The Earth’s upper atmosphere impacts a wide range of technologies, including satellite communication and navigation signals. Specification and forecasting of the upper atmosphere are critical for mitigating these effects.

A recent statistical study (Qin et al., 2018) has suggested that not all electromagnetic ion cyclotron (EMIC) waves can scatter relativistic electrons. However, knowledge of the factors that influence the EMIC wave scattering efficiency is still limited in observations.

We consider the vector emissivity of the polarized radiation transfer in a Lambda-type atomic transition, which we recently proposed in order to account for both CRD and PRD contributions to the scattered radiation.

In this paper, regression-based deep convolutional neural networks (CNN), with 12 layers, are developed for predicting the maximal amplitude of the southward component of the near-Earth magnetic field from a passing interplanetary coronal mass ejection (ICME).

We conducted numerical simulations to examine dayside thermosphere and ionosphere responses to concurrent solar flares and a geomagnetic storm during September 6th – September 11th, 2017, as well as the interplay of flare and storm effects.

We re-examine a 50+ year-old problem of deep central reversals predicted for strong solar spectral lines, in contrast to the smaller reversals seen in observations.

In the context of the solar atmosphere, we re-examine the role of of neutral and ionized species in dissipating the ordered energy of intermediate-mode MHD waves into heat.