Articles | Volume 24, issue 3
https://doi.org/10.5194/npg-24-393-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-24-393-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
31 Jul 2017
Research article |
| 31 Jul 2017
Detecting changes in forced climate attractors with Wasserstein distance
Laboratoire des Sciences du Climat et de l'Environnement, UMR8212 CEA-CNRS-UVSQ, Institut Pierre-Simon Laplace & Université Paris-Saclay,
91191 Gif-sur-Yvette Cedex, France
Pascal Yiou
Laboratoire des Sciences du Climat et de l'Environnement, UMR8212 CEA-CNRS-UVSQ, Institut Pierre-Simon Laplace & Université Paris-Saclay,
91191 Gif-sur-Yvette Cedex, France
Philippe Naveau
Laboratoire des Sciences du Climat et de l'Environnement, UMR8212 CEA-CNRS-UVSQ, Institut Pierre-Simon Laplace & Université Paris-Saclay,
91191 Gif-sur-Yvette Cedex, France
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- Time Adaptive Optimal Transport: A Framework of Time Series Similarity Measure Z. Zhang et al. 10.1109/ACCESS.2020.3016529
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22 citations as recorded by crossref.
- Forecast score distributions with imperfect observations J. Bessac & P. Naveau 10.5194/ascmo-7-53-2021
- A data-driven approach to model calibration for nonlinear dynamical systems C. Greve et al. 10.1063/1.5085780
- Climate Modeling in Low Precision: Effects of Both Deterministic and Stochastic Rounding E. Paxton et al. 10.1175/JCLI-D-21-0343.1
- The Summertime Pacific‐North American Weather Regimes and Their Predictability E. Nabizadeh et al. 10.1029/2022GL099401
- Probability Distributions for Analog-To-Target Distances P. Platzer et al. 10.1175/JAS-D-20-0382.1
- Optimal Transport for Parameter Identification of Chaotic Dynamics via Invariant Measures Y. Yang et al. 10.1137/21M1421337
- Time Adaptive Optimal Transport: A Framework of Time Series Similarity Measure Z. Zhang et al. 10.1109/ACCESS.2020.3016529
- Evaluating the Performance of Climate Models Based on Wasserstein Distance G. Vissio et al. 10.1029/2020GL089385
- Discovering Climate Change during the Early 21st Century via Wasserstein Stability Analysis Z. Xie et al. 10.1007/s00376-024-3324-6
- Multimodel Errors and Emergence Times in Climate Attribution Studies P. Naveau & S. Thao 10.1175/JCLI-D-21-0332.1
- Dynamical Properties of the North Atlantic Atmospheric Circulation in the Past 150 Years in CMIP5 Models and the 20CRv2c Reanalysis D. Rodrigues et al. 10.1175/JCLI-D-17-0176.1
- Quantifying climate model representation of the wintertime Euro-Atlantic circulation using geopotential-jet regimes J. Dorrington et al. 10.5194/wcd-3-505-2022
- The physics of climate variability and climate change M. Ghil & V. Lucarini 10.1103/RevModPhys.92.035002
- Evaluating a stochastic parametrization for a fast–slow system using the Wasserstein distance G. Vissio & V. Lucarini 10.5194/npg-25-413-2018
- Ubiquity of human-induced changes in climate variability K. Rodgers et al. 10.5194/esd-12-1393-2021
- A Century of Nonlinearity in the Geosciences M. Ghil 10.1029/2019EA000599
- Satellite Image Time Series Clustering via Time Adaptive Optimal Transport Z. Zhang et al. 10.3390/rs13193993
- Rough basin boundaries in high dimension: Can we classify them experimentally? T. Bódai & V. Lucarini 10.1063/5.0002577
- Asymptotic behavior of the forecast–assimilation process with unstable dynamics D. Crisan & M. Ghil 10.1063/5.0105590
- A novel metric for quantifying solar irradiance stability: Mapping solar irradiance variability to photovoltaic power generation Q. Tian et al. 10.1016/j.renene.2024.122035
- Multivariate stochastic bias corrections with optimal transport Y. Robin et al. 10.5194/hess-23-773-2019
- Projected Changes in the Atmospheric Dynamics of Climate Extremes in France P. Yiou et al. 10.3390/atmos12111440
Latest update: 29 Jul 2025
Short summary
If climate is viewed as a chaotic dynamical system, its trajectories yield on an object called an attractor. Being perturbed by an external forcing, this attractor could be modified. With Wasserstein distance, we estimate on a derived Lorenz model the impact of a forcing similar to climate change. Our approach appears to work with small data sizes. We have obtained a methodology quantifying the deformation of well-known attractors, coherent with the size of data available.
If climate is viewed as a chaotic dynamical system, its trajectories yield on an object called...
