Estimating en-route turbulence using ADS-B aircraft data

Aviation turbulence is a hazardous weather phenomenon that affects aviation safety and operations. It can be in the form of convective induced turbulence (CIT), clear air turbulence (CAT), mountain waves or in relation to low level jets. Currently, observations of aviation turbulence are based on either reports from pilots or automated observations from the equipment on board of aircraft. Pilot reports were scarce and could be subjective. Besides, due to the wide range of aircrafts deployed by different airlines, not all aircraft were equipped with automatic equipment to measure turbulence. As aviation traffic recovers, the volume of navigation information broadcasted by commercial aircraft has also increased significantly. The Observatory has installed an Automatic Dependent Surveillance - Broadcast (ADS-B) reception system at Tai Mo Shan Weather Radar Station to track ADS-B equipped aircraft within a range of approximately 500 km. This study attempts to identify and estimate turbulence from these ADS-B signals with an aim to expand turbulence observation over the ADS-B coverage. The analysis would be based on the vertical acceleration and attitude information extracted from ADS-B aircraft data. As aircraft maneuvers would induce noise to the turbulence signal, an algorithm was developed to first identify the en-route phase of the aircraft. As an initial step, the study focused on the en-route phase of aircraft only. Several methodologies, including frequency analysis, peaks analysis, etc., were developed to derive turbulence information from ADS-B data. The results were then compared with the observations from flights that encountered turbulence in 2023. The comparison analysis using different methodologies and their limitations would be discussed. Such turbulence detection algorithm has the potential application on the provision of real-time turbulence information within the ADS-B coverage to aviation users.