Speaker
Description
Radionuclides are one of several signatures of nuclear explosions monitored by the International Monitoring System (IMS). Data fusion methods are being developed to combine multiple signatures for improved detectability and source attribution. To utilise radionuclide signatures in a data fusion framework, it is important to quantify the sensitivities of a potential signal to physical processes associated with transport and dispersion of plumes between the source and measurement locations. We perform and analyse atmospheric transport simulations of hypothetical radioxenon releases with the Weather Research and Forecasting (WRF) model to investigate the impact of seasonal and short term variability in atmospheric conditions as well as release location on radionuclide concentrations at surrounding IMS stations. To examine sensitivity to seasonal variability, we identify recurring wind patterns over our emission source region and perform an ensemble of WRF simulations for different representative weather conditions to evaluate resulting changes in signal detectability at IMS stations. Due to the chaotic nature of atmospheric dynamics, mesoscale atmospheric simulations are sensitive to small perturbations in initial condition. We quantify impacts of initial condition sensitivity on signal detection by analyzing an initial condition ensemble of simulations, where timing and location of radioxenon emissions are perturbed under otherwise identical meteorology.
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