Bibliographic Details
| Title: |
Statistical Survey of Collisionless Dissipation in the Terrestrial Magnetosheath. |
| Authors: |
Yanwen Wang1, Bandyopadhyay, Riddhi2, Chhiber, Rohit1,3, Matthaeus, William H.1 whm@udel.edu, Chasapis, Alexandros4, Yan Yang5, Wilder, Frederick D.6, Gershman, Daniel J.3, Giles, Barbara L.3, Pollock, Craig J.7, Dorelli, John3, Russell, Christopher T.8, Strangeway, Robert J.8, Torbert, Roy T.9, Moore, Thomas E.3, Burch, James L.10 |
| Source: |
Journal of Geophysical Research. Space Physics. Jun2021, Vol. 126 Issue 6, p1-17. 17p. |
| Subject Terms: |
Electromagnetic waves, Plasma heating, Collisionless plasmas, Internal energy (Thermodynamics), Surveys |
| Abstract: |
Kinetic dissipation of turbulence is an important physical process occurring in collisionless plasmas. Using in-situ data from the Magnetospheric Multiscale (MMS) Mission, we investigate the statistical distribution of kinetic dissipation in the terrestrial magnetosheath. We make use of an analysis of the Vlasov-Maxwell equations that provides a general description of transfer of internal energy, fluid-flow energy, and electromagnetic energy in collisionless plasma, including both spatial transport and conversion between forms. In particular, we focus on the channels that separately produce proton and electron internal energies. Applying those results to MMS burst-mode data obtained in the weakly collisional, turbulent magnetosheath plasma, it is possible to quantify contributions to dissipation from the compressive pressure-dilatation channel, and from the incompressive pressure-strain channel, for both plasma species. We also employ a simple spatial filtering approach as a first step to quantifying plasma heating at large and small scales. The analysis is carried out for 50 selected turbulent data intervals, and statistical distributions of the results are presented. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of Geophysical Research. Space Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
GreenFILE |