Reliability and importance of structural diversity of climate model ensembles |
| |
Authors: | Tokuta Yokohata James D. Annan Matthew Collins Charles S. Jackson Hideo Shiogama Masahiro Watanabe Seita Emori Masakazu Yoshimori Manabu Abe Mark J. Webb Julia C. Hargreaves |
| |
Affiliation: | 1. National Institute for Environmental Studies, Center for Global Environmental Research, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan 2. Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showamachi, Kanazawa-ku, Yokohama, Kanagawa, 236-0001, Japan 3. College of Engineering, Mathematics and Physical Sciences, University of Exeter, Harrison Building, North Park Road, Exeter, EX4 4QF, UK 4. Institute of Geophysics, The University of Texas at Austin, 10100 Burnet Rd., ROC-196, Mail Code R2200, Austin, TX, 78758, USA 5. Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8568, Japan 6. Met Office, Hadley Centre, FitzRoy Road, Exeter, EX1 3PB, UK
|
| |
Abstract: | We investigate the performance of the newest generation multi-model ensemble (MME) from the Coupled Model Intercomparison Project (CMIP5). We compare the ensemble to the previous generation models (CMIP3) as well as several single model ensembles (SMEs), which are constructed by varying components of single models. These SMEs range from ensembles where parameter uncertainties are sampled (perturbed physics ensembles) through to an ensemble where a number of the physical schemes are switched (multi-physics ensemble). We focus on assessing reliability against present-day climatology with rank histograms, but also investigate the effective degrees of freedom (EDoF) of the fields of variables which makes the statistical test of reliability more rigorous, and consider the distances between the observation and ensemble members. We find that the features of the CMIP5 rank histograms, of general reliability on broad scales, are consistent with those of CMIP3, suggesting a similar level of performance for present-day climatology. The spread of MMEs tends towards being “over-dispersed” rather than “under-dispersed”. In general, the SMEs examined tend towards insufficient dispersion and the rank histogram analysis identifies them as being statistically distinguishable from many of the observations. The EDoFs of the MMEs are generally greater than those of SMEs, suggesting that structural changes lead to a characteristically richer range of model behaviours than is obtained with parametric/physical-scheme-switching ensembles. For distance measures, the observations and models ensemble members are similarly spaced from each other for MMEs, whereas for the SMEs, the observations are generally well outside the ensemble. We suggest that multi-model ensembles should represent an important component of uncertainty analysis. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|