A corotation electric field model of the Earth derived from Swarm satellite magnetic field measurements

2017 ◽  
Vol 122 (8) ◽  
pp. 8733-8754 ◽  
Author(s):  
Stefan Maus
Keyword(s):  
Magnetic Field ◽  
Electric Field ◽  
Field Model ◽  
Field Measurements ◽  
The Earth ◽  
Magnetic Field Measurements ◽  
Swarm Satellite

The effect of plasmaspheric material on magnetopause reconnection

2020 ◽  
Author(s):  
Stephen Fuselier ◽  
Stein Haaland ◽  
Paul Tenfjord ◽  
David Malaspina ◽  
James Burch ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Low Temperature ◽  
Magnetic Reconnection ◽  
Plasma Wave ◽  
Outer Part ◽  
Field Measurements ◽  
Ion Composition ◽  
The Earth ◽  
Magnetospheric Multiscale ◽  
Magnetic Field Measurements

<p>The Earth’s plasmasphere contains cold (~eV energy) dense (>100 cm<sup>-3</sup>) plasma of ionospheric origin. The primary ion constituents of the plasmasphere are H<sup>+ </sup>and He<sup>+</sup>, and a lower concentration of O<sup>+</sup>. The outer part of the plasmasphere, especially on the duskside of the Earth, drains away into the dayside outer magnetosphere when geomagnetic activity increases. Because of its high density and low temperature, this plasma has the potential to modify magnetic reconnection at the magnetopause. To investigate the effect of plasmaspheric material at the magnetopause, Magnetospheric Multiscale (MMS) data are surveyed to identify magnetopause crossings with the highest He<sup>+</sup>densities. Plasma wave, ion, and ion composition data are used to determine densities and mass densities of this plasmaspheric material and the magnetosheath plasma adjacent to the magnetopause. These measurements are combined with magnetic field measurements to determine how the highest density plasmaspheric material in the MMS era may affect reconnection at the magnetopause.</p>

DETERMINATION OF THE ELECTRICAL CONDUCTIVITY OF THE SEA BED IN SHALLOW WATERS

Geophysics ◽  
1968 ◽  
Vol 33 (6) ◽  
pp. 995-1003 ◽  
Author(s):  
Peter R. Bannister
Keyword(s):  
Magnetic Field ◽  
Electric Field ◽  
Sea Water ◽  
Field Measurements ◽  
Bottom Layer ◽  
Dipole Antenna ◽  
Skin Depth ◽  
Noise Component ◽  
Sea Bed ◽  
Magnetic Field Measurements

The electric and magnetic field components produced by horizontal dipole antennas (both electric and magnetic) located within the upper layer of a two‐layer conducting earth are derived for the quasi‐near range. This range is defined as that in which the measurement distance is much greater than an earth skin depth but much less than a free‐space wavelength. Ionospheric effects are neglected. It is assumed that the transmitting and receiving anterenna depths are much less than their horizontal separation, and that the fields in the horizontal direction vary only slightly in a distance of one skin depth. It is well known that if the conductivity and thickness of the first layer (sea water) are known, the conductivity of the bottom layer (the sea bed) may be determined from magnetic field measurements alone. However, when extremely low‐frequency magnetic field measurements are performed at sea, the movement of the magnetic field sensors in the static magnetic field of the earth (which is many times stronger than the field to be measured) introduces a very strong noise component. It is argued that electric field measurements are preferable because the induced noise component is smaller. It is shown that the sea bed conductivity may be determined by measuring only the horizontal electric field components produced by a subsurface horizontal magnetic dipole antenna.

scholarly journals Satellite Measured Ionospheric Magnetic Field Variations over Natural Hazards Sites

2021 ◽  
Vol 13 (12) ◽  
pp. 2360
Author(s):  
Christoph Schirninger ◽  
Hans U. Eichelberger ◽  
Werner Magnes ◽  
Mohammed Y. Boudjada ◽  
Konrad Schwingenschuh ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Natural Hazards ◽  
Field Measurements ◽  
Volcanic Eruptions ◽  
Low Earth Orbit ◽  
Near Surface ◽  
The Earth ◽  
Magnetic Field Measurements ◽  
Spatio Temporal ◽  
Magnetic Field Variations

