• Antonio NavarraEmail author
  • Valeria Simoncini


Climatology and meteorology has been basically a descriptive science without the means to perform quantitative experiments under controlled conditions. In fact, until the second half of the twentieth century, the border between climatology and geography was often blurred and the two disciplines were confused one with the other.The situation changed when the solution of the evolution equations for the climate system became possible using numerical methods. The development of numerical models allowed the application of standard scientific verification machinery for testing hypotheses, but crucial to the success of the strategy is that the model must be a good representation of the real climate system of the Earth. Assessing the quality of models regarding their capability to reproduce the climate became a cornerstone in the scientific progress of climatology. Tighter and tighter standards were required for the model simulations in comparison with the real characteristics of climate. Models were required to reproduce not only the mean properties of climate, but also its variability. In the last decades of the XX century the amount of data available was becoming very large and strong evidence of remote spatial relations between climate variability in geographically diverse regions were emerging. Quantitative techniques were developed to explore the climate variability and its relations among different geographical locations. Methods were borrowed from descriptive statistics, where they were developed to analyze variance of related observations-variable pairs, or to identify unknown relations among variables.


  1. von Storch H, Zwiers FW (1999) Statistical analysis in climate research. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  2. Wilks S Daniel (2005) Statistical methods in the atmospheric sciences, 2nd edn. International Geophysics series, Academic Press, OxfordGoogle Scholar
  3. Jolliffe IT (2002) Principal component analysis, 2nd edn. Springer Series in Statistics, Springer, New YorkGoogle Scholar
  4. Preisendorfer RW (1988) Principal component analysis in meteorology and oceanography, vol 17, Development in atmospheric sciences. Elsevier, AmsterdamGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Ist. Nazionale di Geofisica e VulcanologiaBolognaItaly
  2. 2.Dip. to MatematicaUniversità di BolognaBolognaItaly

Personalised recommendations