  This paper describes a statistical method for short-term forecasting of
surface layer wind velocity amplitude relying on the notion of continuous
cascades. Inspired by recent empirical findings that suggest the existence of
some cascading process in the mesoscale range, we consider that wind speed can
be described by a seasonal component and a fluctuating part represented by a
"multifractal noise" associated with a random cascade. Performances of our
model are tested on hourly wind speed series gathered at various locations in
Corsica (France) and Netherlands. The obtained results show a systematic
improvement of the prediction as compared to reference models like persistence
or Artificial Neural Networks.
