A sophisticated algorithm based on the detection of significant headwind changes, the so-called "windshear ramps", has been developed by the Hong Kong Observatory (HKO) in the alerting of low-level windshear using LIDAR data. The method, named as LIWAS (LIDAR Windshear Alerting System), is particularly efficient in detecting airflow disturbances in the vicinity of the Hong Kong International Airport (HKIA) due to terrain disruption of the background wind. It puts emphasis on sustained headwind change from one level to another level. However, for terrain-disrupted airflow, there may also be abrupt wind changes of smaller spatial scales (e.g. over a distance of a few hundred metres) embedded in the windshear ramp which typically spans a larger spatial scale (e.g. over a couple of kilometres). As such, for the alerting of low-level windshear it may be advantageous to consider both the larger scale windshear ramps and the smaller scale wind changes, i.e. headwind gradients. This paper examines the usefulness of such an approach by applying the method to the windshear cases in spring time over four years. It turns out that the inclusion of headwind gradients helps capture 5-10 % more of the significant windshear reported by the pilots. For a particular runway corridor, the combined use of the two windshear detection methods even outperforms the existing windshear alerting service at HKIA. The paper will discuss the rationale behind the headwind gradient method, a prototype of its implementation, and its combined use with the existing LIWAS alerts. It will also discuss preliminary results on the climatology of headwind changes at HKIA based on LIDAR data, as well as the use of aircraft simulator in improving the calculation of LIDAR-based F-factor.
