Are there multiple scaling regimes in Holocene temperature records?

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Abstract

The concept of multiple scaling regimes in temperature time series is examined, with emphasis on the question whether or not a monoscaling model with one single scaling regime can be rejected from observation data from the Holocene. A model for internal variability with only one regime is simpler and allows more certain predictions on timescales of centuries when combined with existing knowledge of radiative forcing. Our analysis of spectra from stable isotope ratios from Greenland and Antarctica ice cores shows that a scale break around centennial timescales is evident for the last glacial period, but not for the Holocene. Spectra from a number of late Holocene multiproxy temperature reconstructions, and one from the entire Holocene, have also been analysed, without identifying a significant scale break. Our results indicate that a single-regime scaling climate noise, with some non-scaling fluctuations on a millennial timescale superposed, cannot be rejected as a null model for the Holocene climate. The scale break observed from the glacial time ice-core records is likely caused by the influence of Dansgaard–Oeschger events and teleconnections to the Southern Hemisphere on centennial timescales. From our analysis we conclude that the two-regime model is not sufficiently justified for the Holocene to be used for temperature prediction on centennial timescales.

Figures

  • Figure 1. (a) Structure function estimates (empirical moments) Ŝq (1t)= (N −1t) −1 N−1t∑ i=1 |T (ti +1t)− T (ti )| q for the GMST (Had-
  • Figure 2. (a) The instrumental global mean surface temperature (GMST) 1850–2010 (black). A second-order polynomial least-squares fit to the GMST record (blue). (b) Black curves are the Haar fluctuation function of the GMST; the upper curve is multiplied by 10. The red curves are Haar fluctuation functions of 20 realizations of a model comprised of a linear combination of an fGn with β = 0.8 and an fBm with β = 1.6. The blue curves are the same but of a model comprised of a linear combination of an fGn with β = 0.8 and the second-order polynomial trend.
  • Figure 3. (a) The Haar fluctuation of 20 realizations of an fGn with β = 0.8. (b) The Haar fluctuation of one realization in the ensemble. (c) The Haar wavelet variance of the same 20 realizations as in (a). (d) The Haar wavelet variance of the same realization as in (b).
  • Figure 4. (a) The power spectral density of an ensemble mean of synthetic processes comprised of a superposition of a white noise (β = 0.2) and a Brownian motion (β = 1.8). (b) DFA fluctuation function F2(τ ) for ensemble mean of the same process. The dashed lines are the limiting slopes at short/long scales. Their intersection is used to define a transition frequency (vertical dashed line) between the two scaling regimes in (a) and a transition scale for the DFA in (b).
  • Table 1. Results using approach 1 for multiproxy temperature reconstructions.
  • Figure 5. (a) The Moberg et al. (2005) reconstructed temperature for the Northern Hemisphere. (b) Estimated values of β1 and β2. (c) 95 % confidence range for periodograms in the Monte Carlo study. (d) 95 % confidence range for estimates of β2.
  • Table 2. Results using approach 2 for multiproxy temperature reconstructions.
  • Figure 6. Differences in β2 and β1 for a Monte Carlo ensemble with 2000 members of synthetic LRM processes with β = 0.7. The black arrows indicate the differences from the multiproxy reconstructions.

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CITATION STYLE

APA

Nilsen, T., Rypdal, K., & Fredriksen, H. B. (2016). Are there multiple scaling regimes in Holocene temperature records? Earth System Dynamics, 7(2), 419–439. https://doi.org/10.5194/esd-7-419-2016

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