Refinement of Mesoscale and Turbulent-Scale Surface Stresses in the Korean Integrated Model (KIM) for Global Weather Forecasting

Abstract This study attempted to improve the skill of the Korean Integrated Model (KIM) for global numerical weather prediction. To this end, mesoscale stress and turbulent-scale stress caused by subgrid-scale orography (SSO) and surface layer physics, respectively, were refined. The SSO data computation method was revised by considering the mathematical moments of the statistics over the cubed-sphere grid. The modifications made in this study resulted in increased mesoscale stress over mountainous regions. The boundary layer stress due to the turbulent form drag is weakened, but the turbulent stress due to changes in the vegetation table value is largely increased owing to the enhanced roughness length for momentum. The enhancement of mesoscale drag over mountainous areas is robust; however, the partitioning into mesoscale and turbulent stresses varies over particular regions. The forecast skill at medium-range time scales was largely improved not only in surface parameters but also in the upper meteorological variables. Significance Statement Mesoscale surface stress caused by subgrid-scale orography parameterization affects synoptic-scale forecasting by reducing the wind speed above the tropopause. In contrast, turbulent-scale stress due to surface layer physics parameterization is crucial for accurately representing near-surface meteorological variables. This study introduces revisions to both the parameterizations of a global weather forecasting model. The results demonstrate a noticeable improvement in the predictability of medium-range forecasts.