“Low-level wind shear” is a known aviation safety hazard and refers to a sustained change in head wind encountered by an aircraft during takeoff or landing. Because of their small spatiotemporal scales and high variability, automatic alerting of wind shears at airports around the world is almost exclusively detection based (using remote sensing equipment). Numerical modeling studies so far mainly cover individual cases and lack systematic validation. This paper presents the first statistical evaluation of numerical weather prediction (NWP) model performance in predicting low-level wind shear at a major international airport over a 2-yr continuous period. The 200-m-resolution Aviation Model (AVM) of the Hong Kong Observatory is used to generate runway-specific wind shear forecasts at 1-min output intervals for the Hong Kong International Airport (HKIA), known for its susceptibility to wind shear occurrence. The AVM forecasts are then validated against over 800 actual reports of wind shear by aircraft pilots over the two major arrival runway corridors, 07LA and 25RA, at HKIA between 2014 and 2015 using a verification scheme with the same level of spatiotemporal stringency as operational alerting systems at HKIA. With “relative operating characteristic” analysis, positive skill is consistently observed across both runway corridors throughout the study period and across all considered forecast lead times out to 6 h ahead. This study serves to establish and document the current capability of fine-resolution NWP in predicting the phenomenon of low-level wind shear for aviation weather applications.

Hong Kong International Airport (HKIA) is situated in an area of complex terrain. Mountains near the airport can lead to terrain‐disrupted airflow disturbances, which may bring about hazardous weather phenomena for aviation, such as low‐level windshear and turbulence. Timely forecasting of such airflow disturbances would be useful in providing early warnings to the pilots. The Hong Kong Observatory has been running a super high resolution numerical weather prediction model suite, the aviation model (AVM), since late 2013, with spatial resolution up to 200 m immediately around HKIA. After testing and tuning over the past year, the performance of the AVM in forecasting terrain‐disrupted airflow at the airport area is investigated in this study. Two typical cases of such complex airflow are considered, Foehn wind and mountain wave. The AVM is found to capture successfully some salient features of the airflow as observed around HKIA through comparison with light detection and ranging (LIDAR) and weather buoy observations. The model also helps in shedding new light on the airflow from the vertical cross sections of the winds across the mountains. Limitations of the AVM are also discussed.

In aviation meteorology, eddy dissipation rate (EDR) is an internationally‐adopted metric for quantifying intensity of low‐level turbulence (rapid, irregular headwind fluctuations experienced by an aircraft below 1600 feet/500 m). In this paper, calculations of EDR^1/3 profiles along arrival corridors (07LA, 25RA) of the Hong Kong International Airport (HKIA) were performed over a 45 month period (January to September, 2008–2012) based on radial velocity from a scanning Doppler LIDAR using the azimuthal velocity structure function approach. The quality of the LIDAR‐estimated EDR was established by comparison with values calculated from in situ measurements over a 24 month period, which showed that median values of EDR profiles from both sources fell within 0.05 m^2/3 s⁻¹ of each other in over 90% (80%) of instances for 07LA (25RA). The performance in threshold‐based alerting of low‐level turbulence at HKIA was then validated against pilot reports. At alert duration of 10%, alerts based on the maximum value of an EDR profile could capture over 90% (80%) of reported events over 07LA (25RA), while comparable performance with the wind shear and turbulence warning system (WTWS) at HKIA was attainable using suitable alert thresholds. Positive skill, albeit inferior to WTWS, was also observed in the alerting of low‐level wind shear (sustained headwind change of 15 knots or above below 1600 feet/500 m) with a hit rate of about 70% at alert duration of 10%. This study served to establish the value of EDR derived from ground‐based remote‐sensing instruments e.g. LIDAR in alerting of low‐level turbulence for the aviation community.