Uncertainty of 21st Century western U.S. snowfall loss derived from regional climate model large ensemble

IF 8.5 1区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES
Jesse Norris, Stefan Rahimi, Lei Huang, Benjamin Bass, Chad W. Thackeray, Alex Hall
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Abstract

The western United States is dependent on winter snowfall over its major mountain ranges, which gradually melts each year, serving as a natural reservoir for water resources. In a future warmer climate, much of this snowfall could be replaced by rain, making it more challenging to capture and store water. In this study, we utilize an ensemble of dynamically downscaled simulations forced by 14 global climate models (GCMs). These GCMs project wildly different futures, in terms of both temperature and precipitation change, producing significant uncertainty in snowfall projections. Here we exploit the robust statistics of the downscaled ensemble, and diagose the sensitivity of end-of-century snowfall loss across the region to both warming and regional wetting/drying in the driving GCM. The windward slopes of the Sierra Nevada and Cascades are particularly sensitive to warming (losing ~ 15% annual snowfall per degree warming), with little influence of precipitation. By contrast, snowfall loss in the inter-mountain west is less sensitive to warming (~ 5% K−1), but is significantly offset/exacerbated by precipitation changes (~ 0.5% snow per 1% precipitation). Combining such sensitivities with the warming and regional precipitation signals in the full CMIP6 ensemble, we can fully quantify likely snowfall loss and its uncertainty at any location, for any emissions scenario. We find that the western U.S. as a whole will lose 34 ± 8% of its total volumetric snowfall by end-of-century under the high-emissions SSP3-7.0 scenario, but 25 ± 6% and 17 ± 6% under the lower-emissions SSP2-4.5 and SSP1-2.6 scenarios.

Abstract Image

基于区域气候模式大集合的21世纪美国西部降雪损失的不确定性
美国西部依靠其主要山脉的冬季降雪,这些山脉每年逐渐融化,成为水资源的天然水库。在未来变暖的气候中,大部分降雪可能会被雨水所取代,这使得捕获和储存水变得更加困难。在这项研究中,我们利用了由14个全球气候模式(GCMs)强制进行的动态降尺度模拟的集合。在温度和降水变化方面,这些gcm预测的未来非常不同,在降雪量预测中产生了很大的不确定性。利用降尺度集合的鲁棒性统计,分析了世纪末地区降雪损失对增温和驱动GCM的区域干湿变化的敏感性。内华达山脉和喀斯喀特山脉的迎风坡对气候变暖特别敏感(每升温一度就会损失15%的年降雪量),降水的影响很小。相比之下,西部山间地区的降雪损失对变暖不太敏感(~ 5% K−1),但被降水变化显著抵消/加剧(~ 0.5%雪/ 1%降水)。将这种敏感性与整个CMIP6集合中的变暖和区域降水信号相结合,我们可以充分量化任何地点、任何排放情景下可能的降雪损失及其不确定性。我们发现,在高排放的SSP3-7.0情景下,到本世纪末,美国西部整体将损失34±8%的降雪总量,而在低排放的SSP2-4.5和SSP1-2.6情景下,这一比例分别为25±6%和17±6%。
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来源期刊
npj Climate and Atmospheric Science
npj Climate and Atmospheric Science Earth and Planetary Sciences-Atmospheric Science
CiteScore
8.80
自引率
3.30%
发文量
87
审稿时长
21 weeks
期刊介绍: npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols. The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.
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