A clustering approach for analysis of convective weather impacting the NAS

M. Asencio
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引用次数: 13

Abstract

By the year 2025, the number of aircraft operations in the U.S. will significantly increase [1]. In order to address the safety, capacity, and environmental needs that this situation will generate, the Next Generation Air Transportation System (NextGen) is transforming the National Airspace System (NAS) by including 21st Century technology [1, 2]. NASA's NextGen Systems Analysis, Integration, and Evaluation (SAIE) project, under the Airspace System Program (ASP), assesses the cost and NAS performance benefits of these technologies. One of these new near-term technologies is Dynamic Weather Rerouting (DWR), which is being developed by NASA. DWR has the capability to provide rerouting information for flights to efficiently avoid severe convective weather situations. The objective of the research documented in this paper was to design and implement a sampling process for the selection of representative days that best reflect the yearly patterns of convective weather impact to the NAS, which will be used for testing the DWR technology.
对流天气影响NAS的聚类分析方法
到2025年,美国的飞机运营数量将显著增加[1]。为了解决这种情况将产生的安全、容量和环境需求,下一代航空运输系统(NextGen)正在通过包括21世纪技术来改造国家空域系统(NAS)[1,2]。NASA的下一代系统分析、集成和评估(SAIE)项目隶属于空域系统计划(ASP),评估这些技术的成本和NAS性能优势。这些近期的新技术之一是美国宇航局正在开发的动态天气改道(DWR)。DWR有能力为航班提供改道信息,以有效避免强对流天气情况。本文所记录的研究目的是设计和实施一个抽样过程,以选择最能反映对流天气对NAS影响的年度模式的代表性日子,这将用于测试DWR技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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