Evaluation of KIM-Regional/Local Forecast Model Performance Based on the Korea Physics Parameterization Package

  As the demand for high-resolution weather forecasts continues to increase, operational numerical weather prediction centers face challenges in maintaining model consistency across horizontal scales while accurately representing region-specific physical processes. This study evaluates the KIM-Regional/Local system, a unified modeling framework employing the Korea Physics Parameterization Package (KPPP) optimized for the Korean Peninsula. The system operates on two nested scales: a 3-km regional domain covering East Asia (5-day forecasts) and a 1-km local domain covering the Korean Peninsula (2-day forecasts). A key distinction in their configuration is the treatment of convection: cumulus parameterization is applied in the 3-km regional model, whereas the 1-km local model is configured as convection-permitting, explicitly resolving deep convection without a cumulus scheme. Both domains share identical dynamical cores and other KPPP components.
  KPPP introduces several key advancements optimized to regional environmental conditions. These developments include refinements to microphysical processes, along with enhanced radiative parameterizations that account for all-sky radiation and topographic slope and shading effects. The land surface scheme includes observation-based refinements to tree and canopy height, which are expected to improve the representation of surface fluxes. To enhance initial and boundary conditions, an oceanic mixed-layer model is activated, and spatially and temporally varying Charnock coefficients are introduced for sea surface roughness calculations, replacing the previously used constant values. Together, these developments are introduced to better represent key physical processes in the model, while accounting for computational efficiency required for operational application.
  Forecast performance was evaluated for representative summer and winter periods through comprehensive verification of surface and upper-air variables against observations, alongside quantitative precipitation forecasts assessment. The most pronounced improvements are found in surface verification results, particularly in surface wind speed, where the Root Mean Square Error (RMSE) is substantially reduced compared to the current operational system. Overall enhancements are also evident in precipitation performance, with reduced biases across forecast ranges in both the 3-km and 1-km domains. These results indicate that region-specific physics development provides a robust pathway toward operationally reliable high-resolution prediction systems over regions with complex terrain.