Preprints
https://doi.org/10.5194/hess-2022-107
https://doi.org/10.5194/hess-2022-107
 
29 Mar 2022
29 Mar 2022
Status: this preprint is currently under review for the journal HESS.

Development of flexible double distribution quantile mapping for better bias correction in precipitation of GCMs

Young Hoon Song1, Eun-Sung Chung1, and Shamsuddin Shahid2 Young Hoon Song et al.
  • 1Faculty of Civil Engineering, Seoul National University of Science and Technology, 232 Gongneung-ro, Nowon-gu, Seoul 01811, Korea
  • 2School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), 81310 Johor Bahru, Malaysia

Abstract. The double gamma quantile mapping (DGQM) can outperform single gamma quantile mapping (SGQM) for bias correction of global circulation models (GCMs) using two gamma functions for two segments based on 90th quantile. However, there are two ambiguous points: the 90th quantile and considering only the Gamma probability function. Therefore, this study introduced a flexible dividing point, δ (%), which can be adjusted to the regionally observed values at the station and considered the combination of various probability distributions, Weibull, lognormal, and Gamma, for two separate segments. The newly proposed method, flexible double distribution quantile mapping (F-DDQM), was employed to correct the bias of 8 GCMs of Coupled Model Intercomparison Project Phase 6 (CMIP6) to correct bias at 22 stations in South Korea. The results clearly showed higher performance of F-DDQM than DGQM and Flexible-DGQM (F-DGQM) by 25 % and 5 %, respectively, in root mean square error. The F-DGQM also showed better performance in replicating probability distribution, spatial variability and extremes of observed precipitation than other methods. This study contributes to improving the bias correction method for the better projection of extreme values.

Young Hoon Song et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2022-107', Anonymous Referee #1, 24 Apr 2022
  • RC2: 'Comment on hess-2022-107', Anonymous Referee #2, 24 Apr 2022
  • CC1: 'Comment on hess-2022-107', Qin Zhang, 18 May 2022

Young Hoon Song et al.

Young Hoon Song et al.

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Short summary
This study proposed two new concepts for the previous Double Gamma Quantile Mapping (DGQM), such as the inclusion of flexible dividing point between two individual gamma functions and the use of more probability distributions. As a result, F-DDQM method performed the better bias correction for the GCMs very clearly. This new F-DDQM method can be also applied to the various fields such as the use of satellite climate data, reanalysis climate data and spatial downscaling or interpolation.