Prediction of Convectively Induced Turbulence Based on Convection-Parameterizing Numerical Weather Prediction Models

Convective clouds can generate turbulence in the atmosphere, namely convectively induced turbulence (CIT), posing significant weather hazards to aviation operations in, vicinity of, and distant from clouds. Accurate prediction of CIT heavily relies on the representation of convective clouds in numerical weather prediction (NWP) models. Using NWP models at convection-permitting grid spacings — e.g., 3 km — has yielded good results in predicting CIT. However, most state of the art global NWP models, particularly operational models, still use model grid spacings that cannot explicitly resolve convection (e.g., 9 km or coarser), requiring parameterizations of convective clouds.

This study assesses potentials of convection-parameterizing NWP models to predict CIT based on case studies. Various model parameters associated with convection are tested to infer turbulence from the parameterized convection, and different convective parameterizations are compared in terms of the representations of convective clouds.

This research is in response to requirements and funding by the Federal Aviation Administration (FAA). The views expressed are those of the authors and do not necessarily represent the official policy or position of the FAA. The NSF National Center for Atmospheric Research is a major facility sponsored by the U.S. National Science Foundation under Cooperative Agreement No. 1852977.