Sensitivity of Simulated Conditions to Different Parameterization Choices Over Complex Terrain in Central Chile

Abstract

This study evaluates the performance of fourteen high-resolution WRF runs with different combinations of parameterizations in simulating the atmospheric conditions over the complex terrain of central Chile during austral winter and spring. We focus on the validation of results for coastal, interior valleys, and mountainous areas independently, and also present an in-depth analysis of two synoptic-scale events that occurred during the study period: a frontal system and a cut-off low. The performance of the simulations decreases from the coast to higher altitudes, even though the differences are not very clear between the coast and interior valleys for 10 m wind speeds and precipitation. The simulated vertical profiles show a warmer and drier boundary layer and a cooler and moister free atmosphere than observed. The choice of the land-surface model has the largest positive impact on near-surface variables with the five-layer thermal diffusion scheme showing the smallest errors. Precipitation is more sensitive to the choice of cumulus parameterizations, with the simplified Arakawa–Schubert scheme generally providing the best performance for absolute errors. When examining the performance of the model simulating rain/no-rain events for different thresholds, also the cumulus parameterizations better represented the false alarm ratio (FAR) and the bias score (BS). However, the Morrison microphysics scheme resulted in the best critical success index (CSI), while the probability of detection (POD) was better in the simulation without analysis nudging. Overall, these results provide guidance to other researchers and help to identify the best WRF configuration for a specific research or operational goal.