Using In-Cloud Turbulence Observations to Improve Nowcasting and Forecasting of Convectively Induced Turbulence

In-cloud convectively induced turbulence (CIT) is known to be a significant hazard to aviation. Some mechanisms causing CIT are not yet well understood, making CIT challenging to predict. Towards improving nowcasting and forecasting CIT we use in-cloud observations of turbulence in the form of energy dissipation rate to the 1/3 power (EDR) to determine probability density functions of CIT. These in-cloud EDR observations are provided by the Nexrad Turbulence Detection Algorithm (NTDA) and in situ observations from some commercial aircraft. The probability density functions derived from these observations are needed for calibration of CIT diagnostics within NCAR’s Graphical Turbulenc Guidance (GTG) forecast product. Probability densitity functions of CIT based on various observations will be presented herein and compared to other turbulence distributions.

Furthermore, we use in-cloud EDR observations to identify relationships between in-cloud turbulence severity and convective parameters (e.g. total lightning, echo top heights, etc.). These relationships are then utilized to develop and evaluate potential CIT diagnostics for inclusion in NCAR’s graphical turbulence guidance nowcast (GTG-N) system. GTG-N provides a rapidly updating snapshot of the current turbulent conditions over the continental US in order to allow for tactical turbulence avoidance by aircraft, and is therefore well-suited for inclusion of CIT. Preliminary evaluations of CIT diagnostic performance will also be presented.

This research is in part 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.