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Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin
Journal of the American Water Resources Association ( IF 2.6 ) Pub Date : 2020-03-05 , DOI: 10.1111/1752-1688.12834
Jack Lewis 1 , Robert Coats 2
Affiliation  

Two means by which climate change may increase surface soil erosion in mountainous terrain are: (1) increasing the frequency of extreme rainfall events and (2) decreasing the duration of snow cover on bare soil. We used output from four general circulation models (GCMs) and two greenhouse gas trajectories to produce a suite of hydrologic variables at a daily time‐step for historic and projected 21st Century conditions. We statistically disaggregated the daily rainfall to hourly, using hourly rainfall from a network of nine weather stations in the Tahoe Basin, and filtered out rain falling on a snowpack. We applied published equations to convert hourly intensity to raindrop kinetic energy (KE) for each day and grid cell in the Basin, averaged across grid cells, and created time series of total annual and maximum annual hourly kinetic energy (TKE and MKE) on snow‐free ground. Using the Generalized Extreme Value distribution, we calculated the significance of long‐term trends in KE on snow‐free ground, and estimated energy levels for return periods of 2, 20, and 100 years. We then detrended the snowpack data and compared the resulting trends in KE with the trends resulting from changes in both rainfall energy and snowpack under two GCMs. Principal findings include (1) upward trends in MKE, (2) stronger upward trends in TKE; and (3) an effect of increasing rainfall intensities on KE in some cases, and a strong effect of reduced snowpack in all cases examined.

中文翻译:

太浩湖流域模拟气候变暖的雨滴动能趋势

气候变化可能增加山区地形的土壤侵蚀的两种方法是:(1)增加极端降雨事件的发生频率,以及(2)减少裸露土壤上积雪的持续时间。我们使用四个通用循环模型(GCM)的输出和两个温室气体轨迹,在每天的某个时间步生成一套水文变量,以适应​​21世纪的历史状况和预计的状况。我们使用塔霍盆地9个气象站网络中的每小时降雨量,将每日降雨量统计为小时,然后过滤掉积雪上的降雨。我们应用了已发布的方程式,将盆地内网格单元每天的小时强度转换为雨滴动能(KE),并将网格单元之间的平均值平均化,并在无雪地面上创建了年度总动能和年度最大动能(TKE和MKE)的时间序列。使用广义极值分布,我们计算了无雪地面上KE长期趋势的重要性,并估算了2年,20年和100年回归期的能量水平。然后,我们对积雪数据进行了去趋势处理,并将KE的最终趋势与两个GCM下降雨能量和积雪变化的趋势进行了比较。主要发现包括:(1)MKE上升趋势,(2)TKE上升趋势更强;(3)在某些情况下,降雨强度增加对KE的影响,在所有情况下均具有减少积雪的强烈影响。我们计算了无雪地面上KE长期趋势的重要性,并估算了2年,20年和100年回归期的能量水平。然后,我们对积雪数据进行了去趋势处理,并将KE的最终趋势与两个GCM下降雨能量和积雪变化的趋势进行了比较。主要发现包括:(1)MKE上升趋势,(2)TKE上升趋势更强;(3)在某些情况下,降雨强度增加对KE的影响,在所有情况下均降低积雪。我们计算了无雪地面上KE长期趋势的重要性,并估算了2年,20年和100年回归期的能量水平。然后,我们对积雪数据进行了去趋势处理,并将KE的最终趋势与两个GCM下降雨能量和积雪变化的趋势进行了比较。主要发现包括:(1)MKE上升趋势,(2)TKE上升趋势更强;(3)在某些情况下,降雨强度增加对KE的影响,在所有情况下均具有减少积雪的强烈影响。(2)TKE上升趋势更强;(3)在某些情况下,降雨强度增加对KE的影响,在所有情况下均降低积雪。(2)TKE上升趋势更强;(3)在某些情况下,降雨强度增加对KE的影响,在所有情况下均具有减少积雪的强烈影响。
更新日期:2020-03-05
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