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Forecasting snow avalanches using avalanche activity data obtained through seismic monitoring

机译:使用通过地震监测获得的雪崩活动数据预测雪崩

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Accurate avalanche occurrence data are of crucial importance for avalanche forecasting, since recent avalanching provides direct evidence on snowpack instability. We therefore explore how avalanche activity data obtained through seismic monitoring can be used for avalanche forecasting. By visually inspecting, data from a seismic sensor deployed in an avalanche starting zone, we obtained three avalanche catalogues for two entire winters and one period of 10 days with intense wet-snow avalanche activity. Avalanche activity was clustered in time for all catalogues, and diurnal periodicity was clearly present during spring. In winter, when dry-snow avalanches predominantly release, rather weak long-term correlations on the order of several days were found between past and future avalanche activity. We investigated the performance of a simple model to predict future avalanches based on past avalanche activity. Model performance was better in spring than in winter, especially for very short time scales of up to 3h, and for time scales around 24 h. Furthermore, the performance of our very simple model was comparable to the performance of more sophisticated models to forecast wet-snow avalanche release based on meteorological input variables. While it is clear that for operational avalanche forecasting automatic avalanche detection still has to be developed, overall this work shows that avalanche activity data obtained through seismic monitoring would yield very valuable data for wet -snow avalanche forecasting. (C) 2016 Elsevier B.V. All rights reserved.
机译:准确的雪崩发生数据对于雪崩预测至关重要,因为最近的雪崩提供了有关积雪不稳定的直接证据。因此,我们探索如何通过地震监测获得的雪崩活动数据可用于雪崩预测。通过目视检查,从部署在雪崩起始区中的地震传感器获得的数据,我们获得了三个雪崩目录,分别记录了两个冬季和一个10天的强烈雪雪雪崩活动。所有目录的雪崩活动均按时间聚集,春季明显存在昼夜周期性。在冬季,当主要释放干雪雪崩时,过去和将来的雪崩活动之间存在几天左右的长期弱关联。我们调查了基于过去雪崩活动预测未来雪崩的简单模型的性能。春季的模型性能要好于冬季,尤其是在长达3小时的非常短的时标和24小时左右的时标上。此外,我们非常简单的模型的性能可与基于气象输入变量预测湿雪崩释放的更复杂模型的性能相媲美。显然,要进行业务雪崩预测,仍然需要开发自动雪崩检测,但总体而言,这项工作表明,通过地震监测获得的雪崩活动数据将为湿雪崩预测提供非常有价值的数据。 (C)2016 Elsevier B.V.保留所有权利。

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