Projected Hydroclimatic Changes in Two Major River Basins at the Canadian West Coast Based on High-Resolution Regional Climate Simulations

Andre R. Erler Department of Physics, University of Toronto, Toronto, Ontario, Canada

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W. Richard Peltier Department of Physics, University of Toronto, Toronto, Ontario, Canada

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Abstract

The impact of anthropogenic climate change on water resources and flood and drought risk is of great interest for impact modeling and to inform adaptation strategies. Here an analysis of hydroclimatic changes in the Fraser and Athabasca River basins in western Canada is presented, based on an ensemble of climate projections, which have been dynamically downscaled to 10-km resolution using the Weather Research and Forecasting Model in two configurations. The GCM ensemble comprises four independent integrations of the Community Earth System Model under the representative concentration pathway 8.5. Basin-integrated changes in the seasonal cycle of hydroclimatic variables, and the variability of water supply and flood and drought risk, are considered. It is found that fall and winter precipitation generally increase by 20%–30% toward the end of the century, while changes in summer precipitation are smaller and associated with high model uncertainty. Furthermore, a reduction in snowfall and an increase in evapotranspiration are projected. However, projected impacts on water resources east and west of the Rocky Mountains are quite different: in basins closer to the coast (west of the Rocky Mountains) higher temperatures lead to a transition from predominantly solid to liquid precipitation and a significantly weaker spring freshet, followed by drier summers. In the lee of the Rocky Mountains the spring freshet remains largely unaffected and in summer the increase in evapotranspiration (ET) is compensated by increasing precipitation, so that water balance changes appear to be small. It is further found that a shift in runoff seasonality near the coast may lead to significantly increased flood risk in fall.

Supplemental information related to this paper is available at the Journals Online website: https://dx.doi.org/10.1175/JCLI-D-16-0870.s1.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Andre R. Erler, aerler@atmosp.physics.utoronto.ca

Abstract

The impact of anthropogenic climate change on water resources and flood and drought risk is of great interest for impact modeling and to inform adaptation strategies. Here an analysis of hydroclimatic changes in the Fraser and Athabasca River basins in western Canada is presented, based on an ensemble of climate projections, which have been dynamically downscaled to 10-km resolution using the Weather Research and Forecasting Model in two configurations. The GCM ensemble comprises four independent integrations of the Community Earth System Model under the representative concentration pathway 8.5. Basin-integrated changes in the seasonal cycle of hydroclimatic variables, and the variability of water supply and flood and drought risk, are considered. It is found that fall and winter precipitation generally increase by 20%–30% toward the end of the century, while changes in summer precipitation are smaller and associated with high model uncertainty. Furthermore, a reduction in snowfall and an increase in evapotranspiration are projected. However, projected impacts on water resources east and west of the Rocky Mountains are quite different: in basins closer to the coast (west of the Rocky Mountains) higher temperatures lead to a transition from predominantly solid to liquid precipitation and a significantly weaker spring freshet, followed by drier summers. In the lee of the Rocky Mountains the spring freshet remains largely unaffected and in summer the increase in evapotranspiration (ET) is compensated by increasing precipitation, so that water balance changes appear to be small. It is further found that a shift in runoff seasonality near the coast may lead to significantly increased flood risk in fall.

Supplemental information related to this paper is available at the Journals Online website: https://dx.doi.org/10.1175/JCLI-D-16-0870.s1.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Andre R. Erler, aerler@atmosp.physics.utoronto.ca

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  • Abatzoglou, J. T., D. E. Rupp, and P. W. Mote, 2014: Seasonal climate variability and change in the Pacific Northwest of the United States. J. Climate, 27, 21252142, doi:10.1175/JCLI-D-13-00218.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Burn, D. H., 2008: Climatic influences on streamflow timing in the headwaters of the Mackenzie River Basin. J. Hydrol., 352, 225238, doi:10.1016/j.jhydrol.2008.01.019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Christensen, J. H., and Coauthors, 2014: Climate phenomena and their relevance for future regional climate change. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 1217–1308.

  • Cook, B. I., T. R. Ault, and J. E. Smerdon, 2015: Unprecedented 21st century drought risk in the American Southwest and central plains. Sci. Adv., 1, e1400082, doi:10.1126/sciadv.1400082.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dai, A., 2011: Drought under global warming: A review. Wiley Interdiscip. Rev.: Climate Change, 2, 4565, doi:10.1002/wcc.81.

