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Atmospheric Circulations Do Not Explain the Temperature-Industrialization Correlation

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  • McKitrick Ross

    (University of Guelph)

Abstract

Gridded land surface temperature data products are used in climatology on the assumption that contaminating effects from urbanization, land-use change and related socioeconomic processes have been identified and filtered out, leaving behind a "pure" record of climatic change. But several studies have shown a correlation between the spatial pattern of warming trends in climatic data products and the spatial pattern of industrialization, indicating that local non-climatic effects may still be present. This, in turn, could bias measurements of the amount of global warming and its attribution to greenhouse gases. The 2007 report of the Intergovernmental Panel on Climate Change (IPCC) set aside those concerns with the claim that the temperature-industrialization correlation becomes statistically insignificant if certain atmospheric circulation patterns, also called oscillations, are taken into account. But this claim has never been tested and the IPCC provided no evidence for its assertion. I estimate two spatial models that simultaneously control for the major atmospheric oscillations and the distribution of socioeconomic activity. The correlations between warming patterns and patterns of socioeconomic development remain large and significant in the presence of controls for atmospheric oscillations, contradicting the IPCC claim. Tests for outlier influence, spatial autocorrelation, endogeneity bias, residual nonlinearity and other problems are discussed.

Suggested Citation

  • McKitrick Ross, 2010. "Atmospheric Circulations Do Not Explain the Temperature-Industrialization Correlation," Statistics, Politics and Policy, De Gruyter, vol. 1(1), pages 1-20, July.
    • Handle: RePEc:bpj:statpp:v:1:y:2010:i:1:p:20:n:1
    DOI: 10.2202/2151-7509.1004
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    References listed on IDEAS

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    1. Sir Ian Byatt & Ian Castles & David Henderson & Lord Lawson of Blaby & Ross McKitrick & Julian Morris & Sir Alan Peacock & Colin Robinson & Lord Skidelsky, 2006. "COMMENT: Climate Change," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 7(2), pages 145-151, April.
    2. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    3. Jun, Mikyoung & Knutti, Reto & Nychka, Douglas W, 2008. "Spatial Analysis to Quantify Numerical Model Bias and Dependence," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 934-947.
    4. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
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    Cited by:

    1. Ameur, Hachmi Ben & Han, Xuyuan & Liu, Zhenya & Peillex, Jonathan, 2022. "When did global warming start? A new baseline for carbon budgeting," Economic Modelling, Elsevier, vol. 116(C).
    2. Ross McKitrick, 2013. "Encompassing tests of socioeconomic signals in surface climate data," Climatic Change, Springer, vol. 120(1), pages 95-107, September.

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