Earth System Dynamics
Earth System Dynamics
ESD
Articles | Volume 15, issue 4
Articles | Volume 15, issue 4
https://doi.org/10.5194/esd-15-893-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-15-893-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 4
Research article
 | 
17 Jul 2024
Research article |  | 17 Jul 2024

Variability and predictability of a reduced-order land–atmosphere coupled model

Anupama K. Xavier, Jonathan Demaeyer, and Stéphane Vannitsem

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Cited articles

Arbabi, H. and Mezić, I.: Study of dynamics in post-transient flows using Koopman mode decomposition, Phys. Rev. Fluid., 2, 124402, https://doi.org/10.1103/PhysRevFluids.2.124402, 2017. a
Barsugli, J. J. and Battisti, D. S.: The basic effects of atmosphere–ocean thermal coupling on midlatitude variability, J. Atmos. Sci., 55, 477–493, 1998. a
Benzi, R., Hansen, A. R., and Sutera, A.: On stochastic perturbation of simple blocking models, Q. J. Roy. Meteorol. Soc., 110, 393–409, 1984. a
Bishop, C. M. and Nasrabadi, N. M.: Pattern recognition and machine learning, Springer, ISBN-10: 0-387-31073-8, ISBN-13: 978-0387-31073-2, 2006. a
Breeden, M. L., Hoover, B. T., Newman, M., and Vimont, D. J.: Optimal North Pacific blocking precursors and their deterministic subseasonal evolution during boreal winter, Mon. Weather Rev., 148, 739–761, 2020. a, b
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This research focuses on understanding different atmospheric patterns like blocking, zonal, and transition regimes and analyzing their predictability. We used an idealized land–atmosphere coupled model to simulate Earth's atmosphere. Then we identified these blocking, zonal, and transition regimes using Gaussian mixture clustering and studied their predictability using Lyapunov exponents.
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