Team title: Understanding the Suprathermal Seed Population
Team ID: H3-02
Maher Dayeh (Southwest Research Institute, USA), firstname.lastname@example.org
Keywords (impact): Human Exploration
Keywords (activity type): Understanding, Requirements, Forecasting, Data Utilization
- SEP seed population
- Suprathermal particles
Advances in heliospheric ion measurements in the suprathermal (ST) energy range (above the bulk solar wind protons of ~1 keV) over the past two decades have significantly improved our understanding of this particle regime. Most importantly, in situ spacecraft measurements have provided compelling evidence for the ubiquitous presence of ST spectral tails, from which extreme Space Weather events, such as Solar Energetic Particles (SEPs), draw their accelerating material. Despite their increased level of importance for Space Weather and SEP-related predictions, the origin and acceleration processes of these ST particles remain highly controversial, mainly due to the lack of in situ observations very close to the Sun.
Without exception, all current physics-based SEP propagation and acceleration models require an injection spectrum near the shock to get started. Some modelers use an artificial ubiquitous spectrum, while others use an estimated ST spectrum that is inferred from single spacecraft measurements at 1 AU, whenever available. In a trial-and-error scenario, the ST spectral index can also vary within a model so that an optimal agreement between the modeled SEP profile and the observed one can be achieved. Both approaches of estimating the seed spectrum are heuristic and present very rough estimates.
The need of a realistic seed ST spectrum is thus critical to drive SEP predictions near 1 AU and beyond. Our team focuses on the challenges and mitigations pertaining to this topic.
The objective of our team is to examine the feasibility of determining a reliable seed spectrum that can be used by SEP modelers. We utilize multi-spacecraft observations of suprathermal particles and other validated modeling and simulation tools.
- Observational signatures of pre-existing suprathermal particle population (including composition, and spatial and temporal distribution)
Link to team external website: