Improved seasonal prediction using the SINTEX‐F2 coupled model
Abstract The SINTEX‐F1 Coupled General Circulation Model (CGCM) was developed within the EU‐Japan collaborative framework to study global climate variability and its predictability by use of the Earth Simulator. The seasonal prediction system based on the SINTEX‐F1 has demonstrated its outstanding p...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2016-12-01
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| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/2016MS000744 |
| _version_ | 1819106829805813760 |
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| author | Takeshi Doi Swadhin K. Behera Toshio Yamagata |
| author_facet | Takeshi Doi Swadhin K. Behera Toshio Yamagata |
| author_sort | Takeshi Doi |
| collection | DOAJ |
| description | Abstract The SINTEX‐F1 Coupled General Circulation Model (CGCM) was developed within the EU‐Japan collaborative framework to study global climate variability and its predictability by use of the Earth Simulator. The seasonal prediction system based on the SINTEX‐F1 has demonstrated its outstanding performance of predicting El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole since 2005. However, there is much room for improvement in predicting extratropical climate variations. To deal with this, a revised CGCM called SINTEX‐F2 has been developed; the new system is a high‐resolution version with a dynamical sea‐ice model. For the tropical climate variations in the Pacific and the Indian Ocean, the SINTEX‐F2 preserves the high‐prediction skill, and sometimes even shows higher skill especially for strong events, as compared to the SINTEX‐F1. In addition, it has turned out that the new system is more skillful in predicting the subtropics, particularly, the Indian Ocean Subtropical Dipole and the Ningaloo Niño. The improvement may contribute to enhancing prediction skills of the regional rainfall distributions and encourage us to develop an early warning system which may be applied for societal and industrial activities. |
| first_indexed | 2024-12-22T02:44:22Z |
| format | Article |
| id | doaj.art-2ead857b3cf54df28f18de8c28f7db25 |
| institution | Directory Open Access Journal |
| issn | 1942-2466 |
| language | English |
| last_indexed | 2024-12-22T02:44:22Z |
| publishDate | 2016-12-01 |
| publisher | American Geophysical Union (AGU) |
| record_format | Article |
| series | Journal of Advances in Modeling Earth Systems |
| spelling | doaj.art-2ead857b3cf54df28f18de8c28f7db252022-12-21T18:41:33ZengAmerican Geophysical Union (AGU)Journal of Advances in Modeling Earth Systems1942-24662016-12-01841847186710.1002/2016MS000744Improved seasonal prediction using the SINTEX‐F2 coupled modelTakeshi Doi0Swadhin K. Behera1Toshio Yamagata2Application Laboratory/Japan Agency for Marine‐Earth Science and TechnologyYokohama JapanApplication Laboratory/Japan Agency for Marine‐Earth Science and TechnologyYokohama JapanApplication Laboratory/Japan Agency for Marine‐Earth Science and TechnologyYokohama JapanAbstract The SINTEX‐F1 Coupled General Circulation Model (CGCM) was developed within the EU‐Japan collaborative framework to study global climate variability and its predictability by use of the Earth Simulator. The seasonal prediction system based on the SINTEX‐F1 has demonstrated its outstanding performance of predicting El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole since 2005. However, there is much room for improvement in predicting extratropical climate variations. To deal with this, a revised CGCM called SINTEX‐F2 has been developed; the new system is a high‐resolution version with a dynamical sea‐ice model. For the tropical climate variations in the Pacific and the Indian Ocean, the SINTEX‐F2 preserves the high‐prediction skill, and sometimes even shows higher skill especially for strong events, as compared to the SINTEX‐F1. In addition, it has turned out that the new system is more skillful in predicting the subtropics, particularly, the Indian Ocean Subtropical Dipole and the Ningaloo Niño. The improvement may contribute to enhancing prediction skills of the regional rainfall distributions and encourage us to develop an early warning system which may be applied for societal and industrial activities.https://doi.org/10.1002/2016MS000744seasonal predictioncoupled model |
| spellingShingle | Takeshi Doi Swadhin K. Behera Toshio Yamagata Improved seasonal prediction using the SINTEX‐F2 coupled model Journal of Advances in Modeling Earth Systems seasonal prediction coupled model |
| title | Improved seasonal prediction using the SINTEX‐F2 coupled model |
| title_full | Improved seasonal prediction using the SINTEX‐F2 coupled model |
| title_fullStr | Improved seasonal prediction using the SINTEX‐F2 coupled model |
| title_full_unstemmed | Improved seasonal prediction using the SINTEX‐F2 coupled model |
| title_short | Improved seasonal prediction using the SINTEX‐F2 coupled model |
| title_sort | improved seasonal prediction using the sintex f2 coupled model |
| topic | seasonal prediction coupled model |
| url | https://doi.org/10.1002/2016MS000744 |
| work_keys_str_mv | AT takeshidoi improvedseasonalpredictionusingthesintexf2coupledmodel AT swadhinkbehera improvedseasonalpredictionusingthesintexf2coupledmodel AT toshioyamagata improvedseasonalpredictionusingthesintexf2coupledmodel |