  • Daly, C., M. Halbleib, J. I. Smith, W. P. Gibson, M. K. Doggett, G. H. Taylor, J. Curtis, and P. P. Pasteris, 2008: Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int. J. Climatol., 28, 20312064, doi:10.1002/joc.1688.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Das, T., D. W. Pierce, D. R. Cayan, J. A. Vano, and D. P. Lettenmaier, 2011: The importance of warm season warming to western U.S. streamflow changes. Geophys. Res. Lett., 38, L23403, doi:10.1029/2011GL049660.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., A. Phillips, V. Bourdette, and H. Teng, 2012: Uncertainty in climate change projections: The role of internal variability. Climate Dyn., 38, 527546, doi:10.1007/s00382-010-0977-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Efron, B., and R. J. Tibshirani, 1994: An Introduction to the Bootstrap. CRC Press, 456 pp.

    • Crossref
    • Export Citation
  • Eggert, B., P. Berg, J. Haerter, D. Jacob, and C. Moseley, 2015: Temporal and spatial scaling impacts on extreme precipitation. Atmos. Chem. Phys., 15, 59575971, doi:10.5194/acp-15-5957-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Endo, H., A. Kitoh, T. Ose, R. Mizuta, and S. Kusunoki, 2012: Future changes and uncertainties in Asian precipitation simulated by multiphysics and multi–sea surface temperature ensemble experiments with high-resolution Meteorological Research Institute atmospheric general circulation models (MRI-AGCMs). J. Geophys. Res., 117, D16118, doi:10.1029/2012JD017874.

    • Search Google Scholar
    • Export Citation
  • Erler, A. R., and W. R. Peltier, 2016: Projected changes in precipitation extremes for western Canada based on high-resolution regional climate simulations. J. Climate, 29, 88418863, doi:10.1175/JCLI-D-15-0530.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Erler, A. R., W. R. Peltier, and M. d’Orgeville, 2015: Dynamically downscaled high-resolution hydroclimate projections for western Canada. J. Climate, 28, 423450, doi:10.1175/JCLI-D-14-00174.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and Coauthors, 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991, doi:10.1175/2011JCLI4083.1.

  • Grell, G. A., and D. Dévényi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 1693, doi:10.1029/2002GL015311.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gula, J., and W. R. Peltier, 2012: Dynamical downscaling over the Great Lakes Basin of North America using the WRF regional climate model: The impact of the Great Lakes system on regional greenhouse warming. J. Climate, 25, 77237742, doi:10.1175/JCLI-D-11-00388.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harris, I., P. D. Jones, T. J. Osborn, and D. H. Lister, 2014: Updated high-resolution grids of monthly climatic observations—The CRU TS3.10 dataset. Int. J. Climatol., 34, 623642, doi:10.1002/joc.3711.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herring, S. C., M. P. Hoerling, T. C. Peterson, and P. A. Stott, 2014: Explaining extreme events of 2013 from a climate perspective. Bull. Amer. Meteor. Soc., 95, S1S104, doi:10.1175/1520-0477-95.9.S1.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). Asia-Pac. J. Atmos. Sci., 42, 129151.

  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170181, doi:10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Katz, R. W., M. B. Parlange, and P. Naveau, 2002: Statistics of extremes in hydrology. Adv. Water Resour., 25, 12871304, doi:10.1016/S0309-1708(02)00056-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kerkhoven, E., and T. Y. Gan, 2011: Differences and sensitivities in potential hydrologic impact of climate change to regional-scale Athabasca and Fraser River basins of the leeward and windward sides of the Canadian Rocky Mountains respectively. Climatic Change, 106, 583607, doi:10.1007/s10584-010-9958-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 11381140, doi:10.1126/science.1100217.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Leong, D. N., and S. D. Donner, 2015: Climate change impacts on streamflow availability for the Athabasca oil sands. Climatic Change, 133, 651663, doi:10.1007/s10584-015-1479-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lucas-Picher, P., D. Caya, R. de Elía, and R. Laprise, 2008: Investigation of regional climate models internal variability with a ten-member ensemble of 10-year simulations over a large domain. Climate Dyn., 31, 927940, doi:10.1007/s00382-008-0384-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maraun, D., and Coauthors, 2010: Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user. Rev. Geophys., 48, RG3003, doi:10.1029/2009RG000314.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mearns, L., and Coauthors, 2013: Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP). Climatic Change, 120, 965975, doi:10.1007/s10584-013-0831-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes. Mon. Wea. Rev., 137, 9911007, doi:10.1175/2008MWR2556.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mote, P. W., and E. P. Salathé, 2010: Future climate in the Pacific Northwest. Climatic Change, 102, 2950, doi:10.1007/s10584-010-9848-z.

  • Overpeck, J. T., 2013: Climate science: The challenge of hot drought. Nature, 503, 350351, doi:10.1038/503350a.

  • Pachauri, R. K., and Coauthors, 2014: Climatic Change 2014: Synthesis Report. IPCC, 151 pp.

