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Greenhouse statistics-time series analysis
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.
History
Publication status
- Published
Journal
Theoretical and Applied ClimatologyISSN
0177-798XPublisher
Springer VerlagExternal DOI
Issue
2-3Volume
48Page range
63-74Department affiliated with
- Economics Publications
Full text available
- No
Peer reviewed?
- Yes