Abstract

Mediterranean is thought to be sensitive to global climate change, but its future interdecadal variability is uncertain for many climate models. A study was made of the variability of the winter temperature over the Mediterranean Sub-regional Area (MSA), employing a reconstructed temperature series covering the period 1698 to 2010. This paper describes the transformed winter temperature data performed via Empirical Mode Decomposition for the purposes of noise reduction and statistical modeling. This emerging approach is discussed to account for the internal dependence structure of natural climate variability.

Highlights

  • Su i dodici del ciel segni divisi Regola il mondo, e le stagioni alterna

  • Besides an incomplete knowledge or understanding of a particular process, a central problem are the unpredictability, partly inconsistent with the observed warming during the industrial period (Knutti et al, 2008). Another restraint of the Global Circulation Models (GCMs) is that it is unlike that this mixture of funtional relationships and alternative parameterization may be used by a large community of users and for decision-making, being limited to special interest and minority groups of scientists needing the low-flexibility this makes available

  • Concluding remarks In the past decades, there has been an increasing interest for the long-term climate forecasting. Many of these studies have not adequately examined key issues, and relied on research processes that slowed the exchange of information among physical, biological and social scientists (Moss et al, 2010)

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Summary

Introduction

Su i dodici del ciel segni divisi Regola il mondo, e le stagioni alterna. Besides an incomplete knowledge or understanding of a particular process (epistemic uncertainty), a central problem are the unpredictability, partly inconsistent with the observed warming during the industrial period (Knutti et al, 2008). Another restraint of the GCMs is that it is unlike that this mixture of funtional relationships and alternative parameterization may be used by a large community of users and for decision-making, being limited to special interest and minority groups of scientists needing the low-flexibility this makes available

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