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.
Highlights
Due to our lack of understanding of the climate system and limitations of computational power, climate models are far from perfect
We investigate the performance of the newest generation multi-model ensemble (MME) from the Coupled Model Intercomparison Project (CMIP5)
The rank histograms for the MMEs are dome-shape in general, while those of single model ensembles (SMEs) are U-shaped
Summary
Due to our lack of understanding of the climate system and limitations of computational power, climate models are far from perfect. In previous work using these statistical tests (AH10, Y12 and Hargreaves et al 2011), we were unable to reject the hypothesis of reliability for the CMIP3 MME for either modern climate or the climate change of the Last Glacial Maximum. This gives us some confidence in the CMIP3 ensemble. The analysis methods include the explanation of the calculation of rank histogram and the statistical test for the reliability (2–2), the formulation of EDoF (2–3), and the distances between observation and model ensemble members (2–4).
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