In the previous NKS-B project MUD, a methodology was developed for quantitative estimation of the uncertainty of atmospheric dispersion modelling stemming from the inherent uncertainties of meteorological model predictions. Subsequently, in the projects MESO and FAUNA, the implications for nuclear emergency preparedness and management were studied also for short-range models and by applying the methodology to the Fukushima Daiichi emergency. Means to implement the uncertainties in DSSs, and the impacts on real-time emergency management, were described.
In the continuation of the SLIM project, the inherent meteorological uncertainties will be taken into account by incorporating the MUD methodology in the inverse modelling approach aiming at localizing the source. Previously, due to lack of computational power, such methods could not be applied in operational real-time decision support. However, with modern supercomputing facilities available e.g. at national meteorological centres the proposed methodology should be feasible for real-time use, thereby adding value to decision support.
NKS-B 