日本地球惑星科学連合2021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-CG35] 地球規模環境変化の予測と検出

2021年6月4日(金) 13:45 〜 15:15 Ch.08 (Zoom会場08)

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:建部 洋晶(海洋研究開発機構)、河宮 未知生(海洋研究開発機構)

14:00 〜 14:15

[ACG35-02] Minimal CMIP Emulator (MCE): A new method for probabilistic climate projections

*筒井 純一1 (1.電力中央研究所)

キーワード:簡易気候モデル、パラメータアンサンブル、緩和シナリオ

Climate model emulators have a crucial role in assessing warming levels of many emission scenarios from probabilistic climate projections, based on new insights into Earth system response to CO2 and other forcing factors. This presentation describes one such tool, MCE, from model formulation to application examples associated with a recent model intercomparison study. The MCE is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters for probabilistic projections are generated from statistical models and constrained with a Metropolis-Hastings independence sampler. A part of the model parameters associated with CO2-induced warming have a covariance structure, as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). Although perturbed ensembles can cover the diversity of CMIP models effectively, they need to be constrained toward substantially lower climate sensitivity for the resulting historical warming to agree with the observed trends over recent decades. The model's simplicity and resulting successful calibration imply that a method with less complicated structures and fewer control parameters offers advantages when building reasonable perturbed ensembles in a transparent way. Experimental results for future scenarios, including forcing perturbations, show distinct differences between CMIP- and observation-consistent ensembles, suggesting that perturbed ensembles for scenario assessment need to be properly constrained with new insights into forced response over historical periods.