Long-range dependence in North Atlantic sea level

• Type: Article in International Scientific Journal
• Date: 2006

Authors

Barbosa, SM (Author) Other; Fernandes, MJ (Author) FCUP; Silva, ME (Author) FCUP

Journal

Title: Physica A: Statistical Mechanics and its Applications

Vol. 371

Pages: 725-731

ISSN: 0378-4371

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 24 Citations

Scopus - 25 Citations

Scientific classification

FOS: Natural sciences > Physical sciences

Other information

Authenticus ID: P-004-G3F

DOI: 10.1016/j.physa.2006.03.046

Abstract (EN): Sea level is an important parameter in climate and oceanographic applications. In this work the scaling behavior of sea level is analyzed from time series of sea level observations. The wavelet domain is particularly attractive for the identification of scaling behavior in an observed time series. The wavelet spectrum from a scale-by-scale wavelet analysis of variance reproduces in the wavelet domain the power laws underlying a scaling process, allowing the estimation of the scaling exponent from the slope of the wavelet spectrum. Here the scaling exponent is estimated in the wavelet domain for time series of sea level observations in the North Atlantic: at coastal sites from tide gauges, covering 50 years of monthly measurements, and in the open ocean from satellite altimetry, covering 12 years of satellite measurements at 10 days intervals. Both tide gauge and altimetry time series exhibit scaling behavior. Furthermore, the degree of stochastic persistence is spatially coherent and distinct at the coast and in the open ocean. Near the coast, the stochastic structure of the sea level observations is characterized by long-range dependence with a moderate degree of persistence. Larger values of the scaling exponent, consistent with weaker persistence, are concentrated in the northern Atlantic. At mid-latitudes the stochastic dependence of sea level observations is characterized by strong persistence in the form of strong long-range and 1/f dependence.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7