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首页> 外文期刊>Journal of the American Water Resources Association >Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin
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Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin

机译:Tahoe盆地湖中雨滴动能的趋势

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摘要

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.
机译:气候变化可能会增加山地地形的表面土壤侵蚀的两种方法是:(1)增加极端降雨事件的频率和(2)降低裸土上的雪覆盖持续时间。我们使用来自四种一般循环模型(GCMS)的输出和两个温室气体轨迹,在历史和预计的21世纪的条件下,每天步骤生产一套水文变量。我们统计上分类每天降雨到每小时降雨,从Tahoe盆地的九个气象站网络中使用每小时降雨,并过滤落在积雪上的雨水。我们应用已发布的方程,将每日强度转换为每天的雨滴动能(Ke),盆地中的网格单元,跨网格细胞平均,并在雪地上创建了总年度和最高每年每年每年每年每年年间动能(TKE和MKE)的时间序列 - 完美的地面。使用广义极值分布,我们计算了KE在无雪地上的长期趋势的重要性,估计返回期为2,20和100年的能量水平。然后,我们削弱了积雪数据,并将ke的产生趋势与两个GCMS下的降雨能量和积雪中的变化进行了比较。主要调查结果包括(1)MKE的上升趋势,(2)TKE的上升趋势更强; (3)在某些情况下增加降雨强度的影响,并在检查的所有情况下减少积雪的强劲效果。

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