Seasonal predictability based on multi-model intercomparison
Project/Area Number |
18K03749
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Review Section |
Basic Section 17020:Atmospheric and hydrospheric sciences-related
|
Research Institution | Japan, Meteorological Research Institute |
Principal Investigator |
Imada Yukiko 気象庁気象研究所, 気候・環境研究部, 主任研究官 (50582855)
|
Project Period (FY) |
2018-04-01 – 2023-03-31
|
Project Status |
Completed (Fiscal Year 2022)
|
Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
|
Keywords | 大気海洋結合大循環モデル / エルニーニョ・南方振動 / 季節予測 / マルチモデル比較 / 太平洋数十年規模変動 / 季節予測システム / ENSO予測 / 大気海洋結合モデル / ENSO / モデル間相互比較 |
Outline of Final Research Achievements |
Although the skill of climate models in predicting ENSO has improved dramatically in recent years, there are still a few cases where case-specific ENSO development is significantly underpredicted, and the reasons for this vary from case to case, model to model, and method to method. In this study, I conducted a multi-model seasonal predictability study, which has been considered difficult in the past, to explore the key physical processes for prediction. Comparison of seasonal hindcasts using the two state-of-the-art coupled atmosphere-ocean models suggested that the ability to predict multi-decadal variability originating in the South Pacific Ocean affects ENSO forecasting skills. The representation of eddies in the tropical ocean is also shown to be a key factor in ENSO prediction.
|
Academic Significance and Societal Importance of the Research Achievements |
熱帯太平洋に発生するエルニーニョ現象(ENSO)は、異常気象予測の鍵となる現象である。ENSOを数か月前から予測することで、異常気象の発生確率を知り、備えることができる。この目的から、日本では気候モデルを用いた季節予報が定期的に発表されている。一方で、季節予測の技術は飽和しつつあり、新たなブレークスルーが求められている。本研究では、複数の季節予測モデルを用いて個別の事例を丁寧に調べることで、現象の多様性やモデルの多様性を考慮した新しいアプローチに挑戦した。得られる知見は、季節予測技術を次の段階に進めるためのマイルストーンになると期待される。
|
Report
(6 results)
Research Products
(27 results)
-
-
-
-
[Journal Article] Seasonal to decadal predictions with MIROC6: Description and basic evaluation.2020
Author(s)
Kataoka, T., H. Tatebe, H. Koyama, T. Mochizuki, K. Ogochi, H. Naoe, Y. Imada, H. Shiogama, M. Kimoto, M. Watanabe
-
Journal Title
J. Advances in Modeling Earth Systems
Volume: 12
Issue: 12
Pages: 1-25
DOI
Related Report
Peer Reviewed / Open Access
-
-
-
-
[Journal Article] Tropical rainfall predictions from multiple seasonal forecast systems.2019
Author(s)
Michel Dequ, Tina Dippe, Nick Dunstone, David Fereday, Richard G. Gudgel, Richard J. Greatbatch, Leon Hermanson,Yukiko Imada, Shipra Jain, Arun Kumar, Craig MacLachlan, William Merryfield, Wolfgang A. Muller, Hong‐Li Ren, Doug Smith, Yuhei Takaya, Gabriel Vecchi, Xiaosong Yang
-
Journal Title
International Journal of Climatology
Volume: 39
Issue: 2
Pages: 974-988
DOI
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-