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  • Source Publication: Journal of Hydrology, 582, 124513, doi: 10.1016/j.jhydrol.2019.124513. Authors: Meshesha, T.W., J. Wang and N. Demelash Melaku Publication Date: Mar 2020

    Quantifying bacteria fluxes and contaminants from the point and nonpoint sources in a watershed are important for the management of water quality and safeguard public health. Therefore, the appropriate characterization of bacteria from different sources is necessary for understanding of fate and transport of bacteria in watersheds. However, it is challenging to simulate the effects of pH on bacteria, such as Escherichia coli (E. coli) in the original version of Soil and Water Assessment Tool (SWAT). This study aimed to augment SWAT-bacteria module to evaluate the potential effect of pH on E. coli concentrations. We modified SWAT-bacteria module to incorporate pH factor and to check E. coli observations from four sites of Athabasca River Basin. The modified SWAT-bacteria model demonstrated a linear relationship between observed and simulated daily E. coli data with R2 values found between 0.70 and 0.80; NSE: 0.59 and 0.68; PBIAS: 7.94% and 17.85% during calibration for all monitoring sites (2010–2012). While during the validation (2013–2014) the performance statistics found to be: R2: 0.59–0.72; NSE: 0.55–0.66; PBIAS: 10–22%. The results of the sensitivity analysis confirmed that pH is one of the most significant fate factors of E. coli. The modified SWAT-bacteria module provides an improved estimate of E. coli concentration from the river basin. This study contributes new insight to E. coli modelling. Therefore, the modified SWAT-bacteria model could be a powerful tool for the future regional to global scale model of E. coli concentrations thus significantly contribute for the application of effective river basin management.

  • Source Publication: Advances in Water Resources, 137, 103522, doi:10.1016/j.advwatres.2020.103522. Authors: Ben Alaya, M.A., C. Ternynck, S. Dabo-Niang, F. Chebana and T.B.M.J. Ouarda Publication Date: Mar 2020

    Change point detection methods have an important role in many hydrological and hydraulic studies of river basins. These methods are very useful to characterize changes in hydrological regimes and can, therefore, lead to better understanding changes in extreme flows behavior. Flood events are generally characterized by a finite number of characteristics that may not include the entire information available in a discharge time series. The aim of the current work is to present a new approach to detect changes in flood events based on a functional data analysis framework. The use of the functional approach allows taking into account the whole information contained in the discharge time series of flood events. The presented methodology is illustrated on a flood analysis case study, from the province of Quebec, Canada. Obtained results using the proposed approach are consistent with those obtained using a traditional change point method, and demonstrate the capability of the functional framework to simultaneously consider several flood features and, therefore, presenting a comprehensive way for a better exploitation of the information contained in a discharge time series.

  • Source Publication: Journal of Climate, 33, 8, 3253–3269, doi:10.1175/JCLI-D-19-0405.1. Authors: Williamson, S.N., C. Zdanowicz, F.S. Anslow, G.K.C. Clarke, L. Copland, R.K. Danby, G.E. Flowers, G. Holdsworth, A.H. Jarosch, and D.S. Hik Publication Date: Mar 2020

    The climate of high midlatitude mountains appears to be warming faster than the global average, but evidence for such elevation-dependent warming (EDW) at higher latitudes is presently scarce. Here, we use a comprehensive network of remote meteorological stations, proximal radiosonde measurements, downscaled temperature reanalysis, ice cores, and climate indices to investigate the manifestation and possible drivers of EDW in the St. Elias Mountains in subarctic Yukon, Canada. Linear trend analysis of comprehensively validated annual downscaled North American Regional Reanalysis (NARR) gridded surface air temperatures for the years 1979–2016 indicates a warming rate of 0.028°C a−1 between 5500 and 6000 m above mean sea level (MSL), which is ~1.6 times larger than the global-average warming rate between 1970 and 2015. The warming rate between 5500 and 6000 m MSL was ~1.5 times greater than the rate at the 2000–2500 m MSL bin (0.019°C a−1), which is similar to the majority of warming rates estimated worldwide over similar elevation gradients. Accelerated warming since 1979, measured by radiosondes, indicates a maximum rate at 400 hPa (~7010 m MSL). EDW in the St. Elias region therefore appears to be driven by recent warming of the free troposphere. MODIS satellite data show no evidence for an enhanced snow albedo feedback above 2500 m MSL, and declining trends in sulfate aerosols deposited in high-elevation ice cores suggest a modest increase in radiative forcing at these elevations. In contrast, increasing trends in water vapor mixing ratio at the 500-hPa level measured by radiosonde suggest that a longwave radiation vapor feedback is contributing to EDW.

