Editorial Type:
Article
Article Type:
Research Article

Reconstruction of the Spring 2011 Richelieu River Flood by Two Regional Climate Models and a Hydrological Model

Philippe Lucas-Picher Centre pour l’étude et la simulation du climat à l’échelle régionale, Département des sciences de la Terre et de l’atmosphère, Université du Québec à Montréal, and Département de génie de la construction, École de Technologie Supérieure, Université du Québec, Montréal, Québec, Canada

Search for other papers by Philippe Lucas-Picher in
Current site
Google Scholar
PubMed Close
,
Philippe Riboust Département de génie de la construction, École de Technologie Supérieure, Université du Québec, Montréal, Québec, Canada

Search for other papers by Philippe Riboust in
Current site
Google Scholar
PubMed Close
,
Samuel Somot Centre National de Recherches Météorologiques (CNRM-GAME), Météo-France/CNRS, Toulouse, France

Search for other papers by Samuel Somot in
Current site
Google Scholar
PubMed Close
, and
René Laprise Centre pour l’étude et la simulation du climat à l’échelle régionale, Département des sciences de la Terre et de l’atmosphère, Université du Québec à Montréal, Montréal, Québec, Canada

Search for other papers by René Laprise in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Feb 2015
DOI:
https://doi.org/10.1175/JHM-D-14-0116.1
Page(s):
36–54
Restricted access

Abstract

Climate simulations made with two regional climate models (RCMs), the French Aire Limitée Adaptation Dynamique Développement International (ALADIN) and the Canadian Regional Climate Model, version 5 (CRCM5), operating on 10-km meshes for the period 1989–2011, and the Hydro-Québec hydrological model (HSAMI), are used to reconstruct the spring 2011 Richelieu River flood in the southern region of the province of Québec, Canada. The analysis shows that the simulated fields of 2-m air temperature, precipitation, and snow water equivalent by the RCMs closely match the observations with similar multiyear means and a high correlation of the monthly anomalies. The climatic conditions responsible for the 2011 flood are generally well simulated by the RCMs. The use of multidecadal RCM simulations facilitates the identification of anomalies that contributed to the flood. The flood was linked to a combination of factors: the 2010/11 winter was cold and snowy, the snowmelt in spring was fast, and there was a record amount of precipitation in April and May. Driven by outputs from the RCMs, HSAMI was able to reproduce the mean hydrograph of the Richelieu River, but it underestimated the peak of the 2011 flood. HSAMI adequately computes the water transport from the mountains to the river mouth and the storage effect of Lake Champlain, which dampens the flood over a long period. Overall, the results suggest that RCM simulations can be useful for reconstructing high-resolution climate information and providing new variables that can help better understand the causes of extreme climatic events.

Corresponding author address: Dr. Philippe Lucas-Picher, Centre ESCER, Dép. des sciences de la Terre et de l’atmosphère, UQÀM, P.O. Box 8888, Stn. Downtown, Montréal QC H3C 3P8, Canada. E-mail: plp@sca.uqam.ca

Abstract

Climate simulations made with two regional climate models (RCMs), the French Aire Limitée Adaptation Dynamique Développement International (ALADIN) and the Canadian Regional Climate Model, version 5 (CRCM5), operating on 10-km meshes for the period 1989–2011, and the Hydro-Québec hydrological model (HSAMI), are used to reconstruct the spring 2011 Richelieu River flood in the southern region of the province of Québec, Canada. The analysis shows that the simulated fields of 2-m air temperature, precipitation, and snow water equivalent by the RCMs closely match the observations with similar multiyear means and a high correlation of the monthly anomalies. The climatic conditions responsible for the 2011 flood are generally well simulated by the RCMs. The use of multidecadal RCM simulations facilitates the identification of anomalies that contributed to the flood. The flood was linked to a combination of factors: the 2010/11 winter was cold and snowy, the snowmelt in spring was fast, and there was a record amount of precipitation in April and May. Driven by outputs from the RCMs, HSAMI was able to reproduce the mean hydrograph of the Richelieu River, but it underestimated the peak of the 2011 flood. HSAMI adequately computes the water transport from the mountains to the river mouth and the storage effect of Lake Champlain, which dampens the flood over a long period. Overall, the results suggest that RCM simulations can be useful for reconstructing high-resolution climate information and providing new variables that can help better understand the causes of extreme climatic events.

