Examining Meteorological Benefits of Rapid-Scan, Fully Digital Phased Array Radar Observations for Detecting Tornado Formation and Intensification

IF 2.3 4区 地球科学 Q2 ENGINEERING, OCEAN
Brandon K. Cohen, David J. Bodine, Mark Yeary, Jeffrey C. Snyder, Howard B. Bluestein
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引用次数: 1

Abstract

Abstract This study focuses on the application of phased array radars (PARs) to observe tornadoes and their formation. PAR technology for meteorological applications is maturing and may become a valuable tool for the meteorological community. A fully digital PAR offers a range of benefits including adaptive scanning techniques, higher temporal resolution especially via radar imaging modes, and denser vertical sampling to allow for more complete observations of severe hazard structure and evolution. To best understand the benefits of such a system, synthetic PAR observations are generated from archived mobile rapid-scan observations collected by the Rapid X-Band Polarimetric (RaXPol) radar to emulate typical operational radar ranges and PAR-enabled scanning strategy effects. In this study, a synthetic PAR data tool is applied to two tornadic cases (24 May 2011 El Reno, Oklahoma, tornado and the 24 May 2016 Dodge City, Kansas, tornadoes) and one nontornadic case (17 April 2013). Results indicate that, despite increasing standoff ranges and using vertical imaging, a PAR can still observe a similar mode of tornadogenesis [i.e., nondescending tornadic vortex signature (TVS)] as traditional mobile systems but with a slight delay in observing intensification at increasing standoff ranges and reduced change in measured intensity. The PAR-enabled vertical imaging mode does not eliminate our ability to identify the TVS at different spoiling factors, but changes to the structure of the TVS may have operational implications. We hope that the improved understanding of meteorological benefits from these synthetic PAR data can provide useful insight for fully digital PAR radar placement and warning operations. Significance Statement The purpose of this study is to understand the benefits of future radars with faster, more advanced phased array technology. Using mobile radar data, we simulate phased array radar observations for nine tornadic cases and one nontornadic case. Using rapid-scan updates at long distances, we observed that tornado formation and intensification characteristics align with existing literature but exhibit slight delays and reduced intensity. Vertical imaging (simultaneous observations in elevation) does not affect velocity signature detectability but broadens signatures, making intensification less apparent. While our results highlight the utility of phased array radar observations for tornadoes, they also reveal potential detection challenges. Future work should examine additional scanning techniques and variables to assess observational impacts further.
研究快速扫描全数字相控阵雷达观测对龙卷风形成和增强的气象效益
摘要本文主要研究了相控阵雷达(par)在龙卷风及其形成观测中的应用。PAR技术在气象方面的应用日趋成熟,可能成为气象界的一种有价值的工具。全数字PAR具有一系列优势,包括自适应扫描技术、更高的时间分辨率(特别是通过雷达成像模式)和更密集的垂直采样,可以更完整地观察严重危险结构和演变。为了更好地理解这种系统的好处,合成PAR观测数据是由Rapid x波段极化(RaXPol)雷达收集的存档移动快速扫描观测数据生成的,以模拟典型的作战雷达距离和PAR扫描策略效果。在本研究中,一个合成PAR数据工具应用于两个龙卷风案例(2011年5月24日俄克拉荷马州埃尔里诺龙卷风和2016年5月24日堪萨斯州道奇城龙卷风)和一个非龙卷风案例(2013年4月17日)。结果表明,尽管增加了对峙距离并使用垂直成像,PAR仍然可以观测到与传统移动系统相似的龙卷风形成模式[即非下降龙卷风涡特征(TVS)],但在增加对峙距离时观测强度略有延迟,测量强度变化减少。par支持的垂直成像模式不会消除我们识别tv在不同破坏因素下的能力,但tv结构的改变可能会对操作产生影响。我们希望从这些合成PAR数据中提高对气象效益的理解,可以为全数字化PAR雷达的放置和预警操作提供有用的见解。意义声明本研究的目的是了解采用更快、更先进相控阵技术的未来雷达的好处。利用移动雷达数据,模拟了9种龙卷风和1种非龙卷风情况下的相控阵雷达观测结果。使用远距离快速扫描更新,我们观察到龙卷风的形成和增强特征与现有文献一致,但表现出轻微的延迟和强度降低。垂直成像(在高程上同时观测)不影响速度特征的可探测性,但会拓宽特征,使增强不那么明显。虽然我们的研究结果强调了相控阵雷达观测龙卷风的实用性,但它们也揭示了潜在的探测挑战。未来的工作应该研究更多的扫描技术和变量,以进一步评估观测影响。
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来源期刊
CiteScore
4.50
自引率
9.10%
发文量
135
审稿时长
3 months
期刊介绍: The Journal of Atmospheric and Oceanic Technology (JTECH) publishes research describing instrumentation and methods used in atmospheric and oceanic research, including remote sensing instruments; measurements, validation, and data analysis techniques from satellites, aircraft, balloons, and surface-based platforms; in situ instruments, measurements, and methods for data acquisition, analysis, and interpretation and assimilation in numerical models; and information systems and algorithms.
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