  • Source Publication: Hydrology and Earth System Sciences, 24, 735–759, doi: 10.5194/hess-24-735-2020. Authors: Alam, M. S., S. L. Barbour and M. Huang Publication Date: Feb 2020

    One technique to evaluate the performance of oil sands reclamation covers is through the simulation of long-term water balance using calibrated soil–vegetation–atmosphere transfer models. Conventional practice has been to derive a single set of optimized hydraulic parameters through inverse modelling (IM) based on short-term monitoring datasets. This approach is unable to characterize the impact of variability in the cover properties. This study utilizes IM to optimize the hydraulic properties for 12 soil cover designs, replicated in triplicate, at Syncrude's Aurora North mine site. The hydraulic parameters for three soil types (peat cover soil, coarse-textured subsoil, and lean oil sand substrate) were optimized at each monitoring site from 2013 to 2016. The resulting 155 optimized parameter values were used to define distributions for each parameter/soil type, while the progressive Latin hypercube sampling (PLHS) method was used to sample parameter values randomly from the optimized parameter distributions. Water balance models with the sampled parameter sets were used to evaluate variations in the maximum sustainable leaf area index (LAI) for five illustrative covers and quantify uncertainty associated with long-term water balance components and LAI values. Overall, the PLHS method was able to better capture broader variability in the water balance components than a discrete interval sampling method. The results also highlight that climate variability dominates the simulated variability in actual evapotranspiration and that climate and parameter uncertainty have a similar influence on the variability in net percolation.

  • Source Publication: Journal of Climate, Early Online Release, doi:10.1175/JCLI-D-19-0492.1. Authors: Li, C., Y.Sun, F. Zwiers, D. Wang, X. Zhang, G. Chen, and H. Wu Publication Date: Feb 2020

    Based on a newly developed observational dataset and a suite of climate model simulations, we evaluate changes in summer mean wet bulb globe temperature (WBGT) in China from 1961 through 2080. We show that summer mean WBGT has increased almost everywhere across China since 1961 due to human-induced climate change. Consequently, hot summers as measured by summer mean WBGT are becoming more frequent and more conducive to heat stress. Hot summers like the hottest on record during 1961-2015 in Western or Eastern China are now expected occur once every 3-4 years. These hot WBGT summers have become more than 140 times as likely in Eastern China in the present decade 2010s compared to a 1961-1990 baseline period, and more than 1000 times as likely in Western China. The substantially larger influence in Western China is associated with its stronger warming signal, which is likely due to the high Bowen ratio of sensible to latent heat fluxes of dry soils and increases in absorbed solar radiation from the decline in mountain snow cover extent. Observation-constrained projections of future summer mean WBGT under the RCP8.5 emissions scenario indicate that, by the 2040s, almost every summer in China will be at least as hot as the hottest summer in the historical record, and by the 2060s, common summers (that occur once every 2 years) will be even 3.0 °C hotter than the historical record, pointing to potentially large increases in the likelihood of human heat stress and to a massive adaption challenge.

