Accurate prediction of the solar wind speed and arrival of solar transient events are among the most important but still open problems in space weather research. This article implements a Convolutional Neural Network (CNN) coupled Long-Short Term Memory cell (LSTM) deep-learning model for the prediction of solar wind speed at Sun-Earth L1 on a daily and 6-hourly basis. The model is trained and validated using Solar-wind speed observations at Sun-Earth L1. The proposed CNN-LSTM models are developed and trained using data for the period from 01 August 1996 to 31 December 2019 and tested with the data from 01 January 2020 to 30 June 2024. The daily prediction model can forecast solar wind speed with a RMSE of 52.12 km/s and an overall correlation coefficient of 0.79, while the 6-hourly model can forecast solar wind speed with a RMSE of 33.72 km/s and an overall correlation coefficient of 0.93. This shows that without explicitly building in physics based relationships, the Deep Learning based models are able to perform reasonably well compared to existing approaches.

During the extreme space weather event on May 10, 2024, a pronounced super-fountain effect was observed, driven by the prompt penetration electric field (PPEF) and pre-reversal enhancement (PRE) electric field. For this event, the SWARM-A satellite data provided unprecedented insights into the global impact of these electric fields due to its favorable orbit configuration which covered the local dusk sector. Observations revealed significant enhancements in the equatorial fountain, particularly over longitudes between $20^\circ$ E and 55$^\circ$W. Notably, this study also detected the first in-situ observational evidence of electron temperature (T$_e$) increases in the evening equatorial ionosphere during an extreme geomagnetic storm, with T$_e$ enhancements aligning with the super-fountain effect’s latitudinal extent. Additionally, contrasting effects were observed over a nearby longitude, highlighting the complex and localized nature of impact caused by extreme space weather.

We investigate the solar events of late solar cycle 24 in July 2017 observed by a number of spacecraft in the inner heliosphere widely separated in heliolongitude and radial distance. These include spacecraft at L1 point, STEREO-A, near Earth satellites, and MAVEN (near Mars). The GRASP payload onboard Indian GSAT-19 satellite provides a new vantage point for Solar Energetic Particle (SEP) observations near Earth. There were two major Coronal Mass Ejections (CMEs) and a Stream Interaction Region (SIR) event in July 2017, which is a period during the deep descending phase of the historically weak solar cycle 24. The 16 July CME was Earth directed and the 24 July CME was STEREO-A and Mars directed. Earth and Mars were on the opposite sides of the solar disk, while Mars and STEREO-A were aligned with respect to the nominal Parker spiral field. The 24 July event was stronger and wider in heliolongitude. This CME-driven shock had magnetic connectivity to Earth, which produced an SEP event at Earth ~two days later. The spectral indices of the event observed directly at STEREO-A and at the remote location of ACE was found to be similar. The 16 July SIR event was observed by both MAVEN and STEREO-A. Higher particle intensities (a factor of 6 enhancement for 1 MeV protons) are observed by MAVEN (at 1.58 AU) compared to STEREO-A (at 0.96 AU). Also a spectral hardening is observed while comparing the spectral indices at these two locations, indicating proton acceleration at the SIR forward shock during the radial propagation of 0.62 AU in the interplanetary space.