Physics – Plasma Physics
Scientific paper
Dec 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009agufmsh13b1513k&link_type=abstract
American Geophysical Union, Fall Meeting 2009, abstract #SH13B-1513
Physics
Plasma Physics
[2109] Interplanetary Physics / Discontinuities, [2134] Interplanetary Physics / Interplanetary Magnetic Fields, [2164] Interplanetary Physics / Solar Wind Plasma, [7811] Space Plasma Physics / Discontinuities
Scientific paper
Space weather modeling and forecasting techniques are important for a variety of applications, such as satellite operations,GPS navigation, magnetosphere and ionosphere modeling etc. The work described here is intended to help provide a better IMF data forecast near the Earth's magnetosphere by measurements at L1 Lagrange point. Theory, as well as observations made from different satellites simultaneously, shows that the interplanetary magnetic field (IMF) may consist of current layers and wave fronts along which changes in magnetic field are small in the scale of the diameter of the ACE satellite's orbit. The knowledge about current layers and wave fronts along which the changes of IMF are minimal would significantly improve IMF forecast near the Earth by measurements at L1 Lagrange point. Many methods have been developed to determine these structures using measurements at a single spacecraft, based on different fundamental properties of the solar wind and IMF. However, most solar wind parameters, such as density and velocity, cannot be measured with sufficient time resolution comparable with magnetic field measurements. For this reason, methods based on the magnetic field are most frequently used for practical calculations and forecasting. There are two known methods for IMF calculations, MVAB-0 and the upstream-downstream magnetic field cross-product method. In this work, we propose two new methods based on physical laws of the solar wind and magnetic field measurements. We demonstrate their usefulness through comparison of data on the ACE and WIND satellites over long continuous periods of time. We used model skill analysis base on RMS and correlation between the model and measurements. All of these methods depend on a series of 4-6 free parameters, depending on the method. We analyzed all free parameters across a wide range. All analysis was performed on massive parallel computers. Computations reveled that there is no set of constant parameters that allow optimum results across all different satellite positions and IMF parameters. Instead, we introduced the concept of stable areas in parameter space. These stable parameters provide satisfactory results for all time intervals. Model skill and correlation demonstrate irregular behavior in free parameter space. Analysis of this can help to improve the methods significantly if we can determine how free parameters should be chosen depending on measured solar wind conditions.
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