Stochastic systems driven by alpha-stable noises

It has almost become a standard in stochastic mechanics applications of stochasticdifferential equations that the driving forces are modeled as Gaussian white noises, that is, as scalar or vector Brownianmotion increments.However, this modeling may not always lead to responses that comply well with observed data.

In particular the tailsof the observed response distributions may even for linear systems be more fat than the tails obtained for Gaussianwhite noise input. Also the excitation may show jumps that cannot be modeled by Gaussian white noise. The paper supports the possibility of using the larger class of so-calledalpha-stable white noises to provide a better fit.

A geophysical application concerning ice age climate variations is described.