Performance of ALADIN-Climate/CZ over the area of the Czech Republic in comparison with ENSEMBLES regional climate models
Abstract
Nowadays Regional Climate Models (RCMs) are increasingly used for downscaling of information from coarse resolution of global climate models (GCMs) and they represent a more and more popular tool for assessment of future climate changes and their impacts at regional scales. In spite of continual progress of RCMs, their outputs still suffer from many uncertainties and biases.
Therefore, it is necessary to assess their ability to simulate observed climate characteristics and uncertainties in their outputs before they are applied in subsequent studies. In the present study, the assessment of RCM performance in simulating climate in the reference period of 1961-1990 over the area of Czech Republic is presented.
Furthermore, we focused on the intercomparison of the models' results, mainly on the comparison of the Czech model ALADIN-Climate/CZ with outputs of other RCMs. Simulation of ALADIN-Climate/CZ in 25-km horizontal resolution, and thirteen RCM simulations from the ENSEMBLES project were assessed.
Attention was paid especially to comparison of simulated and observed spatial and temporal variability of several climatic variables. The monthly and seasonal values of surface air temperature, precipitation totals and relative humidity were examined for evaluation of temporal variability and 30-year seasonal and monthly values with respect to spatial variability.
Climate model performance was evaluated in several ways, namely by boxplots, maps of variability characteristics, skill scores based on mean square error and Taylor diagrams. Model errors detected by model evaluation depend on many factors (e.g. considered variables and their characteristics, area of analysis, time scale of interest and the method of assessment).
On the basis of incorporated performance criteria model ALADIN-Climate/CZ belonged to a better group of RCMs in most cases. However, it was definitely the worst in simulating spring monthly means of air temperature and relative humidity in all seasons.