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Application of Signal Analysis to the Climate
Author(s) -
Peter Stallinga,
Igor Khmelinskii
Publication year - 2014
Publication title -
international scholarly research notices
Language(s) - English
Resource type - Journals
ISSN - 2356-7872
DOI - 10.1155/2014/161530
Subject(s) - lagging , relaxation (psychology) , time domain , environmental science , signal (programming language) , frequency domain , global warming , climate change , phase (matter) , time constant , constant (computer programming) , climatology , line (geometry) , atmospheric sciences , computer science , physics , mathematics , geology , statistics , medicine , oceanography , programming language , geometry , engineering , quantum mechanics , electrical engineering , computer vision
The primary ingredient of the Anthropogenic Global Warming hypothesis, namely, the assumption that additional atmospheric carbon dioxide substantially raises the global temperature, is studied. This is done by looking at the data of temperature and CO 2 , both in the time domain and in the phase domain of periodic data. Bicentenary measurements are analyzed and a relaxation model is introduced in the form of an electronic equivalent circuit. The effects of this relaxation manifest themselves in delays in the time domain and correlated phase shifts in the phase domain. For extremely long relaxation time constants, the delay is maximally one-quarter period, which for the yearly-periodic signal means 3 months. This is not in line with the analyzed data, the latter showing delays of 9 (−3) months. These results indicate a reverse function of cause and effect, with temperature being the cause for atmospheric CO 2 changes, rather than their effect. These two hypotheses are discussed on basis of literature, where it was also reported that CO 2 variations are lagging behind temperature variations.

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