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Percentile indices for assessing changes in heavy precipitation events

Author

Listed:
  • Christoph Schär

    (ETH Zürich)

  • Nikolina Ban

    (ETH Zürich)

  • Erich M. Fischer

    (ETH Zürich)

  • Jan Rajczak

    (ETH Zürich)

  • Jürg Schmidli

    (Goethe-University)

  • Christoph Frei

    (Federal Office of Meteorology and Climatology MeteoSwiss)

  • Filippo Giorgi

    (Abdus Salam International Centre for Theoretical Physics)

  • Thomas R. Karl

    (National Center for Environmental Information, NOAA)

  • Elizabeth J. Kendon

    (Met Office Hadley Centre)

  • Albert M. G. Klein Tank

    (Royal Netherlands Meteorological Institute (KNMI))

  • Paul A. O’Gorman

    (Department of Earth, Atmospheric and Planetary Sciences, MIT)

  • Jana Sillmann

    (CICERO Center for International Climate and Environmental Research)

  • Xuebin Zhang

    (Climate Research, Environment and Climate Change Canada)

  • Francis W. Zwiers

    (University of Victoria)

Abstract

Many climate studies assess trends and projections in heavy precipitation events using precipitation percentile (or quantile) indices. Here we investigate three different percentile indices that are commonly used. We demonstrate that these may produce very different results and thus require great care with interpretation. More specifically, consideration is given to two intensity-based indices and one frequency-based index, namely (a) all-day percentiles, (b) wet-day percentiles, and (c) frequency indices based on the exceedance of a percentile threshold. Wet-day percentiles are conditionally computed for the subset of wet events (with precipitation exceeding some threshold, e.g. 1 mm/d for daily precipitation). We present evidence that this commonly used methodology can lead to artifacts and misleading results if significant changes in the wet-day frequency are not accounted for. Percentile threshold indices measure the frequency of exceedance with respect to a percentile-based threshold. We show that these indices yield an assessment of changes in heavy precipitation events that is qualitatively consistent with all-day percentiles, but there are substantial differences in quantitative terms. We discuss the reasons for these effects, present a theoretical assessment, and provide a series of examples using global and regional climate models to quantify the effects in typical applications. Application to climate model output shows that these considerations are relevant to a wide range of typical climate-change applications. In particular, wet-day percentiles generally yield different results, and in most instances should not be used for the impact-oriented assessment of changes in heavy precipitation events.

Suggested Citation

  • Christoph Schär & Nikolina Ban & Erich M. Fischer & Jan Rajczak & Jürg Schmidli & Christoph Frei & Filippo Giorgi & Thomas R. Karl & Elizabeth J. Kendon & Albert M. G. Klein Tank & Paul A. O’Gorman & , 2016. "Percentile indices for assessing changes in heavy precipitation events," Climatic Change, Springer, vol. 137(1), pages 201-216, July.
  • Handle: RePEc:spr:climat:v:137:y:2016:i:1:d:10.1007_s10584-016-1669-2
    DOI: 10.1007/s10584-016-1669-2
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    References listed on IDEAS

    as
    1. Boris Orlowsky & Sonia Seneviratne, 2012. "Global changes in extreme events: regional and seasonal dimension," Climatic Change, Springer, vol. 110(3), pages 669-696, February.
    2. Myles R. Allen & William J. Ingram, 2002. "Constraints on future changes in climate and the hydrologic cycle," Nature, Nature, vol. 419(6903), pages 224-232, September.
    3. Elizabeth J. Kendon & Nigel M. Roberts & Hayley J. Fowler & Malcolm J. Roberts & Steven C. Chan & Catherine A. Senior, 2014. "Heavier summer downpours with climate change revealed by weather forecast resolution model," Nature Climate Change, Nature, vol. 4(7), pages 570-576, July.
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    Cited by:

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    2. Goyal, Manish Kumar & Gupta, Anil Kumar & Jha, Srinidhi & Rakkasagi, Shivukumar & Jain, Vijay, 2022. "Climate change impact on precipitation extremes over Indian cities: Non-stationary analysis," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    3. Pinto, Bruno Chaves Morone & Fulginiti, Lilyan E. & Perrin, Richard K., 2022. "Tradeoff Between Irrigated Land Area And Counties’ Revenues In The High Plains Aquifer," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322391, Agricultural and Applied Economics Association.
    4. Changyan Yin & Jiayi Wang & Xin Yu & Yong Li & Denghua Yan & Shengqi Jian, 2022. "Definition of Extreme Rainfall Events and Design of Rainfall Based on the Copula Function," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3759-3778, August.
    5. Wenhui Liu & Jidong Wu & Rumei Tang & Mengqi Ye & Jing Yang, 2020. "Daily Precipitation Threshold for Rainstorm and Flood Disaster in the Mainland of China: An Economic Loss Perspective," Sustainability, MDPI, vol. 12(1), pages 1-14, January.

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