Glenn Sugar

High‐power large‐aperture radar instruments observe numerous meteor head echoes per minute. Head echoes result from reflections of radio waves from plasma surrounding meteoroids as they enter Earth's atmosphere. Knowledge of the spatial distribution of electrons in this plasma is essential to determining the mass loss rate of the meteor as a function of its measured radar cross‐section. Prior work applies theoretical and computational methods to determine the electron density distribution, but assumes the meteoroid emits neutral particles uniformly across its surface. In this paper, a numerical surface ablation model demonstrates that meteoroid mass loss may occur preferentially in the direction facing the oncoming atmosphere. Specifically, meteoroid mass loss becomes proportional to the frontal surface area facing the freestream atmosphere in the limit of high Biot number, but remains isotropic in the limit of low Biot number. Meteoroid rotation has a small effect on the direction of ejected mass, but the effect is insignificant compared to variation in meteoroid properties that affect the Biot number. This result informs our computational meteor plasma model, in which we compare the effect of meteoroid vaporization on the plasma distribution in the limits of low versus high Biot number. The resulting electron density profiles demonstrate order‐of‐magnitude agreement between each other, with peak difference of 70% immediately upstream of the meteoroid. This implies that the directional distribution of vaporizing neutrals likely does not significantly influence head echo observations, lending credence to existing work that assumes isotropic ablation.

High-power large-aperture radar instruments observe numerous meteor head echoes per minute. Head echoes result from reflections of radio waves from plasma surrounding meteoroids as they enter Earth’s atmosphere. Knowledge of the spatial distribution of electrons in this plasma is essential to determining the mass loss rate of the meteor as a function of its measured radar cross-section. Prior work applies theoretical and computational methods to determine the electron density distribution, but assumes the meteoroid emits neutral particles uniformly across its surface. In this paper, a numerical surface ablation model demonstrates that meteoroid mass loss may occur preferentially in the direction facing the oncoming atmosphere. Specifically, meteoroid mass loss becomes proportional to the frontal surface area facing the freestream atmosphere in the limit of high Biot number, but remains isotropic in the limit of low Biot number. Meteoroid rotation has a small effect on the direction of ejected mass, but the effect is insignificant compared to variation in meteoroid properties that affect the Biot number. This result informs our computational meteor plasma model, in which we compare the effect of meteoroid vaporization on the plasma distribution in the limits of low versus high Biot number. The resulting electron density profiles demonstrate order-of-magnitude agreement between each other, with peak difference of 70\% immediately upstream of the meteoroid. This implies that the directional distribution of vaporizing neutrals likely does not significantly influence head echo observations, lending credence to existing work that assumes isotropic ablation.

New, open access tools have been developed to validate ionospheric models in terms of technologically relevant metrics. These are ionospheric errors on GPS 3D position, HF ham radio communications, and peak F‐region density. To demonstrate these tools, we have used output from Sami is Another Model of the Ionosphere (SAMI3) driven by high‐latitude electric potentials derived from Active Magnetosphere and Planetary Electrodynamics Response Experiment, covering the first available month of operation using Iridium‐NEXT data (March 2019). Output of this model is now available for visualization and download via https://sami3.jhuapl.edu. The GPS test indicates SAMI3 reduces ionospheric errors on 3D position solutions from 1.9 m with no model to 1.6 m on average (maximum error: 14.2 m without correction, 13.9 m with correction). SAMI3 predicts 55.5% of reported amateur radio links between 2–30 MHz and 500–2,000 km. Autoscaled and then machine learning “cleaned” Digisonde NmF2 data indicate a 1.0 × 10¹¹ el. m³ median positive bias in SAMI3 (equivalent to a 27% overestimation). The positive NmF2 bias is largest during the daytime, which may explain the relatively good performance in predicting HF links then. The underlying data sources and software used here are publicly available, so that interested groups may apply these tests to other models and time intervals.

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.

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.

High‐power large‐aperture radars detect meteors by reflecting radio waves off dense plasma that surrounds a hypersonic meteoroid as it ablates in the Earth's atmosphere. If the plasma density profile around the meteoroid is known, the plasma's radar cross section can be used to estimate meteoroid properties such as mass, density, and composition. This paper presents head echo plasma density distributions obtained via two numerical simulations of a small ablating meteoroid and compares the results to an analytical solution found in Dimant and Oppenheim (2017a, https://doi.org/10.1002/2017JA023960 , 2017b, https://doi.org/10.1002/2017JA023963 ). The first simulation allows ablated meteoroid particles to experience only a single collision to match an assumption in the analytical solution, while the second is a more realistic simulation by allowing multiple collisions. The simulation and analytical results exhibit similar plasma density distributions. At distances much less than λ _T , the average distance an ablated particle travels from the meteoroid before a collision with an atmospheric particle, the plasma density falls off as 1/ R , where R is the distance from the meteoroid center. At distances substantially greater than λ _T , the plasma density profile has an angular dependence, falling off as 1/ R ² directly behind the meteoroid, 1/ R ³ in a plane perpendicular to the meteoroid's path that contains the meteoroid center, and in front of the meteoroid. When used for calculating meteoroid masses, this new plasma density model can give masses that are orders of magnitude different than masses calculated from a spherically symmetric Gaussian distribution, which has been used to calculate masses in the past.

We present a new method to detect meteor showers using the density‐based spatial clustering of applications with noise algorithm (DBSCAN; Ester et al. ). The DBSCAN algorithm is a modern cluster detection algorithm that is well suited to the problem of extracting meteor showers from all‐sky camera data because of its ability to efficiently extract clusters of different shapes and sizes from large data sets. We apply this shower detection algorithm on a data set that contains 25,885 meteor trajectories and orbits obtained from the NASA All‐Sky Fireball Network and the Southern Ontario Meteor Network (SOMN). Using a distance metric based on solar longitude, geocentric velocity, and Sun‐centered ecliptic radiant, we find 25 strong cluster detections and six weak detections in the data, all of which are good matches to known showers. We include measurement errors in our analysis to quantify the reliability of cluster occurrence and the probability that each meteor belongs to a given cluster. We validate our method through false‐positive/negative analysis and with a comparison to an established shower detection algorithm.

Large horizontal winds and wind shears have been measured in the lower thermosphere by rockets, lidars, and nonspecular meteor radars. This paper describes a detailed analysis of three multihour nonspecular meteor radar data sets collected at the Jicamarca Radio Observatory. This provides some of the highest‐resolution sustained measurements in this part of the atmosphere. These show (1) intense wind speeds, maintaining 180 m/s for half an hour and 160 m/s for another half an hour; (2) winds structured in layers that move up or, more commonly, down in the predawn hours at rates of a few kilometers per hour; (3) intense wind shears that typically persist at around 50 m/s/km but, in one instance, sustains values approaching 100 m/s/km for a few hours.