In this paper, the recently developed variable-resolution option within the Community Earth System Model (VR-CESM) is assessed for long-term regional climate modeling of California at 0.25° (∼28 km) and 0.125° (∼14 km) horizontal resolutions. The mean climatology of near-surface temperature and precipitation is analyzed and contrasted with reanalysis, gridded observational data sets, and a traditional regional climate model (RCM)--the Weather Research and Forecasting (WRF) model. Statistical metrics for model evaluation and tests for differential significance have been extensively applied. With only prescribed sea surface temperatures, VR-CESM tended to produce a warmer summer (by about 1-3°C) and overestimated overall winter precipitation (about 25%–35%) compared to reference data sets. Increasing resolution from 0.25° to 0.125° did not produce a statistically significant improvement in the model results. By comparison, the analogous WRF climatology (constrained laterally and at the sea surface by ERA-Interim reanalysis) was ∼1-3°C colder than the reference data sets, underestimated precipitation by ∼20%-30% at 27 km resolution, and overestimated precipitation by ∼65-85% at 9 km. Overall, VR-CESM produced comparable statistical biases to WRF in key climatological quantities. This assessment highlights the value of variable-resolution global climate models (VRGCMs) in capturing fine-scale atmospheric processes, projecting future regional climate, and addressing the computational expense of uniform-resolution global climate models.
