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Climate 2019, 7(2), 21;

A Physical–Mathematical Approach to Climate Change Effects through Stochastic Resonance

Consiglio Nazionale delle Ricerche (CNR)—Istituto per i Processi Chimico-Fisici (IPCF), Viale Ferdinando Stagno D’Alcontres n°37, S. Agata, 98166 Messina, Italy
Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università di Messina, Viale Ferdinando Stagno D’Alcontres n°31, S. Agata, 98166 Messina, Italy
Istituto Nazionale di Alta Matematica “F. Severi”—INDAM—Gruppo Nazionale per la Fisica Matematica—GNFM, P.le Aldo Moro 5, 00185 Roma, Italy
Author to whom correspondence should be addressed.
Received: 22 November 2018 / Revised: 15 January 2019 / Accepted: 24 January 2019 / Published: 27 January 2019
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The aim of this work is to study the effects induced by climate changes in the framework of the stochastic resonance approach. First, a wavelet cross-correlation analysis on Earth temperature data concerning the last 5,500,000 years is performed; this analysis confirms a correlation between the planet’s temperature and the 100,000, 41,000, and 23,000-year periods of the Milankovitch orbital cycles. Then, the stochastic resonance model is invoked. Specific attention is given to the study of the impact of the registered global temperature increase within the stochastic model. Further, a numerical simulation has been performed, based on: (1) A double-well potential, (2) an external periodic modulation, corresponding to the orbit eccentricity cycle, and (3) an increased value of the global Earth temperature. The effect of temperature increase represents one of the novelties introduced in the present study and is determined by downshifting the interaction potential used within the stochastic resonance model. The numeric simulation results show that, for simulated increasing values of the global temperature, the double-well system triggers changes, while at higher temperatures (as in the case of the absence of a global temperature increase although with a different threshold) the system goes into a chaotic regime. The wavelet analysis allows characterization of the stochastic resonance condition through the evaluation of the signal-to-noise ratio. On the basis of the obtained findings, we hypothesize that the global temperature increase can suppress, on a large time scale corresponding to glacial cycles, the external periodic modulation effects and, hence, the glacial cycles. View Full-Text
Keywords: stochastic resonance model; climate change effects; temperature increasing; simulation stochastic resonance model; climate change effects; temperature increasing; simulation

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Caccamo, M.T.; Magazù, S. A Physical–Mathematical Approach to Climate Change Effects through Stochastic Resonance. Climate 2019, 7, 21.

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