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Infrasound array criteria for automatic detection and front velocity estimation of snow avalanches: towards a real-time early-warning system

机译:用于雪崩自动检测和前沿速度估计的次声阵列标准:朝着实时预警系统发展

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Avalanche risk management is strongly related to the ability to identify and timely report the occurrence of snow avalanches. Infrasound has been applied to avalanche research and monitoring for the last 20 years but it never turned into an operational tool to identify clear signals related to avalanches. We present here a method based on the analysis of infrasound signals recorded by a small aperture array in Ischgl (Austria), which provides a significant improvement to overcome this limit. The method is based on array-derived wave parameters, such as back azimuth and apparent velocity. The method defines threshold criteria for automatic avalanche identification by considering avalanches as a moving source of infrasound. We validate the efficiency of the automatic infrasound detection with continuous observations with Doppler radar and we show how the velocity of a snow avalanche in any given path around the array can be efficiently derived. Our results indicate that a proper infrasound array analysis allows a robust, real-time, remote detection of snow avalanches that is able to provide the number and the time of occurrence of snow avalanches occurring all around the array, which represent key information for a proper validation of avalanche forecast models and risk management in a given area.
机译:雪崩风险管理与识别和及时报告雪崩发生的能力密切相关。在过去的20年中,次声波已被用于雪崩的研究和监测,但从未成为识别与雪崩有关的清晰信号的操作工具。我们在此介绍一种基于对由伊施格尔(奥地利)的小口径阵列记录的次声信号进行分析的方法,该方法为克服该限制提供了重大改进。该方法基于阵列得出的波参数,例如后方位角和视在速度。该方法通过将雪崩视为次声的移动源来定义自动雪崩识别的阈值标准。我们使用多普勒雷达进行连续观测来验证自动次声检测的效率,并说明如何有效地推导阵列周围任何给定路径中雪崩的速度。我们的结果表明,适当的次声阵列分析可以对雪崩进行鲁棒,实时,远程检测,从而能够提供阵列周围雪崩发生的次数和发生时间,这代表了适当的关键信息。验证给定区域的雪崩预测模型和风险管理。

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