Statistics – Applications
Scientific paper
Dec 1996
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1996esasp.392..241k&link_type=abstract
Environment Modelling for Space-based Applications, Symposium Proceedings (ESA SP-392). ESTEC Noordwijk, 18-20 September 1996. E
Statistics
Applications
Scientific paper
An important aspect of space weather applications is the specification of the magnetic field structure and forecasting its dynamical development. The two most widely used approaches to determine the magnetic field configuration, empirical magnetic field models and MHD simulations, both have their strengths and weaknesses. Although self-consistent MHD models yield a more complete description of the physical variables, their representation of the inner magnetosphere is still in a developing stage. Furthermore, the extensive computer resources required makes them impractical for forecasting applications even with the best facilities available at present. Empirical models, for example those developed by Tsyganenko, do not directly answer questions about plasma dynamics, but are easy and fast to use. In addition, the statistical models are sufficiently flexible so that they can be adjusted to fit the actually observed magnetic field properties. We discuss the time-evolving extension of the Tsyganenko models developed by Pulkkinen et al. (1992). This method involves several adjustable parameters which describe the field configuration in the inner magnetosphere during disturbed conditions. The parameter values are found through a minimization procedure using in-situ magnetic field measurements. We discuss the model results during a strongly disturbed storm period, and show that the model is consistent also with auroral observations that were not used as model input. As such, the method is readily available for use of post-event analysis of spacecraft hazards. We suggest that future work should be directed to determining the model parameters (and thus the magnetic field configuration) from advance warning measurements (such as solar wind parameters, Dst, or other available data), in order to develop the model to have also predictive capability for operative use. Reference: T. I. Pulkkinen et al., J. Geophys. Res., vol. 97, 19283-19297, 1992.
Koskinen Hannu E. J.
Pulkkinen Tuija I.
No associations
LandOfFree
Time Evolving Magnetic Field Modelling at Geostationary Distances does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Time Evolving Magnetic Field Modelling at Geostationary Distances, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Time Evolving Magnetic Field Modelling at Geostationary Distances will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1499926