Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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BCCN Sonderseminar

Thursday, 13.12.2007 14 c.t.

Extreme Events: The larger the better predictable?

by Dr. Sarah Hallerberg
from MPI für Physik komplexer Systeme, Dresden

Contact person: Marc Timme


Seminarraum Haus 2, 4. Stock (Bunsenstr.)


We investigate the predictability of extreme events in time series. Common examples for extreme events are natural hazards such as earthquakes, strong precipitation or strong turbulent wind gusts. We focus on the question, under which circumstances large events are better predictable than smaller events. Therefore we use a simple prediction algorithm, and study its performance for the prediction of increments and threshold crossings in stochastic processes. Although our approach is very simple, it allows us to understand effects which are observed for the prediction of strong wind gusts, which can destroy wind turbines or affect aircraft starting and landing.

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