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Does temperature contain a stochastic trend: linking statistical results to physical mechanisms

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  • Robert Kaufmann

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  • Heikki Kauppi
  • Michael Mann
  • James Stock

Abstract

By construction, the time series for radiative forcing that are used to run the 20c3m experiments, which are implemented by climate models, impart non-stationary movements (either stochastic or deterministic) to the simulated time series for global surface temperature. Here, we determine whether stochastic or deterministic trends are present in the simulated time series for global surface temperature by examining the time series for radiative forcing. Statistical tests indicate that the forcings contain a stochastic trend against the alternative hypothesis that the series are trend stationary with a one-time structural change. This result is consistent with the economic processes that impart a stochastic trend to anthropogenic emissions and the physical processes that integrate emissions in the atmosphere. Furthermore, the stochastic trend in the aggregate measure of radiative forcing also is present in the simulated time series for global surface temperature, which is consistent with the relation between these two variables that is represented by a zero dimensional energy balance model. Finally, we propose that internal weather variability imposed on the stochastic trend in radiative forcings is responsible for statistical results, which gives the impression that global surface temperature is trend stationary with a one-time structural change. We conclude that using the ideas of stochastic trends, cointegration, and error correction can generate reliable conclusions regarding the causes of changes in global surface temperature during the instrumental temperature record. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Robert Kaufmann & Heikki Kauppi & Michael Mann & James Stock, 2013. "Does temperature contain a stochastic trend: linking statistical results to physical mechanisms," Climatic Change, Springer, vol. 118(3), pages 729-743, June.
  • Handle: RePEc:spr:climat:v:118:y:2013:i:3:p:729-743
    DOI: 10.1007/s10584-012-0683-2
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    References listed on IDEAS

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    1. Pierre Perron & Francisco Estrada & Carlos Gay-García & Benjamín Martínez-López, 2011. "A time-series analysis of the 20th century climate simulations produced for the IPCC’s AR4," Boston University - Department of Economics - Working Papers Series WP2011-051, Boston University - Department of Economics.
    2. William Rea & Marco Reale & Jennifer Brown, 2011. "Long memory in temperature reconstructions," Climatic Change, Springer, vol. 107(3), pages 247-265, August.
    3. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-287, July.
    4. Dinda, Soumyananda & Coondoo, Dipankor, 2006. "Income and emission: A panel data-based cointegration analysis," Ecological Economics, Elsevier, vol. 57(2), pages 167-181, May.
    5. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-840, September.
    6. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    7. West, Kenneth D, 1988. "Asymptotic Normality, When Regressors Have a Unit Root," Econometrica, Econometric Society, vol. 56(6), pages 1397-1417, November.
    8. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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    Citations

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    Cited by:

    1. J. Isaac Miller, 2017. "Local Climate Sensitivity: A Statistical Approach for a Spatially Heterogeneous Planet," Working Papers 1702, Department of Economics, University of Missouri.
    2. Gonzalo, Jesús & Gadea Rivas, María Dolores, 2017. "Trends in distributional characteristics : Existence of global warming," UC3M Working papers. Economics 24121, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Claudio Morana & Giacomo Sbrana, 2017. "Temperature anomalies, radiative forcing and ENSO," Working Paper series 17-06, Rimini Centre for Economic Analysis.
    4. Claudio, Morana & Giacomo, Sbrana, 2017. "Some Financial Implications of Global Warming: An Empirical Assessment," Working Papers 377, University of Milano-Bicocca, Department of Economics, revised 25 Dec 2017.
    5. Guillaume Chevillon, 2017. "Robust cointegration testing in the presence of weak trends, with an application to the human origin of global warming," Econometric Reviews, Taylor & Francis Journals, vol. 36(5), pages 514-545, May.
    6. repec:oxf:wpaper:750 is not listed on IDEAS
    7. Yoosoon Chang & Robert K. Kaufmann & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2015. "Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate," Working Papers 1622, Department of Economics, University of Missouri, revised 19 Dec 2016.
    8. Dergiades, Theologos & Kaufmann, Robert K. & Panagiotidis, Theodore, 2016. "Long-run changes in radiative forcing and surface temperature: The effect of human activity over the last five centuries," Journal of Environmental Economics and Management, Elsevier, vol. 76(C), pages 67-85.
    9. repec:bla:jorssa:v:180:y:2017:i:3:p:769-791 is not listed on IDEAS
    10. David I. Stern, 2004. "A Multicointegration Model of Global Climate Change," Rensselaer Working Papers in Economics 0406, Rensselaer Polytechnic Institute, Department of Economics.
    11. Claudio Morana & Giacomo Sbrana, 2018. "Some Financial Implications of Global Warming: an Empirical Assessment," Working Papers 2018.01, Fondazione Eni Enrico Mattei.
    12. Tommaso Proietti & Eric Hillebrand, 2017. "Seasonal changes in central England temperatures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 769-791, June.
    13. Beenstock, Michael & Reingewertz, Yaniv & Paldor, Nathan, 2016. "Testing the historic tracking of climate models," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1234-1246.
    14. repec:hal:journl:hal-00914830 is not listed on IDEAS
    15. Pierre Perron & Francisco Estrada & Carlos Gay-García & Benjamín Martínez-López, 2011. "A time-series analysis of the 20th century climate simulations produced for the IPCC’s AR4," Boston University - Department of Economics - Working Papers Series WP2011-051, Boston University - Department of Economics.

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