Evaluation of a CCSM-WRF Downscaling Simulation for California

In this study, the ability of a new WRF-based dynamical downscaling simulation to reproduce the current climate of California is rigorously examined. To improve statistical robustness and regional detail, this GCM- forced simulation is both run for a longer time (40 yrs) and at a higher resolution (12 km) than previous simulations over North America. Spatial representation of modeled precipitation and surface temperature are found to agree much better with observations in the downscaled run than in the forcing GCM, though the climatological magnitude of WRF precipitation is substantially overestimated along windward slopes. This is due to strong overprediction of precipitation intensity; precipitation frequency is actually underpredicted by the model. Potential sources for this bias are investigated. Regional model surface temperatures agree well with observations in most regions and in most seasons, though the model inherits a domain-wide warm bias of several degrees from the GCM in summer and is warmer than observed along the coast in all seasons due to overpredicted near-land GCM SST. Modeled snowfall/snowmelt agrees quite well with observations, but snow water equivalent is found to be much too low due to monthly reinitialization of all regional model fields from GCM values.