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A physical interpretation of the deterministic fractal-multifractal method as a realization of a generalized multiplicative cascade

  • Andrea Cortis
  • , Carlos E. Puente
  • , Huai Hsien Huang
  • , Mahesh L. Maskey
  • , Bellie Sivakumar
  • , Nelson Obregón

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In this study, we attempt to offer a solid physical basis for the deterministic fractal-multifractal (FM) approach in geophysics (Puente, Phys Let A 161:441-447, 1992; J Hydrol 187:65-80, 1996). We show how the geometric construction of derived measures, as Platonic projections of fractal interpolating functions transforming multinomial multifractal measures, naturally defines a non-trivial cascade process that may be interpreted as a particular realization of a random multiplicative cascade. In such a light, we argue that the FM approach is as "physical" as any other phenomenological approach based on Richardson's eddies splitting, which indeed lead to well-accepted models of the intermittencies of nature, as it happens, for instance, when rainfall is interpreted as a quasi-passive tracer in a turbulent flow. Although neither a fractal interpolating function nor the specific multipliers of a random multiplicative cascade can be measured physically, we show how a fractal transformation "cuts through" plausible scenarios to produce a suitable realization that reflects specific arrangements of energies (masses) as seen in nature. This explains why the FM approach properly captures the spectrum of singularities and other statistical features of given data sets. As the FM approach faithfully encodes data sets with compression ratios typically exceeding 100:1, such a property further enhances its "physical simplicity." We also provide a connection between the FM approach and advection-diffusion processes.

Original languageEnglish
Pages (from-to)1421-1429
Number of pages9
JournalStochastic Environmental Research and Risk Assessment
Volume28
Issue number6
DOIs
StatePublished - Jun 2014

Keywords

  • Fractal-multifractal approach
  • Fractals
  • Inverse problem
  • Multifractals
  • Particle swarm optimization
  • Rainfall in time

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