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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.

Aircraft wake is a pair of strong counter-rotating vortices generated behind a flying aircraft, which might be dangerous to the following aircrafts. The real-time and precise locating of aircraft wake vortex-core positions is essential in the aviation safety field, especially in airport traffic management. This study proposes a two-step vortex-core locating method which uses the Gabor filter to make a preliminary locating and the velocity range distribution to make a fine locating consequently. The combination of Gabor filter and Doppler velocity distribution can improve the method's adaptability to complex background wind field and mitigate the impact of noise. Numerical examples and field detection campaigns from Changsha Huanghua International Airport and Hong Kong International Airport have well verified the good performance of the method, in terms of both accuracy and real time.

Tropical cyclone (TC) track predictions of the 10-km resolution WRF (provisionally named "AAMC-WRF") of the Hong Kong Observatory (HKO), spanning (20⁰S - 60⁰N, 45⁰E − 160⁰E) is studied for a 1-year period from April 2018 to Mar 2019. Real-time predictions, up to 4 times a day and T+48 h ahead, are verified against operational analysis positions of HKO for storms over the South China Sea (SCS) and Western North Pacific (WNP); and of the New Delhi Regional Specialised Meteorological Centre (RSMC) for storms over the North Indian Ocean basin (NIO; including the Bay of Bengal). Out of 21 named TCs over SCS and WNP, mean positional errors of the AAMC-WRF are 33 km (T+0), 63 km (T+24), and 107 km (T+48) based on 209, 178 and 142 forecasts. The AAMC-WRF outperformed Meso-NHM, also run in real-time at HKO, with mean error reduction up to 34 km or 24%. Mean positional errors for 13 NIO storms are 38 km (T+0), 69 km (T+24) and 107 km (T+48) based on 183, 131 and 85 forecasts. This is the first study in which TC predictions of a regional model are simultaneously examined over the SCS, WNP and NIO basins through real-time experiments.

“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.

The Hong Kong Observatory conducted six flights in the atmospheric boundary layer of five tropical cyclones: tropical storm Jebi (1309), typhoon Kalmaegi (1415), severe tropical storm Linfa (1510), typhoon Mujigae (1522), and severe typhoon Nida (1604). Three-dimensional wind data with a 20-Hz sampling rate are available for a height range of 500–670 m, with the mean wind speed from these low-level flights ranging from 10 to 62 m s−1. The turbulent momentum flux and turbulence kinetic energy (e) are measured using the eddy-correlation method, while horizontal scales of turbulent eddies, vertical eddy diffusivity (K), and the vertical turbulent mixing length scale are estimated indirectly. The dependence of the momentum flux, e, K, and the vertical mixing length on wind speed and height are compared with previous studies. Both the momentum flux and turbulent kinetic energy increase with the wind speed, although the rate of increase is smaller for higher wind speeds. It is also found that K increases with wind speed according to a power law up to 40 m s−1 before levelling off, while the vertical mixing length is nearly constant at 100 m. The results serve as a reference for evaluating and improving the turbulent parametrizion in tropical-cyclone models, while the observed large turbulent mixing near the top of the inflow layer of the eyewall region should not be neglected in numerical models.

A rare winter thunderstorm event near Hong Kong is documented in this paper. The thunderstorm occurrence was confirmed by the observation of one of the authors and lightning location information systems (both regional and global). It developed over the frontal cloud band associated with the winter monsoon. Observing the upper air measurements, however, the thermodynamic conditions did not seem favorable to the occurrence of the thunderstorm. The convective available potential energy could not be determined in the cool and dry lower troposphere. There was only a moister layer in the middle troposphere. The weather forecaster did not anticipate the occurrence of thunder and lightning. However, some features could have changed dynamically, which suggested the possibility that a thunderstorm would take place. For instance, waves could be identified in the middle troposphere and a broad troughing flow could be analyzed in the lower troposphere. The integrated wave vapor was also of a rather high level. It is hoped that this paper can serve as a useful reference for forecasters in assessing the possibility of thunderstorms occurring during winter over subtropical latitudes in association with frontal cloud bands.

Aircraft wake is a pair of strong counter-rotating vortices generated behind a flying aircraft. It might be very hazardous to a following aircraft and the real-time detection of it is of great interest in aviation safety field. Vortex-core positions and velocity circulations, which respectively represent the location and strength of a wake, are two characteristic parameters that have attracted the main attention in wake vortex detection. This paper introduces a new algorithm, the Path Integration (PI) method, to retrieve the characteristic parameters of wake vortex. The method uses Doppler velocity distribution to locate the vortex-core positions, and the integration of Doppler velocity along a LOS (line-of-sight) is derived as a linear expression about the circulations. From this expression, the circulations can be solved with the least square method. Moreover, an vortex-core position adjusting method is proposed to compensate the compressing and expanding effects of wake vortex caused by the scanning of Lidar beam. Basically, the use of Doppler velocity integration can improve the method’s adaptability in turbulence environment and mitigate the impact of noise. Numerical examples and field detection data from Hong Kong international airport and Tsingtao Liuting airport have well verified the good performance of the method, in terms of both accuracy and efficiency.

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.

