Challenges in developing DDDAS based methodology for volcanic ash hazard analysis - Effect of numerical weather prediction variability and parameter estimation

In this paper, we will present ongoing work on using a dynamic data driven application system (DDDAS) based approach to the forecast of volcanic ash transport and dispersal. Our primary modeling tool will be a new code puffin formed by the combination of a plume eruption model Bent and the ash transport model Puff. Data from satellite imagery, observation of vent parameters and windfields will drive our simulations. We will use ensemble based uncertainty quantification and parameter estimation methodology - polynomial chaos quadrature in combination with data integration to complete the DDDAS loop.