Impacts of different physics schemes on hurricane forecasting in the unified forecast system (UFS)

This study investigates the impacts of different physics schemes on hurricane forecasting across different applications of the unified forecast system (UFS) limited area model (LAM), including the UFS short-range weather (SRW) application, the hurricane analysis and forecast system (HAFS), and the UFS single-column model (SCM). The physics schemes compared here encompass cloud microphysics schemes, planetary boundary layer (PBL) parameterizations, surface layer schemes, gravity wave schemes, and land surface models. All these schemes are implemented through the common community physics package (CCPP) framework. Six experiments, each employing different combinations of physics schemes, were designed to explore their influences on hurricane forecasting. The simulated results from the UFS LAM applications are compared with the observed results from stations, radar, and satellite data. The impacts of various physics schemes on hurricane intensity, track, timing, location, and precipitation are investigated through case studies of different hurricanes, such as Barry, Lorenzo, and Ian. All experiments exhibit a right-of-track bias for hurricanes Barry and Lorenzo. In contrast, the forecasts for hurricane Ian have a left-of-track bias. The results show that the moist turbulence kinetic energy (TKE)-based eddy-diffusivity mass-flux (EDMF) PBL scheme can enhance the hurricane intensity through the moist process. The aerosol-aware (AA) Thompson microphysics scheme appears to provide better precipitation forecasts compared to those from the GFDL microphysics scheme. The combination of these updated physics schemes gives a better track comparing with the result from other old physics settings for hurricane Barry, and it also has an improved intensity in the forecast of hurricane Ian. Sensitivity tests conducted using the UFS SRW application indicate that increasing horizontal resolution and adding vertical levels can enhance model performance. Experiments also revealed that the PBL scheme significantly affects hurricane tracks, a finding further supported by SCM results. Additionally, sensitivity tests demonstrate that improved initial conditions through data assimilation can lead to better simulations of both the hurricane track and intensity, as well as more accurate predictions of hurricane landfall timing and location.