Real time modelling as an emergency decision support system for accidental release of air pollutants Original Research Article

In the framework of the project ‘Windbank’, wind field patterns in an area of 30 km×30 km in the Swiss Plateau between the Alps and the Jura were measured with 22 temporary meteorological stations and two SODARs during 4 months in 1997. Hourly averages from this high resolution network were combined with meteorological information from routine stations and from a weather prediction model. This data-set comprises all available parameters influencing the complex wind flow in the investigated area between the Alps and the Jura. A cluster analysis for this data-set lead to 12 classes with a high separation quality. It is demonstrated, that an on-line acquisition of meteorological data from routine stations and from a weather prediction model can be used to diagnose the recent wind field class with a probability of 96% to hit the correct wind field class. This diagnosis reveals wind fields with a very high spatial resolution in a very short time. Consequently, it is useful as a contribution to a decision support system for safety management after accidental releases of nuclear or chemical air pollutants. Further, a method is outlined to use the weather prediction model to forecast the wind field class. An average probability of 79% to hit the correct wind field classes for a forecast time of up to 24 h is evaluated.