Physics
Scientific paper
Dec 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004agufmsa51b0244s&link_type=abstract
American Geophysical Union, Fall Meeting 2004, abstract #SA51B-0244
Physics
2447 Modeling And Forecasting, 2722 Forecasting, 2740 Magnetospheric Configuration And Dynamics, 2788 Storms And Substorms
Scientific paper
One key characterization of the global state of the magnetosphere is the extent to which the Earth's magnetotail is stretched from a dipolar configuration. When the geosynchronous GOES satellites are on the nightside of the Earth, they directly measure that stretching, at least at one particular local time. GOES magnetometer data has been made available in real time by NOAA's Space Data Center. We have correlated the degree of magnetotail stretching (specifically, T=atan(v/h), where v and h are the usual magnetic components) with Kp, and the low-latitude extent of ion precipitation, b2i, to provide real time nowcasts of the latter two quantities. The correlation between the real-time GOES measurements and Kp ranges between 0.4 and 0.75, depending on the local time of GOES. We emphasize that the degree of magnetotail stretching is a more fundamental characterization of the state of the magnetosphere than is Kp, and thus the moderate correlation likely says more about the extent to which Kp can characterize the magnetosphere than the limitations of the GOES measurements. The major limitation of the magnetotail stretching index is that it varies with local time, but is measured at only one local time. By converting the GOES measurements to an equivalent Kp, therefore, the major purpose is merely to translate the level of activity into a scale familiar to most operational space weather forecasters. The real time measurements of magnetotail stretching are available graphically on our web site at http://sd-www.jhuapl.edu/Aurora/goes_realtime/index.cgi along with movies showing how the magnetotail stretching has varied recently. The result is a representation of the magnetotail stretching data in a format convenient for space weather forecasters.
Meng Chun
Newell Patrick T.
Sotirelis Thomas
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