Corresponding author address: Dr. Philippe Lucas-Picher, Centre ESCER, Dép. des sciences de la Terre et de l’atmosphère, UQÀM, P.O. Box 8888, Stn. Downtown, Montréal QC H3C 3P8, Canada. E-mail: plp@sca.uqam.ca
Save
Cover Journal of Hydrometeorology
Journal of Hydrometeorology

  • Alexandru, A., de Elía R. , and Laprise R. , 2007: Internal variability in regional climate downscaling at the seasonal scale. Mon. Wea. Rev., 135, 3221–3238, doi:10.1175/MWR3456.1.

    • Search Google Scholar
    • Export Citation

  • Anderson, C. J., and Coauthors, 2003: Hydrological processes in regional climate model simulations of the central United States flood of June–July 1993. J. Hydrometeor., 4, 584–598, doi:10.1175/1525-7541(2003)004<0584:HPIRCM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bisson, J. L., and Roberge F. , 1983: Prévisions des apports naturels: Expérience d’Hydro-Québec. Proc. Workshop on Flow Prediction, Toronto, ON, Canada, IEEE, 148–161.

  • Bougeault, P., 1985: A simple parameterization of the large-scale effects of cumulus convection. Mon. Wea. Rev., 113, 2108–2121, doi:10.1175/1520-0493(1985)113<2108:ASPOTL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Colin, J., Déqué M. , Radu R. , and Somot S. , 2010: Sensitivity study of heavy precipitations in Limited Area Model climate simulation: Influence of the size of the domain and the use of the spectral nudging technique. Tellus, 62A, 591–604, doi:10.1111/j.1600-0870.2010.00467.x.

    • Search Google Scholar
    • Export Citation

  • Côté, J., Gravel S. , Méthot A. , Patoine A. , Roch M. , and Staniforth A. , 1998: The operational CMC-MRB global environmental multiscale (GEM) model. Part I: Design considerations and formulation. Mon. Wea. Rev., 126, 1373–1395, doi:10.1175/1520-0493(1998)126<1373:TOCMGE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation

  • Déqué, M., and Somot S. , 2008: Analysis of heavy precipitation for France using ALADIN RCM simulations. Idojaras, 112, 179–190.

  • DiNapoli, S. M., and Misra V. , 2012: Reconstructing the 20th century high-resolution climate of the southeastern United States. J. Geophys. Res., 117, D19113, doi:10.1029/2012JD018303.

    • Search Google Scholar
    • Export Citation

  • Douville, H., Royer J.-F. , and Mahfouf J.-F. , 1995: A new snow parameterization for the Météo-France climate model. Part 1: Validation in stand-alone experiments. Climate Dyn., 12, 21–35, doi:10.1007/BF00208760.

    • Search Google Scholar
    • Export Citation

  • Fischer, E. M., Seneviratne S. I. , Vidale P. L. , Lüthi D. , and Schär C. , 2007: Soil moisture–atmosphere interactions during the 2003 European summer heat wave. J. Climate, 20, 5081–5099, doi:10.1175/JCLI4288.1.

    • Search Google Scholar
    • Export Citation

  • Flesch, T. K., and Reuter G. W. , 2012: WRF Model simulation of two Alberta flooding events and the impact of topography. J. Hydrometeor., 13, 695–708, doi:10.1175/JHM-D-11-035.1.

    • Search Google Scholar
    • Export Citation

  • Harris, I., Jones P. D. , Osborn T. J. , and Lister D. H. , 2014: Updated high-resolution grids of monthly climatic observations—The CRU TS3.10 Dataset. Int. J. Climatol., 34, 623–642, doi:10.1002/joc.3711.

    • Search Google Scholar
    • Export Citation

  • Hernández-Díaz, L., Laprise R. , Sushama L. , Martynov A. , Winger K. , and Dugas B. , 2013: Climate simulation over the CORDEX-Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5). Climate Dyn., 40, 1415–1433, doi:10.1007/s00382-012-1387-z.

