Multispacecraft Study of the Spatio-Temporal Variability of Solar Energetic Particles (SEP) Profiles in the Inner Heliosphere

Information

• NSF Award
• 2325313

Owner

• UNIVERSITY OF NEW HAMPSHIRE

• Award Id

  2325313

• Award Effective Date

  7/15/2023 - a year ago

• Award Expiration Date

  6/30/2026 - a year from now

• Award Amount

  $ 558,790.00

• Award Instrument

  Standard Grant

Solar energetic particles (SEPs) are particles that are accelerated from the Sun in energetic events, such as solar flares and coronal mass ejections. They can move at relativistic speeds and when directed to the Earth, can cause space weather-related issues for human technology as well as radiation risks to humans. This project aims to gain better insights on SEP characteristics – including intensity, flux, and spatio-temporal evolution in the inner heliosphere. The research products will be made publicly available and the work is led by women. Undergraduate students will be mentored.<br/><br/>The project investigates how the near-Sun characteristics of solar energetic particles (SEPs) and their spatio-temporal variability help determine their origin, acceleration and propagation in the inner heliosphere, and constrains modeling of the seed population from which they arise. Data sets from NASA’s Parker Solar Probe and Solar Orbiter will be used. Additionally, the Energetic Particle Radiation Environment Model (EPREM) will be used for simulating the SEP events and the Current Sheet Source Surface (CSSS) model used for mapping the PSP locations back to the Sun for establishing the magnetic connectivity. The three objectives of the study are: Obj 1: Obtain SEP Time Profiles (intensity, integral flux, fluence, spectral index and composition) at multiple locations in the heliosphere and investigate their temporal variability. Obj 2: Model Comparison - use the knowledge gained in Obj 1 to constrain the parameters of EPREM simulations of SEP transport in the steady solar wind and heuristic models of shocks and switchbacks. Obj 3: Preparation of AI-ready Data and Data Reconstruction using algorithms developed using techniques of artificial intelligence and following the recommendations of Poduval et al. 2022 for AI-ready data.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

• Program Officer

  Lisa Winterlwinter@nsf.gov7032928519

• Min Amd Letter Date

  7/13/2023 - a year ago

• Max Amd Letter Date

  7/13/2023 - a year ago

• ARRA Amount

• Name

  University of New Hampshire

• City

  DURHAM

• State

  NH

• Country

  United States

• Address

  51 COLLEGE RD

• Postal Code

  038242620

• Phone Number

  6038622172

• First Name

  Bala

• Last Name

  Poduval

• Email Address

  bala.poduval@unh.edu

• Start Date

  7/13/2023 12:00:00 AM

• First Name

  Jonathan

• Last Name

  Niehof

• Email Address

  Jonathan.Niehof@unh.edu

• Start Date

  7/13/2023 12:00:00 AM

• First Name

  Matthew

• Last Name

  Young

• Email Address

  matthew.young@unh.edu

• Start Date

  7/13/2023 12:00:00 AM

• Text

  SOLAR-TERRESTRIAL

• Code

  1523

• Text

  SOLAR-TERRESTRIAL

• Code

  1523

• Text

  EXP PROG TO STIM COMP RES

• Code

  9150