Tippett Michael K, Cohen Joel E
Department of Applied Physics and Applied Mathematics, Columbia University, New York, New York 10027, USA.
Center of Excellence for Climate Change Research, Department of Meteorology, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Nat Commun. 2016 Feb 29;7:10668. doi: 10.1038/ncomms10668.
Tornadoes cause loss of life and damage to property each year in the United States and around the world. The largest impacts come from 'outbreaks' consisting of multiple tornadoes closely spaced in time. Here we find an upward trend in the annual mean number of tornadoes per US tornado outbreak for the period 1954-2014. Moreover, the variance of this quantity is increasing more than four times as fast as the mean. The mean and variance of the number of tornadoes per outbreak vary according to Taylor's power law of fluctuation scaling (TL), with parameters that are consistent with multiplicative growth. Tornado-related atmospheric proxies show similar power-law scaling and multiplicative growth. Path-length-integrated tornado outbreak intensity also follows TL, but with parameters consistent with sampling variability. The observed TL power-law scaling of outbreak severity means that extreme outbreaks are more frequent than would be expected if mean and variance were independent or linearly related.
在美国乃至全球，龙卷风每年都会造成人员伤亡和财产损失。最大的影响来自于由多个在时间上紧密间隔的龙卷风组成的“爆发”。在这里，我们发现1954 - 2014年期间，美国每次龙卷风爆发的年平均龙卷风数量呈上升趋势。此外，这个数量的方差增长速度比均值快四倍多。每次爆发的龙卷风数量的均值和方差根据泰勒波动尺度幂律（TL）而变化，其参数与乘法增长一致。与龙卷风相关的大气代理指标显示出类似的幂律尺度和乘法增长。路径长度积分的龙卷风爆发强度也遵循TL，但参数与采样变异性一致。观察到的爆发严重性的TL幂律尺度意味着，如果均值和方差是独立的或线性相关的，极端爆发的频率会比预期的更高。
