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Assessing scale effects for statistically downscaling precipitation with GPCC model

Authors

  • Jie Chen,

    Corresponding author
    1. State Key Laboratory of Soil Erosion and Dryland farming on Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, Shaanxi, China
    2. Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada
    • Correspondence to: J. Chen, Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, H3C 1 K3, Canada. E-mail: jie.chen.1@ens.etsmtl.ca

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  • Xunchang J. Zhang,

    1. USDA-ARS Grazinglands Research Lab, El Reno, OK, USA
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    • The contributions of these authors to this article were prepared as part of their official duties as United States Federal Government employees.

  • François P. Brissette

    1. Department of Construction Engineering, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada
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Abstract

The resolution of general circulation models (GCMs) is too coarse to assess the site-specific impacts of climate change. Downscaling approaches have been developed to meet this requirement. As the resolution of climate model increases, it is imperative to know whether the finer resolution of regional climate models (RCMs) would result in any improvement of statistical downscaling quality at the station scale for particular downscaling methods. The objective of this study is to assess the effects of climate model resolutions on statistical downscaling quality of precipitation using the generator for point climate change (GPCC) model. The downscaling is conducted across three scales, from GCM, and mid- and high-resolution RCMs to a station scale for two Canadian stations in the Quebec province. Observed precipitation gridded to the corresponding scales is also studied in parallel, totalling six downscaling experiments. The results show that the statistics of downscaled precipitation are somewhat overestimated for the Sept-Iles station for all six downscaling experiments with the relative error of mean daily, monthly, and annual precipitation ranging between 1.1 and 5.0%, between 2.7 and 5.9% and between 0.5 and 6.2%, respectively, but underestimated for the Bonnard station with the relative error ranging between −4.1 and −10.2%, between −3.2 and −13.3%, and between −2.6 and −12.0%, respectively. The number of wet days per year is well preserved with the difference between observed and downscaled data ranging between −2.9 and 6 d across all downscaling experiments and two stations. The quality of downscaled precipitation is similar between using gridded observations and model-simulated data for both stations. Furthermore, there is no noteworthy scale effect on downscaling quality when downscaling climate model output with GPCC, indicating that for regions without RCM projections, high-quality daily series at stations can be derived directly from GCM projections with this particular downscaling model. © 2013 Royal Meteorological Society

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