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A direct scaling analysis for the sea level rise

  • Giuseppe Roberto Tomasicchio
  • Letizia Lusito
  • Felice D’AlessandroEmail author
  • Ferdinando Frega
  • Antonio Francone
  • Samuele De Bartolo
Original paper

Abstract

The estimation of long-term sea level variability is of primary importance for a climate change assessment. Despite the value of the subject, no scientific consensus has yet been reached on the existing acceleration in observed values. The existence of this acceleration is crucial for coastal protection planning purposes. The absence of the acceleration would enhance the debate on the general validity of current future projections. Methodologically, the evaluation of the acceleration is a controversial and still open discussion, reported in a number of review articles, which illustrate the state-of-art in the field of sea level research. In the present paper, the well-proven direct scaling analysis approach is proposed in order to describe the long-term sea level variability at 12 worldwide-selected tide gauge stations. For each of the stations, it has been shown that the long-term sea level variability exhibits a trimodal scaling behaviour, which can be modelled by a power law with three different pairs of shape and scale parameters. Compared to alternative methods in literature, which take into account multiple correlated factors, this simple method allows to reduce the uncertainties on the sea level rise parameters estimation.

Keywords

Direct scaling analysis Sea level variability Tide gauge stations Projected mean sea level increments 

Notes

Acknowledgements

This work was funded by the Apulia Region through the Regional Cluster Projects ‘Start’ and ‘Eco-Smart Breakwater’. Moreover, the authors thank Prof. G. Salvadori for the fruitful discussions.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Giuseppe Roberto Tomasicchio
    • 1
  • Letizia Lusito
    • 1
  • Felice D’Alessandro
    • 1
    Email author
  • Ferdinando Frega
    • 2
  • Antonio Francone
    • 2
  • Samuele De Bartolo
    • 1
  1. 1.Department of Engineering for InnovationUniversity of SalentoLecceItaly
  2. 2.Department of Civil EngineeringUniversity of CalabriaArcavacata di RendeItaly

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