Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record(QAR)Data Analysis

As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.

地形对香港国际机场起降航道低空风切变的影响

为识别复杂地形影响下香港国际机场(HKIA,Hong Kong International Airport)低空风切变的易发空域,采用大涡模拟方法(LES,large eddy simulation)对机场及其周边地形进行了风场精细化数值模拟。结合风速云图比较东、东南、南、西南风背景下3条跑道起降航道上的风速变化,分析得出了地形与风场分布间的因果关系。通过与无地形情况下的对照试验结果对比,采用F因子(识别逆风)和7节标准(识别侧风)识别机场跑道低空风切变易发区间。结果表明,东风易造成飞机进离场的逆风风速发生时空变化;西南风影响跑道东侧着陆路径上的逆风风速,但几乎不影响跑道西侧离场路径的风速;在东南风和南风背景下,3条跑道起降航道低空段的侧风均受地形影响显著。根据3条跑道进离场航道上的低空风切变易发空域,得到了地形因素对香港国际机场低空风切变的影响范围,研究结果可为机场风切变风险防控提供主动规避措施和建议。

Effects of Dropsonde Data in Field Campaigns on Forecasts of Tropical Cyclones over the Western North Pacific in 2020 and the Role of CNOP Sensitivity

Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones,namely Higos,Nangka,Saudel,and Atsani,over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weather Bureau in 2020.The conditional nonlinear optimal perturbation(CNOP)method has been utilized in real-time to identify the sensitive regions for targeting observations adhering to the procedure of real-time field campaigns for the first time.The observing system experiments were conducted to evaluate the effect of dropsonde data and CNOP sensitivity on TC forecasts in terms of track and intensity,using the Weather Research and Forecasting model.It is shown that the impact of assimilating all dropsonde data on both track and intensity forecasts is case-dependent.However,assimilation using only the dropsonde data inside the sensitive regions displays unanimously positive effects on both the track and intensity forecast,either of which obtains comparable benefits to or greatly reduces deterioration of the skill when assimilating all dropsonde data.Therefore,these results encourage us to further carry out targeting observations for the forecast of tropical cyclones according to CNOP sensitivity.

Ground–Space–Sky Observing System Experiment during Tropical Cyclone Mulan in August 2022

Forecasting tropical cyclone track and intensity is a great challenge for the meteorological community,and safeguarding the life and property of people living near the coast is an important issue.One major reason for challenging forecasts is the lack of observations over the vast oceans.During tropical cyclone Mulan between 8 and 10 August 2022 over the northern part of the South China Sea,the meteorological authority and research institutes of Chinese mainland collaborated with the meteorological service in Hong Kong on conducting the first-ever ground–space–sky observing system experiment on tropical cyclone Mulan.The enhanced targeted observations collected during the experiment include Geostationary Interferometric Infrared Sounder,round-trip radiosondes,and aircraft-launched dropsondes.This paper describes the campaign,technical details of the meteorological models used,and impact of the additional targeted observation data on the tropical cyclone forecast.Ideally,similar enhanced observation campaigns could be conducted in the future,not only in the northern part of the South China Sea,but also in other ocean basins.

Large-scale Circulation Control of the Occurrence of Low-level Turbulence at Hong Kong International Airport

This study identifies the atmospheric circulation features that are favorable for the occurrence of low-level turbulence at Hong Kong International Airport [below 1600 feet （around 500 m）]. By using LIDAR data at the airport, turbulence and nonturbulence cases are selected. It is found that the occurrence of turbulence is significantly related to the strength of the southerly wind at 850 hPa over the South China coast. On the other hand, the east-west wihd at this height demonstrates a weak relation to the occurrence. This suggests that turbulence is generated by flow passing Lantau Island from the south. The southerly wind also transports moisture from the South China Sea to Hong Kong, reducing local stability. This is favorable for the development of strong turbulence. It is also noted that the strong southerly wind during the occurrence of low-level turbulence is contributed by an anomalous zonal gradient of geopotential in the lower troposphere over the South China Sea. This gradient is caused by the combination of variations at different timescales. These are the passage of synoptic extratropical cyclones and anticyclones and the intraseasonal variation in the western North Pacific subtropical high. The seasonal variation in geopotential east of the Tibetan Plateau leads to a seasonal change in meridional wind, by which the frequency of low-level turbulence is maximized in spring and minimized in autumn.

Low-Level Wind Shear Characteristics and Lidar-Based Alerting at Lanzhou Zhongchuan International Airport,China

Lanzhou Zhongchuan International Airport[International Civil Aviation Organization(ICAO)code ZLLL]is located in a wind shear prone area in China,where most low-level wind shear events occur in dry weather conditions.We analyzed temporal distribution and synoptic circulation background for 18 dry wind shear events reported by pilots at ZLLL by using the NCEP final(FNL)operational global analysis data,and then proposed a lidar-based regional divergence algorithm(RDA)to determine wind shear intensity and location.Low-level wind shear at ZLLL usually occurs in the afternoon and evening in dry conditions.Most wind shear events occur in an unstable atmosphere over ZLLL,with changes in wind speed or direction generally found at 700 hPa and 10-m height.Based on synoptic circulations at 700 hPa,wind shear events could be classified as strong northerly,convergence,southerly,and weak wind types.The proposed RDA successfully identified low-level wind shear except one southerly case,achieving94%alerting rate compared with 82%for the operational system at ZLLL and 88%for the ramp detection algorithm(widely used in some operational alert systems)based on the same dataset.The RDA-unidentified southerly case occurred in a near neutral atmosphere,and wind speed change could not be captured by the Doppler lidar.

Characteristics of Spatiotemporal Distribution of Sea Surface Wind along the East Coast of Guangdong Province

We analyzed the frequency distribution characteristics of wind speeds occurring at different offshore sites within a range of 0-200 km based on the sea surface wind data captured via buoys and oil platforms located along the east coast of Guangdong Province. The results of the analysis showed that average wind speed measured for each station reached a maximum in winter while minima occurred in summer, corresponding to obvious seasonal variation, and average wind speed increased with offshore distance. The prevailing wind direction at the nearshore site is the east-erly wind, and the frequency of winds within 6-10 m s^-1 is considerable with that of winds at 〉 10 m s^-1. With the in-crease of the offshore distance, the winds were less affected by the land, and the prevailing wind direction gradually became northerly winds, predominately those at 〉 10 m s^-1. For areas of shorter offshore distance （〈 100 km）, sur-face wind speeds fundamentally conformed to a two-parameter Weibull distribution, but there was a significant dif-ference between wind speed probability distributions and the Weibull distribution in areas more than 100 km off-shore. The mean wind speeds and wind speed standard deviations increased with the offshore distance, indicating that with the increase of the wind speed, the pulsation of the winds increased obviously, resulting in an increase in the ra-tio of the mean wind speed to the standard deviation of wind speed. When the ratio was large, the skewness became negative. When a relatively great degree of dispersion was noted between the observed skewness and the skewness corresponding to the theoretical Weibull curve, the wind speed probability distribution could not be adequately de-scribed by a Weibull distribution. This study provides a basis for the verification of the adaptability of Weibull distri-bution in different sea areas.