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Terrain and building-induced low-level turbulence is studied in this paper. Data from six anemometers, respectively along the North and South Runways of Hong Kong International Airport, are analysed over the period of 2012 to 2018. From this data the recorded turbulence intensities have been computed and the footprints plotted. A joint analysis of the turbulence footprints together with the surrounding environment, using maps and photographs, reveals likely upstream causes influencing the directional distribution of observed turbulence intensities. Signatures from nearby objects and buildings, such as terminals and hangars, are easily identifiable. This paper serves as a unique documentation of possible building influence on wind measurements at a densely-developed, major international airport, and provides useful reference to meteorologists and wind engineers at airports in other parts of the world.

“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.

A weak waterspout was observed at the Hong Kong International Airport on the morning of June 8, 2020. This paper documents the meteorological observations of this weak system, which was well captured by surface wind sensors and a Doppler weather radar, and this study also investigated the capability of a high‐resolution numerical weather prediction model to simulate the system in a near real‐time configuration. Despite the short‐lived nature of the vortex, the model effectively reproduced the occurrence of a weak vortex around the time the system was observed, although with positional errors of the order of a few kilometres. The simulated vertical cross‐sections of the reflectivity and Doppler velocity were consistent with the actual radar observations and reflected the slanting nature of the micro‐vortex. These results may serve as a useful reference for the study of weak waterspouts worldwide.

In aviation, rapidly fluctuating headwind/tailwind may lead to high horizontal windshear, posing potential safety hazards to aircraft. So far, windshear alerts are issued by considering directly the headwind differences measured along the aircraft flight path (e.g. based on Doppler velocities from remote-sensing). In this paper, we propose and demonstrate a new methodology for windshear alerting with the technique of spectral decomposition. Through Fourier transformation of the LIDAR-based headwind profiles in 2012 and 2014 at arrival corridors 07LA and 25RA of the Hong Kong International Airport (HKIA), we study the occurrence of windshear in the spectral domain. Using a threshold-based approach, we investigate performance of single and multiple channel detection algorithms and validate the results against pilot reports. With the receiver operating characteristic (ROC) diagram, we successfully demonstrate feasibility of this approach to alert windshear by showing a comparable performance of the triple channel detection algorithm and a consistent hit rate gain (07LA in particular) of 4.5 to 8 % in quadruple channel detection against GLYGA, which is the currently operational algorithm in HKIA. We also observe that some length scales are particularly sensitive to windshear events which may be closely related to the local geography of HKIA. This study serves to open a new door for the methodology of windshear detection in the spectral domain for the aviation community.

The Doppler Lidar windshear alerting system at the Hong Kong International Airport (HKIA), the first of its kind in the world, has been in operation since 2006. This paper reports on an enhancement to the automatic windshear detection algorithm at HKIA, which aims at filtering out alerts associated with smoother headwind changes spread over longer distances along the aircraft glide path (called “gentle ramps”) which may nonetheless exceed the well-established alerting threshold. Real-time statistics are examined over a 46-month study period between March 2016 and December 2019, covering a total of 2,017,440 min and over 1500 quality-controlled pilot reports of windshear (PIREP). The “gentle ramp removal” (GRR) function is able to effectively cut down the alert duration over the 5 major runway corridors, inclusive of both landing and take-off, which together account for over 98% of the PIREP received at HKIA during the study period. In all 5 runway corridors this is achieved with a proportionately smaller decrease—even with no changes in 2 cases—in the hit rate, highlighting the efficiency of the GRR function. The difference in statistical behaviour across the runway corridors also echo literature findings about the differences in length scale of wind disturbances at different locations within HKIA. This study serves as a unique documentation of the state-of-the-art in operational Lidar windshear detection and can provide useful reference to airports and aviation meteorologists around the world.

In-flight turbulence is recognized as a major safety hazard for the global aviation system, capable of causing serious injuries to crew and passengers as well as structural damage to the aircraft. Its prediction at 1 to 2 days ahead mainly relies on numerical weather prediction (NWP) models, which suffer from various practical and inherent deficiencies. This paper applies the XGBoost algorithm in generating skillful aviation turbulence forecasts through optimal combination of a collection of conventional “turbulence indices” produced by an NWP model. Verification over a 1-year period against over 16000 aircraft pilot reports demonstrated consistent superior performance of the machine-learning based multi-index consensus (MIC) over the Asia-Pacific region, with median gains in skill score between 3% to 17% compared to constituent turbulence indices when taken individually.

