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Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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Abstract

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

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Acknowledgments

This work has been conducted under the framework of ISIMIP, funded by the German Federal Ministry of Education and Research (BMBF) with project funding reference number 01LS1201A. Responsibility for the content of this publication lies with the authors. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the respective climate modelling groups for producing and making available their model output. We also acknowledge the support of the Global Runoff Data Centre and of the Environment Research and Technology Development Fund (S-10) of the Ministry of the Environment, Japan. This work was supported by Japan Society for the Promotion of Science KAKENHI (16H06291), and the Program for Risk Information on Climate Change supported by the Ministry of Education, Culture,Sports, Science, and Technology-Japan (MEXT).

Author information

Authors and Affiliations

  1. Potsdam Institute for Climate Impact Research, Potsdam, Germany

    F. F. Hattermann, V. Krysanova, S. Huang, C. Müller & D. Gerten

  2. School of Geography, University of Nottingham, Nottingham, UK

    S. N. Gosling

  3. Met Office, Exeter, UK

    R. Dankers

  4. University of Guelph, Guelph, Canada

    P. Daggupati

  5. Swedish Meteorological and Hydrological Institute, Norrköping, Sweden

    C. Donnelly

  6. Center for Environmental Systems Research, University of Kassel, Kassel, Germany

    M. Flörke

  7. Water Problems Institute of Russian Academy of Science, Moscow, Russia

    Y. Motovilov

  8. National Climate Center, China Meteorological Administration, Beijing, China

    S. Buda

  9. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China

    T. Yang

  10. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Beijing, China

    T. Yang

  11. Joint Global Change Research Institute, Pacific Northwest National Laboratory, Richland, WA, USA

    G. Leng

  12. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

    Q. Tang

  13. Institute of Physical Geography, Johann Wolfgang Goethe-University Frankfurt am Main, Frankfurt, Germany

    F. T. Portmann

  14. Max Planck Institute for Meteorology, Hamburg, Germany

    S. Hagemann

  15. Geography Department, Humboldt-Universität zu Berlin, Berlin, Germany

    D. Gerten

  16. NASA Goddard Institute for Space Studies, New York, NY, USA

    Y. Wada

  17. Center for Climate Systems Research, Columbia University, New York, NY, USA

    Y. Wada

  18. Faculty of Geosciences, Utrecht University, Utrecht, The Netherlands

    Y. Wada

  19. Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Japan

    Y. Masaki

  20. Vrije Universiteit Brussel, Brussel, Belgium

    T. Alemayehu

  21. International Institute for Applied Systems Analysis, Laxenburg, Austria

    Y. Wada & Y. Satoh

  22. UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany

    L. Samaniego

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  1. F. F. Hattermann
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  2. V. Krysanova
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  3. S. N. Gosling
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  13. G. Leng
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  14. Q. Tang
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  16. S. Hagemann
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  18. Y. Wada
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  19. Y. Masaki
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  21. Y. Satoh
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  22. L. Samaniego
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Corresponding author

Correspondence to F. F. Hattermann.

Additional information

This article is part of a Special Issue on “Hydrological Model Intercomparison for Climate Impact Assessment” edited by Valentina Krysanova and Fred Hattermann.

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Hattermann, F.F., Krysanova, V., Gosling, S.N. et al. Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins. Climatic Change 141, 561–576 (2017). https://doi.org/10.1007/s10584-016-1829-4

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