  • Source Publication: Journal of Climate, 33, 4 1261-1281, doi:10.1175/JCLI-D-19-0134.1 Authors: Tan, Y., F.W. Zwiers, S. Yang, C. Li and K. Deng Publication Date: Feb 2020

    Performance in simulating atmospheric rivers (ARs) over western North America based on AR frequency and landfall latitude is evaluated for 10 models from phase 5 of the Coupled Model Intercomparison Project among which the CanESM2 model performs well. ARs are classified into southern, northern, and middle types using self-organizing maps in the ERA-Interim reanalysis and CanESM2. The southern type is associated with the development and eastward movement of anomalous lower pressure over the subtropical eastern Pacific, while the northern type is linked with the eastward movement of anomalous cyclonic circulation stimulated by warm sea surface temperatures over the subtropical western Pacific. The middle type is connected with the negative phase of North Pacific Oscillation–west Pacific teleconnection pattern. CanESM2 is further used to investigate projected AR changes at the end of the twenty-first century under the representative concentration pathway 8.5 scenario. AR definitions usually reference fixed integrated water vapor or integrated water vapor transport thresholds. AR changes under such definitions reflect both thermodynamic and dynamic influences. We therefore also use a modified AR definition that isolates change from dynamic influences only. The total AR frequency doubles compared to the historical period, with the middle AR type contributing the largest increases along the coasts of Vancouver Island and California. Atmospheric circulation (dynamic) changes decrease northern AR type frequency while increasing middle AR type frequency, indicating that future changes of circulation patterns modify the direct effect of warming on AR frequency, which would increase ARs (relative to fixed thresholds) almost everywhere along the North American coastline.

  • Authors: Sun, Q., F. Zwiers, X. Zhang and G. Li Publication Date: Jan 2020

    Trend scaling relationships between extreme precipitation and temperature are often used to represent the influence of long-term warming on the intensity of extreme precipitation. Indeed, such scaling relationships are often regarded as providing more reliable precipitation projections than direct projection, owing to higher confidence for temperature projections in model simulations. Due to limited data availability, especially for the sub-daily rainfall, so-called binning scaling relationships, which relate extreme precipitation to temperature at the time of occurrence and are estimated empirically either through a binning technique or quantile regression, have been considered as a substitute for trend scaling to project the long-term response of local extreme precipitation to temperature change (Lenderink and Van Meijgaard, 2008; Wasko and Sharma, 2014). Estimates of binning scaling rates are generally based on seasonal subdaily precipitation observations, and thus they are influenced by factors other than temperature that change systematically within a season, synchronously with the seasonal cycle (Zhang et al., 2017). In contrast to trend scaling, binning scaling often suggests faster than Clausius-Clapeyron intensification of sub-daily precipitation extremes with temperature.

    We explore this apparent contradiction between binning and trend scaling using a large ensemble of moderate resolution regional climate simulations for North America. The large amount of data that is available from this ensemble allows us to confidently estimate both trend and binning scaling rates for the climate that is simulated by that model. Specifically, we use a 35-member initial conditions ensemble of regional climate simulations produced with the Canadian CanRCM4 regional climate model for the period 1950-2100, with historical forcings for the period ending 2005 and RCP8.5 forcing subsequently. Each CanRCM4 ensemble member was driven by a corresponding member of a similar large ensemble of global simulations produced with the Canadian global Earth system model CanESM2 (Scinocca et al., 2016).

    We compare binning and trend scaling of precipitation extremes across different durations (1-hour, 3-hour, and 24-hour), considering annual and seasonal values, and both local and regional spatial scales. We provide strong evidence to clarify that binning scaling cannot project the long-term change in precipitation extreme, with substantial disagreement in the spatial pattern and magnitude of scaling rates between binning and trend scaling regardless of the duration, season, and spatial scale. Using the daily dew point temperature as scaling variable rather than dry air temperature does not eliminate the differences between binning and trend scaling rates. While shorter-duration extreme precipitation does appear to intensify faster with warming in CanRCM4, we only find super-adiabatic intensification of annual precipitation extremes in isolated regions regardless of accumulation durations. Compared with annual maximum results, winter extremes intensify more strongly over the western and southeastern North America across all timescales. A decreasing tendency of summer extremes is projected over the north and central Great Plains. The seasonal timing of the occurrences of precipitation extremes are expected to shift towards the cold season, reflecting the different changing tendencies in summer and winter extremes.

     

    Lenderink, G., and Van Meijgaard, E. 2008: Increase in hourly precipitation extremes beyond expectations from temperature changes. Nat. Geosci., 1, https://doi.org/10.1038/ngeo262.

