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  • Authors: The Pacific Climate Impacts Consortium Publication Date: May 2020

    As the Arctic warms, the rate at which microbes in Arctic soil digest soil organic matter increases and, with it, the release of carbon dioxide into the atmosphere also increases. The amount of carbon released into the atmosphere from permafrost in this region is significant and so it is important to measure it accurately and be able to make credible projections of it.

    Publishing in Nature Climate Change, Natali et al. (2019) use observations of CO2 flux from Arctic and Boreal permafrost soil to create a model that allows them to estimate winter (October through the end of April) soil carbon flux over the 2003-2017 period. They also drive their model with global climate model output, to make projections of future CO2 flux in the region. They estimate that approximately 1.7 gigatonnes of carbon (GtC) were released each winter over the 2003-2017 period. The authors also find that, of the variables that they tested, soil temperature had the largest relative influence on CO2 flux. Their projections show future winter Arctic soil fluxes of about 2.0 GtC per year by 2100, for a moderate emissions scenario, and about 2.3 GtC per year, assuming a high-emissions scenario.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: May 2020

    The May 2020 edition of the PCIC Update opens with a special update on COVID-19. This issue contains the following Project and Research Updates: Modelling Climate Impacts on the Nechako River, Okanagan Climate Projections Report Gets Media Attention and New Hydrologic Model Output Available on PCIC's Data Portal. The May 2020 Staff Profile is Dr. Kai Tsuruta. The Education and Outreach section contains the following stories: Presentation on Climate Tools for Resource Road Adaptation, New User Training Material Available, The Pacific Climate Seminar Series (on Dr. Robert Gifford's talk), Future Webinars and PCIC Corporate Report Released. The newsletter also discusses staff changes at PCIC and lists recent publications.

  • Authors: Regional District of North Okanagan, Regional District of Central Okanagan, Regional District of Okanagan-Similkameen, Pinna Sustainability, Natural Resources Canada, Okanagan Basin Water Board Publication Date: Apr 2020

    This report is intended to support a local understanding of how climate across the Okanagan is projected to change, and inform regional planning on how to prepare for future climate events. This report offers climate projections for both the 2050s and the 2080s. The 2050s projections are useful for medium-term planning purposes, while the 2080s provide guidance for long-term planning and decision-making.

  • 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.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Feb 2020

    This is the February 2020 issue of the PCIC Update newsletter. This issue contains the following stories detailing project and research updates: PCIC Data Used in Overheating and Air Quality Guide, Northeast Region Assessment Report Released, The Impact of Dynamical Changes on Atmospheric Rivers Over Western North America, Climate Science Course for Working Professionals in BC, Climate Information for Decision Making Webinar, A PCIC Researcher’s Experience at the Northwest Climate Science Conference, BC Hydro Agreement Renewal, Future Weather Files and a new agreement with the Ministry of Transportation and Infrastructure. The staff profile is on Rod Glover. The PCIC Science Brief is on The Human Influence on North American and Eurasian Precipitation. The staff news section contains a welcome to Md. Shahabul Alam.

  • 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.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Jan 2020

    This is the Pacific Climate Impacts Consortium's 2018-2019 Corporate Report.

  • Authors: Wang, Y., C. Curry, C. Ballantyne, F. Anslow and F. Zwiers Publication Date: Dec 2019

    Analysis of extreme snow events is of great importance in many areas, including risk management and structural design. Severe natural hazards in the mountain regions, such as avalanche, are largely due to heavy snowfall events and seasonally evolving snow-pack. Moreover, guidelines for infrastructure design should include estimates of maximum snow load, not only historically but also as projected under future climate change.

    In this work, we compute annual maximum time series from daily snow depth and snow water equivalent (SWE) data at over 2000 meteorological stations across Canada from 1939- 2016. The more extensive snow depth results are converted to snow loads by applying a suitable density curve that empirically relates extreme snow depth to extreme snow load. An extreme value analysis of the latter is then conducted using the generalized extreme value (GEV) distribution, providing a description of the heavy tail behaviour of the historical snow load. Finally, return values of annual snow load are computed for a range of return periods and compared to previous estimates from the 2015 edition of the National Building Code of Canada.

  • 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.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Nov 2019

    Understanding how human influences are affecting different parts of the climate system allows us to improve future climate projections. Due to the relative sparsity of precipitation data and the large amount of internal variability that it exhibits, detecting and attributing the human influence on precipitation is difficult. This Science Brief covers recent research that uses information about the physical processes responsible for precipitation in order to detect the anthropogenic influence on winter precipitation over North America and Eurasia over the 1920-2015 period.

    Publishing in Geophysical Research Letters, Guo et al. (2019) use a technique known as "dynamical adjustment," to estimate the atmospheric circulation and thermodynamic contributions to observed precipitation over Eastern North America and Northern Eurasia over the 1920-2015 period. They find that the thermodynamic component, due to anthropogenic emissions, contributes to increases in precipitation in both regions. They then compare the spatial pattern and magnitude of these components to those obtained from global climate models driven with anthropogenic forcings. They find strong agreement between the thermodynamic components of precipitation obtained from the observational data and those obtained from climate model output.

  • 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.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Oct 2019

    The October 2019 edition of the PCIC Update newsletter contains stories on: new adaptation reports for the Kootenay and Boundary, and Bulkley Nechako and Fraser-Fort George regions; work on PCIC's online tools; a co-produced report on the Cowichan Valley which was featured in the media; the new Gridded Hydrologic Model Output Data Portal page; the new video series on climate change and BC agriculture; ClimateData.ca going live and PCIC research to support salmon conservation. The newsletter also has a staff profile on Kari Tyler and covers the Pacific Climate Seminar Series, staff changes at PCIC and recent PCIC publications.

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