Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Random Error01:04

Random Error

1.2K
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
1.2K
Precipitation of Ions03:11

Precipitation of Ions

28.1K
Predicting Precipitation
The equation that describes the equilibrium between solid calcium carbonate and its solvated ions is:
28.1K
Magnetostatic Boundary Conditions01:28

Magnetostatic Boundary Conditions

1.0K
An electric field suffers a discontinuity at a surface charge. Similarly, a magnetic field is discontinuous at a surface current. The perpendicular component of a magnetic field is continuous across the interface of two magnetic mediums. In contrast, its parallel component, perpendicular to the current, is discontinuous by the amount equal to the product of the vacuum permeability and the surface current. Like the scalar potential in electrostatics, the vector potential is also continuous...
1.0K
Trends in Lattice Energy: Ion Size and Charge02:54

Trends in Lattice Energy: Ion Size and Charge

24.1K
An ionic compound is stable because of the electrostatic attraction between its positive and negative ions. The lattice energy of a compound is a measure of the strength of this attraction. The lattice energy (ΔHlattice) of an ionic compound is defined as the energy required to separate one mole of the solid into its component gaseous ions. For the ionic solid sodium chloride, the lattice energy is the enthalpy change of the process:
24.1K
Arrhenius Plots02:34

Arrhenius Plots

40.5K
The Arrhenius equation relates the activation energy and the rate constant, k, for chemical reactions. In the Arrhenius equation, k = Ae−Ea/RT, R is the ideal gas constant, which has a value of 8.314 J/mol·K, T is the temperature on the kelvin scale, Ea is the activation energy in J/mole, e is the constant 2.7183, and A is a constant called the frequency factor, which is related to the frequency of collisions and the orientation of the reacting molecules.
The Arrhenius equation can be used...
40.5K
Atomic Emission Spectroscopy: Interference01:30

Atomic Emission Spectroscopy: Interference

244
In atomic emission spectroscopy (AES), high-temperature atomizers excite a broad range of elements and molecules that generate complex emissions from sources such as oxides, hydroxides, and flame combustion products in the flame or plasma. Several strategies can be employed to minimize spectral interferences caused by overlapping emission lines or bands. These include increasing instrument resolution, choosing alternative emission lines, optimally placing the detector in low-background regions,...
244

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Irreversibility and Energy Transfer at Non-MHD Scales in a Magnetospheric Current Disruption Event.

Entropy (Basel, Switzerland)·2025
Same author

Scale dependence of fractal dimension in deterministic and stochastic Lorenz-63 systems.

Chaos (Woodbury, N.Y.)·2023
Same author

B2 Thickness Parameter Response to Equinoctial Geomagnetic Storms.

Sensors (Basel, Switzerland)·2021
Same author

Causality and Information Transfer Between the Solar Wind and the Magnetosphere-Ionosphere System.

Entropy (Basel, Switzerland)·2021
Same author

Analysis of Pseudo-Lyapunov Exponents of Solar Convection Using State-of-the-Art Observations.

Entropy (Basel, Switzerland)·2021
Same author

On Yaglom's Law for the Interplanetary Proton Density and Temperature Fluctuations in Solar Wind Turbulence.

Entropy (Basel, Switzerland)·2020

Related Experiment Video

Updated: Aug 9, 2025

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

5.9K

Chaos and Predictability in Ionospheric Time Series.

Massimo Materassi1, Tommaso Alberti2, Yenca Migoya-Orué3

  • 1Consiglio Nazionale delle Ricerche-Istituto dei Sistemi Complessi (CNR-ISC), Via Madonna del Piano 10, Sesto Fiorentino, 50019 Firenze, Italy.

Entropy (Basel, Switzerland)
|February 25, 2023
PubMed
Summary

Investigating the Earth's ionosphere, this study uses data analysis to quantify its chaotic behavior and predictability. Results suggest limitations on ionospheric prediction models, highlighting the system's complex dynamics.

Keywords:
embedding phase spaceionospherepredictability

More Related Videos

Thermocapillary Convection Space Experiment on the SJ-10 Recoverable Satellite
07:00

Thermocapillary Convection Space Experiment on the SJ-10 Recoverable Satellite

Published on: March 11, 2020

7.5K
Recapitulation of an Ion Channel IV Curve Using Frequency Components
10:14

Recapitulation of an Ion Channel IV Curve Using Frequency Components

Published on: February 8, 2011

13.6K

Related Experiment Videos

Last Updated: Aug 9, 2025

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

5.9K
Thermocapillary Convection Space Experiment on the SJ-10 Recoverable Satellite
07:00

Thermocapillary Convection Space Experiment on the SJ-10 Recoverable Satellite

Published on: March 11, 2020

7.5K
Recapitulation of an Ion Channel IV Curve Using Frequency Components
10:14

Recapitulation of an Ion Channel IV Curve Using Frequency Components

Published on: February 8, 2011

13.6K

Area of Science:

  • Geophysics
  • Space Physics
  • Dynamical Systems Theory

Background:

  • The Earth's ionosphere is a complex system challenging to model, with current models primarily based on physics and chemistry influenced by space weather.
  • The predictability of the ionosphere's residual or mismodelled behavior, whether it's a simple dynamical system or chaotic, remains unclear.

Purpose of the Study:

  • To apply data analysis techniques to assess the chaotic nature and predictability of the local ionosphere.
  • To quantify the ionosphere's behavior using correlation dimension (D2) and Kolmogorov entropy rate (K2).

Main Methods:

  • Calculation of correlation dimension (D2) as a proxy for dynamical complexity.
  • Calculation of Kolmogorov entropy rate (K2) to determine the predictability horizon (K2-1).
  • Analysis of two one-year vertical total electron content (vTEC) time series from Matera, Italy (Solar Maximum 2001, Solar Minimum 2008).

Main Results:

  • Preliminary results demonstrate the feasibility of applying D2 and K2 analyses to ionospheric variability.
  • The calculated D2 and K2 values provide a quantitative measure of the ionosphere's chaos and predictability.

Conclusions:

  • The study provides a method to measure the chaos and predictability of the Earth's ionosphere.
  • These findings are expected to inform and potentially limit claims regarding the predictive capacity of ionospheric models.