    Scinocca, J. F., Kharin, V. V., Jiao, Y., Qian, M. W., Lazare, M., Solheim, L., and Flato. G. M., 2016: Coordinated Global and Regional Climate Modeling. J. Climate, 29, 17-35, https://doi.org/10.1175/Jcli-D-15-0161.1.

    Wasko, C., and Sharma, A. 2014: Quantile regression for investigating scaling of extreme precipitation with temperature. Water Resour. Res., 50, 3608-3614, https://doi.org/10.1002/2013WR015194.

    Zhang, X. B., Zwiers F. W., Li, G. L., Wan, H., Cannon, A. J., 2017: Complexity in estimating past and future extreme short-duration rainfall. Nat. Geosci., 10, 255-239, https://doi.org/10.1038/NGEO2911.

  • Source Publication: Bulletin of the American Meteorological Society, doi:10.1175/BAMS-D-18-0258.1. Authors: Sun, Q., C. Miao, A. Agha Kouchak, I. Mallakpour, D. Ji, and Q Duan Publication Date: Dec 2019

    The projected occurrence of anomalous precipitation under different ENSO conditions may be changed under future climate warming, with an asymmetric response to La Niña and El Niño and an increasing frequency of ENSO-related severe dry and wet events.

    Predicting the changes in teleconnection patterns and related hydroclimate extremes can provide vital information necessary to adapt to the effects of the El Niño Southern Oscillation (ENSO). This study uses the outputs of global climate models to assess the changes in ENSO-related dry/wet patterns and the frequency of severe dry/wet events. The results show anomalous precipitation responding asymmetrically to La Niña and El Niño, indicating the teleconnections may not simply be strengthened. A “dry to drier, wet to wetter” annual anomalous precipitation pattern was projected during La Niña phases in some regions, with drier conditions over southern North America, southern South America, and southern Central Asia, and wetter conditions in Southeast Asia and Australia. These results are robust, with agreement from the 26 models and from a subset of 8 models selected for their good performance in capturing observed patterns. However, we did not observe a similar strengthening of anomalous precipitation during future El Niño phases, for which the uncertainties in the projected influences are large. Under the RCP 4.5 emissions scenario, 45 river basins under El Niño conditions and 39 river basins under La Niña conditions were predicted to experience an increase in the frequency of severe dry events; similarly, 59 river basins under El Niño conditions and 61 river basins under La Niña conditions were predicted to have an increase in the frequency of severe wet events, suggesting a likely increase in the risk of floods. Our results highlight the implications of changes in ENSO patterns for natural hazards, disaster management, and engineering infrastructure.

  • Source Publication: Climatic Change, doi:10.1007/s10584-019-02591-7. Authors: Ben Alaya, M.A., F.W. Zwiers and X. Zhang Publication Date: Dec 2019

    In the context of climate change and projected increase in global temperature, the atmosphere’s water holding capacity is expected to increase at the Clausius-Clapeyron (C-C) rate by about 7% per 1 °C warming. Such an increase may lead to more intense extreme precipitation events and thus directly affect the probable maximum precipitation (PMP), a parameter that is often used for dam safety and civil engineering purposes. We therefore use a statistically motivated approach that quantifies uncertainty and accounts for nonstationarity, which allows us to determine the rate of change of PMP per 1 °C warming. This approach, which is based on a bivariate extreme value model of precipitable water (PW) and precipitation efficiency (PE), provides interpretation of how PW and PE may evolve in a warming climate. Nonstationarity is accounted for in this approach by including temperature as a covariate in the bivariate extreme value model. The approach is demonstrated by evaluating and comparing projected changes to 6-hourly PMP from two Canadian regional climate models (RCMs), CanRCM4 and CRCM5, over North America. The main results suggest that, on the continental scale, PMP increases in these models at a rate of approximately 4% per 1 °C warming, which is somewhat lower than the C-C rate. At the continental scale, PW extremes increase on average at the rate of 5% per 1 °C near surface warming for both RCMs. Most of the PMP increase is caused by the increase in PW extremes with only a minor contribution from changes in PE extremes. Nevertheless, substantial deviations from the average rate of change in PMP rates occur in some areas, and these are mostly caused by sensitivity of PE extremes to near surface warming in these regions.

