Modeling of midlatitude F region response to geomagnetic activity

Citation
I. Kutiev et P. Muhtarov, Modeling of midlatitude F region response to geomagnetic activity, J GEO R-S P, 106(A8), 2001, pp. 15501-15509
Citations number
10
Categorie Soggetti
Space Sciences
Journal title
JOURNAL OF GEOPHYSICAL RESEARCH-SPACE PHYSICS
ISSN journal
21699380 → ACNP
Volume
106
Issue
A8
Year of publication
2001
Pages
15501 - 15509
Database
ISI
SICI code
0148-0227(20010801)106:A8<15501:MOMFRR>2.0.ZU;2-5
Abstract
An empirical model is developed to describe the variations of midlatitude F region ionization along all longitudes within the dip latitude band (30 de grees -55 degreesN), induced by geomagnetic activity, by using the relative deviations (Phi) of the F region critical frequency f(o)F(2) from its mont hly median. The geomagnetic activity is represented by the Kp index. The ma in statistical relationship between Phi and Kp is obtained by using 11 year s of data from 26 midlatitude ionosondes. The statistical analysis reveals that the average dependence of Phi on Kp is quadratic, the average response of the ionosphere to geomagnetic forcing is delayed with a time constant T of about 18 hours, and the instantaneous distribution of Phi along local t imes can be assumed sinusoidal. A continuity equation is written for Phi wi th the "production term" being a function of Kp modulated by a sinusoidal f unction of local time and the "loss": term proportional to Phi with a loss coefficient beta =1/T. A new, modified function of geomagnetic activity (K- f) is introduced, being proportional to Phi averaged over all longitudes. T he model Phi is defined by two standing sinusoidal waves with periods of 24 and 12 hours, rotating synchronously with the Sun, modulated by the modifi ed function K-f. The wave amplitudes and phases, as well as their average o ffset, are obtained by fitting to the data. A new error estimate called "pr ediction efficiency" (Peff) is used, which assigns equal weights to the mod el errors at all deviations of data from medians. The prediction efficiency estimate gives a gain of accuracy of 29%.