We present a path forward on a long-standing issue concerning the flux of small and slow meteoroids, which are believed to be the dominant portion of the incoming meteoric mass flux into the Earth’s atmosphere. Such a flux, which is predicted by dynamical dust models of the Zodiacal Cloud, is not evident in ground-based radar observations. For decades this was attributed to the fact that the radars used for meteor observations lack the sensitivity to detect this population, due to the small amount of ionization produced by slow-velocity meteors. Such a hypothesis has been challenged by the introduction of meteor head echo (HE) observations with High Power and Large Aperture radars, in particular the Arecibo 430 MHz radar. Janches et al. developed a probabilistic approach to estimate the detectability of meteors by these radars and initially showed that, with the current knowledge of ablation and ionization, such particles should dominate the detected rates by one to two orders of magnitude compared to the actual observations. In this paper, we include results in our model from recently published laboratory measurements, which showed that (1) the ablation of Na is less intense covering a wider altitude range; and (2) the ionization probability, β ip , for Na atoms in the air is up to two orders of magnitude smaller for low speeds than originally believed. By applying these results and using a somewhat smaller size of the HE radar target we offer a solution that reconciles these observations with model predictions.

Lack of instrument sensitivity to low electron density (N_e) concentration makes it difficult to measure sharp N_e vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region N_e from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the N_e morphology. While the D/E-region N_e is a function of solar zenith angle (χ), it exhibits strong latitudinal variations for the same χ with a distribution asymmetric about noon. In addition, large longitudinal variations are observed along the same magnetic field pitch angle. The summer midlatitude N_e and sporadic E (E_s) show a distribution similar to each other. The distribution of auroral electron precipitation correlates better with the pitch angle from the magnetosphere than from one at 100 km. Finally, a new TEC retrieval technique is developed for the high-rate RO data with a top reaching at least 120 km. For better characterization of the E- to F-transition in N_e and more accurate TEC retrievals, it is recommended to have all GNSS-RO acquisition routinely up to 220 km.

The sensitivity of radar systems to detect different velocity populations of the incoming micrometeoroid flux is often the first argument considered to explain disagreements between models of the Near-Earth dust environment and observations. Recently, this was argued by Nesvorný et al. to support the main conclusions of a Zodiacal Dust Cloud (ZDC) model which predicts a flux of meteoric material into the Earth's upper atmosphere mostly composed of small and very slow particles. In this paper, we expand on a new methodology developed by Janches et al. to test the ability of powerful radars to detect the meteoroid populations in question. In our previous work, we focused on Arecibo 430 MHz observations since it is the most sensitive radar that has been used for this type of observation to date. In this paper, we apply our methodology to two other systems, the 440 MHz Poker Flat Incoherent Scatter Radar and the 46.5 Middle and Upper Atmosphere radar. We show that even with the less sensitive radars, the current ZDC model over-predicts radar observations. We discuss our results in light of new measurements by the Planck satellite which suggest that the ZDC particle population may be characterized by smaller sizes than previously believed. We conclude that the solution to finding agreement between the ZDC model and sensitive high power and large aperture meteor observations must be a combination of a re-examination not only of our knowledge of radar detection biases, but also the physical assumptions of the ZDC model itself.

A growing number of SmallSat/CubeSat constellations with high-rate (50–100 Hz) global navigation satellite system radio occultations (GNSS-RO) as well as low-rate (1 Hz) precise orbit determination (GNSS-POD) limb-viewing capabilities provide unprecedented spatial and temporal sampling rates for ionospheric studies. In the F-region electron density (N${}_e$) retrieval process, instead of the conventional onion-peeling (OP) inversion, an optimal estimation (OE) inversion technique was recently developed using total electron content measurements acquired by GNSS-POD link. The new technique is applied to data acquired from the COSMIC-1, COSMIC-2, and Spire constellations. Although both OE and OP techniques use the Abel weighting function in N${}_e$ inversion, OE significantly differs in its performance, especially in the lower F- and E-regions. In this work, we evaluate and compare newly derived data sets using F2 peak properties with other space-based and ground-based observations. We determine the F2 peak N${}_e$ (NmF2) and its altitude (hmF2), and compare them with the OP-retrieved values. Good agreement is observed between the two techniques for both NmF2 and hmF2. In addition, we also utilize autoscaled F2 peak measurements from a number of worldwide Digisonde stations (∼30). The diurnal sensitivity and latitudinal variability of the F2 peak between the two techniques are carefully studied at these locations. Good agreement is observed between OE-retrieved NmF2 and Digisonde-measured NmF2. However, significant differences appear between OE-retrieved hmF2 and Digisonde-measured hmF2. During the daytime, Digisonde-measured hmF2 remains ∼25–45 km below the OE-retrieved hmF2, especially at mid and high latitudes. We also incorporate F-region N${}_e$ measurements from two incoherent scatter radar observations at high latitudes, located in the North American (Millstone Hill) and European (EISCAT at Tromso) sectors. The radar measurements show good agreement with OE-retrieved values. Although there are several possible sources of error in the ionogram-derived N${}_e$ profiles, our further analysis on F1 and F2 layers indicates that the low Digisonde hmF2 is caused by the autoscaled method, which tends to detect a height systematically below the F2 peak when the F1 layer is present.

Statistical GNSS-RO measurements of phase and amplitude scintillation are analyzed at the mid-latitudes in the local summer for a 100 km altitude. These conditions are known to contain frequent sporadic-E, and the S${}_4$-${\sigma }_{\varphi }$ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S${}_4$-${\sigma }_{\varphi }$ histograms are presented, showing roughly linear trends until the S${}_4$ saturates near 0.8. To interpret the measurements and understand the sporadic-E contributions, 10,000 simulations of RO signals perturbed by sporadic-E layers are performed using length, intensity, and vertical thickness distributions from previous studies, with the assumption that the sporadic-E layer acts as a Gaussian lens. Many of the key trends observed in the measurement histograms are present in the simulations, providing a key for understanding the complex mapping between layer characteristics and impacts on the GNSS-RO signals. Additionally, the inclusion of Kolmogorov turbulence and a diffusion-limited threshold on the lens strength/(vertical thickness)${}^2$ ratio helps to make the layers more physically realistic and improves agreement with the observations.

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in characterizing the global 3D distribution and variability of ionospheric electron density (N_e). In this study, we developed an optimal estimation (OE) method to retrieve N_e profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles (ε < 0°). Although both OE and onion-peeling (OP) methods use the Abel weighting function in the N_e inversion, they are significantly different in terms of performance in the lower ionosphere. The new OE results can overcome the large N_e oscillations, sometimes negative values, seen in the OP retrievals in the E-region ionosphere. In the companion paper in this Special Issue, the HmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006–2019), COSMIC-2 (2019–present), and Spire (2019–present) constellations, showing a consistent ionospheric N_e morphology. The unprecedented spatiotemporal sampling of the ionosphere from these constellations now allows a detailed analysis of the frequency–wavenumber spectra for the N_e variability at different heights. In the lower ionosphere (~150 km), we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2, and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4, and SW4. The co-existence of eastward- and westward-propagating wave4 components implies the presence of a stationary wave4 (SPW4), as suggested by other earlier studies. Further improvements to the OE method are proposed, including a tomographic inversion technique that leverages the asymmetric sampling about the tangent point associated with GNSS-LEO links.