Abstract
This doctoral thesis aimed on studying the changes in the fundamental thermodynamic parameters of the climate system and their contributions to climate change, which is considered as a change in critical parameters and states of its non-linearly interacting subsystems (atmosphere, cryosphere, hydrosphere, lithosphere, and biosphere). Information on key parameters of the Earth's climate was derived from ground and satellite data, as well as from global databases. The analysis of these data was implemented using modern linear and nonlinear dynamicsmethods. This thesis mainly focused on the study of the spatiotemporal variation of various thermodynamic parameters using tools for analyzing the entropy of the climate system (according to Boltzmann-Gibbs and Tsallis) but also linear and non-linear analysis methods, such as the DFA method (Detrended Fluctuation Analysis) and "Natural Time Analysis". The thesis provides information on the dynamic evolution of the climate system and describes t ...
This doctoral thesis aimed on studying the changes in the fundamental thermodynamic parameters of the climate system and their contributions to climate change, which is considered as a change in critical parameters and states of its non-linearly interacting subsystems (atmosphere, cryosphere, hydrosphere, lithosphere, and biosphere). Information on key parameters of the Earth's climate was derived from ground and satellite data, as well as from global databases. The analysis of these data was implemented using modern linear and nonlinear dynamicsmethods. This thesis mainly focused on the study of the spatiotemporal variation of various thermodynamic parameters using tools for analyzing the entropy of the climate system (according to Boltzmann-Gibbs and Tsallis) but also linear and non-linear analysis methods, such as the DFA method (Detrended Fluctuation Analysis) and "Natural Time Analysis". The thesis provides information on the dynamic evolution of the climate system and describes the spatio-temporal changes that makeup its complexity. More specifically, in the first Chapter, the non-linear behavior of the atmospheric temperature, considered as a basic component of the climate system, is investigated. For this reason, a detailed description of the Detrended Fluctuation Analysis (DFA) and Natural Time Analysis (NTA) methods is first carried out. The DFA method is then applied to global satellite data of tropopause temperature deviations, which are available from the University of Alabama in Huntsville -UAH, and the obtained results are checked using the Maraun criteria. The tropopause temperature time series are then transformed into absolute - values time series or else amplitude time series and expressed in the “natural time” domain to re-apply the DFAmethod followed by the Maraun criteria. The final results reveal the DFA exponent to be between 0.8 and 1, which is confirmed by the analysis of the amplitude time series, natural time, with values ranging from 0.6 to 0.8. These findings indicate the finding of a persistent scaling behavior of the thermal tropopause at different latitudes and indeed in the form of 1/f. In the second Chapter, peat scaling behavior during theHolocene period is investigated aiming on a better understanding of past climate conditions in order to enhance the understanding of future dynamic behaviors of the climate system. In this Chapter, the dynamic characteristics of peat humification, water table depth and air temperature are investigated by analyzing paleoclimate data from the Valdai Uplands region of Russia. The study is carried out through the use of DFA followed by the Maraun criteria and Ensemble Empirical Mode Decomposition (EEMD) analysis. The results of the study show that peat exhibits a persistent scaling behavior, and more specifically in the form of 1/f, which may allow the use of peat as an indicator of climate change in future research. The time series are then converted to "natural time" time series and the DFA method followed by the Maraun criteria is reapplied. The Natural Time DFA results and the Maraun criteria confirm the 1/f type scaling behavior for the peat moisture and air temperature parameters but not for the WTD parameter. The third Chapter explores the complexity and its quantificationfor long time series of climate parameters through the application of Tsallis entropy to the data. For this reason, an overview of the different types of entropy is first provided, and then the Tsallis entropy is applied to global satellite data of tropopause temperature deviations, which are available from the University of Alabama in Huntsville -UAH. The resulting entropy values, calculated for multiple non-extensivity parameters q , provide additional insight into the scaling behavior of the tropopause while the findings highlight the potential utility of Tsallis entropy as a tool for climate time series analysis. In the fourth Chapter, a comprehensive summary of the results from the multi-methodological analyzes carried out in theprevious Chapters is presented, and the conclusions of the thesis are expressed. More specifically, the DFA and NTA methods were applied to global satellite data of tropopause temperature changes, revealing the 1/ f -type scaling behaviorof the thermal tropopause. The study of peat through DFA, NTA EEMD and Hurst analyzes revealed that it is also subject to longrange correlations characterized by a persistent 1/f-type scaling behavior, while highlighting it as a useful climate indicator for studying changes in climate patterns. Tsallis entropy analysis demonstrated the complexity of the time series with different q values revealing distinct entropy patterns.
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