Research article
31 Jul 2017
Research article
| 31 Jul 2017
Detecting changes in forced climate attractors with Wasserstein distance
Yoann Robin et al.
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Total article views: 1,873 (including HTML, PDF, and XML)
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Cited
15 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
- Probability Distributions for Analog-To-Target Distances P. Platzer et al. 10.1175/JAS-D-20-0382.1
- 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
- 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
- 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
- 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
15 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
- Probability Distributions for Analog-To-Target Distances P. Platzer et al. 10.1175/JAS-D-20-0382.1
- 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
- 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
- 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
- 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: 02 Feb 2023
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...