This study investigates the applicability and relevance of the residence time to the characterisation of airborne pollutant removal in the urban environment. Using large-eddy simulations of flow over an idealised building array and a realistic urban area, the statistical and spatial distributions of residence times are analysed for different source locations and wind conditions. For the idealised building array, the mean residence times in the avenue and intersection units depend on the mean flow, turbulent kinetic energy and wind direction. The probability density function (PDF) shows distinct early and late regimes when there are pollutant removal processes associated with different boundaries. For the realistic urban domain, the residence times are significantly shorter and stronger fluctuations are observed in the PDF, especially when the inflow winds are driven by the output from a high-resolution mesoscale model. The residence time is especially useful for applications to assessment and planning, when information about the timescale of pollutant removal is required and the flow is inhomogeneous and unsteady.

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.

A wake vortex is a form of irregular airflow generated by a flying aircraft, which can cause a severe hazard for aviation. To quantify the hazard of a wake after fully roll-up and before rebound, this paper proposes an algorithm to retrieve its characteristic parameters (circulations, vortex-core positions, and vortex-core radii) with a scanning Doppler Lidar. In the algorithm, a governing equation related to the Doppler velocities and characteristic parameters is established based on the aerosols’ weak inertia, from which the target parameters are solved with an optimization method. During the process, the distortion of Doppler velocity caused by the scanning of the Lidar beam is adjusted by the Doppler acceleration to achieve better estimations of the target characteristic parameters. Good performance of the algorithm has been verified by simulation and field detection data.

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.

Weather is well recognized as a significant environmental factor contributing to higher risk of road crashes. In the conventional road safety studies, weather effects had been set out either based on the instant weather conditions recorded by the police officer attained or the average of meteorological observations over a relatively long time period, such as daily, weekly or even monthly, etc. To the best of our knowledge, it is rare that the lag effect of weather in the preceding period on the crash risk in the current period was attempted. With the use of high-resolution meteorological data in very short time interval, it is possible to evaluate the role of lagged weather effect on safety. In this study, we propose a novel distributed lag non-linear model (DLNM), integrated with case-crossover design, to evaluate the lag effect of weather on crash incidence. The proposed modelling framework could describe the non-linear relationship between weather and crash and the lag effects. Also, the possible over-dispersion and autocorrelation of the time-series weather and crash data can be controlled for. The model was estimated using an integrated meteorological, traffic and crash dataset in Hong Kong. For instances, high resolution data on temperature, humidity, rain intensity and wind speed in 1-hour interval was available. The bi-dimensional exposure-lag-response surfaces are established to visualize the varying effects of possible weather factors on crash risk, with respect to the lag size. Such relationship between effect size and lag size is often overlooked in the literatures. Results indicate that model with 4 degrees of freedom for both weather condition (knots at equal spaces) and lag time (knots at equal intervals) best fit with the observations, in accordance to Quasi-likelihood Akaike information criterion (Q-AIC). Then, stratified analyses are conducted to evaluate the difference in the association among different clusters. Findings should shed light on the modelling of non-linear exposure-response relationship and lag effects in traffic safety time series analysis.

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.

Vertically aligned mono-domain nematic liquid crystal elastomers contract when heated. If a temperature gradient is applied across the width of such a cantilever, inhomogeneous strain distribution leads to bending motion. We modelled the kinetics of thermally-induced bending in the limit of a long thin strip and the predicted time-variation of curvature agreed quantitatively with experimental data from samples with a range of critical indices and nematic-isotropic transition temperatures. We also deduced a value for the thermal diffusion coefficient of the elastomer.

This paper focuses on the investigation of contact length and chip morphology in high-speed turning. In this study the performance of five different coatings: TiN, TiCN, TiAlN and CrTiAlN PVD coatings, and an advanced Dymon-IC hydrogenated amorphous carbonbased coating (a-C:H) deposited by plasma-enhanced chemical vapour deposition (PECVD) is investigated in high-speed machining (HSM) of AISI/SAE - 4140 high-strength alloy steel at cutting speeds ranging between 210 and 925 m/min. Modelling of chip contact length is revisited and the results of extensive machining tests supported by use of a high-speed camera are reported. The effects of coatings on the chip compression ratio, back flow angle, tool-chip contact length, frictional force, and tool wear are explored. The paper contributes towards a fundamental understanding of heat generation and partition in metal cutting using coated tools.

This investigation is concerned with the experimental and analytical study of grinding forces generated in plunge surface grinding with a resin-bonded CBN wheel. In contrast to Al2O3 grinding, the pattern of CBN grinding forces is unique which characterises its semi-permanent and other performance properties. To describe such behaviour, a mathematical model is proposed and validated using the experimental data. The applicability of the CIRP parameter ‘equivalent grinding thickness’ was also studied and found to give a fairly good fit of data after making suitable modifications.

The results of a series of plunge surface grinding tests conducted with CBN wheels on fully heat-treated bearing steel showed that the increase in G ratio, compared with Al2O3 wheels, can be a factor of 20 to 200 times. Assessment of grindability in terms of grinding forces, specific energy, surface finish is discussed over a grinding wheel speed range from 20 ms to 60 m. The effects of grain size and grinding conditions are also presented, together with spectral analyses of the process-generated dynamics. For a given workpiece-machine system* CBN wheels exhibit unique characteristics that the grindability will increase with time for all the tests conducted.