Spatial and Temporal Characteristics of Unpredicted Upper-Level Turbulence Events using the Global Aviation Turbulence Forecast System and In-Situ Aircraft Data

Aviation turbulence, one of the major weather hazards in the aviation industry, is normally classified by generation sources, as follows: convectively induced turbulence (CIT), clear-air turbulence (CAT) that is not directly associated with convective systems, but is mainly caused by various atmospheric instabilities near the jet stream, and mountain wave turbulence (MWT) related to vertically propagating mountain waves generated by low-level flows across mountainous areas. To reduce damage caused by unexpected aviation turbulence encounters, we developed the Korean aviation Turbulence Guidance (KTG) system by combining various large-scale forcing-based CAT and MWT diagnostics calculated from the Korea Meteorological Administration (KMA)’s operational global numerical weather prediction (NWP) model outputs. This has been used successfully for operational turbulence forecast. The KTG system generally shows good performance skills for null- and moderate-or-greater (MOG)-level turbulence, but when focusing only on the performance results for MOG-level turbulence, it shows low performance skill of about 30% (i.e., 0.3 of probability of detection for yes; PODY). In this study, to analyze the cause of the low PODY of the KTG forecast for MOG-level turbulence, we looked at all of the unpredicted MOG-level turbulence events from in situ turbulence observation data for one year. And, the spatial and temporal characteristics of the unpredicted MOG-level turbulence events are analyzed to understand which places are the most unpredicted areas in a given NWP model. We also tried to understand how individual CAT and MWT diagnostics currently used in the KTG system are correlated well with the unpredicted and predicted turbulence events. This will be eventually useful for improving the current version of the KTG system to take into account any possible forecasting capability of CIT and other unknown sources related to CAT and MWT.

 

Acknowledgment: This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2022-00410, and was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00250021).