Application of Quantile Mapping Bias Correction for Mid-Future Precipitation Projections over Vietnam

The Quantile Mapping (QM) bias correction (BC) technique was applied for the first time to address biases in the simulated precipitation over Vietnam from the Regional Climate Model (RegCM) driven by five Coupled Model Intercomparison Project Phase 5 (CMIP5) Global Climate Model (GCM) products. The...

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Main Authors: Trinh-Yuan, Long, Matsumoto, Jun, Tangang, Fredolin T, Juneng, Liew, Cruz, Faye T, Narisma, Gemma T, Santisirisomboon, Jerasorn, Phan-Van, Tan, Gunawan, Dodo, Aldrian, Edvin, Ngo-Duc, Thanh
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Published: Archīum Ateneo 2019
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Online Access:https://archium.ateneo.edu/physics-faculty-pubs/114
https://www.jstage.jst.go.jp/article/sola/15/0/15_2019-001/_article
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Institution: Ateneo De Manila University
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Summary:The Quantile Mapping (QM) bias correction (BC) technique was applied for the first time to address biases in the simulated precipitation over Vietnam from the Regional Climate Model (RegCM) driven by five Coupled Model Intercomparison Project Phase 5 (CMIP5) Global Climate Model (GCM) products. The QM process was implemented for the period 1986−2005, and subsequently applied to the mid-future period 2046−2065 under both Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. Comparison with the original model outputs during the independent validation period shows a large bias reduction from 45% to 3% over Vietnam and significant improvements in representing precipitation indices (PI) after applying the QM technique. Moreover, the ensemble average of the BC products generally performed better than an individual BC member in capturing the spatial distribution of the PIs. A drier condition with a longer rainfall break, and shorter consecutive rainfall events are anticipated over Northern and Central Vietnam during their respective wet seasons in the mid-future. Furthermore, this study showed that the QM method minimally modified the future changes in PIs over most of Vietnam; thus, these corrected projections could be used in climate impacts and adaptation studies.