Long-term persistence in the sea surface temperature fluctuations

We study the temporal correlations in the sea surface temperature (SST) fluctuations around the seasonal mean values in the Atlantic and Pacific Oceans. We apply a method that systematically overcome possible trends in the data. We find that the SST persistence, characterized by the correlation C(s) of temperature fluctuations separated by a time period s, displays two different regimes. In the short-time regime which extends up to roughly 10 months, the temperature fluctuations display a non-stationary behavior for both oceans, while in the asymptotic regime it becomes stationary. The long-term correlations decay as C(s)∼s−γ with γ∼0.4 for both oceans which is different from γ∼0.7 found for atmospheric land temperature.

[1]  Richard W. Reynolds,et al.  An Improved Real-Time Global Sea Surface Temperature Analysis , 1993 .

[2]  Shlomo Havlin,et al.  Analysis of daily temperature fluctuations , 1996 .

[3]  Shlomo Havlin,et al.  Global climate models violate scaling of the observed atmospheric variability. , 2002, Physical review letters.

[4]  Talkner,et al.  Power spectrum and detrended fluctuation analysis: application to daily temperatures , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[5]  Jon D. Pelletier,et al.  Long-range persistence in climatological and hydrological time series: analysis, modeling and application to drought hazard assessment , 1997 .

[6]  H. Stanley,et al.  Effect of trends on detrended fluctuation analysis. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Eli Tziperman,et al.  El Ni�o Chaos: Overlapping of Resonances Between the Seasonal Cycle and the Pacific Ocean-Atmosphere Oscillator , 1994, Science.

[8]  Mark A. Cane,et al.  Experimental forecasts of El Niño , 1986, Nature.

[9]  J. Hurrell.  Decadal Trends in the North Atlantic Oscillation: Regional Temperatures and Precipitation , 1995, Science.

[10]  Thomas M. Smith,et al.  Improved Global Sea Surface Temperature Analyses Using Optimum Interpolation , 1994 .

[11]  David Parker,et al.  Interdecadal changes of surface temperature since the late nineteenth century , 1994 .

[12]  Shlomo Havlin,et al.  Long-range correlations and trends in global climate models: Comparison with real data , 2001 .

[13]  G. Vojta,et al.  Fractal Concepts in Surface Growth , 1996 .

[14]  S. Havlin,et al.  Indication of a Universal Persistence Law Governing Atmospheric Variability , 1998 .

[15]  Balaji Rajagopalan,et al.  Analyses of global sea surface temperature 1856–1991 , 1998 .

[16]  Bruce J. West,et al.  Lévy dynamics of enhanced diffusion: Application to turbulence. , 1987, Physical review letters.

[17]  Roberto A. Monetti,et al.  Scaling analysis of trends using DFA , 2001 .

[18]  Time Dependent Correlations In Marine Stratocumulus Cloud Base Height Records , 2001, cond-mat/0111202.

[19]  Jon D. Pelletier,et al.  Analysis and Modeling of the Natural Variability of Climate , 1997 .

[20]  J. Wallace,et al.  The Arctic oscillation signature in the wintertime geopotential height and temperature fields , 1998 .

[21]  Keith W. Dixon,et al.  Anthropogenic Warming of Earth's Climate System , 2001, Science.

[22]  S. Havlin,et al.  Detecting long-range correlations with detrended fluctuation analysis , 2001, cond-mat/0102214.

[23]  C. Peng,et al.  Mosaic organization of DNA nucleotides. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.