    • Search Google Scholar
    • Export Citation

  • Herrmann, M. J., and Somot S. , 2008: Relevance of ERA40 dynamical downscaling for modeling deep convection in the Mediterranean Sea. Geophys. Res. Lett., 35, L04607, doi:10.1029/2007GL032442.

    • Search Google Scholar
    • Export Citation

  • Herrmann, M. J., Somot S. , Calmanti S. , Dubois C. , and Sevault F. , 2011: Representation of spatial and temporal variability of daily wind speed and of intense wind events over the Mediterranean Sea using dynamical downscaling: Impact of the regional climate model configuration. Nat. Hazards Earth Syst. Sci., 11, 1983–2001, doi:10.5194/nhess-11-1983-2011.

    • Search Google Scholar
    • Export Citation

  • International Joint Commission, 2013: Plan of study for the identification of measures to mitigate flooding and the impacts of flooding of Lake Champlain and Richelieu River. IJC Rep., 128 pp. [Available online at www.ijc.org/files/publications/Final_PoS_LakeChamplain-RichelieuRiver.pdf.]

  • Kain, J. S., and Fritsch J. M. , 1990: A one-dimensional entraining/detraining plume model and application in convective parameterization. J. Atmos. Sci., 47, 2784–2802, doi:10.1175/1520-0469(1990)047<2784:AODEPM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kanamitsu, M., and Kanamaru H. , 2007: Fifty-seven-year California reanalysis downscaling at 10 km (CaRD10). Part I: System detail and validation with observations. J. Climate, 20, 5553–5571, doi:10.1175/2007JCLI1482.1.

    • Search Google Scholar
    • Export Citation

  • Kanamitsu, M., Ebisuzaki W. , Woollen J. , Yang S.-K. , Hnilo J. J. , Fiorino M. , and Potter G. L. , 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 1631–1643, doi:10.1175/BAMS-83-11-1631.

    • Search Google Scholar
    • Export Citation

  • Kotlarski, S., Hagemann S. , Krahe P. , Podzun R. , and Jacob D. , 2012: The Elbe River flooding 2002 as seen by an extended regional climate model. J. Hydrol., 472–473, 169–183, doi:10.1016/j.jhydrol.2012.09.020.

    • Search Google Scholar
    • Export Citation

  • Laprise, R., Hernández-Díaz L. , Tete K. , Sushama L. , Šeparović L. , Martynov A. , Winger K. , and Valin M. , 2013: Climate projections over CORDEX Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5). Climate Dyn., 41, 3219–3246, doi:10.1007/s00382-012-1651-2.

    • Search Google Scholar
    • Export Citation

  • Leung, L. R., 2012: Regional climate models. Climate Change Modeling Methodology: Selected Entries from the Encyclopedia of Sustainability Science and Technology, P. J. Rasch, Ed., Springer, 211–233, doi:10.1007/978-1-4614-5767-1_9.

  • Leung, L. R., and Qian Y. , 2003: The sensitivity of precipitation and snowpack simulations to model resolution via nesting in regions of complex terrain. J. Hydrometeor., 4, 1025–1043, doi:10.1175/1525-7541(2003)004<1025:TSOPAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Leung, L. R., Qian Y. , and Bian X. , 2003a: Hydroclimate of the western United States based on observations and regional climate simulations of 1981–2000. Part I: Seasonal statistics. J. Climate, 16, 1892–1911, doi:10.1175/1520-0442(2003)016<1892:HOTWUS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Leung, L. R., Qian Y. , Han J. , and Roads J. O. , 2003b: Intercomparison of global reanalyses and regional simulations of cold season water budgets in the western United States. J. Hydrometeor., 4, 1067–1087, doi:10.1175/1525-7541(2003)004<1067:IOGRAR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lim, Y.-K., Stefanova L. B. , Chan S. C. , Schubert S. D. , and O’Brien J. J. , 2011: High-resolution subtropical summer precipitation derived from dynamical downscaling of the NCEP/DOE reanalysis: How much small-scale information is added by a regional model? Climate Dyn., 37, 1061–1080, doi:10.1007/s00382-010-0891-2.

