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Amandine Kaiser, Davide Faranda, Sebastian Krumscheid, Danijel Belušić, and Nikki Vercauteren

Abstract

Many natural systems undergo critical transitions, i.e., sudden shifts from one dynamical regime to another. In the climate system, the atmospheric boundary layer can experience sudden transitions between fully turbulent states and quiescent, quasi-laminar states. Such rapid transitions are observed in polar regions or at night when the atmospheric boundary layer is stably stratified, and they have important consequences in the strength of mixing with the higher levels of the atmosphere. To analyze the stable boundary layer, many approaches rely on the identification of regimes that are commonly denoted as weakly and very stable regimes. Detecting transitions between the regimes is crucial for modeling purposes. In this work a combination of methods from dynamical systems and statistical modeling is applied to study these regime transitions and to develop an early warning signal that can be applied to nonstationary field data. The presented metric aims to detect nearing transitions by statistically quantifying the deviation from the dynamics expected when the system is close to a stable equilibrium. An idealized stochastic model of near-surface inversions is used to evaluate the potential of the metric as an indicator of regime transitions. In this stochastic system, small-scale perturbations can be amplified due to the nonlinearity, resulting in transitions between two possible equilibria of the temperature inversion. The simulations show such noise-induced regime transitions, successfully identified by the indicator. The indicator is further applied to time series data from nocturnal and polar meteorological measurements.

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David Rodrigues, M. Carmen Alvarez-Castro, Gabriele Messori, Pascal Yiou, Yoann Robin, and Davide Faranda

Abstract

It is of fundamental importance to evaluate the ability of climate models to capture the large-scale atmospheric circulation patterns and, in the context of a rapidly increasing greenhouse forcing, the robustness of the changes simulated in these patterns over time. Here we approach this problem from an innovative point of view based on dynamical systems theory. We characterize the atmospheric circulation over the North Atlantic in the CMIP5 historical simulations (1851–2000) in terms of two instantaneous metrics: local dimension of the attractor and stability of phase-space trajectories. We then use these metrics to compare the models to the Twentieth Century Reanalysis version 2c (20CRv2c) over the same historical period. The comparison suggests that (i) most models capture to some degree the median attractor properties, and models with finer grids generally perform better; (ii) in most models the extremes in the dynamical systems metrics match large-scale patterns similar to those found in the reanalysis; (iii) changes in the attractor properties observed for the ensemble-mean 20CRv2c are artifacts resulting from inhomogeneities in the standard deviation of the ensemble over time; and (iv) the long-term trends in local dimension observed among the 56 members of the 20CR ensemble have the same sign as those observed in the CMIP5 multimodel mean, although the multimodel trend is much weaker.

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Davide Faranda, Valerio Lembo, Manasa Iyer, Denis Kuzzay, Sergio Chibbaro, Francois Daviaud, and Berengere Dubrulle

Abstract

Atmospheric motions are governed by turbulent motions associated to nontrivial energy transfers at small scales (direct cascade) and/or at large scales (inverse cascade). Although it is known that the two cascades coexist, energy fluxes have been previously investigated from the spectral point of view but not on their instantaneous spatial and local structure. Here, we compute local and instantaneous subfilter-scale energy transfers in two sets of reanalyses (NCEP–NCAR and ERA-Interim) in the troposphere and the lower stratosphere for the year 2005. The fluxes are mostly positive (toward subgrid scales) in the troposphere and negative in the stratosphere, reflecting the baroclinic and barotropic nature of the motions, respectively. The most intense positive energy fluxes are found in the troposphere and are associated with baroclinic eddies or tropical cyclones. The computation of such fluxes can be used to characterize the amount of energy lost or missing at the smallest scales in climate and weather models.

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Gabriele Messori, Emanuele Bevacqua, Rodrigo Caballero, Dim Coumou, Paolo De Luca, Davide Faranda, Kai Kornhuber, Olivia Martius, Flavio Pons, Colin Raymond, Kunhui Ye, Pascal Yiou, and Jakob Zscheischler
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Pascal Yiou, Julien Cattiaux, Davide Faranda, Nikolay Kadygrov, Aglae Jézéquel, Philippe Naveau, Aurelien Ribes, Yoann Robin, Soulivanh Thao, Geert Jan van Oldenborgh, and Mathieu Vrac
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Gabriele Messori, Rodrigo Caballero, Freddy Bouchet, Davide Faranda, Richard Grotjahn, Nili Harnik, Steve Jewson, Joaquim G. Pinto, Gwendal Rivière, Tim Woollings, and Pascal Yiou
Open access