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Open AccessArticle

Comparing Bias Correction Methods Used in Downscaling Precipitation and Temperature from Regional Climate Models: A Case Study from the Kaidu River Basin in Western China

by Min Luo 1,2,3,4,5, Tie Liu 1,*, Fanhao Meng 1,3, Yongchao Duan 1,2,3,4,5, Amaury Frankl 2,6, Anming Bao 1 and Philippe De Maeyer 2,4,5
1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2
Department of Geography, Ghent University, 9000 Gent, Belgium
3
University of Chinese Academy of Science, Beijing 100039, China
4
Sino-Belgian Joint Laboratory of Geo-Information, Urumqi 830011, China
5
Sino-Belgian Joint Laboratory of Geo-Information, 9000 Gent, Belgium
6
Research Fund Flanders (FWO), 1000 Brussels, Belgium
*
Author to whom correspondence should be addressed.
Water 2018, 10(8), 1046; https://doi.org/10.3390/w10081046
Received: 29 May 2018 / Revised: 29 July 2018 / Accepted: 1 August 2018 / Published: 7 August 2018
(This article belongs to the Section Hydrology)
The systemic biases of Regional Climate Models (RCMs) impede their application in regional hydrological climate-change effects analysis and lead to errors. As a consequence, bias correction has become a necessary prerequisite for the study of climate change. This paper compares the performance of available bias correction methods that focus on the performance of precipitation and temperature projections. The hydrological effects of these correction methods are evaluated by the modelled discharges of the Kaidu River Basin. The results show that all used methods improve the performance of the original RCM precipitation and temperature simulations across a number of levels. The corrected results obtained by precipitation correction methods demonstrate larger diversities than those produced by the temperature correction methods. The performance of hydrological modelling is highly influenced by the choice of precipitation correction methods. Furthermore, no substantial differences can be identified from the results of the temperature-corrected methods. The biases from input data are often greater from the works of hydrological modelling. The suitability of these approaches depends upon the regional context and the RCM model, while their application procedure and a number of results can be adapted from region to region. View Full-Text
Keywords: Regional Climate Models; climate change; bias correction methods; SWAT model Regional Climate Models; climate change; bias correction methods; SWAT model
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Luo, M.; Liu, T.; Meng, F.; Duan, Y.; Frankl, A.; Bao, A.; De Maeyer, P. Comparing Bias Correction Methods Used in Downscaling Precipitation and Temperature from Regional Climate Models: A Case Study from the Kaidu River Basin in Western China. Water 2018, 10, 1046.

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