  • Source Publication: Environmental Health, 18, 116, doi:10.1186/s12940-019-0550-y Authors: Chhetri, B.K, Galanis, E., Sobie, S., Brubacher, J., Balshaw, R., Otterstatter, M., Mak, S., Lem, M., Lysyshyn, M., Murdock, T., Fleury, M., Zickfeld, K., Zubel, M., Clarkson, L. and T.K. Takaro Publication Date: Dec 2019

    Background
    Climate change is increasing the number and intensity of extreme weather events in many parts of the world. Precipitation extremes have been linked to both outbreaks and sporadic cases of waterborne illness. We have previously shown a link between heavy rain and turbidity to population-level risk of sporadic cryptosporidiosis and giardiasis in a major Canadian urban population. The risk increased with 30 or more dry days in the 60 days preceding the week of extreme rain. The goal of this study was to investigate the change in cryptosporidiosis and giardiasis risk due to climate change, primarily change in extreme precipitation.

    Methods
    Cases of cryptosporidiosis and giardiasis were extracted from a reportable disease system (1997–2009). We used distributed lag non-linear Poisson regression models and projections of the exposure-outcome relationship to estimate future illness (2020–2099). The climate projections are derived from twelve statistically downscaled regional climate models. Relative Concentration Pathway 8.5 was used to project precipitation derived from daily gridded weather observation data (~ 6 × 10 km resolution) covering the central of three adjacent watersheds serving metropolitan Vancouver for the 2020s, 2040s, 2060s and 2080s.

    Results
    Precipitation is predicted to steadily increase in these watersheds during the wet season (Oct. -Mar.) and decrease in other parts of the year up through the 2080s. More weeks with extreme rain (>90th percentile) are expected. These weeks are predicted to increase the annual rates of cryptosporidiosis and giardiasis by approximately 16% by the 2080s corresponding to an increase of 55–136 additional cases per year depending upon the climate model used. The predicted increase in the number of waterborne illness cases are during the wet months. The range in future projections compared to historical monthly case counts typically differed by 10–20% across climate models but the direction of change was consistent for all models.

    Discussion
    If new water filtration measures had not been implemented in our study area in 2010–2015, the risk of cryptosporidiosis and giardiasis would have been expected to increase with climate change, particularly precipitation changes. In addition to the predicted increase in the frequency and intensity of extreme precipitation events, the frequency and length of wet and dry spells could also affect the risk of waterborne diseases as we observed in the historical period. These findings add to the growing evidence regarding the need to prepare water systems to manage and become resilient to climate change-related health risks.

  • Source Publication: Environment International, 128, 125-136, doi:10.1016/j.envint.2019.04.025 Authors: Sun, Q., C. Miao, M. Hanel, A.G.L. Borthwick, Q. Duan, D. Jid and H. Li Publication Date: Dec 2019

    The effects of heat stress are spatially heterogeneous owing to local variations in climate response, population density, and social conditions. Using global climate and impact models from the Inter-Sectoral Impact Model Intercomparison Project, our analysis shows that the frequency and intensity of heat events increase, especially in tropical regions (geographic perspective) and developing countries (national perspective), even with global warming held to the 1.5 °C target. An additional 0.5 °C increase to the 2 °C warming target leads to >15% of global land area becoming exposed to levels of heat stress that affect human health; almost all countries in Europe will be subject to increased fire danger, with the duration of the fire season lasting 3.3 days longer; 106 countries are projected to experience an increase in the wheat production-damage index. Globally, about 38%, 50%, 46%, 36%, and 48% of the increases in exposure to health threats, wildfire, crop heat stress for soybeans, wheat, and maize could be avoided by constraining global warming to 1.5 °C rather than 2 °C. With high emissions, these impacts will continue to intensify over time, extending to almost all countries by the end of the 21st century: >95% of countries will face exposure to health-related heat stress, with India and Brazil ranked highest for integrated heat-stress exposure. The magnitude of the changes in fire season length and wildfire frequency are projected to increase substantially over 74% global land, with particularly strong effects in the United States, Canada, Brazil, China, Australia, and Russia. Our study should help facilitate climate policies that account for international variations in the heat-related threats posed by climate change.

