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Assessment of future precipitation indices in the Shikoku region using a statistical downscaling model

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Abstract

In this study, we used the statistical downscaling model (SDSM) to estimate mean and extreme precipitation indices under present and future climate conditions for Shikoku, Japan. Specifically, we considered the following mean and extreme precipitation indices: mean daily precipitation, R10 (number of days with precipitation >10 mm/day), R5d (annual maximum precipitation accumulated over 5 days), maximum dry-spell length (MaDSL), and maximum wet-spell length (MaWSL). Initially, we calibrated the SDSM model using the National Center for environmental prediction (NCEP) reanalysis dataset and daily time series of precipitation for ten locations in Shikoku which were acquired from the surface weather observation point dataset. Subsequently, we used the validated SDSM, using data from NCEP and outputs form general circulation models (GCM), to predict future precipitation indices. Specifically, the HadCM3 GCM was run under the special report on emissions scenarios (SRES) A2 and B2 scenarios, and the CGCM3 GCM was run under the SRES A2 and A1B scenarios. The results showed that: (1) the SDSM can reasonably be used to simulate mean and extreme precipitation indices in the Shikoku region; (2) the values of annual R10 were predicated to decrease in the future in northern Shikoku under all climate scenarios; conversely, the values of annual R10 were predicted to increase in the future in the range of 0–15 % in southern and western Shikoku. The values of annual MaDSL were predicted to increase in northern Shikoku, and the values of annual MaWSL were predicted to decrease in northeastern Shikoku; (3) the spatial variation of precipitation indices indicated the potential for an increased occurrence of drought across northeastern Shikoku and an increased occurrence of flood events in the southwestern part of Shikoku, especially under the A2 and A1B scenarios; (4) characteristics of future precipitation may differ between the northern and southern sides of the Shikoku Mountains. Regional variations in extreme precipitation indices were not notably evident in the B2 scenario compared to the other scenarios.

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Authors and Affiliations

  1. Department of Environmental and Agricultural Engineering, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo, 183-8509, Japan

    Kenichi Tatsumi

  2. Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, 3172-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa, 236-0001, Japan

    Tsutao Oizumi

  3. Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, 69, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan

    Yosuke Yamashiki

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  1. Kenichi Tatsumi
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  2. Tsutao Oizumi
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  3. Yosuke Yamashiki
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Correspondence to Kenichi Tatsumi.

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Tatsumi, K., Oizumi, T. & Yamashiki, Y. Assessment of future precipitation indices in the Shikoku region using a statistical downscaling model. Stoch Environ Res Risk Assess 28, 1447–1464 (2014). https://doi.org/10.1007/s00477-014-0847-x

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