Neelin J David, Sahany Sandeep, Stechmann Samuel N, Bernstein Diana N
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095-1565;
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095-1565.
Proc Natl Acad Sci U S A. 2017 Feb 7;114(6):1258-1263. doi: 10.1073/pnas.1615333114. Epub 2017 Jan 23.
Precipitation accumulations, integrated over rainfall events, can be affected by both intensity and duration of the storm event. Thus, although precipitation intensity is widely projected to increase under global warming, a clear framework for predicting accumulation changes has been lacking, despite the importance of accumulations for societal impacts. Theory for changes in the probability density function (pdf) of precipitation accumulations is presented with an evaluation of these changes in global climate model simulations. We show that a simple set of conditions implies roughly exponential increases in the frequency of the very largest accumulations above a physical cutoff scale, increasing with event size. The pdf exhibits an approximately power-law range where probability density drops slowly with each order of magnitude size increase, up to a cutoff at large accumulations that limits the largest events experienced in current climate. The theory predicts that the cutoff scale, controlled by the interplay of moisture convergence variance and precipitation loss, tends to increase under global warming. Thus, precisely the large accumulations above the cutoff that are currently rare will exhibit increases in the warmer climate as this cutoff is extended. This indeed occurs in the full climate model, with a 3 °C end-of-century global-average warming yielding regional increases of hundreds of percent to >1,000% in the probability density of the largest accumulations that have historical precedents. The probabilities of unprecedented accumulations are also consistent with the extension of the cutoff.
将降雨事件期间的降水量进行累计,会受到风暴事件的强度和持续时间的影响。因此,尽管在全球变暖的情况下,降水强度普遍预计会增加,但尽管降水量的累积对社会影响至关重要,却一直缺乏一个预测累积量变化的清晰框架。本文提出了降水累积量概率密度函数(pdf)变化的理论,并对全球气候模型模拟中的这些变化进行了评估。我们表明,一组简单的条件意味着,在高于物理截止尺度的情况下,最大累积量的频率大致呈指数增长,且随事件规模增大而增加。概率密度函数呈现出一个近似幂律的范围,在此范围内,概率密度随量级大小每增加一级而缓慢下降,直至在大累积量处达到截止,这限制了当前气候中所经历的最大事件。该理论预测,由水汽辐合方差和降水损失的相互作用控制的截止尺度,在全球变暖的情况下趋于增加。因此,随着这个截止尺度的扩大,目前罕见的高于截止值的大累积量在更温暖的气候中将呈现增加趋势。这确实在完整的气候模型中出现了,到本世纪末全球平均升温3°C时,有历史先例的最大累积量的概率密度在区域上增加了数百%至超过1000%。前所未有的累积量的概率也与截止尺度的扩大相一致。