Christy Yan Yu Leung

Case studies of low-level windshear and turbulence encountered by aircraft with actual pilot reports under all sky conditions are conducted for the first time at Hong Kong International Airport (HKIA) for late autumn to early winter (October to December of the year). These observational analyses follow from the recent enhancements of meteorological instrumentation at HKIA, namely, range–height indicator (RHI) scans of the light detection and ranging system (LIDAR) and the installation of Doppler microwave cloud radar in July 2025. Some novel features of windshear and turbulence are revealed in the present paper. In particular, windshear due to a low-level jet in the presence of liquid clouds shows up clearly in the cloud radar picture. The elevated and elongated mountain wake is well captured by the LIDAR’s RHI scans. And terrain-induced windshear is analyzed for light northerly wind conditions at HKIA. The combination of LIDAR and microwave cloud radar has the potential to provide a truly all-weather windshear and turbulence alerting service for aircraft. However, further research still needs to be performed, and this paper also discusses the future algorithm developments that would be required for this all-weather protection to be realized.

A waterspout was sighted in the offshore waters of Hong Kong in mid-October 2025, the second-latest occurrence of this weather phenomenon in a single year since 1959. Due to the close proximity of the phenomenon to Lamma Island in Hong Kong, detailed sighting information and photographs of the waterspout are available for analysis. This paper investigates the meteorological background of the event, the stability of the atmosphere, and weather radar images from two dual-polarization weather radar stations within the territory to determine the type and intensity of the observed waterspout and its formation mechanism. At that time, the atmosphere was rather unstable, with high values for CAPE and bulk Richardson number, along with an upper-level divergence area that provided updraft momentum for convective development. Detailed observations from these weather radar images showed that the waterspout was a rather weak system with relatively low radar reflectivity and generally weak Doppler velocities, although the velocity signatures, such as Doppler velocity couplets, and azimuthal shear were quite clear. The potential for an operational 2-kilometer ensemble prediction system (EPS) from the Hong Kong Observatory to indicate a favorable environment for waterspout development was also investigated. While the EPS cannot be expected to resolve the waterspout problem or reproduce its exact location and timing, it can capture weak low-level cyclonic anomalies and convergences near Lamma Island that would provide favorable conditions for the formation of waterspouts and are broadly consistent with the observed mesoscale environment.

Accurate characterization of aircraft turbulence is vital for aviation safety and efficiency. This study leverages 2021 data from nationwide Pilot Reports (PIREPs) and China Eastern Airlines’ in situ Eddy Dissipation Rate (EDR) measurements to systematically compare these two primary turbulence monitoring sources. We quantify their consistencies and discrepancies in capturing turbulence intensity and spatiotemporal patterns to assess their respective value and limitations. The findings indicate that while the diurnal and monthly variation trends of turbulence distributions are generally consistent between the two datasets, significant differences exist in intensity distribution, vertical profiles, and spatial patterns. By examining 242 turbulence events concurrently recorded by both China Eastern Airlines’ EDR and pilot reports, the study identifies a spatial discrepancy within 40 km and an average reporting delay of approximately two minutes in PIREPs, with the delay becoming more pronounced as turbulence intensity increases. Furthermore, pilot-reported “severe” turbulence corresponds to EDR values notably lower than the ICAO standard, revealing a systematic overestimation bias.

Cloud liquid water content (CLWC) based on microwave radiometer data was investigated in this study. First, its consistency with radiosonde-based CLWC was established. Integrated CLWC was also checked against the liquid water path. CLWC performance in four weather types was considered: dense fog, clouds in spring, rainstorms, and typhoons. CLWC provides new insights into weather events. In particular, it could be useful for nowcasting low visibility associated with sea fog. It was also found to be inversely proportional to visibility in two cases of low visibility in Hong Kong. In springtime, low-level clouds and liquid water were found to exist extensively inside clouds. In rainstorm cases, supercooled cloud liquid water was absent during heavy rain but may exist within clouds when rain stops or light rain occurs. Similar observations were made in typhoon cases, namely during the direct impact of Typhoon Wipha on Hong Kong. Supercooled cloud liquid was present when outer rainbands of the typhoon affected Hong Kong with a smaller amount of rainfall. However, when Hong Kong was hit by a typhoon’s eyewall, rain was heavier, and supercooled liquid water was absent. These features are consistent with the radiosonde-based CLWC profiles. Radiometer-based CLWC is pseudocontinuous and provides additional insight into liquid water distribution in clouds under various weather conditions.

