Does a Scale-Aware Convective Parameterization Scheme Improve the Simulation of Heavy Rainfall Events?

Abstract

Precipitation predictability using the non-scale-aware and scale-aware convective parameterization schemes (CPSs) was investigated to assess the necessity of the CPSs within the gray-zone. This study evaluates the performance of the Weather Research and Forecasting (WRF) model's CPS for 135 heavy rainfall events (HREs) over the Korean Peninsula for 10 years (i.e., 2011-2020). We tested the Kain-Fritsch (KF) scheme (non-scale-aware) and Multi-scale Kain-Fritsch (MSKF) scheme (scale-aware) in the WRF model. The MSKF scheme shows an overall improved performance of precipitation simulation compared to the KF scheme, but the precipitation forecast performance of CPS depends on the characteristics of HREs. When the HREs are characterized by synoptic-scale atmospheric conditions with strong winds and large-scale water vapor transport, the forecast performance of both CPSs is similar because a cloud microphysics scheme can explicitly resolve most of the precipitation. However, in the case of HREs with weak synoptic forcing conditions (e.g., moisture transport and winds) related to the localized and meso-scale HREs, the MSKF scheme can improve overall simulated precipitation by increasing grid-scale precipitation and reducing the overestimation of subgrid-scale precipitation simulated in the KF scheme. Therefore, using the scale-aware CPS in the gray-zone can provide more accurate precipitation forecasts regardless of the environmental condition of the HREs. In this study, we evaluate the predictability of precipitation using two types of convective parameterization schemes (CPS), non-scale-aware and scale-aware, in the Weather Research and Forecasting (WRF) model. The scale-aware CPS utilizes scale-aware parameters to adjust convection processes based on horizontal resolution. We focus on heavy rainfall events (HREs) over the Korean Peninsula for 10 years from 2011 to 2020. A HRE is defined as rainfall greater than 110 mm in 12 hr. The results show that the scale-aware CPS improved the precipitation forecast performance compared to the non-scale-aware CPS, and the precipitation forecast performance of CPS differs depending on the characteristics of HREs. For HREs characterized by the synoptic forcing conditions with strong winds and large-scale horizontal advection of water vapor, both CPSs perform well, but their forecast performance decreases for HREs with weak synoptic forcing conditions. We also find that for localized heavy rain cases, using the scale-aware CPS helps improve precipitation forecasts at 4-km horizontal resolution. We evaluate the impacts of the non-scale-aware and scale-aware convective parameterization scheme (CPS) in the gray-zone using the Weather Research and Forecasting The precipitation forecast performance of CPS depends on the type of heavy rainfall event (HRE) and environmental conditions The scale-aware CPS in the gray-zone can provide more accurate precipitation forecasts regardless of the environmental condition of the HREs