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A Three-Layer Atmosphere-Ocean Time Series Model of Global Climate Change

Author

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  • David I. Stern

    () (Department of Economics, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, USA)

Abstract

Time series models of global climate change have tended to estimate a low climate sensitivity and a fast adjustment rate to equilibrium. These results appear to be biased by omission of a key variable - heat stored in the ocean. I develop a time series model of the ocean atmosphere climate system where atmospheric temperature moves towards a long-run equilibrium with both radiative forcing and ocean heat content, which is distributed between upper ocean and deep ocean components. The time series model utilizes the notion of multicointegration to impose energy balance relations on an autoregressive model. As there are only around fifty years of observations on ocean heat content I use the Kalman filter to estimate heat content as a latent state variable constrained by the available observations. The estimate of the equilibrium climate sensitivity is 8.4K with a confidence interval of 5.0 to 11.7K. Temperature takes centuries to adjust to an increase in radiative forcing. The transient climate sensitivity at the point of carbon dioxide doubling is 1.7K.

Suggested Citation

  • David I. Stern, 2005. "A Three-Layer Atmosphere-Ocean Time Series Model of Global Climate Change," Rensselaer Working Papers in Economics 0510, Rensselaer Polytechnic Institute, Department of Economics.
  • Handle: RePEc:rpi:rpiwpe:0510
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    File URL: http://www.economics.rpi.edu/workingpapers/rpi0510.pdf
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    References listed on IDEAS

    as
    1. Engsted, Tom & Haldrup, Niels, 1999. " Multicointegration in Stock-Flow Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(2), pages 237-254, May.
    2. Granger, C W J & Lee, T H, 1989. "Investigation of Production, Sales and Inventory Relationships Using Multicointegration and Non-symmetric Error Correction Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 145-159, Supplemen.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    4. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, vol. 59(2), pages 283-306, March.
    5. David I. Stern, 2004. "A Multicointegration Model of Global Climate Change," Rensselaer Working Papers in Economics 0406, Rensselaer Polytechnic Institute, Department of Economics.
    6. Hui Liu & Gabriel Rodriguez, 2003. "Human Activities and Global Warming: A Cointegration Analysis," Working Papers 0307E, University of Ottawa, Department of Economics.
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    More about this item

    JEL classification:

    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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