Relationship of the Reproducibility of Multiple Variables among Global Climate Models

Numerous efforts have been made for evaluating the performance of global climate models with such expectation that those models with higher reproducibility of the current climate should provide more reliable projections of climate changes into the future. Attempts have been made to define a single general metric through which the overall performance of a global climate model can be assessed. On the basis of general metrics defined through several techniques of multivariate analysis, the present study compares global climate models from a viewpoint of their reproducibility of climatological-mean fields of multiple variables. The analyses indicate that a reproducibility of a particular variable is not necessarily independent of that of others, which may bring redundant information into a general metric. The model reproducibility in upper and mid-tropospheric temperature and lower-tropospheric humidity, for example, tends to be anti-correlated with that in upper and mid-tropospheric humidity. It is argued that attention has to be paid to this kind of trade-off relationships among some variables and resultant redundancy in synthesizing multiple metrics. A possibility is suggested that an arbitrary selection of variables can yield some redundant information of variables. The redundancy is, however, found to exert no serious influence on the quality of a general metric as long as it is based on the sufficient number of variables. In our attempt to evaluate the climate models by introducing general performance metrics with reduced redundancy of variables, the overall model ranking is found rather insensitive to the specific definition of the metric.