✦ LIBER ✦

Inference about trends in global temperature data

✍ Scribed by John W. Galbraith; Christopher Green

Publisher: Springer
Year: 1992
Tongue: English
Weight: 681 KB
Volume: 22
Category: Article
ISSN: 0165-0009
DOI: 10.1007/bf00143028

No coin nor oath required. For personal study only.

✦ Synopsis

Interpretation of the effects of increasing atmospheric carbon dioxide on temperature is made more difficult by the fact that it is unclear whether sufficient global warming has taken place to allow a statistically significant finding of any upward trend in the temperature series. We add to the few existing statistical results by reporting tests for both deterministic and stochastic non-stationarity (trends) in time series of global average temperature. We conclude that the statistical evidence is sufficient to reject the hypothesis of a stochastic trend; however, there is evidence of a trend which could be approximated by a deterministic linear model.

The authors are grateful to the SSHRC (Green) and FCAR (Galbraith) for financial support under grants 10-89-0205 and NC-0047.

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