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Title: Fixed points, stable manifolds, weather regimes, and their predictability

Abstract

In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemble forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.

Authors:
 [1];  [2];  [3]
  1. Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France)
  2. Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Paris (France)
  3. Univ. of California, Los Angeles, CA (United Staes). Atmospheric and Oceanic Sciences and Inst. of Geophysics and Planetary Physics
Publication Date:
Research Org.:
Laboratoire de Meteorologie Dynamique (CNRS and IPSL), Ecole Normale Superieure, Paris (France)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1076437
Grant/Contract Number:  
FG02-07ER64439
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Chaos: An Interdisciplinary Journal of Nonlinear Science
Additional Journal Information:
Journal Volume: 19; Journal Issue: 4; Journal ID: ISSN 1054-1500
Publisher:
American Institute of Physics (AIP)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; atmospheric flow, local predictability, multiple regimes, separatrix

Citation Formats

Deremble, Bruno, D'Andrea, Fabio, and Ghil, Michael. Fixed points, stable manifolds, weather regimes, and their predictability. United States: N. p., 2009. Web. doi:10.1063/1.3230497.
Deremble, Bruno, D'Andrea, Fabio, & Ghil, Michael. Fixed points, stable manifolds, weather regimes, and their predictability. United States. https://doi.org/10.1063/1.3230497
Deremble, Bruno, D'Andrea, Fabio, and Ghil, Michael. 2009. "Fixed points, stable manifolds, weather regimes, and their predictability". United States. https://doi.org/10.1063/1.3230497. https://www.osti.gov/servlets/purl/1076437.
@article{osti_1076437,
title = {Fixed points, stable manifolds, weather regimes, and their predictability},
author = {Deremble, Bruno and D'Andrea, Fabio and Ghil, Michael},
abstractNote = {In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemble forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.},
doi = {10.1063/1.3230497},
url = {https://www.osti.gov/biblio/1076437}, journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
issn = {1054-1500},
number = 4,
volume = 19,
place = {United States},
year = {Tue Oct 27 00:00:00 EDT 2009},
month = {Tue Oct 27 00:00:00 EDT 2009}
}

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Cited by: 7 works
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Works referencing / citing this record:

Predicting Climate Change Using Response Theory: Global Averages and Spatial Patterns
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Multiple equilibria and oscillatory modes in a mid-latitude ocean-forced atmospheric model
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