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Inference about trends in global temperature data

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Abstract

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.

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Authors and Affiliations

  1. Department of Economics, McGill University, H3A 2T7, Montreal, Quebec, Canada

    John W. Galbraith

  2. Department of Economics and Centre for Climate and Global Change Research, McGill University, H3A 2T7, Montreal, Quebec, Canada

    Christopher Green

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  1. John W. Galbraith
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  2. Christopher Green
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Additional information

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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Galbraith, J.W., Green, C. Inference about trends in global temperature data. Climatic Change 22, 209–221 (1992). https://doi.org/10.1007/BF00143028

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  • DOI: https://doi.org/10.1007/BF00143028

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