Reliable short-time prediction of thermospheric mass density along the satellite orbit is always essential but challenging for the operation of Low-Earth orbit (LEO) satellites. In this paper, three machine-learning prediction algorithms are investigated, including the Bidirectional Long Short-Term Memory (Bi-LSTM), the Transformer, and the Light Gradient Boosting Machine (LightGBM) ensemble model of the above models. We use satellite data from CHAMP, GOCE, and SWARM-C to evaluate the robustness and accuracy of different density variations. The comparison demonstrates that all models achieve compelling predictions and are much better than NRLMSISE-00. The LightGBM ensemble model (LE-model) consistently outperforms others in accuracy and stability. Furthermore, when the obtained density data from the newly launched satellites are limited, the trained LE-model can provide a valid prediction for the new satellite orbit by transfer learning. This study offers a promising insight into the short-time prediction of thermospheric mass density using ensemble-transfer learning and may be advantageous to future research on space whether.

Ionospheric Total Electron Content (TEC) prediction has important reference significance for the accuracy of global navigation satellite systems (GNSS) based global positioning system, satellite communications and other space communications applications. In the study, an available prediction model of global IGS-TEC map is established based on testing several different LSTM-based algorithms. We find that Multi-step auxiliary algorithm based prediction model performs the best. It can precisely predict the global ionospheric IGS-TEC in the next 6 days (the MAD and RMSE are 2.485 and 3.511 TECU, respectively). Then, the autoencoder network algorithm is adopted to construct an assimilation model that transforming IGS-TEC map to MIT-TEC map. In order to judge the validity of the assimilation model, the outputs of the assimilation model are evaluated and compared with the IRI2016 model in four different geomagnetic storm events. It seems that the assimilation model can accurately forecast MIT-TEC by inputting the predicted IGS-TEC value. The performance of assimilation model for the predicting MIT-TEC is better than that of IRI2016.

As there are strong crustal magnetic fields in some Martian concentrated regions. it has long been a goal of Martian science to understand how crustal magnetic field affects surrounding space environment. In the paper, using the data measured by MAVEN, the ratio of electron/CO2 density ( Ne/NCO2) in region with different levels of Martian ionospheric magnetic fields are studied. It seems that ratio of dayside Ne/NCO2 in region with stronger ionospheric magnetic field is larger while the altitude is more than 260 km. On the other hand, the effect of crustal magnetic field intensity on the nightside ratio of Ne/NCO2 is weak. Since the topological structure of magnetic field is very vulnerable to the solar wind, the correlation between Ne/NCO2 and solar wind parameters are analyzed. We find that there is obvious negative correlation between dayside ratio of Ne/NCO2 and solar wind dynamic pressure in the region with strong ionospheric magnetic field, which may imply that the ionospheric plasmas are significantly escaped in response to enhanced solar wind dynamic pressure pulses in the dayside region. However, the effect of solar wind on nightside ratio of Ne/NCO2 is very little. These results can be useful for understanding the dynamic process in the Martian ionosphere.

This paper presents a comprehensive study of the intense current structure (ICS) at the dayside magnetopause, by using the high-resolution data from the Magnetospheric Multiscale (MMS) mission. About 3,600 ICSs with current density exceeding 1.2 μA/m2 have been detected during phase 1a and 1b within the magnetopause boundary layer (MBL). We find that most ICSs have a temporal duration of less than 1 second and thickness of less than one ion inertial length. The number of ICSs decreases with the thickness increasing from the electron-scale to the ion-scale. The occurrence rate of the ICS is relatively higher close to Earth and in the dusk sector near the meridian, probably caused by the large solar wind dynamic pressure. In a local boundary normal coordinate system, the occurrence rate is higher on the magnetosheath side. For most ICSs, the current is carried by electrons. The perpendicular current is larger than the parallel current for more ICSs. The energy conversion J·E is primarily through the perpendicular current and electric field, while the non-ideal energy conversion J·E’ is mainly dominated by the parallel component. ICSs provide much stronger energy conversion and dissipation compared to the ambient plasma in the MBL. This study improves our understanding of the characteristics of the ICS and its role in solar wind-magnetosphere coupling.