Rainfall estimation using the weather research and forecasting (WRF) model is sensitive to physical parameterizations and downscaling configurations. Concerned with the correlations between physical parameterizations and dynamical downscaling, these significant… Click to show full abstract
Rainfall estimation using the weather research and forecasting (WRF) model is sensitive to physical parameterizations and downscaling configurations. Concerned with the correlations between physical parameterizations and dynamical downscaling, these significant issues were considered simultaneously in this study, and WRF‐based ensembles were integrated and used to estimate eight representative rainfall events. The results revealed that both rainfall estimates and intensities were sensitive to downscaling configurations. Specifically, light rainfall events that were homogeneous over space and time were estimated well using a 5 km horizontal resolution and were overestimated with a 1 km resolution where the planetary boundary layer (PBL) schemes were probably the source of positive errors in light rain conditions. However, when the rainfall was intense and displayed spatiotemporal heterogeneity, the rainfall peaks and volume were only well estimated with a 1 km resolution where cumulus (CU) schemes were the dominant schemes, demonstrating that higher resolutions could better reproduce rainfall patterns for wetter cases. At a 10 km horizontal resolution, the simulations did not display much accuracy, and different physics schemes did not make a substantial difference. Therefore, the rainfall characteristics cannot be ignored. More importantly, the contributions of microphysics, CU and PBL ensembles were quantified, and the sensitivities of the rainfall estimates to three downscaling configurations were studied.
               
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