  • Source Publication: Journal of Hydrometeorology, 20, 10, 2069-2089, doi:10.1175/JHM-D-18-0233.1 Authors: Ben Alaya, M.A.., F. Zwiers, and X. Zhang Publication Date: Oct 2019

    Recently dam managers have begun to use data produced by regional climate models to estimate how probable maximum precipitation (PMP) might evolve in the future. Before accomplishing such a task, it is essential to assess PMP estimates derived from regional climate models (RCMs). In the current study PMP over North America estimated from two Canadian RCMs, CanRCM4 and CRCM5, is compared with estimates derived from three reanalysis products: ERA-Interim, NARR, and CFSR. An additional hybrid dataset (MSWEP-ERA) produced by combining precipitation from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset and precipitable water (PW) from ERA-Interim is also considered to derive PMP estimates that can serve as a reference. A recently developed approach using a statistical bivariate extreme values distribution is used to provide a probabilistic description of the PMP estimates using the moisture maximization method. Such a probabilistic description naturally allows an assessment of PMP estimates that includes quantification of their uncertainty. While PMP estimates based on the two RCMs exhibit spatial patterns similar to those of MSWEP-ERA and the three sets of reanalyses on the continental scale over North America, CanRCM4 has a tendency for overestimation while CRCM5 has a tendency for modest underestimation. Generally, CRCM5 shows good agreement with ERA-Interim, while CanRCM4 is more comparable to CFSR. Overall, the good ability of the two RCMs to reproduce the major characteristics of the different components involved in the estimation of PMP suggests that they may be useful tools for PMP estimation that could serve as a basis for flood studies at the basin scale.

  • Source Publication: Journal of Hydrometeorology, 20, 9, 1757-1778, doi:10.1175/JHM-D-18-0262.1. Authors: Shrestha, R.R., A.J. Cannon, M. Schnorbus and H. Alford Publication Date: Sep 2019

    We describe a state-of-the-art framework for projecting hydrologic impacts due to enhanced warming and amplified moisture fluxes in the subarctic environment under anthropogenic climate change. We projected future hydrologic changes based on phase 5 of the Coupled Model Intercomparison Project global climate model simulations using the Variable Infiltration Capacity hydrologic model and a multivariate bias correction/downscaling method for the Liard basin in subarctic northwestern Canada. Subsequently, the variable importance of key climatic controls on a set of hydrologic indicators was analyzed using the random forests statistical model. Results indicate that enhanced warming and wetness by the end of century would lead to pronounced declines in annual and monthly snow water equivalent (SWE) and earlier maximum SWE. Prominent changes in the streamflow regime include increased annual mean and minimum flows, earlier maximum flows, and either increased or decreased maximum flows depending on interactions between temperature, precipitation, and snow. Using the variable importance analysis, we find that precipitation exerts the primary control on maximum SWE and annual mean and maximum flows, and temperature has the main influence on timings of maximum SWE and flow, and minimum flow. Given these climatic controls, the changes in the hydrologic indicators become progressively larger under the scenarios of 1.5°, 2.0°, and 3.0°C global mean temperature increases above the preindustrial period. Hence, the framework presented in this study provides a detailed diagnosis of the hydrologic changes as well as controls and interactions of the climatic variables, which could be generalized for understanding regional scale changes in subarctic/nival basins.

