Deterministic chaos versus stochasticity in analysis and modelling of rainfall structure

Koutsoyiannis, D; Pachakis, D

dc.contributor.author	Koutsoyiannis, D	en
dc.contributor.author	Pachakis, D	en
dc.date.accessioned	2014-03-01T02:54:23Z
dc.date.available	2014-03-01T02:54:23Z
dc.date.issued	1995	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36849
dc.subject	Τime series analysis	en
dc.subject.classification	Rain and rainfall	en
dc.title	Deterministic chaos versus stochasticity in analysis and modelling of rainfall structure	en
heal.type	conferenceItem	en
heal.publicationDate	1995	en
heal.abstract	In recent years, new methods for time series analysis, devised for description and characterization of chaotic behavior, yielded some fascinating results. Among them, the fact that deterministic processes may sometimes be statistically indistinguishable from random noise. Currently, discussion is going on about how to characterize a process and how to recognize whether it is stochastic or deterministic. A popular method for revealing the underlying dynamics from a time series, is the phase-space reconstruction via time delay embedding. This method is used here as a means to detect possible low-dimensional determinism in a historical rainfall time series and to compare the historical series synthetic series generated by a stochastic model. Specifically, the synthetic series has been produced using the scaling model of storm hyetograph combined with a stochastic process describing storm arrivals, durations and total depths. The comparison aims at revealing potential essential differences in the structure of the historical and synthetic data sets.	en
heal.journalName	5th International Conference on Precipitation	en