Abstrakt
We used the Koppen-Trewartha classification on the CMIP5 family of global climate model (GCM) simulations and global Climatic Research Unit (CRU) data for comparison. This evaluation provides preliminary insight on GCM performance and errors.
For the overall model intercomparison and evaluation, we used 2 simple statistical characteristics: normalized error, which assesses the total relative difference of the area classified by the individual model with respect to the area resulting from CRU data, and overlap, calculating relative area of matching grid boxes in model results and CRU data. With the additional analysis of the classification on world maps, we show that there are some common features in the model results.
Many models have problems capturing the rainforest climate type Ar, mainly in Amazonia. The desert climate type BW is underestimated by as many as half of the models, with Australia being a typical example of a region where the BW is not well represented.
The boreal climate type E is overestimated by many models, mostly spreading over to the areas of observed tundra type Ft. All applied metrics indicate that with the current generation of GCMs, there is no clear tendency for models to improve the representation of climate types with higher spatial resolution.