  • Source Publication: npj Climate and Atmospheric Science, 2, 24, doi:10.1038/s41612-019-0079-3 Authors: Sillmann, J., C. Weum Stjern, G. Myhre, B. Samset, Ø. Hodnebrog, O. Boucher, P. Forster, A. Kirkevåg, J.F. Lamarque, D. Olivié, D. Shindell, A. Voulgarakis, F. Zwiers, T. Andrews, G. Faluvegi, M. Kasoar, T. Richardson, T. Takemura, and V. Kharin Publication Date: Jul 2019

    Global warming due to greenhouse gases and atmospheric aerosols alter precipitation rates, but the influence on extreme precipitation by aerosols relative to greenhouse gases is still not well known. Here we use the simulations from the Precipitation Driver and Response Model Intercomparison Project that enable us to compare changes in mean and extreme precipitation due to greenhouse gases with those due to black carbon and sulfate aerosols, using indicators for dry extremes as well as for moderate and very extreme precipitation. Generally, we find that the more extreme a precipitation event is, the more pronounced is its response relative to global mean surface temperature change, both for aerosol and greenhouse gas changes. Black carbon (BC) stands out with distinct behavior and large differences between individual models. Dry days become more frequent with BC-induced warming compared to greenhouse gases, but so does the intensity and frequency of extreme precipitation. An increase in sulfate aerosols cools the surface and thereby the atmosphere, and thus induces a reduction in precipitation with a stronger effect on extreme than on mean precipitation. A better understanding and representation of these processes in models will provide knowledge for developing strategies for both climate change and air pollution mitigation.

  • Source Publication: Geophysical Research Letters, doi:10.1029/2019GL082908. Authors: Li, C., F. Zwiers, X. Zhang, G. Chen, J. Lu, G. Li, J. Norris, Y. Tan, Y. Sun and M. Liu Publication Date: Jun 2019

    Climate models project that extreme precipitation events will intensify in proportion to their intensity during the 21st century at large spatial scales. The identification of the causes of this phenomenon nevertheless remains tenuous. Using a large ensemble of North American regional climate simulations, we show that the more rapid intensification of more extreme events also appears as a robust feature at finer regional scales. The larger increases in more extreme events than in less extreme events are found to be primarily due to atmospheric circulation changes. Thermodynamically induced changes have relatively uniform effects across extreme events and regions. In contrast, circulation changes weaken moderate events over western interior regions of North America, and enhance them elsewhere. The weakening effect decreases and even reverses for more extreme events, whereas there is further intensification over other parts of North America, creating an “intense gets intenser” pattern over most of the continent.

  • Authors: Lower Mainland Facilities Management, Pinna Sustainability, The Pacific Climate Impacts Consortium Publication Date: May 2019

    Rising temperatures, shifting precipitation patterns, and extreme weather events are already affecting Vancouver Coastal Health (VCH) and our Communities of Care. Chronic stresses and acute shocks are creating a “new climate reality” for health facilities and service delivery, and reshaping our working context.

    With this series of reports, Lower Mainland Facilities Management (LMFM) demonstrates forward-thinking public sector leadership; positions health authorities to meet legislated requirements for addressing climate risk and reducing emissions; and, enables major infrastructure projects to assess climate resilience.

  • Source Publication: Journal of Climate, early online access, doi: 10.1175/JCLI-D-18- 0461.1. Authors: Seiler, C., Publication Date: Apr 2019

    Extratropical cyclones (ETCs) are known to intensify due to three vertically interacting positive potential vorticity perturbations that are associated with potential temperature anomalies close to the surface (θB), condensational heating in the lower-level atmosphere (qsat), and stratospheric intrusion in the upper-level atmosphere (qtr). This study presents the first climatological assessment of how much each of these three mechanisms contributes to the intensity of extreme ETCs. Using relative vorticity at 850 hPa as a measure of ETC intensity, results show that in about half of all cases the largest contributions during maximum ETC intensity are associated with qsat (53% of all ETCs), followed by qtr (36%) and θB (11%). The relative frequency of storms that are dominated by qsat is higher 1) during warmer months (61% of all ETCs during warmer months) compared to colder months (50%) and 2) in the Pacific (56% of all ETCs in the Pacific) compared to the Atlantic (46%). The relative frequency of ETCs that are dominated by θB is larger 1) during colder months (13%) compared to warmer months (3%), 2) in the Atlantic (15%) compared to the Pacific (8%), and 3) in western (11%–20%) compared to eastern ocean basins (4%–9%). These findings are based on piecewise potential vorticity inversion conducted for intense ETCs that occurred from 1980 to 2016 in the Northern Hemisphere (3273 events; top 7%). The results may serve as a baseline for evaluating ETC biases and uncertainties in global climate models.

