Plamen Muhtarov

A new method for reconstruction of the vertical electron density distribution in the upper ionosphere and plasmasphere

Ground-based ionosphere sounding measurements alone are incapable of reliably modeling the topside electron density distribution above the F layer peak density height. Such information can be derived from Global Positioning System (GPS)-based total electron content (TEC) measurements. A novel technique is presented for retrieving the electron density height profile from three types of measurements: ionosonde (foF2, foE, M3000F2, hmf2), TEC (GPS-based), and O+-H+ ion transition level. The method employs new formulae based on Chapman, sech-squared, and exponential ionosphere profilers to construct a system of equations, the solution of which system provides the unknown ion scale heights, sufficient to construct a unique electron density profile at the site of measurements. All formulae are based on the assumption of diffusive equilibrium with constant scale height for each ion species. The presented technique is most suitable for middle- and high-geomagnetic latitudes and possible applications include: development, evaluation, and improvement of theoretical and empirical ionospheric models, development of similar reconstruction methods utilizing low-earth-orbiting satellite measurements of TEC, operational reconstruction of the electron density on a real-time basis, etc.

Autocorrelation method for temporal interpolation and short-term prediction of ionospheric data

An autocorrelation method is developed for temporal interpolation and short-term prediction of ionospheric characteristics. The ionospheric data are considered as a realization of a periodic process with randomly dispersed measured values superimposed on it. The autocorrelation function or its nonnalized autocorrelation coefficients are determined from the measured data over a period of 20–30 days, and on that basis an autocorrelation model is obtained. This model is then used to interpolate the missing values in the monthly tables of ionospheric characteristics, here called “gaps.” The interpolation at a given hour is performed by calculating weighting coefficients for the neighboring measured values. The procedure selects those measurement values around the gap which have the highest autocorrelation coefficients. The model can be used to extrapolate (predict) the data, treating the prediction period (usually 24 hours) as a gap placed at the end of the available data. The method also calculates the so-called prediction error, which is found to be close to the standard deviation of the measured data. The interpolation and prediction error are estimated to be less than 12% in the case of ƒoF2.

Modeling of midlatitude F region response to geomagnetic activity

An empirical model is developed to describe the variations of midlatitude F region ionization along all longitudes within the dip latitude band (30°-55°N), induced by geomagnetic activity, by using the relative deviations (Φ) of the Fregion critical frequency f 0 F 2 from its monthly median. The geomagnetic activity is represented by the Kp index. The main statistical relationship between Φ and Kp is obtained by using 11 years of data from 26 midlatitude ionosondes. The statistical analysis reveals that the average dependence of Φ 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 Φ along local times can be assumed sinusoidal. A continuity equation is written for Φ with the production term being a function of Kp modulated by a sinusoidal function of local time and the loss term proportional to Φ with a loss coefficient β=1/T. A new, modified function of geomagnetic activity (K f ) is introduced, being proportional to Φ averaged over all longitudes. The model Φ is defined by two standing sinusoidal waves with periods of 24 and 12 hours, rotating synchronously with the Sun, modulated by the modified function K f . The wave amplitudes and phases, as well as their average offset, are obtained by fitting to the data. A new error estimate called prediction efficiency (Peff) is used, which assigns equal weights to the model errors at all deviations of data from medians. The prediction efficiency estimate gives a gain of accuracy of 29%.

Empirical modelling of ionospheric storms at midlatitudes

Abstract The reaction of the F-layer to geomagnetic storms is studied between 35° and 55° (dipole latitude) with as indicator the relative deviation of foF2 to its monthly median. A longitude/UT Fourier development yields the longitudinally averaged offset, the diurnal and the semidiurnal wave. These are evaluated in terms of the total energy input into the auroral thermosphere (“Power Index” P) as solutions of a continuity equation written for this ionospheric characteristic. Production, loss and drift terms are introduced in the equation, representing the main physical processes controlling the ionospheric disturbances during storms. The ionospheric characteristic is presented as the sum of the average offset and the slowly rotating standing wave. The expression matches the data satisfactorily for storms in the summer hemisphere, while in winter there is significant discrepancy, possibly as a consequence of interhemispheric influences.