Long-term persistence in the sea surface temperature fluctuations

Monetti, Roberto A.; Havlin, Shlomo; Bunde, Armin

doi:10.1016/s0378-4371(02)01662-x

Cited by 137 publications

(121 citation statements)

References 23 publications

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“…Thus, the net result drawn is that the difference between the scaling exponents in both sea and land contributions to the surface air temperature stems mainly from the sea surface temperature (SST), which exhibits stronger scaling in the Southern than in the Northern Hemisphere. This finding is in line with that of Monetti et al (2003), according to which a stronger persistence is observed over the oceans (Atlantic and Pacifc Oceans) than over the continents. Scaling in SST up to decades was also demonstrated in observations and coupled atmosphereocean models with complex and mixed-layer oceans by Fraedrich and Blender (2003) and others (e.g., Ausloos and Ivanova, 2001;Eichner et al, 2003).…”

Section: Dfa Exponent In the Time Series Of The Monthly Mean Lsat Anosupporting

confidence: 91%

On the scaling effect in global surface air temperature anomalies

2013

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The annual and the monthly mean values of the land-surface air temperature anomalies from 1880–2011, over both hemispheres, are used to investigate the existence of long-range correlations in their temporal evolution. The analytical tool employed is the detrended fluctuation analysis, which eliminates the noise of the non-stationarities that characterize the land-surface air temperature anomalies in both hemispheres. The reliability of the results obtained from this tool (e.g., power-law scaling) is investigated, especially for large scales, by using error bounds statistics, the autocorrelation function (e.g., rejection of its exponential decay) and the method of local slopes (e.g., their constancy in a sufficient range). The main finding is that deviations of one sign of the land-surface air temperature anomalies in both hemispheres are generally followed by deviations with the same sign at different time intervals. In other words, the land-surface air temperature anomalies exhibit persistent behaviour, i.e., deviations tend to keep the same sign. Taking into account our earlier study, according to which the land and sea surface temperature anomalies exhibit scaling behaviour in the Northern and Southern Hemisphere, we conclude that the difference between the scaling exponents mainly stems from the sea surface temperature, which exhibits a stronger memory in the Southern than in the Northern Hemisphere. Moreover, the variability of the scaling exponents of the annual mean values of the land-surface air temperature anomalies versus latitude shows an increasing trend from the low latitudes to polar regions, starting from the classical random walk (white noise) over the tropics. There is a gradual increase of the scaling exponent from low to high latitudes (which is stronger over the Southern Hemisphere)

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Section: Dfa Exponent In the Time Series Of The Monthly Mean Lsat Anosupporting

confidence: 91%

On the scaling effect in global surface air temperature anomalies

2013

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“…[2] In the past decade it has been recognized that multidecadal temperature records are long-term correlated [Koscielny- Bunde et al, 1996;Pelletier and Turcotte, 1997;Koscielny-Bunde et al, 1998;Talkner and Weber, 2000;Weber and Talkner, 2001;Eichner et al, 2003;Monetti et al, 2003;Király et al, 2006], with a correlation exponent g ' 0.7 for continental and coastline regions, and g in a broad range around 0.4 for marine regions.…”

Section: Introductionmentioning

confidence: 99%

Long‐term memory in 1000‐year simulated temperature records

Rybski

Bunde

Storch³

2008

J. Geophys. Res.

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[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,

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“…temperatures, relative humidity, wind, atmospheric general circulations, etc.) were found to be characterized by LTM (Koscielny- Bunde et al 1998;Eichner et al 2003;Monetti et al 2003;Kantelhardt et al 2006;Chen et al 2007;Rybski et al 2008;Vyushin and Kushner 2009;Feng et al 2009;Franzke 2010;Dangendorf et al 2014;Massah and Kantz 2016). As the name implies, LTM measures the connections of climate states observed at different time points.…”

Section: Introductionmentioning

confidence: 99%

On memory and non-memory parts of surface air temperatures over China: can they be simulated by decadal hindcast experiments in CMIP5?

Xiong

Yuan

et al. 2018

Clim Dyn

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It has been well recognized that, for most climatic records, their current states are influenced by both past conditions and current dynamical excitations. However, how to properly use this idea to improve the climate predictive skills, is still an open question. In this study, we evaluated the decadal hindcast experiments of 11 models (participating in phase 5 of the Coupled Model Intercomparison Project, CMIP5) in simulating the effects of past conditions (memory part, M(t)) and the current dynamical excitations (non-memory part, (t) ). Poor skills in simulating the memory part of surface air temperatures (SAT) are found in all the considered models. Over most regions of China, the CMIP5 models significantly overestimated the long-term memory (LTM) of SAT. While in the southwest, the LTM was significantly underestimated. After removing the biased memory part from the simulations using fractional integral statistical model (FISM), the remaining non-memory part, however, was found reasonably simulated in the multi-model means. On annual scale, there were high correlations between the simulated and the observed (t) over most regions of the country, and for most cases they had the same sign. These findings indicated that the current errors of dynamical models may be partly due to the unrealistic simulations of the impacts from the past. To improve predictive skills, a new strategy was thus suggested. As FISM is capable of extracting M(t) quantitatively, by combining FISM with dynamical models (which may produce reasonable estimations of (t) ), improved climate predictions with the effects of past conditions properly considered may become possible.

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Long-term persistence in the sea surface temperature fluctuations

Cited by 137 publications

References 23 publications

On the scaling effect in global surface air temperature anomalies

On the scaling effect in global surface air temperature anomalies

Long‐term memory in 1000‐year simulated temperature records

On memory and non-memory parts of surface air temperatures over China: can they be simulated by decadal hindcast experiments in CMIP5?

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