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Probabilistic analysis of recent snow avalanche activity and weather in the French Alps

机译:法国阿尔卑斯山近期雪崩活动和天气的概率分析

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The characterization of statistical relationships between snow avalanche occurrence and climate can be useful for avalanche prediction. We investigated the relationship between avalanche occurrences between 1978 and 2003 and meteorological parameters for 576 avalanche events from 12 avalanche tracks in the Valloire valley in the French Alps. Probabilities of avalanche occurrence based on logistic regression analyses were calculated at a daily and yearly time scale, by differentiating high- and low-frequency avalanche tracks. For high-frequency avalanche tracks, the daily probability of avalanche depends on the precipitation (water equivalent, i.e. WE) the day before a given avalanche event, along with the mean air temperature the day of the event. For low-frequency avalanche tracks, on the other hand, it depends on precipitation (WE) the day preceding a given event, only. We also tested the relationship between various meteorological parameters and the type of avalanche. The occurrence of dry snow avalanches is related to total precipitation (WE) on the day of and the day before a given event, whereas that of wet snow avalanches depends on precipitation (WE) the day of a given event, and maximum air temperature during the event. Our results show that for high-frequency avalanche tracks, annual probabilities of high avalanche activity depend on the occurrences of successive days (≥ 3 days) with high precipitation in winter and above-average air temperature (mean± 1 S.D.). For low-frequency avalanche tracks, probabilities of high avalanche activity depend on the occurrences of successive days (≥ 3 days) with high precipitation in winter. The sensitivity of these models was tested through bootstrap analyses. We also discuss the role of meteorological parameters highlighted in these models.
机译:雪崩发生与气候之间统计关系的表征对于雪崩预测很有用。我们调查了1978年至2003年雪崩发生与法国阿尔卑斯山瓦卢瓦尔河谷12条雪崩轨道中576次雪崩事件的气象参数之间的关系。通过区分高频和低频雪崩轨迹,在每日和每年的时间尺度上计算基于逻辑回归分析的雪崩发生概率。对于高频雪崩航迹,雪崩的日发生概率取决于给定雪崩事件发生前一天的降水量(水当量,即WE)以及该事件发生当天的平均气温。另一方面,对于低频雪崩轨迹,它仅取决于给定事件前一天的降水量(WE)。我们还测试了各种气象参数与雪崩类型之间的关系。干雪崩的发生与给定事件发生的当天和之前的总降水量(WE)有关,而湿雪崩的发生取决于给定事件发生的当天的降水量(WE)以及事件期间的最高气温事件。我们的结果表明,对于高频雪崩轨道,高雪崩活动的年概率取决于冬季连续出现的日子(≥3天),冬季降水高和气温高于平均水平(平均值±1 S.D.)。对于低频雪崩轨道,高雪崩活动的概率取决于冬季连续降雨(≥3天)与高降水量的发生。这些模型的敏感性通过引导分析进行了测试。我们还将讨论在这些模型中突出显示的气象参数的作用。

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