An early warning indicator for atmospheric blocking events using transfer operators

Abstract

The existence of persistent midlatitude atmospheric flow regimes with time-scales larger than 5-10 days and indications of preferred transitions between them motivates to develop early warning indicators for such regime transitions. In this paper, we use a hemispheric barotropic model together with estimates of transfer operators on a reduced phase space to develop an early warning indicator of the zonal to blocked flow transition in this model. It is shown that, the spectrum of the transfer operators can be used to study the slow dynamics of the flow as well as the non-Markovian character of the reduction. The slowest motions are thereby found to have time scales of three to six weeks and to be associated with meta-stable regimes (and their transitions) which can be detected as almost-invariant sets of the transfer operator. From the energy budget of the model, we are able to explain the meta-stability of the regimes and the existence of preferred transition paths. Even though the model is highly simplified, the skill of the early warning indicator is promising, suggesting that the transfer operator approach can be used in parallel to an operational deterministic model for stochastic prediction or to assess forecast uncertainty.

References in corpus (8)

• Finding community structure in very large networks
• Maps of random walks on complex networks reveal community structure
• Dynamical ensembles in stationary states
• Ruelle-Perron-Frobenius spectrum for Anosov maps
• Data-driven non-Markovian closure models
• Multi-level Dynamical Systems: Connecting the Ruelle Response Theory and the Mori-Zwanzig Approach
• Estimating long term behavior of flows without trajectory integration: the infinitesimal generator approach
• Deep ocean early warning signals of an Atlantic MOC collapse

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