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Geochemical Journal, Vol. 52, 2018
doi:10.2343/geochemj.2.0503

Lessons learned from atmospheric modeling studies after the Fukushima nuclear accident: Ensemble simulations, data assimilation, elemental process modeling, and inverse modeling

Mizuo Kajino1,2,3*, Tsuyoshi Thomas Sekiyama1, Anne Mathieu4, Irène Korsakissok4, Raphaël Périllat4,5, Denis Quélo4, Arnaud Quérel4,6 Olivier Saunier4, Kouji Adachi1, Sylvain Girard4,7, Takashi Maki1, Keiya Yumimoto8,1, Damien Didier4, Olivier Masson9, and Yasuhito Igarashi1

1Meteorological Research Institute (MRI), Japan Meteorological Agency (JMA), Tsukuba, Ibaraki 305-0052, Japan
2Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577, Japan
3RIKEN Advanced Institute for Computational Science, Kobe, Hyogo 650-0047, Japan
4Institut de Radioprotection et de Sûreté Nucléaire (IRSN), PSE-SANTE, SESUC, BMCA, 92262, Fontenay-aux-Roses Cedex, France
5Strathom Energie, 75002, Paris, France
6Bertin Technologies, 78180, Montigny-le-Bretonneux, France
7Phimeca, Engineering, 75012, Paris, France
8Research Institute for Applied Mechanics, Kyushu University, Kasuga, Fukuoka 816-8580, Japan
9Institut de Radioprotection et de Sûreté Nucléaire (IRSN), BP3, 13115, St Paul lez Durance Cedex, France

(Received May 26, 2017; Accepted September 13, 2017)

Abstract: Modeling studies on the atmospheric diffusion and deposition of the radiocesium associated with the Fukushima Dai-ichi Nuclear Power Plant accident is reviewed here, with a focus on a research collaboration between l'Institut de Radioprotection et de Sûreté Nucléaire (IRSN) - the French institute in charge of evaluating the consequences of nuclear accidents and advising authorities in case of a crisis - and the Meteorological Research Institute (MRI) of the Japan Meteorological Agency - an operational weather forecasting center in Japan. While the modelers have come to know that wet deposition is one of the key processes, the size of its influence is unknown. They also know that the simulation results vary, but they do not know exactly why. Under the research collaboration, we aimed to understand the atmospheric processes, especially wet deposition, and to quantify the uncertainties of each component of our simulation using various numerical techniques, such as ensemble simulations, data assimilation, elemental process modeling, and inverse modeling. The outcomes of these collaborative research topics are presented in this paper. We also discuss the future directions of atmospheric modeling studies: data assimilation using the high temporal and spatial resolution surface concentration measurement data, and consideration of aerosol properties such as size and hygroscopicity into wet and dry deposition schemes.
Key words: Ensemble simulation, Data assimilation, Wet deposition, Aerosol properties, Inverse modeling


*Corresponding author E-mail: kajino@mri-jma.go.jp

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