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Hurricane trend detection
Natural Hazards ( IF 3.7 ) Pub Date : 2020-08-11 , DOI: 10.1007/s11069-020-04219-x
Craig Loehle , Erica Staehling

Because a change in the frequency (number/year) of hurricanes could be a result of climate change, we analyzed the historical record of Atlantic basin and US landfalling hurricanes, as well as US continental accumulated cyclone energy to evaluate issues related to trend detection. Hurricane and major hurricane landfall counts exhibited no significant overall trend over 167 years of available data, nor did accumulated cyclone energy over the continental USA over 119 years of available data, although shorter-term trends were evident in all three datasets. Given the χ2 distribution evinced by hurricane and major hurricane counts, we generated synthetic series to test the effect of segment length, demonstrating that shorter series were increasingly likely to exhibit spurious trends. Compared to synthetic data with the same mean, the historical all-storm data were more likely to exhibit short-term trends, providing some evidence for long-term persistence at timescales below 10 years. Because this might be due to known climate modes, we examined the relationship between the Atlantic multidecadal oscillation (AMO) and hurricane frequency in light of these short-term excursions. We found that while ratios of hurricane counts with AMO phase matched expectations, statistical tests were less clear due to noise. Over a period of 167 years, we found that an upward trend of roughly 0.7/century is sufficient to be detectable with 80% confidence over the range from 1 to 21 storms/year. Storm energy data 1900–2018 over land were also analyzed. The trend was again zero. The pattern of spurious trends for short segments was again found. Results for AMO periods were similar to count data. Atlantic basin all storms and major storms (1950–2018) did not exhibit any trend over the whole period or after 1990. Major storms 1950–1989 exhibited a significant downward trend. All-storm basin scale storms exhibited short-term trends matching those expected from a Poisson process. A new test for Poisson series was developed based on the 95% distribution of slopes for simulated data across a range of series lengths. Because short data series are inherently likely to yield spurious trends, care is needed when interpreting hurricane trend data.



中文翻译:

飓风趋势检测

因为飓风发生频率(数量/年)的变化可能是气候变化的结果,所以我们分析了大西洋海盆和美国登陆飓风以及美国大陆累积气旋能量的历史记录,以评估与趋势检测相关的问题。飓风和主要飓风登陆数在167年的可用数据中均未显示出明显的总体趋势,在119年的可用数据中,美国大陆上的气旋能量也未累积,尽管在所有三个数据集中,短期趋势均很明显。鉴于χ 2由飓风和主要飓风数量所证实的分布,我们生成了合成序列以测试分段长度的影响,表明较短的序列越来越有可能出现虚假趋势。与具有相同均值的合成数据相比,历史全风暴数据更有可能显示短期趋势,这为10年以下时标的长期持续性提供了一些证据。因为这可能是由于已知的气候模式造成的,所以我们根据这些短期旅行研究了大西洋多年代际振荡(AMO)与飓风频率之间的关系。我们发现,尽管飓风计数与AMO阶段的比率符合预期,但由于噪声,统计测试仍不清楚。在167年的时间里,我们发现上升趋势大约为0。7 /世纪足以在每年1到21次风暴之间以80%的置信度进行检测。还分析了1900-2018年陆地上的风暴能数据。趋势再次为零。再次发现短线段的虚假趋势模式。AMO期间的结果与计数数据相似。大西洋盆地在整个时期或1990年以后,所有风暴和大风暴(1950–2018)都没有表现出任何趋势。1950–1989年的大风暴表现出明显的下降趋势。全风暴盆地规模的风暴表现出与泊松过程所预期的短期趋势一致的短期趋势。根据斜率在一系列序列范围内的模拟数据的95%分布,开发了一种针对Poisson序列的新测试。由于短数据序列天生就有可能产生虚假趋势,因此在解释飓风趋势数据时需要格外小心。

更新日期:2020-08-11
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