scholarly journals Self-Organized Criticality of Rainfall in Central China

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Zhiliang Wang ◽  
Chunyan Huang

Rainfall is a complexity dynamics process. In this paper, our objective is to find the evidence of self-organized criticality (SOC) for rain datasets in China by employing the theory and method of SOC. For this reason, we analyzed the long-term rain records of five meteorological stations in Henan, a central province of China. Three concepts, that is, rain duration, drought duration, accumulated rain amount, are proposed to characterize these rain events processes. We investigate their dynamics property by using scale invariant and found that the long-term rain processes in central China indeed exhibit the feature of self-organized criticality. The proposed theory and method may be suitable to analyze other datasets from different climate zones in China.

2006 ◽  
Vol 13 (4) ◽  
pp. 409-412 ◽  
Author(s):  
Y. Ida ◽  
M. Hayakawa

Abstract. An extremely large earthquake (with magnitude of 8.2) happened on 8 August 1993 near the Guam island, and ultra-low-frequency (ULF) (frequency less than 1 Hz) electromagnetic fields were measured by 3-axis induction magnetometers at an observing station (with the epicentral distance of 65 km) with sampling frequency of 1 Hz. In order to study electromagnetic signature of prefracture criticality, we have undertaken the fractal (mono-fractal) analysis by means of the Higuchi's method for the ULF data during the 1993 Guam earthquake. Then, it is found that the fractal dimension exhibits five maxima 99, 75, 52, 21, and 9–4 days before the earthquake main shock, which suggests the ULF electromagnetic signature of nonlinear evolution (in the sense of self-organized criticality) taking place in the lithosphere just before the 1993 large Guam earthquake. That is, there take place step-like changes in the lithosphere during the long-term of the order of several months before the main shock.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Shi Kai ◽  
Liu Chun-Qiong ◽  
Li Si-Chuan

We analyze long-term time series of daily average PM10 concentrations in Chengdu city. Detrended fluctuation analysis of the time series shows long range correlation at one-year temporal scale. Spectral analysis of the time series indicates 1/f noise behavior. The probability distribution functions of PM10 concentrations fluctuation have a scale-invariant structure. Why do the complex structures of PM10 concentrations evolution exhibit scale-invariant? We consider that these complex dynamical characteristics can be recognized as the footprint of self-organized criticality (SOC). Based on the theory of self-organized criticality, a simplified sandpile model for PM10 pollution with a nondimensional formalism is put forward. Our model can give a good prediction of scale-invariant in PM10 evolution. A qualitative explanation of the complex dynamics observed in PM10 evolution is suggested. The work supports the proposal that PM10 evolution acts as a SOC process on calm weather. New theory suggests one way to understand the origin of complex dynamical characteristics in PM10 pollution.


Fractals ◽  
1993 ◽  
Vol 01 (03) ◽  
pp. 650-662 ◽  
Author(s):  
L. PIETRONERO

Irreversible fractal growth models like DLA and DBM have confronted us with theoretical problems of a new type that cannot be described in terms of the standard concepts like field theory and the renormalization group. The Fixed Scale Transformation is a theoretical scheme of a new type that is able to treat these problems in a reasonably systematic way. The idea is to focus on the dynamics at a given scale and to compute accurately the correlations at this scale by suitable lattice path integrals. The use of scale invariant growth rules then allows the generalization of these correlations to coarse-grained cells of any size and therefore to obtain the fractal dimension. We summarize the present status of the FST approach by focusing on the most recent results about the scale invariant dynamics of DLA/DBM. The possible extensions to other problems like the sand pile model (self-organized-criticality) and simplified models of turbulence will also be considered.


2011 ◽  
Vol 22 (05) ◽  
pp. 483-493 ◽  
Author(s):  
MIN LIN ◽  
GANG WANG

A modified Olami–Feder–Christensen (OFC) earthquake model on scale-free networks with assortative mixing is introduced. In this model, the distributions of avalanche sizes and areas display power-law behaviors. It is found that the period distribution of avalanches displays a scale-invariant law with the increment of range parameter d. More importantly, different assortative topologies lead to different dynamical behaviors, such as the distribution of avalanche size, the stress evolution process, and period distribution.


2002 ◽  
Vol 7 (2) ◽  
pp. 123-137
Author(s):  
R. Šiugždaitė ◽  
S. Norvaišas

In the article we propose new decision support tools for region energetics development. The method is based on analysing complex system’s state and comparing it with the self-organized criticality (SOC) class that characterize the long-term system’s stability. We start with urban system modelling using cellular automata (CA) with the best fit to real data and then we raise hypothesis about adequacy of urban and energetics system elements distribution. The urban data analysis shows that it is in SOC state for wide rank of countries. We calculate required parameters for energetics system, which are used in decision making for the system long-term development.