  • Pollock, E. W., and A. B. G. Bush, 2013: Changes in snow mass balance in the Canadian Rocky Mountains caused by CO2 rise: Regional atmosphere model results. Atmos.–Ocean, 51, 505521, doi:10.1080/07055900.2013.852964.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rupp, D. E., J. T. Abatzoglou, and P. W. Mote, 2017: Projections of 21st century climate of the Columbia River basin. Climate Dyn., 49, 17831799, doi:10.1007/s00382-016-3418-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salathé, E. P., L. R. Leung, Y. Qian, and Y. Zhang, 2010: Regional climate model projections for the State of Washington. Climatic Change, 102, 5175, doi:10.1007/s10584-010-9849-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salathé, E. P., A. F. Hamlet, C. F. Mass, S.-Y. Lee, M. Stumbaugh, and R. Steed, 2014: Estimates of twenty-first-century flood risk in the Pacific Northwest based on regional climate model simulations. J. Hydrometeor., 15, 18811899, doi:10.1175/JHM-D-13-0137.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sauchyn, D. J., J.-M. St-Jacques, and B. H. Luckman, 2015: Long-term reliability of the Athabasca River (Alberta, Canada) as the water source for oil sands mining. Proc. Natl. Acad. Sci. USA, 112, 12 62112 626, doi:10.1073/pnas.1509726112.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schindler, A., A. Toreti, M. Zampieri, E. Scoccimarro, S. Gualdi, S. Fukutome, E. Xoplaki, and J. Luterbacher, 2015: On the internal variability of simulated daily precipitation. J. Climate, 28, 36243630, doi:10.1175/JCLI-D-14-00745.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, M. Ziese, and B. Rudolf, 2013: GPCC’s new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor. Appl. Climatol., 115, 1540, doi:10.1007/s00704-013-0860-x .

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., T. Corti, E. L. Davin, M. Hirschi, E. B. Jaeger, I. Lehner, B. Orlowsky, and A. J. Teuling, 2010: Investigating soil moisture–climate interactions in a changing climate: A review. Earth Sci. Rev., 99, 125161, doi:10.1016/j.earscirev.2010.02.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Šeparović, L., A. Alexandru, R. Laprise, A. Martynov, L. Sushama, K. Winger, K. Tete, and M. Valin, 2013: Present climate and climate change over North America as simulated by the fifth-generation Canadian regional climate model. Climate Dyn., 41, 31673201, doi:10.1007/s00382-013-1737-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shrestha, R. R., M. A. Schnorbus, A. T. Werner, and A. J. Berland, 2012: Modelling spatial and temporal variability of hydrologic impacts of climate change in the Fraser River basin, British Columbia, Canada. Hydrol. Processes, 26, 18401860, doi:10.1002/hyp.9283.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smirnov, N. V., 1939: On the estimation of the discrepancy between empirical curves of distribution for two independent samples. Bull. Math. Univ. Moscou, 2 (2), 3–14.

  • Smirnov, N. V., 1948: Table for estimating the goodness of fit of empirical distributions. Ann. Math. Stat., 19, 279281, doi:10.1214/aoms/1177730256.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steinskog, D. J., D. B. Tjøstheim, and N. G. Kvamstø, 2007: A cautionary note on the use of the Kolmogorov–Smirnov test for normality. Mon. Wea. Rev., 135, 11511157, doi:10.1175/MWR3326.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stott, P., 2015: Attribution: Weather risks in a warming world. Nat. Climate Change, 5, 517518, doi:10.1038/nclimate2640.

  • Teutschbein, C., and J. Seibert, 2012: Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods. J. Hydrol., 456457, 1229, doi:10.1016/j.jhydrol.2012.05.052.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Teutschbein, C., and J. Seibert, 2013: Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions? Hydrol. Earth Syst. Sci., 17, 50615077, doi:10.5194/hess-17-5061-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Teutschbein, C., F. Wetterhall, and J. Seibert, 2011: Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale. Climate Dyn., 37, 20872105, doi:10.1007/s00382-010-0979-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tewari, M., and Coauthors, 2004: Implementation and verification of the unified NOAH land surface model in the WRF model. 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 14.2a. [Available online at https://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm.]

  • von Storch, H., and F. W. Zwiers, 2002: Statistical Analysis in Climate Research. Cambridge University Press, 495 pp.

  • Wang, W., and Coauthors, 2012: ARW version 3 modeling system user’s guide (January 2012). Mesoscale & Miscroscale Meteorology Division, National Center for Atmospheric Research. [Available online at http://www2.mmm.ucar.edu/wrf/users/docs/user_guide_V3/contents.html.]

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