A resampling scheme for regional climate simulations and its performance compared to a dynamical RCM

A new statistical method for regional climate simulations is introduced. Its simulations are constrained only by the parameters of a linear regression line for a characteristic climatological variable. Simulated series are generated by resampling from segments of observation series such that the resulting series comply with the prescribed regression parameters and possess realistic annual cycles and persistence. The resampling guarantees that the simulated series are physically consistent both with respect to the combinations of different meteorological variables and to their spatial distribution at each time step. The resampling approach is evaluated by means of a cross validation experiment for the Elbe river basin: Its simulations are compared both to an observed climatology and to data simulated by a dynamical RCM. This cross validation shows that the approach is able to reproduce the observed climatology with respect to statistics such as long-term means, persistence features (e.g., dry spells) and extreme events. The agreement of its simulations with the observational data is much closer than for the RCM data.