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Greenhouse statistics-time series analysis
journal contributionposted on 2023-06-08, 11:11 authored by Richard TolRichard Tol, Aart F de Vos
The relationship global mean temperature - atmospheric concentration of carbon dioxide is modelled by means of time series analysis as it is used in a non-experimental statistical context. The goal is to test the hypothesis that the global mean surface air temperature rises due to the rising atmospheric concentrations of greenhouse gases. Starting with some naive time series models we show that the enhanced greenhouse effect is plausible. Taking the long-term natural variability of the climate into account casts doubt on this claim but properly quantifying the size of the variability restores the significance of the greenhouse parameter. Although statistics cannot constitute a proof of the hypothesis, the results of this paper are strong enough to conclude that at least part of the recent high temperatures is, with high probability, caused by the increase in the atmospheric concentration of carbon dioxide.
JournalTheoretical and Applied Climatology
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- Economics Publications
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