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Quantifying the early snowmelt event of 2015 in the Cascade Mountains, USA by developing and validating MODIS-based snowmelt timing maps

机译:通过开发和验证基于MODIS的融雪时序图来量化2015年美国喀斯喀特山脉的早期融雪事件

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Spring snowmelt serves as the major hydrological contribution to many watersheds of the US West. Since the 1970s the conterminous western USA has seen an earlier arrival of spring snowmelt. The extremely low snowpack and early melt of 2015 in the Cascade Mountains may be a harbinger of winters to come, underscoring the interest in advancements in spring snowmelt monitoring. Target-of-opportunity and point measurements of snowmelt using meteorological stations or stream gauges are common sources of these data, however, there have been few attempts to identify snowmelt timing using remote sensing. In this study, we describe the creation of snowmelt timing maps (STMs) which identify the day of year that each pixel of a remotely sensed image transitions from "snow-covered" to "no snow" during the spring melt season, controlling for cloud coverage and ephemeral spring snow storms. Derived from the 500 m MODerate-resolution Imaging Spectroradiometer (MODIS) standard snow map, MOD10A2, this new dataset provides annual maps of snowmelt timing, with corresponding maps of cloud interference and interannual variability in snow coverage from 2001-2015. We first show that the STMs agree strongly with in-situ snow telemetry (SNOTEL) meteorological station measurements in terms of snowmelt timing. We then use the STMs to investigate the early snowmelt event of 2015 in the Cascade Mountains, USA, highlighting the protected areas of Mt. Rainier, Crater Lake, and Lassen Volcanic National Parks. In 2015 the Cascade Mountains experienced snowmelt 41 days earlier than the 2001-2015 average, with 25% of its land area melting > 65 days earlier than average. The upper elevations of the Cascade Mountains experienced the greatest snowmelt anomaly. Our results are relevant to land managers and biologists as they plan adaptation strategies for mitigating the effects of climate change throughout temperate mountains.
机译:春季融雪是美国西部许多流域的主要水文贡献。自1970年代以来,毗邻的美国西部出现了春季融雪的较早到达。喀斯喀特山脉极低的积雪和2015年的初融可能预示着冬天的来临,这突显了人们对春季融雪监测的兴趣。使用气象站或流量表进行融雪的机会目标和点测量是这些数据的常见来源,但是,很少有尝试使用遥感来识别融雪时间的尝试。在这项研究中,我们描述了融雪时序图(STMs)的创建,该映射确定了春季融雪季节中遥感图像的每个像素从“积雪”到“无雪”过渡的一年中的某天。覆盖和短暂的春季暴风雪。这个新的数据集来自500 m中等分辨率成像光谱仪(MODIS)标准降雪图MOD10A2,提供了每年的融雪时间图,以及2001-2015年期间的云干扰和雪覆盖率年际变化的相应图。我们首先表明STM在融雪时间方面与现场雪遥测(SNOTEL)气象站测量非常吻合。然后,我们使用STM来调查2015年美国喀斯喀特山脉的早期融雪事件,着重介绍Mt. Mt保护区。雷尼尔,火山口湖和拉森火山国家公园。 2015年,喀斯喀特山脉的积雪比2001-2015年的平均值早了41天,其中25%的土地融化时间比平均值早了65天。喀斯喀特山脉的高海拔地区经历了最大的融雪异常。我们的结果与土地管理者和生物学家有关,他们规划了缓解气候变化对整个温带山区气候变化影响的策略。

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