Processes and threats related to natural hazards play an important role in the evolution of the Earth and in human history. The purpose of this study is to investigate magnetic field variations measured at low Earth orbit (LEO) altitudes possibly associated with earthquakes, volcanic eruptions, and artificial outbursts. We focus on two missions with well equipped magnetometer packages, the China Seismo-Electromagnetic Satellite (CSES) and ESA’s three spacecraft Swarm fleet. After a natural hazards survey in the context of this satellites, and consideration of external magnetospheric and solar influences, together with spacecraft interferences, wavelet analysed spatio-temporal patterns in ionospheric magnetic field variations related to atmospheric waves are examined in detail. We provide assessment of the links between specific lithospheric or near surface sources and ionospheric magnetic field measurements. For some of the diverse events the achieved statistical results show a change in the pattern between pre- and post-event periods, we show there is an increase in the fluctuations for the higher frequency (smaller scales) components. Our results are relevant to studies which establish a link between space based magnetic field measurements and natural hazards.

GRACE-FO and Swarm integrated data analysis reveals ionospheric disturbances on the accelerometer measurements

2020 ◽  
Author(s):  
Myrto Tzamali ◽  
Athina Peidou ◽  
Spiros Pagiatakis
Keyword(s):  
Magnetic Field ◽  
Electromagnetic Field ◽  
Electric Field ◽  
Poynting Vector ◽  
Field Measurements ◽  
Temporal Variations ◽  
Space Environment ◽  
The Earth ◽  
Leo Satellites ◽  
The Magnetic Field

<p>Low Earth Orbit (LEO) satellites are subject to numerous disturbances related to the Earth’s upper ionosphere. Perturbations induced by the activity of the electromagnetic field (EM) at the upper ionospheric layers have not been fully understood yet. This study focuses on the disturbances shown on GRACE-FO accelerometer measurements when the EM field was disturbed by an intense geomagnetic storm occurred on August 2018. A thorough analysis of the accelerometer measurements of GRACE-C as well as the magnetic and electric field measurements from Swarm constellation is conducted, to enlighten their impulse-response relationship. We derive the temporal variations of the magnetic field by removing the main static field and we calculate the Poynting vector employing the Swarm magnetic field measurements and electric field data, by implementing rigorous data analyses to analyze the spatiotemporal characteristics of the energy flow of the electromagnetic field. Results show that GRACE-C accelerometer measurements are highly disturbed in the higher latitudes especially near the auroral regions. The signature of the spatial temporal variations of the magnetic field and the Poynting vector demonstrates very similar behaviour with GRACE-C disturbances. Cross wavelet analysis between Poynting vector and GRACE-C accelerometer disturbances shows a very strong coherence. With the two LEO missions, i.e. GRACE-FO and Swarm, orbiting the Earth in very similar orbits, further analysis towards integrating their measurements will enhance our understanding of the interaction of LEO satellites with the space environment and how this interaction is depicted in their measurements.</p>

A Machine Learning technique for ULF wave classification in Swarm magnetic field measurements

2021 ◽  
Author(s):  
Alexandra Antonopoulou ◽  
George Balasis ◽  
Constantinos Papadimitriou ◽  
Zoe Boutsi ◽  
Omiros Giannakis ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Machine Learning ◽  
Field Measurements ◽  
Data Availability ◽  
Machine Learning Technique ◽  
Ulf Wave ◽  
The Earth ◽  
Swarm Satellites ◽  
Magnetic Field Measurements ◽  
Learning Technique

<p>Ultra-low frequency (ULF) magnetospheric plasma waves play a key role in the dynamics of the Earth’s magnetosphere and, therefore, their importance in Space Weather studies is indisputable. Magnetic field measurements from recent multi-satellite missions are currently advancing our knowledge on the physics of ULF waves. In particular, Swarm satellites have contributed to the expansion of data availability in the topside ionosphere, stimulating much recent progress in this area. Coupled with the new successful developments in artificial intelligence, we are now able to use more robust approaches for automated ULF wave identification and classification. The goal of this effort is to use a machine learning technique to classify ULF wave events using magnetic field data from Swarm. We construct a Convolutional Neural Network that takes as input the wavelet power spectra of the Earth’s magnetic field variations per track, as measured by each one of the three Swarm satellites, aiming to classify ULF wave events in four categories: Pc3 wave events, background noise, false positives, and plasma instabilities. Our primary experiments show promising results, yielding successful identification of 90% accuracy. We are currently working on producing larger datasets, by analyzing Swarm data from mid-2014 onwards, when the final constellation was formed.</p>

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