U.S. Landfalling and North Atlantic Hurricanes: Statistical Modeling of Their Frequencies and Ratios
U.S. Landfalling and North Atlantic Hurricanes: Statistical Modeling of Their Frequencies and Ratios
复制标题
美国登陆和北大西洋飓风：频率和比率的统计模型
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
J. Smith
中科院分区：
文献类型：
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作者：
G. Villarini;G. Vecchi;J. Smith
摘要利用热带大西洋海表温度（SST）、热带平均海温、北大西洋涛动（NAO）和南方涛动指数（SOI）模拟了1878 ~ 2008年美国登陆和北大西洋飓风次数及其比值的时间序列。采用两个海温输入数据集来检验重建海温数据对建模结果的不确定性。由于在记录的最早部分有记录的飓风可能会被低估，因此我们考虑了未校正的飓风数据集（HURDAT）和最近提出的校正时间序列。计数数据的建模使用条件泊松回归模型，其中的发生率可以线性或非线性地依赖于气候指数。模型选择遵循逐步方法并使用两个惩罚标准。这些结果不允许人们识别一个单一的“最佳”模型，因为不同的模型配置(不同的海表温度…
AbstractTime series of U.S. landfalling and North Atlantic hurricane counts and their ratios over the period 1878–2008 are modeled using tropical Atlantic sea surface temperature (SST), tropical mean SST, the North Atlantic Oscillation (NAO), and the Southern Oscillation index (SOI). Two SST input datasets are employed to examine the uncertainties in the reconstructed SST data on the modeling results. Because of the likely undercount of recorded hurricanes in the earliest part of the record, both the uncorrected hurricane dataset (HURDAT) and a time series with a recently proposed undercount correction are considered.Modeling of the count data is performed using a conditional Poisson regression model, in which the rate of occurrence can depend linearly or nonlinearly on the climate indexes. Model selection is performed following a stepwise approach and using two penalty criteria. These results do not allow one to identify a single “best” model because of the different model configurations (different SST d...