  • Source Publication: Journal of Advances in Modeling Earth Systems, 11, 5, doi:10.1029/2018MS001532. Authors: He. Y., N. McFarlane and A. H. Monahan Publication Date: Mar 2019

    This paper presents a new mathematical formulation to account for the effects turbulent motions in comprehensive global climate models. The new formulation is based on recently published theoretical advances and results of high‐resolution numerical model simulations for specialized atmospheric turbulence regimes. The new formulation is tested and evaluated using a simplified model configuration designed to represent a single grid volume of a global climate model.

  • Source Publication: Hydrology and Earth System Sciences, 23, 811-828, doi:10.5194/hess-23-811-2019. Authors: Islam, S. Ul, C.L. Curry, S.J. Dery and F.W. Zwiers Publication Date: Feb 2019

    In response to ongoing and future-projected global warming, mid-latitude, nival river basins are expected to transition from a snowmelt-dominated flow regime to a nival–pluvial one with an earlier spring freshet of reduced magnitude. There is, however, a rich variation in responses that depends on factors such as the topographic complexity of the basin and the strength of maritime influences. We illustrate the potential effects of a strong maritime influence by studying future changes in cold season flow variability in the Fraser River Basin (FRB) of British Columbia, a large extratropical watershed extending from the Rocky Mountains to the Pacific Coast. We use a process-based hydrological model driven by an ensemble of 21 statistically downscaled simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), following the Representative Concentration Pathway 8.5 (RCP 8.5).

    Warming under RCP 8.5 leads to reduced winter snowfall, shortening the average snow accumulation season by about one-third. Despite this, large increases in cold season rainfall lead to unprecedented cold season peak flows and increased overall runoff variability in the VIC simulations. Increased cold season rainfall is shown to be the dominant climatic driver in the Coast Mountains, contributing 60 % to mean cold season runoff changes in the 2080s. Cold season runoff at the outlet of the basin increases by 70 % by the 2080s, and its interannual variability more than doubles when compared to the 1990s, suggesting substantial challenges for operational flow forecasting in the region. Furthermore, almost half of the basin (45 %) transitions from a snow-dominated runoff regime in the 1990s to a primarily rain-dominated regime in the 2080s, according to a snowmelt pulse detection algorithm. While these projections are consistent with the anticipated transition from a nival to a nival–pluvial hydrologic regime, the marked increase in FRB cold season runoff is likely linked to more frequent landfalling atmospheric rivers in the region projected in the CMIP5 models, providing insights for other maritime-influenced extratropical basins.

  • Source Publication: Nature Scientific Data, 6, 180299, doi:10.1038/sdata.2018.299. Authors: Werner, A.T., R.R. Shrestha, A.J. Cannon, M.S. Schnorbus, F.W. Zwiers, G. Dayon and F. Anslow Publication Date: Jan 2019

    We describe a spatially contiguous, temporally consistent high-resolution gridded daily meteorological dataset for northwestern North America. This >4 million km2 region has high topographic relief, seasonal snowpack, permafrost and glaciers, crosses multiple jurisdictional boundaries and contains the entire Yukon, Mackenzie, Saskatchewan, Fraser and Columbia drainages. We interpolate daily station data to 1/16° spatial resolution using a high-resolution monthly 1971–2000 climatology as a predictor in a thin-plate spline interpolating algorithm. Only temporally consistent climate stations with at least 40 years of record are included. Our approach is designed to produce a dataset well suited for driving hydrological models and training statistical downscaling schemes. We compare our results to two commonly used datasets and show improved performance for climate means, extremes and variability. When used to drive a hydrologic model, our dataset also outperforms these datasets for runoff ratios and streamflow trends in several, high elevation, sub-basins of the Fraser River.

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