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Wavelet-Lag Regression Analysis of Atlantic Tropical Cyclones

By John Moore, Aslek Grinsted and Svetlana Jevrejeva


We discuss a novel wavelet-lag coherence method to study of cause-and-effect relations over a large space of timescales, phase lags and periods. We use 135 years of observational records to demonstrate how sea-surface temperature, sea-level pressure and cyclone numbers are linked. We examine the statistical properties of the time series and test how departure from Normality affects results found using the method. We also examine how historical inaccuracy in counting tropical cyclone numbers could influence the findings. Robustly we find that SST and cyclones in a negative feedback loop, where rising SST causes increased numbers of cyclones, which reduce SST. This is statistically most significant at decadal and not at longer periods. Only at periods of about 30 years (to significant differences arise in using recently proposed corrections to cyclone numbers, and forcing the empirical distribution of cyclone numbers to be Normal. This Could be incorrectly interpreted as support for a long period Atlantic Multidecadal Oscillation, whereas it actually reflects the time-varying bias functions applied to the observations. There is evidence of some linkage between Northern hemisphere snow cover and cyclone numbers, however this seems to be due to a common causative relationship between the known tropical cyclone drivers of ENSO and decadal scale North Atlantic ocean-atmospheric circulation systems

Publisher: Springer
Year: 2009
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