SPEAKER: Robert Lund

ABSTRACT:

This talk overviews changepoint issues in climate studies. Changepoints are ubiquitous features in climatic time series,occurring whenever stations relocate or gauges are changed. Ignoring changepoints can produce spurious conclusions. Changepoint tests involving cumulative sums, likelihood ratio, and maximums of F statistics are introduced; the asymptotic distributions of these
statistics are quantified under the changepoint-free null hypothesis. We find that cumulative sum procedures work best when the changepoint is near the center of the data record; otherwise, maximums of F statistics perform better. Next, issues of autocorrelation are addressed. Series with positive autocorrelation can have long sojourns above and below mean levels, hence mimicing a mean shift. We show how to modify the above methods to account for autocorrelation features. The methods are illustrated in several applications, including changes in temperatures and Atlantic Basin tropical storm counts.

Bio: Robert Lund received the Ph.D. degree in statistics from The University of North Carolina in 1993. He is currently a Professor in the Department of Mathematical Sciences at Clemson University. He is a Fellow of the American Statistical Association and was the 2005-2007 Editor of the Journal of the American Statistical Association, Reviews Section. He has published over 50 refereed papers and has graduated 8 doctoral students. His interests are in time series, applied probability, and statistical climatology.