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A time-series analysis of the 20th century climate simulations produced for the IPCC’s AR4

Author

Listed:
  • Pierre Perron

    (Department of Economics, Boston University)

  • Francisco Estrada

    (Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México)

  • Carlos Gay-García

    (Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México)

  • Benjamín Martínez-López

    (Centro de Ciencias de la Atmósfera, Universidad Nacional Autónoma de México)

Abstract

For more than two decades a debate regarding the time-series properties of global and hemispheric temperatures has taken place on the climate change literature and it has hardly been settled at the present time. This paper analyzes the IPCC's AR4 20c3m simulations using modern econometric techniques and provides new evidence to support that global temperatures can be better described as a trend-stationarity process with one-time structural change. As a consequence, the cointegration techniques that have been commonly used in the literature are not adequate and results produced using such techniques should be revised. Furthermore, the analysis of these simulations indicates that the increase in the rate of warming shown by observed and simulated global temperature series since the mid 1970's is produced by external forcing factors that cannot be interpreted as being part of natural variability. As stated in Gay et al. (2009), it can be argued that in terms of Article 2 of the Framework Convention on Climate Change, significant anthropogenic interference with the climate system has already occurred and that current climate models are capable of accurately simulating the response of the climate system, even if it consists in a rapid or abrupt change, to changes in external forcing factors.

Suggested Citation

  • 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.
  • Handle: RePEc:bos:wpaper:wp2011-051
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    References listed on IDEAS

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    Cited by:

    1. Yoosoon Chang & Robert K. Kaufmann & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2015. "Time Series Analysis of Global Temperature Distributions: Identifying and Estimating Persistent Features in Temperature Anomalies," Working Papers 1513, Department of Economics, University of Missouri, revised 25 Jul 2016.
    2. Pierre Perron & Francisco Estrada & Benjamín Martínez-López, 2012. "Statistical evidence about human influence on the climate system," Boston University - Department of Economics - Working Papers Series WP2012-012, Boston University - Department of Economics.
    3. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2020. "Trends in distributional characteristics: Existence of global warming," Journal of Econometrics, Elsevier, vol. 214(1), pages 153-174.
    4. Marco Gallegati, 2018. "A systematic wavelet-based exploratory analysis of climatic variables," Climatic Change, Springer, vol. 148(1), pages 325-338, May.
    5. Richard S.J. Tol & Francisco Estrada, 2013. "Estimating the Global Impacts of Climate Variability and Change During the 20th Century," Working Paper Series 6213, Department of Economics, University of Sussex Business School.
    6. Chang, Yoosoon & Kaufmann, Robert K. & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2020. "Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate," Journal of Econometrics, Elsevier, vol. 214(1), pages 274-294.
    7. Pierre Perron & Mototsugu Shintani & Tomoyoshi Yabu, 2017. "Testing for Flexible Nonlinear Trends with an Integrated or Stationary Noise Component," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 822-850, October.
    8. Kim, Dukpa & Oka, Tatsushi & Estrada, Francisco & Perron, Pierre, 2020. "Inference related to common breaks in a multivariate system with joined segmented trends with applications to global and hemispheric temperatures," Journal of Econometrics, Elsevier, vol. 214(1), pages 130-152.
    9. Francisco Estrada & Pierre Perron, "undated". "Detection and attribution of climate change through econometric methods," Boston University - Department of Economics - Working Papers Series 2013-015, Boston University - Department of Economics.
    10. Dukpa Kim & Tatsushi Oka & Francisco Estrada & Pierre Perron, 2017. "Inference Related to Common Breaks in a Multivariate System with Joined Segmented Trends with Applications to Global and Hemispheric Temperatures," Boston University - Department of Economics - Working Papers Series WP2017-003, Boston University - Department of Economics.
    11. Francisco Estrada & Luis Filipe Martins & Pierre Perron, 2017. "Characterizing and attributing the warming trend in sea and land surface temperatures," Boston University - Department of Economics - Working Papers Series WP2017-009, Boston University - Department of Economics.
    12. Pierre Perron & Eduardo Zorita & Francisco Estrada & Pierre Perron, 2017. "Extracting and Analyzing the Warming Trend in Global and Hemispheric Temperatures," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 711-732, September.
    13. 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.

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