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  • Nonlinear Sciences - Chaotic Dynamics; Nonlinear Sciences - Chaotic Dynamics  (1)
  • TWC 100  (1)
  • 1
    Publication Date: 2021-03-29
    Description: The separation of natural and anthropogenically caused climatic changes is an important task of contemporary climate research. For this purpose, a detailed knowledge of the natural variability of the climate during warm stages is a necessary prerequisite. Beside model simulations and historical documents, this knowledge is mostly derived from analyses of so-called climatic proxy data like tree rings or sediment as well as ice cores. In order to be able to appropriately interpret such sources of palaeoclimatic information, suitable approaches of statistical modelling as well as methods of time series analysis are necessary, which are applicable to short, noisy, and non-stationary uni- and multivariate data sets. Correlations between different climatic proxy data within one or more climatological archives contain significant information about the climatic change on longer time scales. Based on an appropriate statistical decomposition of such multivariate time series, one may estimate dimensions in terms of the number of significant, linear independent components of the considered data set. In the presented work, a corresponding approach is introduced, critically discussed, and extended with respect to the analysis of palaeoclimatic time series. Temporal variations of the resulting measures allow to derive information about climatic changes ...
    Description: thesis
    Keywords: 551.6 ; VBE 000 ; TWC 100 ; Modellierung von Prozessen in der Geosphäre ; Instr. Ergebn. zu Klimaänderungen und Klimaschwankungen
    Language: English
    Type: monograph , publishedVersion
    Format: 169 S.
    Format: application/pdf
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  • 2
    Publication Date: 2024-04-30
    Description: 9 pages, 6 figures
    Description: Many natural systems show emergent phenomena at different scales, leading to scaling regimes with signatures of deterministic chaos at large scales and an apparently random behavior at small scales. These features are usually investigated quantitatively by studying the properties of the underlying attractor, the compact object asymptotically hosting the trajectories of the system with their invariant density in the phase space. This multi-scale nature of natural systems makes it practically impossible to get a clear picture of the attracting set. Indeed, it spans over a wide range of spatial scales and may even change in time due to non-stationary forcing. Here, we combine an adaptive decomposition method with extreme value theory to study the properties of the instantaneous scale-dependent dimension, which has been recently introduced to characterize such temporal and spatial scale-dependent attractors in turbulence and astrophysics. To provide a quantitative analysis of the properties of this metric, we test it on the well-known low-dimensional deterministic Lorenz-63 system perturbed with additive or multiplicative noise. We demonstrate that the properties of the invariant set depend on the scale we are focusing on and that the scale-dependent dimensions can discriminate between additive and multiplicative noise despite the fact that the two cases have exactly the same stationary invariant measure at large scales. The proposed formalism can be generally helpful to investigate the role of multi-scale fluctuations within complex systems, allowing us to deal with the problem of characterizing the role of stochastic fluctuations across a wide range of physical systems.
    Description: Published
    Description: 023144
    Description: OSA2: Evoluzione climatica: effetti e loro mitigazione
    Description: JCR Journal
    Keywords: Nonlinear Sciences - Chaotic Dynamics; Nonlinear Sciences - Chaotic Dynamics
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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