2021 ◽  
Vol 9 ◽  
Author(s):  
Dietmar Plenz ◽  
Tiago L. Ribeiro ◽  
Stephanie R. Miller ◽  
Patrick A. Kells ◽  
Ali Vakili ◽  
...  

Self-organized criticality (SOC) refers to the ability of complex systems to evolve toward a second-order phase transition at which interactions between system components lead to scale-invariant events that are beneficial for system performance. For the last two decades, considerable experimental evidence has accumulated that the mammalian cortex with its diversity in cell types, interconnectivity, and plasticity might exhibit SOC. Here, we review the experimental findings of isolated, layered cortex preparations to self-organize toward four dynamical motifs presently identified in the intact cortex in vivo: up-states, oscillations, neuronal avalanches, and coherence potentials. During up-states, the synchronization observed for nested theta/gamma oscillations embeds scale-invariant neuronal avalanches, which can be identified by robust power law scaling in avalanche sizes with a slope of −3/2 and a critical branching parameter of 1. This precise dynamical coordination, tracked in the negative transients of the local field potential (nLFP) and spiking activity of pyramidal neurons using two-photon imaging, emerges autonomously in superficial layers of organotypic cortex cultures and acute cortex slices, is homeostatically regulated, exhibits separation of time scales, and reveals unique size vs. quiet time dependencies. A subclass of avalanches, the coherence potentials, exhibits precise maintenance of the time course in propagated local synchrony. Avalanches emerge in superficial layers of the cortex under conditions of strong external drive. The balance of excitation and inhibition (E/I), as well as neuromodulators such as dopamine, establishes powerful control parameters for avalanche dynamics. This rich dynamical repertoire is not observed in dissociated cortex cultures, which lack the differentiation into cortical layers and exhibit a dynamical phenotype expected for a first-order phase transition. The precise interactions between up-states, nested oscillations, and avalanches in superficial layers of the cortex provide compelling evidence for SOC in the brain.


2018 ◽  
Vol 856 ◽  
pp. 228-256 ◽  
Author(s):  
Hesam Salehipour ◽  
W. R. Peltier ◽  
C. P. Caulfield

Motivated by the importance of stratified shear flows in geophysical and environmental circumstances, we characterize their energetics, mixing and spectral behaviour through a series of direct numerical simulations of turbulence generated by Holmboe wave instability (HWI) under various initial conditions. We focus on circumstances where the stratification is sufficiently ‘strong’ so that HWI is the dominant primary instability of the flow. Our numerical findings demonstrate the emergence of self-organized criticality (SOC) that is manifest as an adjustment of an appropriately defined gradient Richardson number, $Ri_{g}$, associated with the horizontally averaged mean flow, in such a way that it is continuously attracted towards a critical value of $Ri_{g}\sim 1/4$. This self-organization occurs through a continuously reinforced localization of the ‘scouring’ motions (i.e. ‘avalanches’) that are characteristic of the turbulence induced by the breakdown of Holmboe wave instabilities and are developed on the upper and lower flanks of the sharply localized density interface, embedded within a much more diffuse shear layer. These localized ‘avalanches’ are also found to exhibit the expected scale-invariant characteristics. From an energetics perspective, the emergence of SOC is expressed in the form of a long-lived turbulent flow that remains in a ‘quasi-equilibrium’ state for an extended period of time. Most importantly, the irreversible mixing that results from such self-organized behaviour appears to be characterized generically by a universal cumulative turbulent flux coefficient of $\unicode[STIX]{x1D6E4}_{c}\sim 0.2$ only for turbulent flows engendered by Holmboe wave instability. The existence of this self-organized critical state corroborates the original physical arguments associated with self-regulation of stratified turbulent flows as involving a ‘kind of equilibrium’ as described by Turner (1973, Buoyancy Effects in Fluids, Cambridge University Press).


2012 ◽  
Vol 69 (12) ◽  
pp. 3449-3462 ◽  
Author(s):  
Jun-Ichi Yano ◽  
Changhai Liu ◽  
Mitchell W. Moncrieff

Abstract Atmospheric convection has a tendency to organize on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden–Julian oscillation. The present paper examines two major competing mechanisms of self-organization in a cloud-resolving model (CRM) simulation from a phenomenological thermodynamic point of view. The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with increasing column-integrated water, reminiscent of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as CRM experiments give mixed results. In this study, a CRM experiment over a large-scale domain with a constant sea surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms is further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes.


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