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Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends

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Abstract

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.

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Acknowledgments

The authors wish to thank the city of Longueuil (Quebec, Canada) for the support for this research. We would further like to thank the anonymous reviewers and editor for the comments and suggestions on the manuscript. Special thanks to Julien Boé from French Climate Modeling and Global Change Team, CERFACS/CNRS for stimulating the discussions and his agreement for Fig. 2.

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Authors and Affiliations

  1. Department of Construction Engineering, École de technologie supérieure, Université du Québec, 1100 Notre-Dame Street West, Montréal, Québec, H3C 1K3, Canada

    Eustache Gooré Bi & Frédéric Monette

  2. Department of Civil Engineering, City of Longueuil, 4250, chemin de la Savane, Longueuil, Québec, J3Y 9G4, Canada

    Eustache Gooré Bi

  3. Centre pour l’Étude et la Simulation du Climat à l’Échelle Régionale (ESCER), Université du Québec à Montréal (UQAM), Montréal, Québec, Canada

    Philippe Gachon

  4. Laboratoire des Sciences du Climat et de l’Environnement-IPSL, CNRS/CEA/UVSQ, Orme des Merisiers, 91191, Gif-sur-Yvette, France

    Mathieu Vrac

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  1. Eustache Gooré Bi
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  2. Philippe Gachon
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  3. Mathieu Vrac
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  4. Frédéric Monette
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Correspondence to Eustache Gooré Bi.

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Gooré Bi, E., Gachon, P., Vrac, M. et al. Which downscaled rainfall data for climate change impact studies in urban areas? Review of current approaches and trends. Theor Appl Climatol 127, 685–699 (2017). https://doi.org/10.1007/s00704-015-1656-y

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  • DOI: https://doi.org/10.1007/s00704-015-1656-y

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