Long‐term memory in 1000‐year simulated temperature records

Abstract

[1] We study the appearance of long-term persistence in temperature records, obtained from the global coupled general circulation model ECHO-G for two runs, using detrended fluctuation analysis. The first run is a historical simulation for the years 1000-1990 (with greenhouse gas, solar, and volcanic forcing), while the second run is a 1000-year ''control run'' with constant external forcings. We consider daily data of all grid points as well as their biannual averages in order to suppress 2-year oscillations appearing in the model records for some sites near the equator. Our results substantially confirm earlier studies of (considerably shorter) instrumental data and extend their results from decades to centuries. In the case of the historical simulation we find that most continental sites have correlation exponents g between 0.8 and 0.6. For the ocean sites the long-term correlations seem to vanish at the equator and become nonstationary at the Arctic and Antarctic circles. In the control run the long-term correlations are less pronounced. Compared with the historical run, the correlation exponents are increased, and show a more pronounced latitude dependence, visible also at continental sites. When analyzing biannual averages, we find stronger long-term correlations in the historical run at continental sites and a less pronounced latitude dependence. In all cases, the exponent g does not depend on the continentality of the sites.Citation: Rybski, D., A. Bunde, and H. von Storch (2008), Long-term memory in 1000-year simulated temperature records,

On the scaling effect in global surface air temperature anomalies

“…4 shows the DFA results of one of the random samplings with a = 0.51 and standard deviation 0.03 for each geographical area. In other words, we find that the DFA exponent that characterizes the fluctuations in the shuffled data is near 0.5, thus indicating that the Joseph phenomenon is the main effect (Mandelbrot and Wallis, 1968;Rybski et al, 2008). On the other hand, the estimated DFA exponents depicted in Fig.…”

“…Recently, six reconstructed records of the Northern Hemisphere (NH) temperatures, analysed by Rybski et al (2006), revealed long-term persistence. Due to the long-term persistent correlations, the mean temperature variations σ (m, L) between L years (moving averages over m years) were substantially larger than for uncorrelated or short-term correlated data.…”

Applicatıon of detrended fluctuation analysis to temperature data from Turkey

“…In the literature, there exist many studies that investigate the long-term correlation of temperature data. Some of these studies (Koscielny- Bunde et al, 1998;Bunde et al, 2001;Govindan et al, 2003) claim that the scaling exponent is universal for the temperature data while the others Kurnaz, 2004;Pattanyús-Ábrahám et al, 2004;Kiràly and Jánosi, 2005;Bartos and Jánosi, 2006;Kiràly et al, 2006;Rybski et al, 2008) claim the opposite. Apart from temperature data, the DFA analysis has also been applied to some meteorological and climatological variables such as wind speed (Govindan and Kantz, 2004;Kavasseri and Nagarajan, 2004), relative humidity (Chen et al, 2007), cloud breaking (Ivanova and Ausloos, 1999) and NAO (North Atlantic Oscillation) index (Caldeira et al, 2007).…”

What Is Climate?

“…GCM control runs (with fixed boundary conditions, i.e., with fixed atmospheric composition, solar output, and orbital parameters and without volcanism) are found to generate a macroweather regime with H ≈ −0.4 out to the extreme lowfrequency limit of the models (several millennia [ Blender et al ., 2006;Rybski et al ., 2008 ;). Since GCMs are essentially weather models with extra couplings, the name "macro weather" is appropriate.…”