Comparison of climate change scenarios generated from regional climate model experiments and statistical downscaling

We compare regional climate change scenarios (temperature and precipitation ) over eastern Nebraska produced by a semiempirical statistical downscaling (SDS) technique and regional climate model (RegCM2) experiments, both usin g large scale information from the same coarse resolution general circulati on model (GCM) control and 2 x CO2 simulations. The SDS method is based on the circulation pattern classification technique in combination with stocha stic generation of daily time series of temperature and precipitation. It u ses daily values of 700 mbar geopotential heights as the large-scale circul ation variable. The regional climate model is driven by initial and lateral boundary conditions from the GCM, The RegCM2 exhibited greater spatial var iability than the SDS method for change in both temperature and precipitati on. The SDS method produced a seasonal cycle of temperature change with a m uch larger amplitude than that of the RegCM2 or the GCM. Daily variability of temperature mainly decreased for both downscaling methods and the GCM. C hanges in mean daily precipitation varied between SDS and RegCM2. The RegCM 2 simulated both increases and decreases in the probability of precipitatio n, while the SDS method produced only increases. We explore possible dynami cal and physical reasons for the differences in the scenarios produced by t he two methods and the GCM.