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Avalanche warning onChowkibal-Tangdhar axis (J&K):A hybrid approach

机译:乔基巴尔-汤加尔轴(J&K)上的雪崩警告:一种混合方法

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摘要

Conventional as well as numerical techniques are beingwidely used for the prediction of snow avalanches.The present approach combines both the techniquesand delivers avalanche danger warning for 24 h in advance. Initially different levels of avalanche danger have been decided by observing fresh snow of 24 hand standing snow from a snow-meteorological database of the past ten winters (1992-2002) along with adatabase of avalanche warning and occurrences. Finallythese levels have been characterized by a criticalrange calculated by using a discriminant function,which is a function of all the significant snow and meteorological parameters. The significant snow and meteorological parameters have been selected by correlationanalysis. For the selection of significant parametersand to calculate the critical range for each of the dangerlevels, a new term, i.e. index of avalanche has been introduced and its variation in different ranges of snow and meteorological parameters has been discussed. Forthe winter of 2003-2004, model outcome has beencompared with the actual avalanche occurrences. Out oftotal 122 days during winter, there were 27 avalanchedays and 95 non-avalanche days. The accuracy of themodel for avalanche occurrence is 67% and for non-occurrence it is 84%.
机译:常规和数值技术被广泛用于雪崩的预测。本方法结合了这两种技术并提前24小时发出雪崩危险警告。最初,通过观察过去十个冬季(1992-2002年)的雪气象数据库以及雪崩预警和发生的数据库,观察到24只手直积雪的新鲜雪,确定了不同级别的雪崩危险。最后,这些水平的特征是通过使用判别函数计算出的临界范围,该判别函数是所有重要降雪和气象参数的函数。通过相关分析选择了重要的降雪和气象参数。为了选择重要的参数并计算每种危险等级的临界范围,引入了一个新术语,即雪崩指数,并讨论了其在不同范围的雪和气象参数中的变化。在2003年至2004年冬季,模型结果已与实际雪崩发生次数进行了比较。冬季总共122天中,有27个雪崩日和95个非雪崩日。该模型的雪崩发生率的准确性为67%,非雪崩发生率为84%。

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