Articles | Volume 32, issue 2
https://doi.org/10.5194/npg-32-139-2025
https://doi.org/10.5194/npg-32-139-2025
Research article
 | 
26 May 2025
Research article |  | 26 May 2025

Finite-size local dimension as a tool for extracting geometrical properties of attractors of dynamical systems

Martin Bonte and Stéphane Vannitsem

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Cited articles

Abarbanel, H. D. I.: Analysis of Observed Chaotic Data, Springer, New York, NY, 69–93, ISBN 978-1-4612-0763-4, https://doi.org/10.1007/978-1-4612-0763-4_5, 1996. a, b
Bac, J. and Zinovyev, A.: Local intrinsic dimensionality estimators based on concentration of measure, in: 2020 International Joint Conference on Neural Networks (IJCNN), 19–24 July 2020, Glasgow, UK, 1–8, https://doi.org/10.1109/IJCNN48605.2020.9207096, 2020. a
Beirlant, J., Goegebeur, Y., Segers, J., Teugels, J., De Waal, D., and Ferro, C.: Statistics of Extremes: Theory and Applications, in: Wiley Series in Probability and Statistics, Wiley, ISBN 9780471976479, https://doi.org/10.1002/0470012382, 2004. a
Berenguer, M., Sempere-Torres, D., and Pegram, G. G.: SBMcast – An ensemble nowcasting technique to assess the uncertainty in rainfall forecasts by Lagrangian extrapolation, J. Hydrol., 404, 226–240, https://doi.org/10.1016/j.jhydrol.2011.04.033, 2011. a
Bowler, N., Pierce, C., and Seed, A.: STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP, Q. J. Roy. Meteorol. Soc., 132, 2127–2155, https://doi.org/10.1256/qj.04.100, 2007. a, b
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Short summary
In recent years, there have been more and more floods due to intense precipitation, such as the July 2021 event in Belgium. Predicting precipitation is a difficult task, even just for the next few hours. This study focuses on a tool that assesses whether a given situation is stable or not (i.e., whether it is likely to stay as it is or could evolve in an unpredictable manner).
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