Long-Range Correlations of Global Sea Surface Temperature.

Scaling behaviors of the global monthly sea surface temperature (SST) derived from 1870-2009 average monthly data sets of Hadley Centre Sea Ice and SST (HadISST) are investigated employing detrended fluctuation analysis (DFA). The global SST fluctuations are found to be strong positively long-range...

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Bibliographic Details
Published in:PLOS ONE
Main Authors: Lei Jiang, Xia Zhao, Lu Wang
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2016
Subjects:
R
Q
Online Access:https://doi.org/10.1371/journal.pone.0153774
https://doaj.org/article/fe30c2778cd240f1beaef505dfa00fb4
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Summary:Scaling behaviors of the global monthly sea surface temperature (SST) derived from 1870-2009 average monthly data sets of Hadley Centre Sea Ice and SST (HadISST) are investigated employing detrended fluctuation analysis (DFA). The global SST fluctuations are found to be strong positively long-range correlated at all pertinent time-intervals. The value of scaling exponent is larger in the tropics than those in the intermediate latitudes of the northern and southern hemispheres. DFA leads to the scaling exponent α = 0.87 over the globe (60°S~60°N), northern hemisphere (0°N~60°N), and southern hemisphere (0°S~60°S), α = 0.84 over the intermediate latitude of southern hemisphere (30°S~60°S), α = 0.81 over the intermediate latitude of northern hemisphere (30°N~60°N) and α = 0.90 over the tropics 30°S~30°N [fluctuation F(s) ~ sα], which the fluctuations of monthly SST anomaly display long-term correlated behaviors. Furthermore, the larger the standard deviation is, the smaller long-range correlations (LRCs) of SST in the corresponding regions, especially in three distinct upwelling areas. After the standard deviation is taken into account, an index χ = α * σ is introduced to obtain the spatial distributions of χ. There exists an obvious change of global SST in central east and northern Pacific and the northwest Atlantic. This may be as a clue on predictability of climate and ocean variabilities.