Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods
We performed bias correction in future climate change scenarios to provide better accuracy of models through adaptation to future climate change. The proposed combination of the change factor (CF) and quantile mapping (QM) methods combines the individual advantages of both methods for adjusting the...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2014/704151 |
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| author | Donghyuk Kum Kyoung Jae Lim Chun Hwa Jang Jichul Ryu Jae E. Yang Seong Joon Kim Dong Soo Kong Younghun Jung |
| author_facet | Donghyuk Kum Kyoung Jae Lim Chun Hwa Jang Jichul Ryu Jae E. Yang Seong Joon Kim Dong Soo Kong Younghun Jung |
| author_sort | Donghyuk Kum |
| collection | DOAJ |
| description | We performed bias correction in future climate change scenarios to provide better accuracy of models through adaptation to future climate change. The proposed combination of the change factor (CF) and quantile mapping (QM) methods combines the individual advantages of both methods for adjusting the bias in global circulation models (GCMs) and regional circulation models (RCMs). We selected a study site in Songwol-dong, Seoul, Republic of Korea, to test and assess our proposed method. Our results show that the combined CF + QM method delivers better performance in terms of correcting the bias in GCMs/RCMs than when both methods are applied individually. In particular, our proposed method considerably improved the bias-corrected precipitation by capturing both the high peaks and amounts of precipitation as compared to that from the CF-only and QM-only methods. Thus, our proposed method can provide high-accuracy bias-corrected precipitation data, which could prove to be highly useful in interdisciplinary studies across the world. |
| format | Article |
| id | doaj-art-90099407d7c343f89ec58434308027e6 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-90099407d7c343f89ec58434308027e62025-02-03T05:45:55ZengWileyAdvances in Meteorology1687-93091687-93172014-01-01201410.1155/2014/704151704151Projecting Future Climate Change Scenarios Using Three Bias-Correction MethodsDonghyuk Kum0Kyoung Jae Lim1Chun Hwa Jang2Jichul Ryu3Jae E. Yang4Seong Joon Kim5Dong Soo Kong6Younghun Jung7Department of Regional Infrastructure Engineering, Kangwon National University, Chuncheon, Gangwon 200-701, Republic of KoreaDepartment of Regional Infrastructure Engineering, Kangwon National University, Chuncheon, Gangwon 200-701, Republic of KoreaDepartment of Regional Infrastructure Engineering, Kangwon National University, Chuncheon, Gangwon 200-701, Republic of KoreaNational Institute of Environmental Research, Incheon 404-708, Republic of KoreaDepartment of Biological Environment, Kangwon National University, Chuncheon, Gangwon 200-701, Republic of KoreaDepartment of Civil & Environmental System Engineering, Konkuk University, Seoul 143-701, Republic of KoreaDepartment of Life Science, Kyonggi University, Suwon 443-760, Republic of KoreaDepartment of Regional Infrastructure Engineering, Kangwon National University, Chuncheon, Gangwon 200-701, Republic of KoreaWe performed bias correction in future climate change scenarios to provide better accuracy of models through adaptation to future climate change. The proposed combination of the change factor (CF) and quantile mapping (QM) methods combines the individual advantages of both methods for adjusting the bias in global circulation models (GCMs) and regional circulation models (RCMs). We selected a study site in Songwol-dong, Seoul, Republic of Korea, to test and assess our proposed method. Our results show that the combined CF + QM method delivers better performance in terms of correcting the bias in GCMs/RCMs than when both methods are applied individually. In particular, our proposed method considerably improved the bias-corrected precipitation by capturing both the high peaks and amounts of precipitation as compared to that from the CF-only and QM-only methods. Thus, our proposed method can provide high-accuracy bias-corrected precipitation data, which could prove to be highly useful in interdisciplinary studies across the world.http://dx.doi.org/10.1155/2014/704151 |
| spellingShingle | Donghyuk Kum Kyoung Jae Lim Chun Hwa Jang Jichul Ryu Jae E. Yang Seong Joon Kim Dong Soo Kong Younghun Jung Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods Advances in Meteorology |
| title | Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods |
| title_full | Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods |
| title_fullStr | Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods |
| title_full_unstemmed | Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods |
| title_short | Projecting Future Climate Change Scenarios Using Three Bias-Correction Methods |
| title_sort | projecting future climate change scenarios using three bias correction methods |
| url | http://dx.doi.org/10.1155/2014/704151 |
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