 |
| Titel |
Detection of intermittent events in atmospheric time series |
| VerfasserIn |
P. Paradisi, R. Cesari, L. Palatella, Daniele Contini, A. Donateo |
| Konferenz |
EGU General Assembly 2009
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250019801
|
|
|
|
|
|
| Zusammenfassung |
| The modeling approach in atmospheric sciences is based on the assumption that local fluxes
of mass, momentum, heat, etc... can be described as linear functions of the local
gradient of some intensive property (concentration, flow strain, temperature,...). This is
essentially associated with Gaussian statistics and short range (exponential) correlations.
However, the atmosphere is a complex dynamical system displaying a wide range
of spatial and temporal scales. A global description of the atmospheric dynamics
should include a great number of degrees of freedom, strongly interacting on several
temporal and spatial scales, thus generating long range (power-law) correlations and
non-Gaussian distribution of fluctuations (Lévy flights, Lévy walks, Continuous Time
Random Walks) [1]. This is typically associated with anomalous diffusion and scaling,
non-trivial memory features and correlation decays and, especially, with the emergence
of flux-gradient relationships that are non-linear and/or non-local in time and/or
space.
Actually, the local flux-gradient relationship is greatly preferred due to a more clear
physical meaning, allowing to perform direct comparisons with experimental data, and,
especially, to smaller computational costs in numerical models. In particular, the linearity of
this relationship allows to define a transport coefficient (e.g., turbulent diffusivity) and the
modeling effort is usually focused on this coefficient. However, the validity of the local (and
linear) flux-gradient model is strongly dependent on the range of spatial and temporal scales
represented by the model and, consequently, by the sub-grid processes included in the
flux-gradient relationship.
In this work, in order to check the validity of local and linear flux-gradient relationships,
an approach based on the concept of renewal critical events [2] is introduced. In fact, in
renewal theory [2], the dynamical origin of anomalous behaviour and non-local flux-gradient
relation is associated with the occurrence of critical events in the atmospheric dynamics. The
critical events are associated with transitions between meta-stable configurations.
Consequently, this approach could give some effort in the study of Extreme Events in
meteorology and climatology and in weather classification schemes. Then, the renewal
approach could give some effort in the modelling of non-Gaussian closures for turbulent
fluxes [3].
In the proposed approach the main features that need to be estimated are: (a) the
distribution of life-times of a given atmospheric meta-stable structure (Waiting Times
between two critical events); (b) the statistical distribution of fluctuations; (c) the presence of
memory in the time series. These features are related to the evaluation of memory content
and scaling from the time series. In order to analyze these features, in recent years
some novel statistical techniques have been developed. In particular, the analysis of
Diffusion Entropy [4] was shown to be a robust method for the determination of the
dynamical scaling. This property is related to the power-law behaviour of the life-time
statistics and to the memory properties of the time series. The analysis of Renewal
Aging [5], based on renewal theory [2], allows to estimate the content of memory
in a time series that is related to the amount of critical events in the time series
itself.
After a brief review of the statistical techniques (Diffusion Entropy and Renewal Aging),
an application to experimental atmospheric time series will be illustrated.
References
[1] Weiss G.H., Rubin R.J., Random Walks: theory and selected applications, Advances in
Chemical Physics,1983, 52, 363-505 (1983).
[2] D.R. Cox, Renewal Theory, Methuen, London (1962).
[3] P. Paradisi, R. Cesari, F. Mainardi, F. Tampieri: The fractional Fick’s law for non-local
transport processes, Physica A, 293, p. 130-142 (2001).
[4] P. Grigolini, L. Palatella, G. Raffaelli, Fractals 9 (2001) 439.
[5] P. Allegrini, F. Barbi, P. Grigolini, P. Paradisi: Renewal, modulation and superstatistics in
times series, Physical Review E 73 (4), 046136 (2006) . |
|
|
|
|
|
|