An Exploratory Study on the Use of Root-Mean-Square Vertical Acceleration Data from Aircraft for the Detection of Low-Level Turbulence at an Operating Airport

Low-level turbulence is a meteorological hazard that disrupts the operation of airports and is particularly pronounced at Hong Kong International Airport (HKIA), which is impacted by various sources of low-level turbulence (e.g., terrain disrupting wind flow, sea breeze, and thunderstorms). The possibility of using root-mean-square vertical acceleration (RMSVA) data from Automatic Dependent Surveillance–Broadcast (ADS-B) for low-level turbulence monitoring is studied in this paper. Comparisons are performed between RMSVA and Light Detection And Ranging (LIDAR)-based Eddy Dissipation Rate (EDR) maps and the aircraft-based EDR. Moreover, the LIDAR-based EDR map, aircraft EDR, and pilot report for turbulence reporting are compared for two typical cases at HKIA. It was found that the various estimates/reports of turbulence are generally consistent with one another, at least based on the limited sample considered in this paper. However, at very low altitudes close to the touchdown of arrival flights, RMSVA may not be available due to a lack of ADS-B data. With effective quality control and further in-depth study, it will be possible to use RMSVA to monitor low-level turbulence and to alert pilots if turbulence is reported by the pilot of the preceding flight based on RMSVA. The technical details of the various comparisons and the assumptions made are described herein.