Ionospheric plasma blobs have long been studied since it was first reported in 1986. Blobs are localized regions of enhanced plasma with a factor of 2 or 3 above ambient plasma. In this paper, we studied the occurrence of blobs over Nigeria (9.08⁰N, 8.67⁰E geographic coordinates) using the SWARM constellation satellites – ionospheric plasma density dataset specifically. We considered only the nighttime pass of the satellites over Nigeria with time frame 18:00 to 04:59 LT. The satellites passed over Nigeria 126 times in 2019 with 41 cases of plasma blobs. The results show that 58% of the cases were found without bubbles nearby, 29% of the cases were found in the presence of small-scale fluctuations in ionospheric plasma density (henceforth “SSFiI”). From the spectral analysis, the average wavelength, period and the propagating speed of SSFiI are 11 km, 2-4 seconds, and 2.75 – 5.5 km/s, respectively. The rate of change of the electron density inside the blobs associated with SSFiI was ~50% above that of the blobs in the absence of SSFiI. This suggests that bubbles may not be the only prerequisite for the development and dynamics of blobs; and SSFiI may play a significant role in the morphology and dynamics of blobs.

AbstractIt is believed that galactic cosmic rays and solar energetic particles are the two major sources of ionizing radiation. However, the radiation source may also be due to relativistic electrons that are associated with precipitation from the Van Allen radiation belts. In this study, we use Automated Radiation Measurements for Aerospace Safety (ARMAS) measurements to investigate the precipitation mechanism of energetic radiation belt electrons. ARMAS instruments are flown on agency‐sponsored (NASA, National Oceanic and Atmospheric Administration, National Science Foundation, Federal Aviation Administration, DOE) flights, commercial space transportation companies and airliners (>9 km) in automated radiation collection mode. We identified magnetic conjunction events between ARMAS and NASA's Van Allen Probes to study the highly variable, dynamic mesoscale radiation events observed by ARMAS instruments at aviation altitudes and their relationship to various plasma waves in the inner magnetosphere measured by the Van Allen Probes. The results show that there is a strong correlation between dose rates observed by ARMAS and plasmaspheric hiss wave power measured by the Van Allen Probes, but no such relationship with electromagnetic ion cyclotron waves and only a modest correlation with whistler mode chorus waves. These results suggest that the space environment could have a potentially significant effect on passenger safety.

Accelerometer-derived neutral mass density (NMD) is an important quantity describing the variability of the upper atmosphere. NMD is widely used to calibrate and validate some models used for satellite orbit determination and prediction. Quantifying the true NMD is nearly impossible due to, among others, the lack of simultaneous in-situ measurements for cross-validation and the incomplete characterization of the uncertainties of these NMD products. This study investigates the error distribution of three different accelerometer-derived NMD products from the CHAMP satellite mission during time periods of both high and low solar activity. Using a multimodel ensemble comprised of both physical and empirical models, the study characterizes the error variance of the NMD. The strategies employed here may be useful and applicable to other space missions spanning over longer time periods. The results show considerable differences among the three CHAMP data sets and also reveal a pronounced latitude dependence in their error distributions. The median error standard deviation of CHAMP NMD is smaller during time periods of high solar activity (11.0%) than during periods of low solar activity (13.1%). The results indicate that the method of processing the accelerometer data has a significant impact on the uncertainty estimates of the different CHAMP NMD products.

We present results from a study of the time lags between changes in the energy flow into the polar regions and the response of the thermosphere to the heating. Measurements of the neutral density from the CHAMP and GRACE missions are used, along with calculations of the total Poynting flux entering the poles. During two major geomagnetic storms in 2003 these data show increased densities are first seen on the dayside edge of the auroral ovals after a surge in the energy input. At lower latitudes the densities reach their peak values on the dayside earlier than on the night side. A puzzling response seen in the CHAMP measurements during the November 2003 storm was that the density at a fixed location near the “Harang discontinuity’ remained at unusually low levels during three sequential orbit passes, while elsewhere the density increased. The entire database of measurements from the CHAMP and GRACE missions were used to derive maps of the density time lags across the globe. The maps show a large gradient between short and long time delays between $60^{\circ}$ and $30^{\circ}$ geographic latitude. They confirm the findings from the two storm periods, that near the equator the density on the dayside responds earlier than on the nightside. The time lags are longest near 18 – 20 h local time. The time lag maps could be applied to improve the accuracy of empirical thermosphere models, and developers of numerical models may find these results useful for comparisons with their calculations.

AbstractThe Mass Spectrometer and Incoherent Scatter radar (MSIS) model family has been developed and improved since the early 1970's. The most recent version of MSIS is the Naval Research Laboratory (NRL) MSIS 2.0 empirical atmospheric model. NRLMSIS 2.0 provides species density, mass density, and temperature estimates as function of location and space weather conditions. MSIS models have long been a popular choice of thermosphere model in the research and operations community alike, but—like many models—does not provide uncertainty estimates. In this work, we develop an exospheric temperature model based in machine learning that can be used with NRLMSIS 2.0 to calibrate it relative to high‐fidelity satellite density estimates directly through the exospheric temperature parameter. Instead of providing point estimates, our model (called MSIS‐UQ) outputs a distribution which is assessed using a metric called the calibration error score. We show that MSIS‐UQ debiases NRLMSIS 2.0 resulting in reduced differences between model and satellite density of 25% and is 11% closer to satellite density than the Space Force's High Accuracy Satellite Drag Model. We also show the model's uncertainty estimation capabilities by generating altitude profiles for species density, mass density, and temperature. This explicitly demonstrates how exospheric temperature probabilities affect density and temperature profiles within NRLMSIS 2.0. Another study displays improved post‐storm overcooling capabilities relative to NRLMSIS 2.0 alone, enhancing the phenomena that it can capture.