New snow metrics for a warming world
New snow metrics for a warming world
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DOI：
10.1002/hyp.14262
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发表时间：
2020-10
影响因子：
3.2
通讯作者：
A. Nolin;E. Sproles;D. Rupp;R. Crumley;Mariana J. Webb;Ross T. Palomaki;E. Mar
中科院分区：
文献类型：
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作者：
A. Nolin;E. Sproles;D. Rupp;R. Crumley;Mariana J. Webb;Ross T. Palomaki;E. Mar
雪是地球上对气候最敏感的土地覆盖类型。传统的积雪指标可能无法充分捕捉积雪的变化性质。例如，4月1日的雪水当量（SWE）是径流预测的有效指标，但它不能表达仲冬融化事件的影响，现在预计在变暖的雪气候中，我们也不能假设基于站点的测量将代表未来几十年的雪情。遥感和气候模型数据为一套从地方到全球尺度的多用途降雪指标提供了能力。这些指标需要足够简单，以“讲述”积雪随时间和空间的变化，但在解释时不能过于简单或过于复杂。我们描述了一套基于NASA中分辨率成像光谱仪（MODIS）的全球卫星数据和美国降尺度气候模型输出的空间显式，多时相积雪指标。我们描述并提供了积雪频率（SCF），雪消失日期（SDD），风险雪（ARS）和暖冬频率（FWW）的例子。使用这些回顾性和前瞻性的降雪指标，我们评估了三个水文气候不同的美国流域的当前和未来的降雪相关条件：特拉基，科罗拉多源头，上康涅狄格州。在美国西部的两个流域，SCF和SDD与地面积雪遥测（SNOTEL）网络的数据相比，对积雪的年度差异表现出更大的敏感性。美国东部流域没有地面数据网络，因此这些来自MODIS的指标提供了独特的有价值的降雪信息。ARS和FWW指标表明，特拉基流域非常容易从降雪转换为降雨（ARS）和仲冬融化事件（FWW）在整个季节性雪区。相比之下，科罗拉多源头和上康涅狄格流域更冷，在世纪中后期更不容易受到影响。
Snow is Earth's most climatically sensitive land cover type. Traditional snow metrics may not be able to adequately capture the changing nature of snow cover. For example, April 1 snow water equivalent (SWE) has been an effective index for streamflow forecasting, but it cannot express the effects of midwinter melt events, now expected in warming snow climates, nor can we assume that station‐based measurements will be representative of snow conditions in future decades. Remote sensing and climate model data provide capacity for a suite of multi‐use snow metrics from local to global scales. Such indicators need to be simple enough to “tell the story” of snowpack changes over space and time, but not overly simplistic or overly complicated in their interpretation. We describe a suite of spatially explicit, multi‐temporal snow metrics based on global satellite data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and downscaled climate model output for the U.S. We describe and provide examples for Snow Cover Frequency (SCF), Snow Disappearance Date (SDD), At‐Risk Snow (ARS), and Frequency of a Warm Winter (FWW). Using these retrospective and prospective snow metrics, we assess the current and future snow‐related conditions in three hydroclimatically different U.S. watersheds: the Truckee, Colorado Headwaters, and Upper Connecticut. In the two western U.S. watersheds, SCF and SDD show greater sensitivity to annual differences in snow cover compared with data from the ground‐based Snow Telemetry (SNOTEL) network. The eastern U.S. watershed does not have a ground‐based network of data, so these MODIS‐derived metrics provide uniquely valuable snow information. The ARS and FWW metrics show that the Truckee Watershed is highly vulnerable to conversion from snowfall to rainfall (ARS) and midwinter melt events (FWW) throughout the seasonal snow zone. In comparison, the Colorado Headwaters and Upper Connecticut Watersheds are colder and much less vulnerable through mid‐ and late‐century.