Climate Change Projections in RegCM CORDEX-CORE Simulations via Koeppen–Trewartha Climate Classification

The analysis of climate patterns can be performed for each climatic variable separately or the data can be aggregated using e.g. a kind of climate classification. The advantage of such a method, in our case Koeppen-Trewartha classification, is putting together the most important variables, i.e. temperature and precipitation, considering not only annual means, but through monthly values the annual course as well. These classifications usually correspond to vegetation distribution in the sense that each climate type is dominated by one vegetation zone or eco-region. This way climate classifications also represent a convenient tool for the assessment and validation of climate models and for the analysis of simulated future climate changes.

The RegCM results of CORDEX-CORE experiments over nine CORDEX domains are analysed using selected CMIP5 simulations (mostly HadGEM, MPI and NorESM) driving the RegCM. Validation based on ERA-Interim driven runs compared to CRU database (E-OBS for higher resolution in Europe) shows some systematic biases in different types. Through the analysis of the control experiments together with the performance of driving GCMs we can assess the sources of the biases in present conditions as well as to see the added value, which comes mainly from the better description of topography in higher resolution and thus appearance of mountainous tundra type, as well as better representation of coastal region and thus separating maritime and continental subtypes. Finally, for two scenarios RCP8.5 and RCP2.6 we show the projections of the individual types‘ area changes, individual transformations of types or their shifts in CORDEX domains (e.g. decrease of boreal and tundra type area, their shift to the higher latitudes and altitudes, increase of temperate climate, deserts, savana, more significant for RCP8.5). We compare the changes with the signal of climate change for driving GCMs to identify the added value of higher resolution RCM simulations.