Skip navigation
Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/4340
Title: Modified approach to reduce GCM bias in downscaled precipitation: A study in Ganga River Basin
Authors: Sharma C.
Ojha, C. S. P.
Shukla A.K.
Pham Q.B.
Linh N.T.T.
Fai C.M.
Loc H.H.
Dung T.D.
Published in: Water (Switzerland)
Abstract: Reanalysis data is widely used to develop predictor-predictand models, which are further used to downscale coarse gridded general circulation models (GCM) data at a local scale. However, large variability in the downscaled product using different GCMs is still a big challenge. The first objective of this study was to assess the performance of reanalysis data to downscale precipitation using different GCMs. High bias in downscaled precipitation was observed using different GCMs, so a different downscaling approach is proposed in which historical data of GCM was used to develop a predictor-predictand model. The earlier approach is termed "Re-Obs" and the proposed approach as "GCM-Obs". Both models were assessed using mathematical derivation and generated synthetic series. The intermodal bias in different GCMs downscaled precipitation using Re-Obs and GCM-Obs model was also checked. Coupled Model Inter-comparison Project-5 (CMIP5) data of ten different GCMs was used to downscale precipitation in different urbanized, rural, and forest regions in the Ganga river basin. Different measures were used to represent the relative performances of one downscaling approach over other approach in terms of closeness of downscaled precipitation with observed precipitation and reduction of bias using different GCMs. The effect of GCM spatial resolution in downscaling was also checked. The model performance, convergence, and skill score were computed to assess the ability of GCM-Obs and Re-Obs models. The proposed GCM-Obs model was found better than Re-Obs model to statistically downscale GCM. It was observed that GCM-Obs model was able to reduce GCM-Observed and GCM-GCM bias in the downscaled precipitation in the Ganga river basin. ¬© 2019 by the authors.
Citation: Water (Switzerland)(2019), 11(10): -
URI: https://doi.org/10.3390/w11102097
http://repository.iitr.ac.in/handle/123456789/4340
Issue Date: 2019
Publisher: MDPI AG
Keywords: Downscaling
Ganga river basin
GCM bias
General circulation models (GCM)
Model performance
Precipitation
ISSN: 20734441
Author Scopus IDs: 57207884881
7004206177
56447884900
57208495034
57211268069
56678333400
57189027363
57208529225
Author Affiliations: Sharma, C., Civil Engineering Department, Indian Institute of Technology, Roorkee, 247667, India
Ojha, C.S.P., Civil Engineering Department, Indian Institute of Technology, Roorkee, 247667, India
Shukla, A.K., Civil Engineering Department, Indian Institute of Technology, Roorkee, 247667, India
Pham, Q.B., Department of Hydraulic and Ocean Engineering, National Cheng-Kung University, Tainan, 701, Taiwan
Linh, N.T.T., Department of Hydraulic and Ocean Engineering, National Cheng-Kung University, Tainan, 701, Taiwan, Faculty of Water Resource Engineering, Thuyloi University, Hanoi, 100000, Viet Nam
Fai, C.M., Civil Engineering Department, College of Engineering, Universiti Tenaga Nasional (UNITEN), Kajang, 43000, Malaysia
Loc, H.H., Faculty of Environmental and Food Engineering, Nguyen Tat Thanh University, Ho Chi Minh City, 700000, Viet Nam, National Institute of Education, 1, Nanyang Walk637616, Singapore
Dung, T.D., Center of Water Management and Climate Change, Vietnam National University Ho Chi Minh City, Ho Chi Minh City, 700000, Viet Nam
Funding Details: Acknowledgments: The authors would like to appreciate the financial support received from Bold 2025 grant coded RJO: 10436494 by Innovation & Research Management Center (iRMC), Universiti Tenaga Nasional (UNITEN), Malaysia. In addition, the authors are thankful to Global Precipitation Climatology Center (GPCC) for providing the gridded precipitation and wet day frequency data.
Corresponding Author: Loc, H.H.; Faculty of Environmental and Food Engineering, Nguyen Tat Thanh UniversityViet Nam; email: huuloc20686@gmail.com
Appears in Collections:Journal Publications [CE]

Files in This Item:
There are no files associated with this item.
Show full item record


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.