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Snow-cover reconstruction methodology for mountainous regions based on historic in situ observations and recent remote sensing data

机译:基于历史现场观测和最新遥感数据的山区积雪重建方法

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摘要

Spatially distributed snow-cover extent can be derived from remote sensingdata with good accuracy. However, such data are available for recent decadesonly, after satellite missions with proper snow detection capabilities werelaunched. Yet, longer time series of snow-cover area are usuallyrequired, e.g., for hydrological model calibration or water availabilityassessment in the past. We present a methodology to reconstruct historicalsnow coverage using recently available remote sensing data and long-termpoint observations of snow depth from existing meteorological stations. Themethodology is mainly based on correlations between station records andspatial snow-cover patterns. Additionally, topography and temporalpersistence of snow patterns are taken into account. The methodology wasapplied to the Zerafshan River basin in Central Asia – a very data-sparseregion. Reconstructed snow cover was cross validated against independentremote sensing data and shows an accuracy of about 85%. The methodologycan be used in mountainous regions to overcome the data gap for earlierdecades when the availability of remote sensing snow-cover data was stronglylimited.
机译:空间分布的积雪范围可以从遥感数据中以较高的精度得出。但是,只有在启动具有适当雪探测功能的卫星任务后,此类数据才可用于最近几十年。然而,通常需要较长时间的积雪区域序列,例如,过去用于水文模型校准或水可用性评估。我们提出了一种使用最近可用的遥感数据和来自现有气象站的积雪深度的长期观测来重建历史雪覆盖的方法。该方法主要基于台站记录与空间积雪模式之间的相关性。另外,考虑了雪型的地形和时间持久性。该方法被应用于中亚的Zerafshan流域,这是一个数据稀少的地区。对照独立的遥感数据,对重建的积雪进行了交叉验证,其准确性约为85%。当遥感积雪数据的可用性受到极大限制时,该方法可用于山区克服数十年的数据空白。

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