skip to main content


Title: Formation of Plasma Around a Small Meteoroid: Electrostatic Simulations
Abstract

Obtaining meteoroid mass from head echo radar cross section depends on the assumed plasma density distribution around the meteoroid. An analytical model presented in Dimant and Oppenheim (2017a,https://doi.org/10.1002/2017JA023960; 2017b,https://doi.org/10.1002/2017JA023963) and simulation results presented in Sugar et al. (2018,https://doi.org/10.1002/2018JA025265) suggest the plasma density distribution is significantly different than the spherically symmetric Gaussian distribution used to calculate meteoroid masses in many previous studies. However, these analytical and simulation results ignored the effects of electric and magnetic fields and assumed quasi‐neutrality. This paper presents results from the first particle‐in‐cell simulations of head echo plasma that include electric and magnetic fields. The simulations show that the fields change the ion density distribution by less than ∼2% in the meteor head echo region, but the electron density distribution changes by up to tens of percent depending on the location, electron energies, and magnetic field orientation with respect to the meteoroid path.

 
more » « less
Award ID(s):
1755020
NSF-PAR ID:
10460200
Author(s) / Creator(s):
 ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Journal of Geophysical Research: Space Physics
Volume:
124
Issue:
5
ISSN:
2169-9380
Page Range / eLocation ID:
p. 3810-3826
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    We present results and analysis of finite‐difference time‐domain (FDTD) simulations of electromagnetic waves scattering off meteor head plasma using an analytical model and a simulation‐derived model of the head plasma distribution. The analytical model was developed by (Dimant & Oppenheim, 2017b,https://doi.org/10.1002/2017JA023963) and the simulation‐derived model is based on particle‐in‐cell (PIC) simulations presented in (Sugar et al., 2019,https://doi.org/10.1029/2018JA026434). Both of these head plasma distribution models show the meteor head plasma is significantly different than the spherically symmetric distributions used in previous studies of meteor head plasma. We use the FDTD simulation results to fit a power law model that relates the meteoroid ablation rate to the head echo radar cross section (RCS), and show that the RCS of plasma distributions derived from the Dimant‐Oppenheim analytical model and the PIC simulations agree to within 4 dBsm. The power law model yields more accurate meteoroid mass estimates than previous methods based on spherically symmetric plasma distributions.

     
    more » « less
  2. Abstract

    Both high‐power large aperture radars and smaller meteor radars readily observe the dense head plasma produced as a meteoroid ablates. However, determining the mass of such meteors based on the information returned by the radar is challenging. We present a new method for deriving meteor masses from single‐frequency radar measurements, using a physics‐based plasma model and finite‐difference time‐domain (FDTD) simulations. The head plasma model derived in Dimant and Oppenheim (2017),https://doi.org/10.1002/2017ja023963depends on the meteoroids altitude, speed, and size. We use FDTD simulations of a radar pulse interacting with such head plasmas to determine the radar cross section (RCS) that a radar system would observe for a meteor with a given set of physical properties. By performing simulations over the observed parameter space, we construct tables relating meteor size, velocity, and altitude to RCS. We then use these tables to map a set of observations from the MAARSY radar (53.5 MHz) to fully defined plasma distributions, from which masses are calculated. To validate these results, we repeat the analysis using observations of the same meteors by the EISCAT radar (929 MHz). The resulting masses are strongly linearly correlated; however, the masses derived from EISCAT measurements are on average 1.33 times larger than those derived from MAARSY measurements. Since this method does not require dual‐frequency measurements for mass determination, only validation, it can be applied in the future to observations made by many single‐frequency radar systems.

     
    more » « less
  3. Abstract

    Using Magnetospheric Multiscale (MMS) observations and combined MHD/test particle simulations, we further explore characteristic ion velocity distributions in the plasma sheet boundary layer. The observations are characterized by earthward beams, which at a slightly later time are accompanied by weaker but faster tailward beams. Two events are presented showing different histories. The first event happens at entry from the lobe into the plasma sheet. Energy‐time dispersion indicates a source region about 25 tailward of the satellite. The second event follows the passage of a dipolarization front closer to Earth. In contrast to earlier MHD simulations, but in better qualitative agreement with the first observation, reconnection in the present simulation was initiated near. Simulated distributions right at the boundary are characterized by a single crescent‐shaped earthward beam, as discussed earlier (Birn, Hesse, et al., 2015,https://doi.org/10.1002/2015JA021573). Farther inside, or at a later time, the distributions now also show a simple reflected beam, evolving toward a more ring‐like distribution. The simulations provide insight into the acceleration sites: The innermost edges of the direct and reflected beams consist of ions accelerated in the vicinity of the reconnection site. This supports the validity of estimating the acceleration location based on a time‐of‐flight analysis (after Onsager et al., 1990,https://doi.org/10.1029/GL017i011p01837). However, this assumption becomes invalid at later times when the acceleration becomes dominated by the earthward propagating dipolarization electric field, such that earthward and tailward reflected beams are no longer accelerated at the same location and the same time.

     
    more » « less
  4. Abstract

    Electron ring velocity space distributions have previously been seen in numerical simulations of magnetic reconnection exhausts and have been suggested to be caused by the magnetization of the electron outflow jet by the compressed reconnected magnetic fields (Shuster et al., 2014,https://doi.org/10.1002/2014GL060608). We present a theory of the dependence of the major and minor radii of the ring distributions solely in terms of upstream (lobe) plasma conditions, thereby allowing a prediction of the associated temperature and temperature anisotropy of the rings in terms of upstream parameters. We test the validity of the prediction using 2.5‐dimensional particle‐in‐cell (PIC) simulations with varying upstream plasma density and temperature, finding excellent agreement between the predicted and simulated values. We confirm the Shuster et al. suggestion for the cause of the ring distributions, and also find that the ring distributions are located in a region marked by a plateau, or shoulder, in the reconnected magnetic field profile. The predictions of the temperature are consistent with observed electron temperatures in dipolarization fronts, and may provide an explanation for the generation of plasma with temperatures in the 10s of MK in super‐hot solar flares. A possible extension of the model to dayside reconnection is discussed. Since ring distributions are known to excite whistler waves, the present results should be useful for quantifying the generation of whistler waves in reconnection exhausts.

     
    more » « less
  5. Abstract

    We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML‐AIM). ML‐AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020,https://doi.org/10.1029/2020JA027908), the FAC‐derived auroral conductance model of Robinson et al. (2020,https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993,https://doi.org/10.1029/92gl02109). The ML‐AIM inputs are 60‐min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML‐AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML‐AIM produces physically accurate ionospheric potential patterns such as the two‐cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML‐AIM, the Weimer (2005,https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data‐assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML‐AIM than others. ML‐AIM is unique and innovative because it predicts ionospheric responses to the time‐varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005,https://doi.org/10.1029/2004ja010884) designed to provide a quasi‐static ionospheric condition under quasi‐steady solar wind/IMF conditions. Plans are underway to improve ML‐AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.

     
    more » « less