{"title":"模拟未来空中交通管理自动化的数字气象模型研究","authors":"J. Grado, Carmen Salguero Tascon","doi":"10.1109/WETICE.2011.40","DOIUrl":null,"url":null,"abstract":"Aviation Meteorology plays an essential role for the Air Traffic Management (ATM) automation. The availability of accurate estimates of atmosphere properties would largely increase safety and efficiency of air traffic operations. The work presented here looks forward to a net-centric serviceoriented ATM system architecture where available data, airground connectivity and modern computational resources and techniques are taken advantage of to attain a 4D predictive model of atmospheric properties specifically designed for real-time support to air vehicle operations in highly dense terminal manoeuvring areas. The effort, conducted as part of the ATLANTIDA project, consists of the development of a digital meteo model (DMET) that combines atmospheric data from several sources into a 4D predictive scenario that is made available to subscribers through periodic updates. Atmospheric data sources include forecasts from global and mesoscale weather models as well as live observations provided by ground stations and aircraft in the scene. The model produced consists of a 4D grid of pressure, temperature and wind data fields valid over an airspace cube of about 150 × 150 × 20 km, within a time interval of 2.5 hours. On top of this model, minimum time, minimum consumption and other interesting trajectories are simulated and shown, all being processed remotely in a supercomputing centre.","PeriodicalId":274311,"journal":{"name":"2011 IEEE 20th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises","volume":"200 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"On the Development of a Digital Meteorological Model for Simulating Future Air Traffic Management Automation\",\"authors\":\"J. Grado, Carmen Salguero Tascon\",\"doi\":\"10.1109/WETICE.2011.40\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aviation Meteorology plays an essential role for the Air Traffic Management (ATM) automation. The availability of accurate estimates of atmosphere properties would largely increase safety and efficiency of air traffic operations. The work presented here looks forward to a net-centric serviceoriented ATM system architecture where available data, airground connectivity and modern computational resources and techniques are taken advantage of to attain a 4D predictive model of atmospheric properties specifically designed for real-time support to air vehicle operations in highly dense terminal manoeuvring areas. The effort, conducted as part of the ATLANTIDA project, consists of the development of a digital meteo model (DMET) that combines atmospheric data from several sources into a 4D predictive scenario that is made available to subscribers through periodic updates. Atmospheric data sources include forecasts from global and mesoscale weather models as well as live observations provided by ground stations and aircraft in the scene. The model produced consists of a 4D grid of pressure, temperature and wind data fields valid over an airspace cube of about 150 × 150 × 20 km, within a time interval of 2.5 hours. On top of this model, minimum time, minimum consumption and other interesting trajectories are simulated and shown, all being processed remotely in a supercomputing centre.\",\"PeriodicalId\":274311,\"journal\":{\"name\":\"2011 IEEE 20th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises\",\"volume\":\"200 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 20th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WETICE.2011.40\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 20th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WETICE.2011.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the Development of a Digital Meteorological Model for Simulating Future Air Traffic Management Automation
Aviation Meteorology plays an essential role for the Air Traffic Management (ATM) automation. The availability of accurate estimates of atmosphere properties would largely increase safety and efficiency of air traffic operations. The work presented here looks forward to a net-centric serviceoriented ATM system architecture where available data, airground connectivity and modern computational resources and techniques are taken advantage of to attain a 4D predictive model of atmospheric properties specifically designed for real-time support to air vehicle operations in highly dense terminal manoeuvring areas. The effort, conducted as part of the ATLANTIDA project, consists of the development of a digital meteo model (DMET) that combines atmospheric data from several sources into a 4D predictive scenario that is made available to subscribers through periodic updates. Atmospheric data sources include forecasts from global and mesoscale weather models as well as live observations provided by ground stations and aircraft in the scene. The model produced consists of a 4D grid of pressure, temperature and wind data fields valid over an airspace cube of about 150 × 150 × 20 km, within a time interval of 2.5 hours. On top of this model, minimum time, minimum consumption and other interesting trajectories are simulated and shown, all being processed remotely in a supercomputing centre.