Issue |
Radioprotection
Volume 55, May 2020
Coping with uncertainties for improved modelling and decision making in nuclear emergencies. Key results of the CONFIDENCE European research project
|
|
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Page(s) | S75 - S79 | |
Section | EARLY PHASE MODELLING | |
DOI | https://doi.org/10.1051/radiopro/2020015 | |
Published online | 01 May 2020 |
Article
Operationalising an ensemble approach in the description of uncertainty in atmospheric dispersion modelling and an emergency response
1
PHE – Public Health England, Chilton,
Didcot, UK
2
IRSN – Institut de Radioprotection et de Sûreté Nucléaire,
Fontenay-aux-Roses, France
3
Met Office,
Exeter, UK
4
PHIMECA Engineering,
Paris, France
5
EK – Centre for Energy Research,
Budapest, Hungary
6
RIVM – National Institute for Public Health and the Environment,
Bilthoven, The Netherlands
7
KNMI – Royal Netherlands Meteorological Institute,
De Bilt, The Netherlands
* Corresponding author: peter.bedwell@phe.gov.uk
Uncertainties were propagated through the chain of atmospheric dispersion and radiological assessment models based on an ensemble approach for a range of scenarios. It was apparent that the time taken to complete model runs, ranging from several hours to a few tens of hours, was not appropriate for an emergency response. Thus, for an operational method, there was a requirement to reduce the number of ensemble members and/or reduce model run time for a single ensemble member, such that a measure of uncertainty may be obtained within the timeframe of one hour, but without significant detriment to the model endpoints derived, the uncertainty estimated and the radiation protection advice inferred. This study proposes recommendations for operationalising an ensemble approach used in the description of uncertainty in atmospheric dispersion modelling and an emergency response.
Key words: operational / ensemble / uncertainty / atmospheric dispersion / emergency response
© The Authors, published by EDP Sciences 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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