Cloud diagnosis impact on deposition modelling applied to the Fukushima accident
Résumé
In case of a nuclear accident, they are two phases concerning the dispersion of radioactive materials: 1. Forecast: Anticipating the consequences of an atmospheric release of radioactive material. 2. Aftermath: Understand the soil contamination and the possible harm suffered by the populations during the event. Wet deposition modeling is important to achieve these goals. The cloud diagnosis is a key issue for wet deposition modelling since it allows distinguishing between two processes: in-cloud scavenging: the collection of radioactive particles into the cloud below-cloud scavenging: the removal of radioactive material due to the falling drops. Which cloud diagnosis to use for the atmospheric transport models ? Cloud diagnosis choice have a major impact to the volume of the atmosphere considered as-. Then, the repartition between in-cloud and below-cloud may be strongly impacted by the cloud diagnosis. Cloud water mixing ratio (Q C) is the most interesting variable, which describes only the cloud water. Q c provides satisfactory results and is not sensitive to the threshold. We therefore recommend to use Q c to distinguish in-cloud and below-cloud scavenging in the atmospheric transport modelling. Comparison of observed and diagnosed cloud maps, the 16 th March 00:00 EGU 2017 8845 At the Fukushima airport, a deposit as large as 36 kBq.m-2 of Cs-137 was measured. Both dry and wet deposition were probably involved since a raining event occurred on the 15th of March when the plume was passing nearby.
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EGU2017_poster_Querel_etal.pdf (669.1 Ko)
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EGU2017-8845.pdf (33.15 Ko)
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Licence : CC BY NC ND - Paternité - Pas d'utilisation commerciale - Pas de modification
