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- Title
Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5.
- Authors
Tomoo Ogura; Hideo Shiogama; Masahiro Watanabe; Masakazu Yoshimori; Tokuta Yokohata; Annan, James D.; Hargreaves, Julia C.; Naoto Ushigami; Kazuya Hirota; Yu Someya
- Abstract
This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used a low-resolution version of the Model for Interdisciplinary Research on Climate version 5 (MIROC5) Atmosphere-Ocean General Circulation Model (AOGCM) and compared the output of a perturbed parameter ensemble (PPE) experiment in the pre-industrial control setting with satellite observation data. The model biases and the parametric uncertainty of the biases are evaluated with respect to TOA radiation and clouds. We used the output of the PPE experiment without flux adjustment, which is consistent with the experimental design of the CMIP5. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. Especially, the cooling bias of the shortwave cloud radiative effect in low latitudes could not be removed, neither in the zonal mean nor at each latitude--longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning.
- Subjects
RADIATION; CLOUDS; METEOROLOGY; ATMOSPHERIC models; BOX models (Climatology)
- Publication
Geoscientific Model Development Discussions, 2017, p1
- ISSN
1991-9611
- Publication type
Article
- DOI
10.5194/gmd-2017-117