Low Atlantic hurricane activity in the 1970s and 1980s compared to the past 270 years

Hurricane activity in the North Atlantic Ocean has increased significantly since 1995 (refs 1, 2). This trend has been attributed to both anthropogenically induced climate change and natural variability, but the primary cause remains uncertain. Changes in the frequency and intensity of hurricanes in the past can provide insights into the factors that influence hurricane activity, but reliable observations of hurricane activity in the North Atlantic only cover the past few decades. Here we construct a record of the frequency of major Atlantic hurricanes over the past 270 years using proxy records of vertical wind shear and sea surface temperature (the main controls on the formation of major hurricanes in this region) from corals and a marine sediment core. The record indicates that the average frequency of major hurricanes decreased gradually from the 1760s until the early 1990s, reaching anomalously low values during the 1970s and 1980s. Furthermore, the phase of enhanced hurricane activity since 1995 is not unusual compared to other periods of high hurricane activity in the record and thus appears to represent a recovery to normal hurricane activity, rather than a direct response to increasing sea surface temperature. Comparison of the record with a reconstruction of vertical wind shear indicates that variability in this parameter primarily controlled the frequency of major hurricanes in the Atlantic over the past 270 years, suggesting that changes in the magnitude of vertical wind shear will have a significant influence on future hurricane activity.     

An arid-adapted middle Pleistocene vertebrate fauna from south-central Australia

How well the ecology, zoogeography and evolution of modern biotas is understood depends substantially on knowledge of the Pleistocene. Australia has one of the most distinctive, but least understood, Pleistocene faunas. Records from the western half of the continent are especially rare. Here we report on a diverse and exceptionally well preserved middle Pleistocene vertebrate assemblage from caves beneath the arid, treeless Nullarbor plain of south-central Australia. Many taxa are represented by whole skeletons, which together serve as a template for identifying fragmentary, hitherto indeterminate, remains collected previously from Pleistocene sites across southern Australia. A remarkable eight of the 23 Nullarbor kangaroos are new, including two tree-kangaroos. The diverse herbivore assemblage implies substantially greater floristic diversity than that of the modern shrub steppe, but all other faunal and stable-isotope data indicate that the climate was very similar to today. Because the 21 Nullarbor species that did not survive the Pleistocene were well adapted to dry conditions, climate change (specifically, increased aridity) is unlikely to have been significant in their extinction.     

Using wavelets to obtain a consistent ordinary least squares estimator of the long‐memory parameter

We develop an ordinary least squares estimator of the long‐memory parameter from a fractionally integrated process that is an alternative to the Geweke and Porter‐Hudak (1983) estimator. Using the wavelet transform from a fractionally integrated process, we establish a log‐linear relationship between the wavelet coefficients' variance and the scaling parameter equal to the log‐memory parameter. This log‐linear relationship yields a consistent ordinary least squares estimator of the long‐memory parameter when the wavelet coefficients' population variance is replaced by their sample variance. We derive the small sample bias and variance of the ordinary least squares estimator and test it against the GPH estimator and the McCoy–Walden maximum likelihood wavelet estimator by conducting a number of Monte Carlo experiments. Based upon the criterion of choosing the estimator which minimizes the mean squared error, the wavelet OLS approach was superior to the GPH estimator, but inferior to the McCoy–Walden wavelet estimator for the processes simulated. However, given the simplicity of programming and running the wavelet OLS estimator and its statistical inference of the long‐memory parameter we feel the general practitioner will be attracted to the wavelet OLS estimator. Copyright © 1999 John Wiley & Sons, Ltd.