Collaborative Research: A Next-Generation Model of the Corona and Solar Wind

Information

  • NSF Award
  • 1138256
Owner
  • Award Id
    1138256
  • Award Effective Date
    1/1/2011 - 13 years ago
  • Award Expiration Date
    8/31/2012 - 12 years ago
  • Award Amount
    $ 31,277.00
  • Award Instrument
    Standard Grant

Collaborative Research: A Next-Generation Model of the Corona and Solar Wind

The proposers will develop a strategic capability for solar physics modeling by combining SAIC's MAS code with Colorado's ENLIL code, which are among the most sophisticated models available today. Coupling MAS and ENLIL will deliver cutting-edge techniques for deriving time-dependent photospheric magnetic field data, as well as result in a GUI-driven product that will appeal broadly to the solar and heliospheric scientific community. The proposing team includes experts in solar magnetometry, surface flux evolution modeling, coronal and solar wind modeling, and computational physics. Their new model will encapsulate the capabilities of both MAS and ENLIL, as well as important improvements that will be developed and incorporated during the course of this work. <br/><br/>Observed photospheric magnetic fields are the primary boundary conditions to the MAS and ENLIL simulations, and their solar wind solutions are strongly dependent on these boundary conditions. Thus the proposed work includes detailed studies to improve the quality of this observational input. The proposers intend to drive their new model with time-dependent output from flux transport codes, allowing production of a real-time model of the solar wind which would be delivered to the Community Coordinated Modeling Center (CCMC). Ultimately, this model might replace the current Wang-Sheeley-Arge model at the National Weather Service's Space Environment Center in Boulder, Colorado. While global magnetohydrodynamic (MHD) models are, by necessity, complex, the proposers plan to minimize unnecessary complications for users by providing a uniform GUI interface with which to initiate model runs. The collaborators here will also provide a set of GUI tools for post-processing, analysis, and visualization of model output, since much of this work has already been done as part of previous and ongoing programs.

  • Program Officer
    Therese Moretto Jorgensen
  • Min Amd Letter Date
    5/11/2011 - 13 years ago
  • Max Amd Letter Date
    5/11/2011 - 13 years ago
  • ARRA Amount

Institutions

  • Name
    Predictive Science Incorporated
  • City
    San Diego
  • State
    CA
  • Country
    United States
  • Address
    9990 Mesa Rim Road
  • Postal Code
    921213933
  • Phone Number
    3039993801

Investigators

  • First Name
    Jon
  • Last Name
    Linker
  • Email Address
    linkerj@predsci.com
  • Start Date
    5/11/2011 12:00:00 AM