Climatic Change

, Volume 107, Issue 3–4, pp 267–276 | Cite as

On long range dependence in global surface temperature series

An editorial comment
Article

Abstract

Long Range Dependence (LRD) scaling behavior has been argued to characterize long-term surface temperature time series. LRD is typically measured by the so-called “Hurst” coefficient, “H”. Using synthetic temperature time series generated by a simple climate model with known physics, I demonstrate that the values of H obtained for observational temperature time series can be understood in terms of the linear response to past estimated natural and anthropogenic external radiative forcing combined with the effects of random white noise weather forcing. The precise value of H is seen to depend on the particular noise realization. The overall distribution obtained over an ensemble of noise realizations is seen to be a function of the relative amplitude of external forcing and internal stochastic variability and additionally in climate “proxy” records, the amount of non-climatic noise present. There is no obvious reason to appeal to more exotic physics for an explanation of the apparent scaling behavior in observed temperature data.

Supplementary material

10584_2010_9998_MOESM1_ESM.doc (121 kb)
(PDF 121 kb)

References

  1. Ammann CM, Joos F, Schimel DS, Otto-Bliesner BL, Tormas RA (2007) Solar influence on climate during the past millennium: results from transient simulations with the NCAR Climate System Model. Proc Natl Acad Sci U S A 104:3713–3718CrossRefGoogle Scholar
  2. Blender R, Fraedrich K (2003) Long time memory in global warming simulations. Geophys Res Lett 30(14):1769CrossRefGoogle Scholar
  3. Bloomfield P, Nychka D (1992) Climate spectra and detecting climate change. Clim Change 21:275–287CrossRefGoogle Scholar
  4. Brohan P, Kennedy JJ, Haris I, Tett SFB, Jones PD (2006) Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850. J Geophys Res 111:D12106. doi:10.1029/2005JD006548 CrossRefGoogle Scholar
  5. Crowley TJ (2000) Causes of climate change over the past 1000 years. Science 289:270–277CrossRefGoogle Scholar
  6. Delworth TL, Mann ME (2000) Observed and simulated multidecadal variability in the northern hemisphere. Clim Dyn 16:661–676CrossRefGoogle Scholar
  7. Eichner J, Koscielny-Bunde E, Bunde A, Havlin S, Schellnhuber H (2003) Power-law persistence and trends in the atmosphere: a detailed study of long temperature records. Clim Dyn 68E:046133. doi:10.1103/PhysRevE.68.046133 Google Scholar
  8. Fraedrich K, Blender R (2003) Scaling of atmosphere and ocean temperature correlations in observations and climate models. Phys Rev Lett 90:108501. doi:10.1103/PhysRevLett.90.108501 CrossRefGoogle Scholar
  9. Vyushin DI, Kushner PJ (2009) Power-law and long-memory characteristics of the atmospheric general circulation. J Climate 22:2890–2904CrossRefGoogle Scholar
  10. Gil-Alana L (2005) Statistical modeling of the temperatures in the Northern Hemisphere using fractional integration techniques. J Climate 18:5357–5369CrossRefGoogle Scholar
  11. Hasselmann K (1976) Stochastic climate models. Part 1: theory. Tellus 28:473–485CrossRefGoogle Scholar
  12. IPCC (2007) Climate Change 2007: the physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  13. Király A, Bartos I, Janosi IM (2006) Correlation properties of daily temperature anomalies over land. Tellus A 58:593–600. doi:10.1111/j.1600-0870.2006.00195.x CrossRefGoogle Scholar
  14. Koutsoyiannis D, Efstratiadis A, Mamassis N, Christofides A (2008) On the credibility of climate predictions. Hydrol Sci J 53(4):671–684CrossRefGoogle Scholar
  15. Mann ME (2008) Smoothing of climate time series revisited. Geophys Res Lett 35:L16708. doi:10.1029/2008GL034716 CrossRefGoogle Scholar
  16. Mann ME, Lees J (1996) Robust estimation of background noise and signal detection in climatic time series. Clim Change 33:409–445CrossRefGoogle Scholar
  17. Mann ME, Rutherford S, Wahl E, Ammann C (2007) Robustness of proxy-based climate field reconstruction methods. J Geophys Res 112:D12109. doi:10.1029/2006JD008272 CrossRefGoogle Scholar
  18. Mann ME, Zhang Z, Hughes MK, Bradley RS, Miller SK, Rutherford S, Ni F (2008) Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia. Proc Natl Acad Sci 105:13252–13257CrossRefGoogle Scholar
  19. McGuffie K, Henderson-Sellers A (1997) Climate modeling primer, 2nd Edn. Wiley, ChichesterGoogle Scholar
  20. Mills T (2007) Time series modelling of two millenia of northern hemisphere temperatures: long memory or shifting trends? J R Stat Soc Ser A 170:83–94CrossRefGoogle Scholar
  21. Myhre G, Highwood EJ, Shine KP, Stordal F (1998) New estimates of radiative forcing due to well mixed greenhouse gases. Geophys Res Lett 25:2715–2718CrossRefGoogle Scholar
  22. North GR, Cahalan RF, Coakley JA (1981) Energy balance climate models. Rev Geophys 19:91–121CrossRefGoogle Scholar
  23. Rea W, Reale M, Brown J (2011) Long memory in temperature reconstruction. Clim Change (this issue)Google Scholar
  24. Smith R (1993) Long-range dependence and global warming. In: Barnett V, Turkman F (eds) Statistics for the environment. Wiley, Chichester, pp 141–161Google Scholar
  25. Vyushin DJ, Kushner PJ, Mayer J (2009) On the origins of temporal power-law behavior in the global atmospheric circulation. Geophys Res Lett 36:L14706. doi:10.1029/2009GL038771 CrossRefGoogle Scholar
  26. Wigley TML, Raper SCB (1990) Natural variability of the climate system and detection of the greenhouse effect. Nature 344:324–327. doi:10.1038/344324a0 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of Meteorology and Earth and Environmental Systems InstitutePennsylvania State UniversityUniversity ParkUSA

Personalised recommendations