    • Search Google Scholar
    • Export Citation

  • Livneh, B., Rosenberg E. A. , Lin C. , Nijssen B. , Mishra V. , Andreadis K. M. , Maurer E. P. , and Lettenmaier D. P. , 2013: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States: Update and extensions. J. Climate, 26, 9384–9392, doi:10.1175/JCLI-D-12-00508.1.

    • Search Google Scholar
    • Export Citation

  • Lorenz, C., and Kunstmann H. , 2012: The hydrological cycle in three state-of-the-art reanalyses: Intercomparison and performance analysis. J. Hydrometeor., 13, 1397–1420, doi:10.1175/JHM-D-11-088.1.

    • Search Google Scholar
    • Export Citation

  • Lucas-Picher, P., Arora V. K. , Caya D. , and Laprise R. , 2003: Implementation of a large-scale variable velocity river flow routing algorithm in the Canadian regional climate model. Atmos.–Ocean, 41, 139–153, doi:10.3137/ao.410203.

    • Search Google Scholar
    • Export Citation

  • Lucas-Picher, P., Caya D. , Biner S. , and Laprise R. , 2008a: Quantification of the lateral boundary forcing of a regional climate model using an ageing tracer. Mon. Wea. Rev., 136, 4980–4996, doi:10.1175/2008MWR2448.1.

    • Search Google Scholar
    • Export Citation

  • Lucas-Picher, P., Caya D. , de Elía R. , and Laprise R. , 2008b: Investigation of regional climate models’ internal variability with a ten-member ensemble of ten years over a large domain. Climate Dyn., 31, 927–940, doi:10.1007/s00382-008-0384-8.

    • Search Google Scholar
    • Export Citation

  • Lucas-Picher, P., Boberg F. , Christensen J. H. , and Berg P. , 2013a: Dynamical downscaling with reinitializations: A method to generate finescale climate datasets suitable for impact studies. J. Hydrometeor., 14, 1159–1174, doi:10.1175/JHM-D-12-063.1.

    • Search Google Scholar
    • Export Citation

  • Lucas-Picher, P., Somot S. , Déqué M. , Decharme B. , and Alias A. , 2013b: Evaluation of the regional climate model ALADIN to simulate the climate over North America in the CORDEX framework. Climate Dyn., 41, 1117–1137, doi:10.1007/s00382-012-1613-8.

    • Search Google Scholar
    • Export Citation

  • Martynov, A., Laprise R. , Sushama L. , Winger K. , Šeparović L. , and Dugas B. , 2013: Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: Model performance evaluation. Climate Dyn., 41, 2973–3005, doi:10.1007/s00382-013-1778-9.

    • Search Google Scholar
    • Export Citation

  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343–360, doi:10.1175/BAMS-87-3-343.

    • Search Google Scholar
    • Export Citation

  • Minville, M., Brissette F. , and Leconte R. , 2008: Uncertainty of the impact of climate change on the hydrology of a Nordic watershed. J. Hydrol., 358, 70–83, doi:10.1016/j.jhydrol.2008.05.033.

    • Search Google Scholar
    • Export Citation

  • Noilhan, J., and Planton S. , 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, 536–549, doi:10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Radu, R., Déqué M. , and Somot S. , 2008: Spectral nudging in a spectral regional climate model. Tellus, 60A, 898–910, doi:10.1111/j.1600-0870.2008.00341.x.

    • Search Google Scholar
    • Export Citation

  • Rasmussen, R., and Coauthors, 2011: High-resolution coupled climate runoff simulations of seasonal snowfall over Colorado: A process study of current and warmer climate. J. Climate, 24, 3015–3048, doi:10.1175/2010JCLI3985.1.

    • Search Google Scholar
    • Export Citation

  • Riboust, P., and Brissette F. , 2014a: Climate change impacts and uncertainties on spring flooding of Lake Champlain and the Richelieu River. J. Amer. Water Resour. Assoc., in press.

    • Search Google Scholar
    • Export Citation

  • Riboust, P., and Brissette F. , 2014b: Analysis of Lake-Champlain/Richelieu River's historical 2011 flood. Can. Water Resour. J., in press.

