The classical approach to storm statistics in the ocean is an Eulerian analysis of wave time series at a given location, in which the wave data can be observations or results of wave models. The information obtained from this approach is storm frequency, duration and intensity, from which extremes at the particular location can be estimated. The availability of spatial information of wave characteristics at successive time intervals, which is available from large scale forecasts or hindcast allows the follow-up of storm evolution in space and time. Using this data it is possible to study the spatial evolution of storms, i.e to provide a Lagrangean description of storm characteristics. In this paper the principles for spatio-temporal identification and statistical analysis of storm variability are formulated. Using ten years of wave data the HIPOCAS North Atlantic hindcast data, storms were identified using both approaches and two different sets of storm characteristics were obtained. The enhanced information that is possible to obtain from the Lagrangean approach in comparison to the Eulerian is illustrated.

This content is only available via PDF.
You do not currently have access to this content.