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Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps – a matter of model limitations or unpredictable nature?

机译:对阿尔卑斯山一场非预期的雪雨洪水的回顾性分析–是模型限制还是不可预测的性质?

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摘要

A rain-on-snow flood occurred in the Bernese Alps, Switzerland, on 10 October 2011, and caused significant damage. As the flood peak was unpredicted by the flood forecast system, questions were raised concerning the causes and the predictability of the event. Here, we aimed to reconstruct the anatomy of this rain-on-snow flood in the Lötschen Valley (160 km2) by analyzing meteorological data from the synoptic to the local scale and by reproducing the flood peak with the hydrological model WaSiM-ETH (Water Flow and Balance Simulation Model). This in order to gain process understanding and to evaluate the predictability.ududThe atmospheric drivers of this rain-on-snow flood were (i) sustained snowfall followed by (ii) the passage of an atmospheric river bringing warm and moist air towards the Alps. As a result, intensive rainfall (average of 100 mm day-1) was accompanied by a temperature increase that shifted the 0° line from 1500 to 3200 m a.s.l. (meters above sea level) in 24 h with a maximum increase of 9 K in 9 h. The south-facing slope of the valley received significantly more precipitation than the north-facing slope, leading to flooding only in tributaries along the south-facing slope. We hypothesized that the reason for this very local rainfall distribution was a cavity circulation combined with a seeder-feeder-cloud system enhancing local rainfall and snowmelt along the south-facing slope.ududBy applying and considerably recalibrating the standard hydrological model setup, we proved that both latent and sensible heat fluxes were needed to reconstruct the snow cover dynamic, and that locally high-precipitation sums (160 mm in 12 h) were required to produce the estimated flood peak. However, to reproduce the rapid runoff responses during the event, we conceptually represent likely lateral flow dynamics within the snow cover causing the model to react "oversensitively" to meltwater.ududDriving the optimized model with COSMO (Consortium for Small-scale Modeling)-2 forecast data, we still failed to simulate the flood because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus we conclude that this rain-on-snow flood was, in general, predictable, but requires a special hydrological model setup and extensive and locally precise meteorological input data. Although, this data quality may not be achieved with forecast data, an additional model with a specific rain-on-snow configuration can provide useful information when rain-on-snow events are likely to occur.
机译:2011年10月10日,瑞士伯尔尼阿尔卑斯山发生了一场雪雨洪水,造成了严重破坏。由于洪水预报系统无法预测洪水高峰,因此引发了有关事件原因和可预测性的问题。在这里,我们旨在通过分析天气数据到局部范围的气象数据,并使用水文模型WaSiM-ETH(水)再现洪峰,来重建洛琴山谷(160 km2)的这种雪雨洪水的解剖结构流量和平衡仿真模型)。这是为了获得对过程的了解并评估可预测性。 ud ud雪上雨水洪水的大气驱动因素是(i)持续降雪,其次(ii)一条通向大气的河流将温暖潮湿的空气吹向阿尔卑斯山。结果,大雨(平均每天1天为100毫米)伴随着温度升高,使0°线从1500 m.s.l.转移到1200 ma.s.l。 (海拔高度米)在24小时内,在9小时内最大增加了9K。山谷的南坡比北坡收到更多的降水,仅在沿南坡的支流中泛滥。我们假设出现这种局部降雨的原因是空腔循环与播种机-送料云系统相结合,增强了朝南的斜坡上的局部降雨和融雪。 ud ud通过应用并大幅度重新校准了标准水文模型设置,我们证明了既需要潜热通量又需要合理的热通量来重建积雪动态,并且需要局部高降水量(12小时内为160毫米)来产生估计的洪峰。但是,为了重现事件期间的快速径流响应,我们从概念上描述了积雪内部可能发生的侧向流动动力学,从而导致模型对融化水“过度敏感”地反应。 ud ud使用COSMO(小型模型联盟)来驱动优化模型)-2预报数据,由于COSMO-2预报数据低估了当地的降水峰值和温度升高,因此我们仍然无法模拟洪水。因此,我们得出的结论是,这种大雨雪洪水总体上是可预见的,但需要特殊的水文模型设置以及广泛且局部精确的气象输入数据。尽管用预报数据可能无法达到此数据质量,但是当可能发生雪上降雨事件时,具有特定雪上降雨配置的其他模型可以提供有用的信息。

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