Christy Yan Yu Leung, Haoming Chen, Xiaoming Shi, Ping Cheung, Pak Wai Chan
{"title":"2024年5月21日缅甸高空强湍流事件的分析与模拟","authors":"Christy Yan Yu Leung, Haoming Chen, Xiaoming Shi, Ping Cheung, Pak Wai Chan","doi":"10.1002/met.70058","DOIUrl":null,"url":null,"abstract":"<p>A severe turbulence event was encountered by Singapore airlines SQ321 on 21 May 2024 over Myanmar which led to one fatality and multiple injuries. Analysis of ADS-B data indicated the event happen during the cruising phase of flight over the Irrawaddy Delta, Myanmar. Fluctuations in the vertical speed induced large vertical acceleration and indicated a severe magnitude of aviation turbulence. A study on the satellite and lightning data hinted that the turbulence was likely related to convectively induced turbulence on the downwind side of developing convective clouds. Simulation using Model for Prediction Across Scales (MPAS) with convective permitting resolution indicated the development of convective cells along the coast, moderate turbulence with Eddy Dissipation Rate (EDR) over 0.2 was simulated a couple of hours ahead, but its embedded as small scattered areas within the clouds. The precise location of severe turbulence are still difficult to simulate due to the stochastic nature of turbulence. The seamless blended forecast for significant convection and deep learning model utilising high-pass filtered satellite imageries indicated the growth of convective activity and the presence of convectively induced turbulence in the region. The analysis suggested the importance for having forecasts products showing indication for rapid convective development, which is closely related to convectively induced turbulence or near cloud turbulence. The utilisation of these products within the operations of flights could better safeguard aviation safety.</p>","PeriodicalId":49825,"journal":{"name":"Meteorological Applications","volume":"32 3","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/met.70058","citationCount":"0","resultStr":"{\"title\":\"Analysis and Simulations for the Severe Turbulence Event Aloft Myanmar on 21 May 2024\",\"authors\":\"Christy Yan Yu Leung, Haoming Chen, Xiaoming Shi, Ping Cheung, Pak Wai Chan\",\"doi\":\"10.1002/met.70058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>A severe turbulence event was encountered by Singapore airlines SQ321 on 21 May 2024 over Myanmar which led to one fatality and multiple injuries. Analysis of ADS-B data indicated the event happen during the cruising phase of flight over the Irrawaddy Delta, Myanmar. Fluctuations in the vertical speed induced large vertical acceleration and indicated a severe magnitude of aviation turbulence. A study on the satellite and lightning data hinted that the turbulence was likely related to convectively induced turbulence on the downwind side of developing convective clouds. Simulation using Model for Prediction Across Scales (MPAS) with convective permitting resolution indicated the development of convective cells along the coast, moderate turbulence with Eddy Dissipation Rate (EDR) over 0.2 was simulated a couple of hours ahead, but its embedded as small scattered areas within the clouds. The precise location of severe turbulence are still difficult to simulate due to the stochastic nature of turbulence. The seamless blended forecast for significant convection and deep learning model utilising high-pass filtered satellite imageries indicated the growth of convective activity and the presence of convectively induced turbulence in the region. The analysis suggested the importance for having forecasts products showing indication for rapid convective development, which is closely related to convectively induced turbulence or near cloud turbulence. 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Analysis and Simulations for the Severe Turbulence Event Aloft Myanmar on 21 May 2024
A severe turbulence event was encountered by Singapore airlines SQ321 on 21 May 2024 over Myanmar which led to one fatality and multiple injuries. Analysis of ADS-B data indicated the event happen during the cruising phase of flight over the Irrawaddy Delta, Myanmar. Fluctuations in the vertical speed induced large vertical acceleration and indicated a severe magnitude of aviation turbulence. A study on the satellite and lightning data hinted that the turbulence was likely related to convectively induced turbulence on the downwind side of developing convective clouds. Simulation using Model for Prediction Across Scales (MPAS) with convective permitting resolution indicated the development of convective cells along the coast, moderate turbulence with Eddy Dissipation Rate (EDR) over 0.2 was simulated a couple of hours ahead, but its embedded as small scattered areas within the clouds. The precise location of severe turbulence are still difficult to simulate due to the stochastic nature of turbulence. The seamless blended forecast for significant convection and deep learning model utilising high-pass filtered satellite imageries indicated the growth of convective activity and the presence of convectively induced turbulence in the region. The analysis suggested the importance for having forecasts products showing indication for rapid convective development, which is closely related to convectively induced turbulence or near cloud turbulence. The utilisation of these products within the operations of flights could better safeguard aviation safety.
期刊介绍:
The aim of Meteorological Applications is to serve the needs of applied meteorologists, forecasters and users of meteorological services by publishing papers on all aspects of meteorological science, including:
applications of meteorological, climatological, analytical and forecasting data, and their socio-economic benefits;
forecasting, warning and service delivery techniques and methods;
weather hazards, their analysis and prediction;
performance, verification and value of numerical models and forecasting services;
practical applications of ocean and climate models;
education and training.