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Perturbed physics ensemble using the MICROC5 coupled atmosphere-ocean GCM without flux corrections: experimental design and results: parametric uncertainty of climate sensitivity

In this study, we constructed a perturbed physics ensemble (PPE) for the MIROC5 coupled atmosphere-ocean general circulation model (CGCM) to investigate the parametric uncertainty of climate sensitivity (CS). Previous studies of PPEs have mainly used the atmosphere-slab ocean models. A few PPE studi...

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Bibliographic Details
Published in:Climate dynamics 2012-12, Vol.39 (12), p.3041
Main Authors: Shiogama, Hideo, Watanabe, Masahiro, Yoshimori, Masakazu, Yokohata, Tokuta, Ogura, Tomoo, Annan, James D, Hargreaves, Julia C, Abe, Manabu, Kamae, Youichi, Oishi, Ryouta, Nobui, Rei, Emori, Seita, Nozawa, Toru, Abe-Ouchi, Ayako, Kimoto, Masahide
Format: Article
Language:English
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Summary:In this study, we constructed a perturbed physics ensemble (PPE) for the MIROC5 coupled atmosphere-ocean general circulation model (CGCM) to investigate the parametric uncertainty of climate sensitivity (CS). Previous studies of PPEs have mainly used the atmosphere-slab ocean models. A few PPE studies using a CGCM applied flux corrections, because perturbations in parameters can lead to large radiation imbalances at the top of the atmosphere and climate drifts. We developed a method to prevent climate drifts in PPE experiments using the MIROC5 CGCM without flux corrections. We simultaneously swept 10 parameters in atmosphere and surface schemes. The range of CS (estimated from our 35 ensemble members) was not wide (2.2-3.2°C). The shortwave cloud feedback related to changes in middle-level cloud albedo dominated the variations in the total feedback. We found three performance metrics for the present climate simulations of middle-level cloud albedo, precipitation, and ENSO amplitude that systematically relate to the variations in shortwave cloud feedback in this PPE. Keywords Climate sensitivity * Cloud feedback * General circulation model * Perturbed physics ensemble * Metrics
ISSN:0930-7575
1432-0894
DOI:10.1007/s00382-012-1441-x