Project Phase 3 (CMIP3) climate simulations to train and evaluate a nonlinear and nonstationary extreme value model of annual extreme streamflow. The model was subsequently used to project changes under CMIP5-based climate change scenarios. Using this combination of process-based and statistical modeling, we project that the moderate (e.g., 2–20-year return period) extreme streamflow events will decrease in intensity. In contrast, projections of high intensity events (e.g., 100–200-year return period), which reflect complex interactions between temperature and precipitation changes, are inconclusive. The results provide a basis for developing a general understanding of the future streamflow extremes changes in nival basins and through careful consideration and adoption of appropriate covariates, the methodology could be employed for basins spanning a range of hydro-climatological regimes.

  • Source Publication: Earth's Future, doi:10.1002/2017EF000639 Authors: Li, C., X. Zhang, F.W. Zwiers, Y. Fang and A.M. Michalak Publication Date: Oct 2017

    Wet bulb globe temperature (WBGT) accounts for the effect of environmental temperature and humidity on thermal comfort, and can be directly related to the ability of the human body to dissipate excess metabolic heat and thus avoid heat stress. Using WBGT as a measure of environmental conditions conducive to heat stress, we show that anthropogenic influence has very substantially increased the likelihood of extreme high summer mean WBGT in northern hemispheric land areas relative to the climate that would have prevailed in the absence of anthropogenic forcing. We estimate that the likelihood of summer mean WGBT exceeding the observed historical record value has increased by a factor of at least 70 at regional scales due to anthropogenic influence on the climate. We further estimate that, in most northern hemispheric regions, these changes in the likelihood of extreme summer mean WBGT are roughly an order of magnitude larger than the corresponding changes in the likelihood of extreme hot summers as simply measured by surface air temperature. Projections of future summer mean WBGT under the RCP8.5 emissions scenario that are constrained by observations indicate that by 2030s at least 50% of the summers will have mean WBGT higher than the observed historical record value in all the analyzed regions, and that this frequency of occurrence will increase to 95% by mid‐century.

  • Source Publication: Earth's Future, accepted, doi:10.1002/2017EF000639. Authors: Li, C., X. Zhang, F. Zwiers, Y. Fang and A. Micha Publication Date: Oct 2017

    Wet bulb Globe Temperature (WBGT) accounts for the effect of environmental temperature and humidity on thermal comfort, and can be directly related to the ability of the human body to dissipate excess metabolic heat and thus avoid heat stress. Using WBGT as a measure of environmental conditions conducive to heat stress, we show that anthropogenic influence has very substantially increased the likelihood of extreme high summer mean WBGT in northern hemispheric land areas relative to the climate that would have prevailed in the absence of anthropogenic forcing. We estimate that the likelihood of summer mean WGBT exceeding the observed historical record value has increased by a factor of at least 70 at regional scales due to anthropogenic influence on the climate. We further estimate that, in most northern hemispheric regions, these changes in the likelihood of extreme summer mean WBGT are roughly an order of magnitude larger than the corresponding changes in the likelihood of extreme hot summers as simply measured by surface air temperature. Projections of future summer mean WBGT under the RCP8.5 emissions scenario that are constrained by observations indicate that by 2030s at least 50% of the summers will have mean WBGT higher than the observed historical record value in all the analyzed regions, and that this frequency of occurrence will increase to 95% by mid-century.

  • Authors: Ouali, D. Publication Date: Oct 2017

    Talk delivered by Dr. Dhouha Ouali, PCIC Research Associate with the Marine Environmental Observation Prediction and Response Network on October 25th, 2017.

    Regional frequency analysis (RFA) of hydro-meteorological variables is a commonly used tool to provide quantile estimates of extreme events at ungauged sites. Given the high complexity of hydro-meteorological processes, it is worthwhile to account for the possible nonlinear connections between hydro-meteorological variables and catchments characteristics in all RFA steps. Moreover, to provide relatively reliable quantiles estimates, it is often recommended to only consider sites with sufficiently long data series which lead to ignoring a considerable part of the available information. A number of regression-based RFA methods are proposed to remedy the limitations of the classical approaches, mainly dealing with the non-linear aspect and the exploitation of the hydro-meteorological data. Comprehensive comparisons are carried out between the classical and the proposed methodologies using 151 hydrometric stations from the province of Quebec. The performances of the proposed methods are assessed using new and classical evaluation criteria in a cross-validation procedure.

  • Source Publication: Water Resources Research, 53, 8366–8382, doi:10.1002/2017WR020596 Authors: Bonnet, R., J. Boé, G. Dayon and E. Martin Publication Date: Oct 2017

    Characterizing and understanding the multidecadal variations of the continental hydrological cycle is a challenging issue given the limitation of observed data sets. In this paper, a new approach to derive twentieth century hydrological reconstructions over France with an hydrological model is presented. The method combines the results of long-term atmospheric reanalyses downscaled with a stochastic statistical method and homogenized station observations to derive the meteorological forcing needed for hydrological modeling. Different methodological choices are tested and evaluated. We show that using homogenized observations to constrain the results of statistical downscaling help to improve the reproduction of precipitation, temperature, and river flows variability. In particular, it corrects some unrealistic long-term trends associated with the atmospheric reanalyses. Observationally constrained reconstructions therefore constitute a valuable data set to study the multidecadal hydrological variations over France. Thanks to these reconstructions, we confirm that the multidecadal variations previously noted in French river flows have mainly a climatic origin. Moreover, we show that multidecadal variations exist in other hydrological variables (evapotranspiration, snow cover, and soil moisture). Depending on the region, the persistence from spring to summer of soil moisture or snow anomalies generated during spring by temperature and precipitation variations may explain river flows variations in summer, when no concomitant climate variations exist.

  • Source Publication: The Cryosphere, doi:10.5194/tc-2017-157 Authors: Kushner, P.J., et al. (F.W. Zwiers 24th co-author) Publication Date: Sep 2017

    This study assesses the ability of the Canadian Seasonal to Interannual Prediction System (CanSIPS) and the Canadian Earth-system Model 2 (CanESM2) to predict and simulate snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth-System Models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5) archive, and initial condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow cover over the Canadian land mass, reflecting a broader Northern Hemisphere positive bias. It also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea-ice trends there. The strengths and weaknesses of the modeling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea-ice thickness initialization using statistical predictors available in real time.

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