PI: Aaron Ridley / University of Michigan - The Community-based Whole Magnetosphere Model
Next Team Meeting:
PI: Joachim Raeder / University of New Hampshire -Development and Validation of a Comprehensive Magnetosphere Ionosphere Model
Next Team Meeting:
The first strategic goal is a comprehensive, coupled, quantitative 3D model that predicts plasma and magnetic field conditions for both inner and outer magnetosphere, including the plasmasphere, ring current, and radiation belts, and the ionosphere, including polar regions.
Expected features of such a model include:
- The use of Interplanetary Magnetic Field (IMF) and solar wind data from L1 monitors or from heliospheric prediction models and F10.7 or some other EUV proxy as input;
- 3D magnetic and electric fields determined from the bow shock to the ionospheric E region at all latitudes (this implicitly requires proper kinetic treatment of the ring current);
- Determination of the electron density in the ionosphere and plasmasphere (this A.30-3 implicitly requires a comprehensive ionosphere-thermosphere model that includes forcing from below through tides and gravity waves);
- Determination of radiation belt electron and ion populations;
- Determination of ionospheric currents and the resulting ground magnetic perturbations;
- The ability to handle the worst known magnetic storm conditions in a numerically robust manner;
- The ability to be executed in real time with reasonable computer resources;
- Use of established metrics and skill scores for the primary predicted quantities, in particular total electron content (TEC), radiation belt fluxes, and ground perturbations; and
- Ability to deliver a working version, with rigorous evaluation and validation procedures, to the CCMC and/or other NASA LWS or NSF centers within 3-5 years.
Desirable features of such a model include:
- Ability to employ input from several SW/IMF monitors;
- Ability to describe ionospheric ion outflow and multiple ion species in the outer magnetosphere, ring current, and plasmasphere;
- Ability to automatically assess output quality through concurrent real time data; and
- Ability to assimilate data.
