| Project/Area Number |
23340137
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Meteorology/Physical oceanography/Hydrology
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
MASUNAGA Hirohiko 名古屋大学, 地球水循環研究センター, 准教授 (00444422)
OKAMOTO Hajime 九州大学, 応用力学研究所, 教授 (10333783)
SHIOGAMA Hideo 国立環境研究所, 地球環境研究センター, 主任研究員 (30391113)
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| Co-Investigator(Renkei-kenkyūsha) |
OGURA Tomoo 国立環境研究所, 地球環境研究センター, 主任研究員 (10370264)
YOKOHATA Tokuta 国立環境研究所, 地球環境研究センター, 研究員 (20391170)
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| Project Period (FY) |
2011-04-01 – 2014-03-31
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥20,150,000 (Direct Cost: ¥15,500,000、Indirect Cost: ¥4,650,000)
Fiscal Year 2013: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2012: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2011: ¥7,150,000 (Direct Cost: ¥5,500,000、Indirect Cost: ¥1,650,000)
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| Keywords | 気候 / 気候モデル / 衛星データ / 物理アンサンブル / 雲フィードバック / 気候変化 / 地球温暖化 / 全球気候モデル / 雲のフィードバック / ENSO / 不確実性 / 雲 / 人工衛星データ |
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| Research Abstract |
Future projection of global mean temperature rise has contained uncertainty, even in the latest IPCC Assessment Report. This uncertainty is partly attributed to potential errors in parameterization processes (of clouds in particular) in global climate models (GCMs). Therefore, this study attempted to clarify sources of uncertainty in cloud feedbacks to climate warming by generating a large ensemble in which model parameters as well as parameterization schemes have been perturbed. Also, satellite data for cloud properties were actively used to assess climate model simulations.
Physics ensemble based on the MIROC GCM is a novel set of numerical experiments to explore the cloud feedback processes, and was successfully recognised in international climate science community. Comparisons of mean cloud and cloud macrophysical properties between GCM and satellite data could prodive clues for improving GCM for the subsequent climate change projection.
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