Chapters authored
Solar Proton Activity over the Solar Cycle 24 and Associated Space Radiation Doses
The least number of proton events and ground-level enhancements was recorded in the solar cycle 24 which corresponds with the least smoothed sunspot number compared to the last three previous solar cycles. This was attributed to the weak sun’s polar field and decreasing strength of the interplanetary magnetic field at the start of the solar cycle. The majority contribution to background radiation dose within our earth’s atmosphere is galactic cosmic rays and trapped particles in the Van Allen Belts. However, solar proton events cause sudden spikes in radiation doses, and this depends on the fluence and energy spectra of the events. While these doses are least detected in the lower atmosphere, they have significant radiation damage to spacecraft electronic components and astronauts on long space missions and at higher atmospheric altitudes. Therefore, the prediction of such events and estimation of their effective radiation damage is an important consideration for planning long space missions and spacecraft design materials.
Part of the book: Magnetosphere and Solar Winds, Humans and Communication
Ionospheric Electron Density and Electron Content Models for Space Weather Monitoring
Monitoring and prediction of space weather phenomena and associated effects requires an understanding of the ionospheric response related to ionospheric electron content and electron density redistribution. These ionospheric response effects to space weather over time have been quantified by ground station measurements (ionosondes, radars, and GPS), satellite and rocket measurements, and estimations from ionospheric models. However, the progressive development of ionospheric models has had inconsistences in trying to describe the redistribution of electron density in response to extreme space weather conditions. In this chapter, we review and discuss the recent developments, progress, improvements, and existing challenges in the developed ionospheric models for prediction and forecasting space weather events and the need for continuous validation. The utilization of deep learning and neural network techniques in developing more flexible, reliable, and accurate data-driven ionospheric models for space weather prediction is also discussed. We also emphasized the roles of International and national Organizations like COSPAR, URSI, ITU, CCIR, and other research and education institutions in supporting and maintaining observatories for real-time monitoring and measurements of ionospheric electron density and TEC.
Part of the book: Magnetosphere and Solar Winds, Humans and Communication