    • Search Google Scholar
    • Export Citation

  • Ricard, J. L., and Royer J. F. , 1993: A statistical cloud scheme for use in an AGCM. Ann. Geophys., 11, 1095–1115.

  • Rienecker, M. M., and Coauthors, 2011: MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 3624–3648, doi:10.1175/JCLI-D-11-00015.1.

    • Search Google Scholar
    • Export Citation

  • Rost, A., 2010: Snow board: A look at the importance of snow information. Meteorological Technology International, June 2010, UKiP, Dorking, United Kingdom, 26–29.

  • Rummukainen, M., 2010: State-of-the-art with regional climate models. Wiley Interdiscip. Rev.: Climate Change,1, 82–96, doi:10.1002/wcc.8.

  • Salzmann, N., and Mearns L. O. , 2012: Assessing the performance of multiple regional climate model simulations for seasonal mountain snow in the upper Colorado River basin. J. Hydrometeor., 13, 539–556, doi:10.1175/2011JHM1371.1.

    • Search Google Scholar
    • Export Citation

  • Sanchez-Gomez, E., Somot S. , and Déqué M. , 2009a: Ability of an ensemble of regional climate models to reproduce the weather regimes during the period 1961–2000. Climate Dyn., 33, 723–736, doi:10.1007/s00382-008-0502-7.

    • Search Google Scholar
    • Export Citation

  • Sanchez-Gomez, E., Somot S. , and Mariotti A. , 2009b: Future changes in the Mediterranean water budget projected by an ensemble of regional climate models. Geophys. Res. Lett., 36, L21401, doi:10.1029/2009GL040120.

    • Search Google Scholar
    • Export Citation

  • Šeparović, L., Alexandru A. , Laprise R. , Martynov A. , Sushama L. , Winger K. , Tete K. , and Valin M. , 2013: Present climate and climate change over North America as simulated by the fifth-generation Canadian Regional Climate Model (CRCM5). Climate Dyn., 41, 3167–3201, doi:10.1007/s00382-013-1737-5.

    • Search Google Scholar
    • Export Citation

  • Sheffield, J., Livneh B. , and Wood E. F. , 2012: Representation of terrestrial hydrology and large-scale drought of the continental United States from the North American Regional Reanalysis. J. Hydrometeor., 13, 856–876, doi:10.1175/JHM-D-11-065.1.

    • Search Google Scholar
    • Export Citation

  • Stefanova, L., Misra V. , Chan S. , Griffin M. , O’Brien J. J. , and Smith T. J. III, 2012: A proxy for high-resolution regional reanalysis for the southeast United States: Assessment of precipitation variability in dynamically downscaled reanalyses. Climate Dyn., 38, 2449–2466, doi:10.1007/s00382-011-1230-y.

    • Search Google Scholar
    • Export Citation

  • Sundqvist, H., Berge E. , and Kristjansson J. E. , 1989: Condensation and cloud parameterization studies with a mesoscale numerical weather prediction model. Mon. Wea. Rev., 117, 1641–1657, doi:10.1175/1520-0493(1989)117<1641:CACPSW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Verseghy, D. L., 2009: CLASS—The Canadian Land Surface Scheme (version 3.4): Technical documentation (version 1.1). Internal Rep., Climate Research Division, Science and Technology Branch, Environment Canada, 180 pp. [Available online at www.usask.ca/ip3/download/CLASS_v3_4_Documentation_v1_1.pdf.]

  • Voldoire, A., and Coauthors, 2013: The CNRM-CM5.1 global climate model: Description and basic evaluation. Climate Dyn., 40, 2091–2121, doi:10.1007/s00382-011-1259-y.

    • Search Google Scholar
    • Export Citation

  • von Storch, H., Zorita E. , and Cubasch U. , 1993: Downscaling of global climate change estimates to regional scales: An application to Iberian rainfall in wintertime. J. Climate, 6, 1161–1171, doi:10.1175/1520-0442(1993)006<1161:DOGCCE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 409 76 6
PDF Downloads 127 48 6