Evidence for inherent nonlinearity in temporal rainfall

Stéphane G. Roux, V. Venugopal, Kurt Fienberg, Alain Arneodo, Efi Foufoula-Georgiou

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


We examine the underlying structure of high resolution temporal rainfall by comparing the observed series with surrogate series generated by a invertible nonlinear transformation of a linear process. We document that the scaling properties and long range magnitude correlations of high resolution temporal rainfall series are inconsistent with an inherently linear model, but are consistent with the nonlinear structure of a multiplicative cascade model. This is in contrast to current studies that have reported for spatial rainfall a lack of evidence for a nonlinear underlying structure. The proposed analysis methodologies, which consider two-point correlation statistics and also do not rely on higher order statistical moments, are shown to provide increased discriminatory power as compared to standard moment-based analysis.

Original languageEnglish (US)
Pages (from-to)41-48
Number of pages8
JournalAdvances in Water Resources
Issue number1
StatePublished - Jan 1 2009


  • Multifractals
  • Multiscaling
  • Nonlinearity
  • Rainfall
  • Surrogates
  • Wavelets

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