日本地球惑星科学連合2023年大会

講演情報

[E] 口頭発表

セッション記号 A (大気水圏科学) » A-CG 大気海洋・環境科学複合領域・一般

[A-CG34] 地球規模環境変化の予測と検出

2023年5月23日(火) 10:45 〜 12:00 104 (幕張メッセ国際会議場)

コンビーナ:河宮 未知生(海洋研究開発機構)、立入 郁(海洋研究開発機構)、建部 洋晶(海洋研究開発機構)、V Ramaswamy(NOAA GFDL)、座長:立入 郁(海洋研究開発機構)

11:15 〜 11:30

[ACG34-08] The role of coupled human-environment modeling in Earth system science

★Invited Papers

*Alan V Di Vittorio1、Timothy R Shippert2、Benjamin Bond-Lamberty2、Eva Sinha2 (1.Lawrence Berkeley National Laboratory、2.Pacific Northwest National Laboratory)

キーワード:Earth system, Human system, Human-Earth feedbacks, Model

A recent workshop exploring the role of human-environment feedbacks in global analysis demonstrated broad interest in this topic across communities and highlighted current limitations and potential paths forward with respect to modeling, uncertainty, and scenario development. I will provide some background on research in human-environment interactions, summarize perspectives from this workshop, and give an overview of the role that coupled human-environment modeling plays in Earth system science. Important considerations include the identification of relevant feedbacks, data and modeling uncertainties, addressing inconsistent representations of practices and processes across models, and the incorporation of climate impacts into scenarios. I will also share research progress on the synchronously coupled system comprising the Global Change Analysis Model (GCAM) and the Energy Exascale Earth System Model (E3SM).

The updated coupling of GCAM and E3SM facilitates direct experimentation and analysis of feedbacks between human and environmental systems. A main feature of this new coupling is that the human component is at the same level as the other components of the Earth system model (land, atmosphere, ocean, etc.) and interacts with them through the shared coupling software. Annually, terrestrial productivity is passed from E3SM to GCAM to make land use and CO2 emission projections for the next year, which are in turn passed back to E3SM. Previous experiments have shown that the incorporation of these feedbacks affects land use/cover change, crop prices, terrestrial carbon, local surface temperature, and land carbon-atmosphere feedbacks. Preliminary results indicate that this newly coupled system is robust in relation to the previous experiments. This coupling addresses inconsistency across models, enables a new type of scenario development, and provides a modeling framework that is more easily updated and expanded.