Convectively induced turbulence (CIT) is a severe aviation hazard. It is challenging to forecast CIT because low-resolution models cannot explicitly resolve convective motions at kilometer scales. In this study, we used the Model for Prediction Across Scales (MPAS) to simulate CIT cases with convection-permitting resolution ( \(\sim \) 1 km) in the region of the CIT events and coarse resolution in other parts of the globe. We developed a method to estimate the eddy dissipation rate (EDR) using the resolved wind field of the MPAS simulations. The method is based on explicit filtering and reconstruction in the turbulence modeling for large-eddy simulations (LES). It estimates turbulence kinetic energy (TKE), which is then used to derive EDR. The new method produces different turbulence distribution and intensity than previous methods based on second-order structure functions and convective gravity wave drag, with higher accuracy and better correlation with observations for CIT cases tested in this study. The 1-km resolution simulation generates more accurate EDR and improves spatial patterns, but it is computationally demanding. The 3-km resolution can get benefits from reasonable accuracy and affordable computational cost. Because convection-permitting resolutions are in the gray zone for simulating convection, we evaluated the sensitivity of the prediction to the variations in physical and numerical schemes. Varying cumulus convection parameterization and monotonicity of numerical schemes are identified as practical approaches to generate beneficial ensemble spread. However, the physical perturbation-based ensemble has limitations, and initial condition perturbations are still necessary to encompass uncertainties in the development of convection.
