scholarly journals Characterization of HILDCAA events using Recurrence Quantification Analysis

2016 ◽  
Author(s):  
Odim Mendes ◽  
Margarete Oliveira Domingues ◽  
Ezequiel Echer ◽  
Rajkumar Hajra ◽  
Varlei Everton Menconi
Keyword(s):  
Recurrence Quantification Analysis ◽  
Analysis Method ◽  
Dynamical Characteristics ◽  
Auroral Activity ◽  
Long Duration ◽  
Recurrence Quantification ◽  
Potential Applicability ◽  
Quantification Analysis

Abstract. Taking into account the primary mechanisms for transfer particles and energy into the magnetosphere, we have studied the dynamical characteristics of High-Intensity Long-Duration Continuous Auroral Activity (HILDCAA) events using a long-term geomagnetic database (1975–2012). The Recurrence Quantification Analysis method was applied on the auroral electrojet indices during HILDCAA events to characterize their dynamics. After, we compared those results with the ones obtained for geomagnetically quiet periods when there was no appreciable auroral activity. As result, the quantification allowed to find specific characteristics of these two distinct regimes. The HILDCAA events can be described as unique processes responsible for complex transfers of energy and particles from the solar wind plasmas into the magnetosphere-ionosphere system. We also suggest that the scenario of these processes is related to concurrent magnetospheric mechanisms (magnetic reconnection and viscous interaction). At last, we reinforce the potential applicability of the RQA method for characterization of various nonlinear geomagnetic processes related to these phenomenology.

scholarly journals Characterization of high-intensity, long-duration continuous auroral activity (HILDCAA) events using recurrence quantification analysis

2017 ◽  
Vol 24 (3) ◽  
pp. 407-417 ◽  
Author(s):  
Odim Mendes ◽  
Margarete Oliveira Domingues ◽  
Ezequiel Echer ◽  
Rajkumar Hajra ◽  
Varlei Everton Menconi
Keyword(s):  
Magnetic Reconnection ◽  
High Intensity ◽  
Recurrence Quantification Analysis ◽  
The Other ◽  
Geomagnetic Disturbances ◽  
Auroral Activity ◽  
Long Duration ◽  
Ae Index ◽  
Recurrence Quantification ◽  
Quantification Analysis

Abstract. Considering the magnetic reconnection and the viscous interaction as the fundamental mechanisms for transfer particles and energy into the magnetosphere, we study the dynamical characteristics of auroral electrojet (AE) index during high-intensity, long-duration continuous auroral activity (HILDCAA) events, using a long-term geomagnetic database (1975–2012), and other distinct interplanetary conditions (geomagnetically quiet intervals, co-rotating interaction regions (CIRs)/high-speed streams (HSSs) not followed by HILDCAAs, and events of AE comprised in global intense geomagnetic disturbances). It is worth noting that we also study active but non-HILDCAA intervals. Examining the geomagnetic AE index, we apply a dynamics analysis composed of the phase space, the recurrence plot (RP), and the recurrence quantification analysis (RQA) methods. As a result, the quantification finds two distinct clusterings of the dynamical behaviours occurring in the interplanetary medium: one regarding a geomagnetically quiet condition regime and the other regarding an interplanetary activity regime. Furthermore, the HILDCAAs seem unique events regarding a visible, intense manifestations of interplanetary Alfvénic waves; however, they are similar to the other kinds of conditions regarding a dynamical signature (based on RQA), because it is involved in the same complex mechanism of generating geomagnetic disturbances. Also, by characterizing the proper conditions of transitions from quiescent conditions to weaker geomagnetic disturbances inside the magnetosphere and ionosphere system, the RQA method indicates clearly the two fundamental dynamics (geomagnetically quiet intervals and HILDCAA events) to be evaluated with magneto-hydrodynamics simulations to understand better the critical processes related to energy and particle transfer into the magnetosphere–ionosphere system. Finally, with this work, we have also reinforced the potential applicability of the RQA method for characterizing nonlinear geomagnetic processes related to the magnetic reconnection and the viscous interaction affecting the magnetosphere.

scholarly journals Recurrence quantification analysis as a tool for characterization of molecular dynamics simulations

1999 ◽  
Vol 59 (1) ◽  
pp. 992-998 ◽  
Author(s):  
Cesare Manetti ◽  
Marc-Antoine Ceruso ◽  
Alessandro Giuliani ◽  
Charles L. Webber ◽  
Joseph P. Zbilut
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Recurrence Quantification Analysis ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Dynamics Simulations

Characterization of various structures in gas-solid fluidized beds by recurrence quantification analysis

Particuology ◽  
2013 ◽  
Vol 11 (6) ◽  
pp. 647-656 ◽  
Author(s):  
M. Tahmasebpour ◽  
R. Zarghami ◽  
R. Sotudeh-Gharebagh ◽  
N. Mostoufi
Keyword(s):  
Fluidized Beds ◽  
Recurrence Quantification Analysis ◽  
Recurrence Quantification ◽  
Quantification Analysis

RECURRENCE QUANTIFICATION ANALYSIS IN WATERSHED ECOSYSTEM RESEARCH

2011 ◽  
Vol 21 (04) ◽  
pp. 1113-1125 ◽  
Author(s):  
HOLGER LANGE
Keyword(s):  
Time Series ◽  
Recurrence Quantification Analysis ◽  
Data Driven ◽  
Model Data ◽  
Ecosystem Research ◽  
Data Comparison ◽  
Recurrence Quantification ◽  
Quantification Analysis ◽  
Term Monitoring

In ecosystem research, data-driven approaches to modeling are of major importance. Models are more often than not shaped by the spatiotemporal structure of the observations: an inverse modeling approach prevails. Here, I investigate the insights obtained from Recurrence Quantification Analysis of observed ecosystem time series. As a typical example of available long-term monitoring data, I choose time series from hydrology and hydrochemistry. Besides providing insights into the nonstationary and nonlinear dynamics of these variables, RQA also enables a detailed and temporally local model-data comparison.

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