Self-organized criticality and predictability in atmospheric flows : the quantum world of clouds and rain
This book presents a new concept of General Systems Theory and its application to atmospheric physics. It reveals that energy input into the atmospheric eddy continuum, whether natural or manmade, results in enhancement of fluctuations of all scales, manifested immediately in the intensification of...
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| Main Author: | |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
2017.
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| Series: | Springer atmospheric sciences.
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| Subjects: | |
| ISBN: | 9783319545462 9783319545455 |
| Physical Description: | 1 online resource (xix, 139 pages) : illustrations |
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Table of contents
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| 024 | 7 | |a 10.1007/978-3-319-54546-2 |2 doi | |
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| 100 | 1 | |a Selvam, A. M., |e author. | |
| 245 | 1 | 0 | |a Self-organized criticality and predictability in atmospheric flows : |b the quantum world of clouds and rain / |c Amujuri Mary Selvam. |
| 264 | 1 | |a Cham, Switzerland : |b Springer, |c 2017. | |
| 300 | |a 1 online resource (xix, 139 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a počítač |b c |2 rdamedia | ||
| 338 | |a online zdroj |b cr |2 rdacarrier | ||
| 490 | 1 | |a Springer atmospheric sciences, |x 2194-5217 | |
| 505 | 0 | |a Preface; References; About the Book; Contents; About the Author; 1 Nonlinear Dynamics and Chaos: Applications in Meteorology and Atmospheric Physics; Abstract; 1.1 Introduction; 1.2 New Science of Nonlinear Dynamics and Chaos; 1.2.1 Dynamical Systems and Fractal Space-Time Fluctuations; 1.2.2 Fractals in Pure Mathematics; 1.2.3 Fractal Fluctuations and Statistical Analysis; 1.2.4 Golden Mean and Self-similar, Fractal Geometrical Structures in Nature; 1.2.5 Fibonacci Sequence and Self-similar Structures; 1.2.6 Fivefold and Spiral Symmetry Associated with Fibonacci Sequence. | |
| 505 | 8 | |a 1.2.7 Quasicrystalline Structure: The Quasiperiodic Penrose Tiling Pattern1.2.8 Fractal Time Signals, and Power Laws; 1.2.9 Self-organized Criticality: Space-Time Fractals; 1.2.10 Turbulent (Chaotic) Fluctuations and Self-similar Structure Formation; 1.2.11 Self-similarity: A Signature of Identical Iterative Growth Process; 1.3 Fractals and Self-organized Criticality in Meteorology and Atmospheric Physics; 1.3.1 Observed Structure of Atmospheric Flows and Signatures of Deterministic Chaos; 1.3.2 Limitations of Conventional Atmospheric Boundary Layer (ABL) Models. | |
| 505 | 8 | |a 1.3.3 Traditional Numerical Weather Prediction, Deterministic Chaos and Predictability1.3.4 Current Techniques in Numerical Weather Prediction (NWP): Major Drawbacks; 1.4 Applications of Nonlinear Dynamics and Chaos for Weather Prediction: Current Status; 1.4.1 Space-Time Cascade Model for Fractal Fluctuations in Atmospheric Flows; 1.4.2 General Systems Theory for Fractal Space-Time Fluctuations in Atmospheric Flows; 1.5 Conclusions; References; 2 Noise or Random Fluctuations in Physical Systems: A Review; Abstract; 2.1 Introduction; 2.2 Statistical Methods for Data Analysis. | |
| 505 | 8 | |a 2.3 Statistical Normal Distribution2.4 Power Laws-History; 2.5 Power-Law Distributions and Complex Systems; 2.6 Power Laws, Scale Invariance and Self-similarity; 2.7 Power Laws, Self-similarity, and Fractals; 2.8 Power Laws, 1/f Noise, and Long-Term Memory; 2.9 Power Laws, Phase Transitions, and Critical Phenomena; 2.10 Power Laws and Self-organized Criticality; 2.11 Current Status of Power-Law Distributions; 2.12 Power-Law Relations (Bivariate) and Power-Law (Probability) Distributions; 2.13 Allometric Scaling and Fractals; 2.14 Fractals and the Golden Section in Plant Growth. | |
| 505 | 8 | |a 2.15 Turbulent Fluid Flow Structure, Fractals, and the Golden Ratio2.16 Fractal Space-Time and the Golden Section; 2.17 Power-Law (Probability) Distributions in Meteorological Parameters; 2.17.1 Power-Law (Probability) Distributions in Precipitation; 2.17.2 Power-Law (Probability) Distributions in Temperature; 2.17.3 Power-Law (Probability) Distributions in Quaternary Ice Volume Fluctuations; 2.17.4 Power-Law (Probability) Distributions in Atmospheric Pollution; 2.18 General Systems Theory Model for Self-organized Criticality in Atmospheric Flows; References. | |
| 504 | |a Includes bibliographical references and index. | ||
| 506 | |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty | ||
| 520 | |a This book presents a new concept of General Systems Theory and its application to atmospheric physics. It reveals that energy input into the atmospheric eddy continuum, whether natural or manmade, results in enhancement of fluctuations of all scales, manifested immediately in the intensification of high-frequency fluctuations such as the Quasi-Biennial Oscillation and the El-Nino-Southern Oscillation cycles. Atmospheric flows exhibit self-organised criticality, i.e. long-range correlations in space and time manifested as fractal geometry to the spatial pattern concomitant with an inverse power law form for fluctuations of meteorological parameters such as temperature, pressure etc. Traditional meteorological theory cannot satisfactorily explain the observed self-similar space time structure of atmospheric flows. A recently developed general systems theory for fractal space-time fluctuations shows that the larger-scale fluctuation can be visualised to emerge from the space-time averaging of enclosed small-scale fluctuations, thereby generating a hierarchy of self-similar fluctuations manifested as the observed eddy continuum in power spectral analyses of fractal fluctuations. The interconnected network of eddy circulations responds as a unified whole to local perturbations such as global-scale response to El-Nino events. The general systems theory model predicts an inverse power law form incorporating the golden mean? for the distribution of space-time fluctuation patterns and for the power (variance) spectra of the fluctuations. Since the probability distributions of amplitude and variance are the same, atmospheric flows exhibit quantumlike chaos. Long-range correlations inherent to power law distributions of fluctuations are identified as nonlocal connection or entanglement exhibited by quantum systems such as electrons or photons. The predicted distribution is close to the Gaussian distribution for small-scale fluctuations, but exhibits a fat long tail for large-scale fluctuations. Universal inverse power law for fractal fluctuations rules out unambiguously linear secular trends in climate parameters. | ||
| 590 | |a SpringerLink |b Springer Complete eBooks | ||
| 650 | 0 | |a Atmospheric physics. | |
| 650 | 0 | |a Self-organizing systems. | |
| 655 | 7 | |a elektronické knihy |7 fd186907 |2 czenas | |
| 655 | 9 | |a electronic books |2 eczenas | |
| 776 | 0 | 8 | |i Print version: |a Selvam, A.M. |t Self-organized criticality and predictability in atmospheric flows. |d Cham, Switzerland : Springer, 2017 |z 3319545450 |z 9783319545455 |w (OCoLC)971046676 |
| 830 | 0 | |a Springer atmospheric sciences. | |
| 856 | 4 | 0 | |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-54546-2 |y Plný text |
| 992 | |c NTK-SpringerEES | ||
| 999 | |c 98914 |d 98914 | ||
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