Convective weather (thunderstorm clusters with horizontal extents from tens to hundreds of kilometers, and vertically up to 10 - 15 kilometers in the troposphere) along aircraft flight trajectory is a key factor influencing air traffic management decisions and aviation safety. For an airport, aircraft arrival performance is typically more sensitive to weather conditions than departures. The occurrence of thunderstorms along or around flight routes may force the arriving aircraft to hold/vector in the terminal maneuvering area (TMA) following air traffic control (ATC) instructions, leading to additional fuel burn and delays. Such effects could cascade and bring further negative impacts to air traffic inside TMA. In this work, we perform a joint analysis of high-resolution radar rainfall distribution with 2-D aircraft flight trajectory data surrounding the Hong Kong International Airport (HKIA) to uncover the potential spatio-temporal impact of thunderstorms on air traffic. Results indicate that aircraft arrival traffic is sensitive to the location of convective weather in TMA, which also introduces a time lag effect on subsequent air traffic on the order of hours.

Eleven tropical cyclones that landed in Guangdong Province since 2012 and experienced strengthening or weakening over the offshore area were studied. Since the structure of the tropical cyclone boundary layer significantly influences the variation of the intensity of the cyclone, continuous observations of the wind profile radar at a coastal radar station in Guangdong Province were combined with aircraft observation data of the No. 1604 “Nida” cyclone to analyse the variations in the distributions of the radial wind, tangential wind, and angular momentum in the typhoon boundary layer and the similarities and differences between the boundary layers of the 11 tropical cyclones during the strengthening or weakening of their intensities. The analysis results show that the presence of the supergradient wind and the enhancement effect of the radial inflow play important roles in enhancing the intensity of a tropical cyclone. The observations indicate that when the tangential wind velocity in the maximum wind velocity radius reaches the velocity of the supergradient wind and when the radial inflow either gradually increases towards the centre of the tropical cyclone or gradually covers the entire boundary layer, the angular momentum tends to be shifted towards the centre. At this time, the maximum radial inflow, maximum tangential wind, and maximum angular momentum are in the same height range in the vertical direction. When a strong radial outflow occurs in the boundary layer of a tropical cyclone or the area with maximum wind velocity is located in the air outflow, the angular momentum cannot easily be transported towards the centre of the typhoon. Therefore, the spatial configuration of the three physical quantities will determine future changes in the intensity of tropical cyclones. The scope of the results presented here is limited to the 11 selected cases and suggests extending the analysis to more data.

An observational and simulation study of a tornado event in Hong Kong that occurred in the morning of 29 August 2018 is documented in this paper. Rotating airflow associated with the tornado is well captured by the Doppler velocity from a Terminal Doppler Weather Radar (TDWR) in Hong Kong. The Doppler velocity patterns show the typical signature of a velocity couplet associated with a meso/microcyclone, and for most part of its lifetime, it captures clearly the evolution with time. Weather radar echoes of those thunderstorms inducing the current tornado, as well as the meso/microcyclone itself, are also successfully reproduced in a real-time simulation by a fine-resolution numerical weather prediction (NWP) model initialised 3 hours earlier, albeit with a time lag of about 15 minutes when compared to the actual event. The model simulation displays some interesting features of the cyclone, including the vertical structure of horizontal and vertical velocities and cloud liquid water content, which are consistent with literature that accounts in other parts of the world. The vertical profile of maximum radial velocity associated with the velocity couplet also compares well between the actual weather radar observation and numerical simulation. The results in this paper could serve as an interesting reference for both meteorologists and wind engineers, also demonstrating the power of very high-resolution NWP in predicting such events in a real-time fashion.

Terrain-induced windshear at Hong Kong International Airport (HKIA) could be hazardous to the landing and departing aircraft. Such windshear occurring in a planetary boundary layer without temperature inversions is studied in this paper by using the data from the Terminal Doppler Weather Radar and Light Detection and Ranging systems. A high resolution numerical model, called aviation model (AVM), is also employed to find out its capability to forecast the occurrence of such windshear. The model is found to have skills in capturing the terrain-induced windshear, including the terrain-induced microburst due to the mountains of Lantau Island. Moreover, the windshear detection algorithm as applied to the AVM output, called AVM-GLYGA, is able to give advance alert for the occurrence of low-level windshear. The model also offers new dataset, such as vertical velocity and vertical cross sections across the windshear feature, to study the terrain-induced windshear phenomena with new insights. The AVM is found to have good skills in depicting the terrain-disrupted airflow at the airport area, and more comprehensive study would be conducted to study the skills of AVM-GLYGA as compared with pilot windshear report as sky truth.

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.

