French, S., Haywood, S., Oughton, D., and Turcanu, C.: Different types of uncertainty in nuclear emergency management, Radioprotection, 55, S175–S180,
https://doi.org/10.1051/radiopro/2020029, 2020.
a
Girard, S.: A nonlinear PCA based on manifold approximation, Computation. Stat., 15, 145–167,
https://hal.inria.fr/hal-00724764, 2000. a
Girard, S. and Iovleff, S.: Auto-associative models, nonlinear Principal component analysis, manifolds and projection pursuit, in: Principal Manifolds for Data Visualisation and Dimension Reduction, edited by: Gorban, A. N., Kégl, B., Wunsch, D. C., and Zinovyev, A. Y., vol. 58 of Lecture Notes in Computational Science and Engineering, Springer-Verlag,
https://doi.org/10.1007/978-3-540-73750-6_8, 202–218, 2008.
a
Girard, S., Korsakissok, I., and Mallet, V.: Screening sensitivity analysis of a radionuclides atmospheric dispersion model applied to the Fukushima disaster, Atmos. Environ., 95, 490–500,
https://doi.org/10.1016/j.atmosenv.2014.07.010, 2014.
a
Girard, S., Mallet, V., Korsakissok, I., and Mathieu, A.: Emulation and Sobol' sensitivity analysis of an atmospheric dispersion model applied to the Fukushima nuclear accident, J. Geophys. Res.-Atmos., 121, 3484–3496,
https://doi.org/10.1002/2015jd023993, 2016.
a,
b,
c
Girard, S., Armand, P., Duchenne, C., and Yalamas, T.: Stochastic perturbations and dimension reduction for modelling uncertainty of atmospheric dispersion simulations, Atmos. Environ., 224, 117313,
https://doi.org/10.1016/j.atmosenv.2020.117313, 2020.
a
Kolouri, S., Park, S. R., Thorpe, M., Slepcev, D., and Rohde, G. K.: Optimal mass transport: signal processing and machine-learning applications, IEEE Signal Proc. Mag., 34, 43–59,
https://doi.org/10.1109/MSP.2017.2695801, 2017.
a
Korsakissok, I., Mathieu, A., and Didier, D.: Atmospheric dispersion and ground deposition induced by the Fukushima Nuclear Power Plant accident: a local-scale simulation and sensitivity study, Atmos. Environ., 70, 267–279,
https://doi.org/10.1016/j.atmosenv.2013.01.002, 2013.
a
Le, N. B. T., Mallet, V., Korsakissok, I., Mathieu, A., Perillat, R., and Didier, D.: Metamodeling and optimization of probabilistic scores for long-range atmospheric dispersion applied to the Fukushima nuclear disaster, in: vol. 20, EGU General Assembly Conference Abstracts, Vienna, Austria, 8–13 April 2018, 2018.
a,
b,
c
Le, N. B. T., Korsakissok, I., Mallet, V., Périllat, R., and Mathieu, A.: Uncertainty study on atmospheric dispersion simulations using meteorological ensembles with a Monte Carlo approach, applied to the Fukushima nuclear accident, Atmospheric Environment: X, 10, 100112,
https://doi.org/10.1016/j.aeaoa.2021.100112, 2021.
a
Leadbetter, S. J., Andronopoulos, S., Bedwell, P., Chevalier-Jabet, K., Geertsema, G., Gering, F., Hamburger, T., Jones, A., Klein, H., Korsakissok, I., Mathieu, A., Pázmándi, T., Périllat, R., Rudas, C., Sogachev, A., Szántó, P., Tomas, J., Twenhöfel, C., de Vries, H., and Wellings, J.: Ranking uncertainties in atmospheric dispersion modelling following the accidental release of radioactive material, Radioprotection, 55, S51–S55,
https://doi.org/10.1051/radiopro/2020012, 2020.
a
Lumet, E., Rochoux, M. C., Jaravel, T., and Lacroix, S.: Uncertainty-aware surrogate modeling for urban air pollutant dispersion prediction, Build. Environ., 267, 112287,
https://doi.org/10.1016/j.buildenv.2024.112287, 2025.
a
Mallet, V., Tilloy, A., Poulet, D., Girard, S., and Brocheton, F.: Meta-modeling of ADMS-Urban by dimension reduction and emulation, Atmos. Environ., 184, 37–46,
https://doi.org/10.1016/j.atmosenv.2018.04.009, 2018.
a
Milnor, J. W.: Topology from the Differentiable Viewpoint, Princeton University Press, ISBN 9780691048338, 1997. a
Nagy, A., Perko, T., Müller, T., Raskob, W., and Benighaus, L.: Uncertainty visualization using maps for nuclear AND radiological emergencies, Radioprotection, 55, S197–S203,
https://doi.org/10.1051/radiopro/2020033, 2020.
a
Nomura, S., Gilmour, S., Tsubokura, M., Yoneoka, D., Sugimoto, A., Oikawa, T., Kami, M., and Shibuya, K.: Mortality risk amongst nursing home residents evacuated after the Fukushima nuclear accident: a retrospective cohort study, PLoS One, 8, 1–9,
https://doi.org/10.1371/journal.pone.0060192, 2013.
a
Nomura, S., Blangiardo, M., Tsubokura, M., Ozaki, M., and Hodgson, S.: Postnuclear disaster evacuation and chronic health in adults in Fukushima, Japan: a long-term retrospective analysis, BMJ Open, 6, 1–9,
https://doi.org/10.1136/bmjopen-2015-010080, 2016.
a
Périllat, R.: Data for the paper “Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models”, Zenodo [data set],
https://doi.org/10.5281/zenodo.14747261, 2024b.
a
Périllat, R., Korsakissok, I., Girard, S., and Quentric, E.: Emulators for the rapid prediction of consequences in case of nuclear hazards, in: 20th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, HARMO20, Tartu, Estonia, 14–18 June 2021, hal-04337764, 2020.
a,
b
Roustant, O., Ginsbourger, D., and Deville, Y.: DiceKriging, DiceOptim: two R packages for the analysis of computer experiments by kriging-based metamodeling and optimization, J. Stat. Softw., 51, 1–55,
https://doi.org/10.18637/jss.v051.i01, 2012.
a
Swallow, B., Rigby, M., Rougier, J. C., Manning, A. J., Lunt, M., and O'Doherty, S.: Parametric uncertainty in complex environmental models: a cheap emulation approach for models with high-dimensional output, arXiv [preprint],
https://doi.org/10.48550/arXiv.1702.03696, 2017.
a
Tombette, M., Quentric, E., Quélo, D., Benoit, J.-P., Mathieu, A., Korsakissok, I., and Didier, D.: C3X: A software platform for assessing the consequences of an accidental release of radioactivity into the atmosphere, Poster presentation, presented at the 4th European IRPA Congress, 23–27 June 2014, Geneva, Switzerland, 2014. a
