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High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China

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Abstract

The community of climate change impact assessments and adaptations research needs regional high-resolution (spatial) meteorological data. This study produced two downscaled precipitation datasets with spatial resolutions of as high as 3 km by 3 km for the Heihe River Basin (HRB) from 2011 to 2014 using the Weather Research and Forecast (WRF) model nested with Final Analysis (FNL) from the National Center for Environmental Prediction (NCEP) and ERA-Interim from the European Centre for Medium-Range Weather Forecasts (ECMWF) (hereafter referred to as FNLexp and ERAexp, respectively). Both of the downscaling simulations generally reproduced the observed spatial patterns of precipitation. However, users should keep in mind that the two downscaled datasets are not exactly the same in terms of observations. In comparison to the remote sensing-based estimation, the FNLexp produced a bias of heavy precipitation centers. In comparison to the ground gauge-based measurements, for the warm season (May to September), the ERAexp produced more precipitation (root-mean-square error (RMSE) = 295.4 mm, across the 43 sites) and more heavy rainfall days, while the FNLexp produced less precipitation (RMSE = 115.6 mm) and less heavy rainfall days. Both the ERAexp and FNLexp produced considerably more precipitation for the cold season (October to April) with RMSE values of 119.5 and 32.2 mm, respectively, and more heavy precipitation days. Along with simulating a higher number of heavy precipitation days, both the FNLexp and ERAexp also simulated stronger extreme precipitation. Sensitivity experiments show that the bias of these simulations is much more sensitive to micro-physical parameterizations than to the spatial resolution of topography data. For the HRB, application of the WSM3 scheme may improve the performance of the WRF model.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China (Grant Nos. 91425304 and 41471171), the Youth Innovation Promotion Association CAS (2015038), and the Kezhen Outstanding Young Scholars from IGSNRR (No. 2015RC101).

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Authors and Affiliations

  1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Xuezhen Zhang, Jingyun Zheng & Quansheng Ge

  2. Key Laboratory of Regional Climate-Environment for East-Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Zhe Xiong

  3. University of the Chinese Academy of Sciences, Beijing, 100049, China

    Xuezhen Zhang & Jingyun Zheng

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  1. Xuezhen Zhang
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  2. Zhe Xiong
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Correspondence to Xuezhen Zhang.

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Zhang, X., Xiong, Z., Zheng, J. et al. High-resolution precipitation data derived from dynamical downscaling using the WRF model for the Heihe River Basin, northwest China. Theor Appl Climatol 131, 1249–1259 (2018). https://doi.org/10.1007/s00704-017-2052-6

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  • DOI: https://doi.org/10.1007/s00704-017-2052-6

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