The Korea Meteorological Administration (KMA) implemented a 10-yr project to develop its own global model (GM) by 2020. To reflect the complex topography and unique weather characteristics of the Korean Peninsula, a high-resolution model with accurate physics and input data is required. The WRF single-moment 6-class microphysics scheme (WSM6) and WRF double-moment 6-class microphysics scheme (WDM6) that will be implemented in the Korea GM (KGM) are evaluated. Comparisons of the contoured frequency by altitude diagram (CFAD), time–height cross sections, and vertical profiles of hydrometeors are utilized to assess the two schemes in simulating summer monsoon and convective precipitation cases over the Korean Peninsula during 2011. The results show that WSM6 and WDM6 overestimate the height of the melting level and bright band as compared to radar observations. However, the accuracy of WDM6 is in better agreement with radar observations. This is attributed to the difference in the sedimentation process simulated by the additional second-moment total number concentrations of liquid-phase particles in WDM6. WDM6 creates larger raindrops and higher relative humidity beneath the melting layer, allowing the scheme to simulate a more realistic reflectivity profile than WSM6 for the summer monsoon case. However, for the convective case, both schemes underestimate the precipitation and there is resolution dependence in the WRF Model’s ability to simulate convective precipitation.

The effects of attenuation correction in rainfall estimation with X-band dual-polarization radar were investigated with a dense rain gauge network. The calibration bias in reflectivity (ZH) was corrected using a self-consistency principle. The attenuation correction ofZHand the differential reflectivity (ZDR) were performed by a path integration method. After attenuation correction,ZHandZDRwere significantly improved, and their scatter plots matched well with the theoretical relationship betweenZHandZDR. The comparisons between the radar rainfall estimation and the rain gauge rainfall were investigated using the bulk statistics with different temporal accumulations and spatial averages. The bias significantly improves from 70% to 0% withR(ZH). However, the improvement withR(ZH,ZDR)was relatively small, from 3% to 1%. This indicated that rainfall estimation using a polarimetric variable was more robust at attenuation than was a single polarimetric variable method. The bias did not show improvement in comparisons between the temporal accumulations or the spatial averages in either rainfall estimation method. However, the random error improved from 68% to 25% with different temporal accumulations or spatial averages. This result indicates that temporal accumulation or spatial average (aggregation) is important to reduce random error.