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A comparison of three multi-site statistical downscaling models for daily rainfall in the North China Plain

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Abstract

Three statistical downscaling methods (conditional resampling statistical downscaling model: CR-SDSM, the generalised linear model for daily climate time series: GLIMCLIM, and the non-homogeneous hidden Markov model: NHMM) for multi-site daily rainfall were evaluated and compared in the North China Plain (NCP). The comparison focused on a range of statistics important for hydrological studies including rainfall amount, extreme rainfall, intra-annual variability, and spatial coherency. The results showed that no single model performed well over all statistics/timescales, suggesting that the user should chose appropriate methods after assessing their advantages and limitations when applying downscaling methods for particular purposes. Specifically, the CR-SDSM provided relatively robust results for annual/monthly statistics and extreme characteristics, but exhibited weakness for some daily statistics, such as daily rainfall amount, dry-spell length, and annual wet/dry days. GLIMCLIM performed well for annual dry/wet days, dry/wet spell length, and spatial coherency, but slightly overestimated the daily rainfall. Additionally, NHMM performed better for daily rainfall and annual wet/dry days, but slightly underestimated dry/wet spell length and overestimated the daily extremes. The results of this study could be applied when investigating climate change impact on hydrology and water availability for the NCP, which suffers from intense water shortages due to climate change and human activities in recent years.

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Acknowledgments

This work was supported by the National Basic Research Program of China (2010CB428406) and Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05090309). We wish to thank Dr. Richard E. Chandler from University College London (UK) and Dr. Chi Yang from Beijing Normal University (China) for the help of running GLIMCLIM model, and Dr. David Post, Ms. Jin Teng and two anonymous reviewers for their invaluable comments and constructive suggestions used to improve the quality of the manuscript.

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Authors and Affiliations

  1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Wenbin Liu & Changming Liu

  2. CSIRO Land and Water, Private Bag 5, Wembley, WA, 6913, Australia

    Guobin Fu & Stephen P. Charles

  3. Graduate University of Chinese Academy of Sciences, Beijing, 10049, China

    Wenbin Liu

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  1. Wenbin Liu
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Correspondence to Guobin Fu.

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Liu, W., Fu, G., Liu, C. et al. A comparison of three multi-site statistical downscaling models for daily rainfall in the North China Plain. Theor Appl Climatol 111, 585–600 (2013). https://doi.org/10.1007/s00704-012-0692-0

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  • DOI: https://doi.org/10.1007/s00704-012-0692-0

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