The present study aims to explore the technical feasibility of simulating in advance, and thus forecasting, the occurrence of low-level windshear at an airport in the complex terrain of the Qinghai–Tibet Plateau. Three cases of windshear at Xining Airport are investigated. They are related to synoptic scale subsidence flow and downward momentum transfer, terrain modification of a cold front, and wind convergence arising from synoptic- and mesoscale high-pressure areas. The simulation results are compared with actual Doppler LIDAR observations. It is found that the simulations reproduce the windshear features reasonably well. The low-level wind speed and/or wind direction convergence are clearly represented in the simulations. The simulated LIDAR radial velocity has a correlation coefficient of over 0.9 with the actual LIDAR radial velocity. Though the present study involves a limited number of cases, it is found to be feasible to use a high-resolution numerical weather prediction model to simulate low-level windshear at an airport on the plateau. It is hoped that this methodology could be extended from the Hong Kong International Airport to the plateau airports, and then to airports in other parts of the world.

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.

With the availability of more ground-based remote-sensing meteorological equipment at Hong Kong International Airport, many more interesting features of terrain-disrupted airflow have been observed, such as the applications of short-range Doppler LIDAR. This paper documents a number of new features observed at the airport area, such as the hydraulic jump-like feature, vortex, and extensive mountain wake/reverse flow. The technical feasibility of using a numerical resolution weather prediction model to simulate such features is also explored. It is found that the presently available input data and numerical model may not be able to capture the fine features of the atmospheric boundary layer, and thus they are not very successful in reproducing many small-scale terrain-disrupted airflow features downstream of an isolated hill. On the other hand, more larger-scale terrain-disrupted flow features may be better captured, but there are still limitations with the available turbulence parameterization schemes. This paper aims at documenting the newly observed flow features at the Hong Kong International Airport, enhancing the understanding of low-level windshear, and evaluating the outputs of numerical resolution simulations for reproducing such observed features and its technical feasibility on short-term forecasting.

Airport Arrival Rate (AAR) is a parameter specifying the number of arrival aircrafts that an airport can accept within an hour and it is commonly used for air traffic flow control. The Hong Kong International Airport (HKIA) is one of the busiest airports in the world for passenger and the world’s busiest for cargo in 2024. Situated in a sub-tropical climate, HKIA often experiences significant convective weather and squall lines associated with cold fronts, low-pressure troughs and tropical cyclones during spring and summer. These intense convective activities sometimes disrupt the air traffic flow and cause significant travel delays in HKIA. An assessment of the impact of convective activities (related to its intensity and coverage) to AAR would facilitate early planning and necessary air traffic flow control. This study attempts to predict the Airport Arrival Rate via machine learning techniques using aircraft data, airport operational data and meteorological data. The aircraft data specifies the aircraft positions extracted from ADS-B data which can be used to evaluate the degree of congestion in the air space. The airport operational data shows the scheduled AAR for the day, which varies depending on the seasons and holidays. For meteorological data, the weather radar data indicates the location and intensity of convection. Besides, radar nowcast products for the next two hours can provide information on the short-term evolution of the significant convection. This paper will present the formulation of a convolutional neural network (CNN) model to predict the AAR. Due to imbalanced data and the changes in air traffic throughout the years, techniques of coupled CNN model and incremental learning are employed and evaluated. The results and limitations for these techniques will be discussed in the paper. It is worth noting that there are many other factors affecting AAR, not just the weather, but this study may serve as an estimation of the weather’s impact on air traffic. Following validation and evaluation, the Hong Kong Observatory may utilize the model to work with the air traffic flow management team in Hong Kong to improve air traffic flow planning.

Because of terrain disruption of the airflow and interface between different airmasses, wave motions may be observed in the vicinity of the Hong Kong International Airport using plan position indicator scans and range height indicator scans with Doppler light detection and ranging systems. This paper documents three cases of wave motion that are not commonly observed near this airport and have never been described before in the literature for Hong Kong, including one mountain wave case and two cases of interfaces between airmasses. These waves may have impacts on aviation safety by leading to the occurrence of low-level windshear and turbulence. They are studied further using a high-resolution numerical weather prediction model. It is found that the model is capable of capturing some features of the waves, such as their occurrence mechanisms. However, some details of the waves are not successfully reproduced, such as the changes in the number of wave crests/troughs with time. Further study should also be conducted to reproduce the wavelengths of these waves.