Low-level turbulence [rapid headwind fluctuations below 1600 ft (500 m)] poses potential safety hazards to landing/departing aircraft and is capable of disrupting air traffic. Timely, accurate alerts of low-level turbulence require reliable determination of its intensity, quantified by an internationally adopted aircraft-independent metric [cube root of the eddy dissipation rate (EDR1/3)], which cannot be directly measured but only inferred from observational data. In this paper, a large-scale survey of terrain-induced low-level turbulence intensity around the Hong Kong International Airport (HKIA) during tropical cyclone (TC) passage is presented, utilizing EDR1/3 values determined from multiple remote sensing and in situ sources, including the scanning Doppler lidar, the terminal Doppler weather radar (TDWR), a high-resolution anemometer, and the operational Windshear and Turbulence Warning System (WTWS) at HKIA. Over a 18 720-min study period spanning five TC cases between 2010 and 2012, ground-based EDR1/3 was computed using a variety of first-principle and empirical methods and was shown to demonstrate a strong linear correlation with airborne values determined from quick access recorder (QAR) data of over 350 landing flights. Spatiotemporal features as experienced on board aircraft were also reproduced by the lidar- and TDWR-derived profiles. Positive skill could be extracted from threshold-based alerting of low-level turbulence events by considering each ground-based source individually, while a combination of lidar and TDWR alerts demonstrated enhanced performance and hence the potential value of complementary surveillance under clear-air and in rain conditions. This study serves to establish the ability of ground-based instruments in correlating with airborne EDR1/3 and the performance of threshold-based alerting algorithms for turbulence events, contributing toward improvements in turbulence-alerting techniques for the aviation community.

High frequency aircraft observations from the Government Flying Service of the Hong Kong Government, penetrating a tropical cyclone at low altitude over the South China Sea, were thinned by arithmetic means over different time intervals to identify structures of tropical cyclone at different scales. It is found that the thinning process can reduce serial correlation in observational errors and enhance the representation of aircraft observations. Assimilation experiments demonstrate that aircraft observations can improve the track and intensity forecasts of Typhoon Nida (2016). The changes in dynamic structures indicate that the imbalance generated from assimilating aircraft observations at the sub-grid scale can be alleviated by using longer time intervals of the arithmetic mean. Assimilating aircraft observations at the grid scale achieves optimal forecasts based on verifications against independent observations and investigations of environmental and ventilation flows. In addition, it is indicated that decreasing the quality control threshold and changing the observational error of aircraft observations in the data assimilation can reduce the representation errors.

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 EDR1/3 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 m2/3 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.

The fixed-wing aircraft of Government Flying Service of the Hong Kong Government has recently equipped with an upgraded meteorological measuring system. This system provides horizontal wind velocity components up to 90 m/s at an accuracy of 0.5 m/s for straight and level flight. Besides search and rescue (SAR) missions, this aircraft is also used for windshear and turbulence investigation flights at the Hong Kong International Airport. In a SAR operation in July 2009, the aircraft flew close to the eye of tropical cyclone Molave, when it was located at about 200 km to the east of Hong Kong over the south China coastal waters. The aircraft provided valuable information about the winds in association with Molave because aircraft reconnaissance for tropical cyclones is not carried out for South China Sea. Based on the aircraft measurements, the 1-second mean wind reached the maximum value of 88 knots at a height of 200 m above mean sea level. Assuming a power law with altitude with an exponent of 0.11 over open waters, the corresponding 1-second mean wind at a height of 10 m would be about 63 knots. The maximum 10-minute mean wind reached 69 knots with an average height of 260 m above mean sea level. The corresponding mean at 10 m would be about 48 knots. As such, based on the aircraft measurements (in which the aircraft might not fly into the areas of maximum winds associated with the tropical cyclone), Molave had at least a strength of tropical storm to severe tropical storm at the times of the measurements. Nowadays, the determination of the intensity of tropical cyclones over the South China Sea is normally based on remote sensing data only (e.g. radar and satellite observations). To the knowledge of the authors, the results presented in the paper are the first time that direct measurements of the winds near the centre of a tropical cyclone over the northern part of the South China Sea are made with an aircraft. Apart from the mean wind and gust, other properties of the wind field of Molave are studied, e.g. frequency spectrum of the horizontal wind data, and thus the turbulence associated with this tropical cyclone.

Hong Kong Observatory currently uses a series of meteorological instruments, including long-range LIDAR (light detection and ranging) systems, to provide alerting services of low-level windshear and turbulence for Hong Kong International Airport. For some events that are smaller in spatial dimensions and are rapidly changing, such as low altitude windshear and turbulence associated with buildings or man-made structures, it would be necessary to involve meteorological instruments that offer greater spatial resolution. Therefore, the Observatory has set up a short-range LIDAR on the roof of the AsiaWorld-Expo during the summers over the past several years, conducting field research on the feasibility of strengthening early alerting for windshear and turbulence over the north runway’s eastern arrival runway (Runway 25RA) and developing an automated early alerting algorithm. This paper takes the pilot reports for Runway 25RA during the 2013 field research as verification samples, using different thresholds for radial wind velocity spatial and temporal changes detected by the short-range LIDAR to calculate the relative operating characteristic (ROC) curve, and analyzes its early alerting performance.