Speaker
Description
Atmospheric transport models (ATMs) are used to model the transport of radionuclides both to determine the origins of unknown releases and to model the background concentrations from known sources. To do this ATMs rely on meteorological information from four-dimensional numerical weather prediction (NWP) models. However, the chaotic nature of the atmosphere means that the meteorological information provided by these models is uncertain. Therefore, meteorological experts are increasingly running ensemble NWPs to produce probabilistic weather forecasts. A number of studies have been carried out coupling ensemble NWPs with ATMs but to date few centres produce ensemble ATM output on an operational basis (i.e. on demand in response to incidents). This work will present an approach to using ensemble NWP data using stack measurements and observations from Qb sensors from the Xenon Environmental Monitoring at Hartlepool (XENAH) collaboration to demonstrate both the benefits and challenges of coupling ensemble NWPs with ATMs in an operational setting.
Promotional text
Challenges and benefits of accounting for meteorological uncertainty in operational dispersion modelling demonstrated using emission and observation data as part of the XENAH project.
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