1 / 26

Complexity of the Magnetosphere: Dynamical and Statistical Features

Earth's Magnetosphere . Multiscale Magnetosphere. Strongly driven magnetosphere: 81 intense storms ( 2001). . Conditional Probability Distribution Functions: . . . Multiscale phenomenon . Veeramani et al., 2007,Sharma et al., Ann. Geo., 2008. Modeling Dynamics in Multiscale Systems. Global behavior Data-derived modeling of dynamics - low dimensional (mean-field) - predictable dynamics (weighted mean field)Multiscale phenomenon Statistical properties.

jaden
Download Presentation

Complexity of the Magnetosphere: Dynamical and Statistical Features

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. Complexity of the Magnetosphere: Dynamical and Statistical Features Surja Sharma University of Maryland, College Park

    2. Earths Magnetosphere

    3. Multiscale Magnetosphere

    5. Conditional Probability Distribution Functions:

    6. Modeling Dynamics in Multiscale Systems

    13. Spatio-Temporal Dynamics: Mutual Information Function

    14. Average Mutual Information

    15. Average Mutual Information (6-hr averages)

    16. Long-range Correlations Measure of inherent behavior Characterizes underlying statistical processes Clustering of events Extreme events Nonequilibrium systems

    17. Detrended Fluctuation Analysis (DFA) Detection of long-range correlations in time series data Based on auto-correlation function C(s) Removes effects due to non-stationarities Yields a scaling exponent: F(s) ~ s-a a = 0.5 - uncorrelated (diffusion) > 0.5 - long-range correlation

    18. Auto-correlation Function of AL index

    19. Mutual Information Function AL index

    20. DFA analysis of AL index

    21. DFA Analysis of Solar Wind Bz

    22. DFA Analysis Return Intervals

    23. Recurrence Time Distribution

    24. Recurrence Time Distribution

    25. Magnetosphere : 3D Picture

    27. Summary Three approaches: Nonlinear dynamics (Data-derived modelng) Statistical Physics (Non-equilibrium?) Simulations (MHD on global scale and EMHD on shortest scales) Improved data-derived modeling: Forecasting global behavior Mean-field and weighted mean-field approach Spatio-temporal modeling: Mutual information functions Multiscale nature of the magnetosphere Unpredictable component Conditional (Bayesian) probabilities Long-term Correlations DFA - Uncorrelated behavior beyond 5 hrs

More Related