GLOBAL AND LOCAL VARIATIONS OF THE ELECTRIC FIELD IN THE SURFACE ELECTRODE LAYER
Abstract
The paper presents a mathematical model of the atmospheric surface electrode layer structure, taking into account the combined action of global and local electric field generators. Spatiotemporal modeling is based on the conjugation of harmonic trigonometric functions of the diurnal cycle for local turbulent exchange and for the global total current density. When modeling the behavior of the electric field, analytical solutions of the electrode effect equations in the atmosphere are used. The proposed approach consists of a step-by-step substitution of the total electric current density and the turbulent diffusion coefficient instantaneous values, obtained from the equations of their periodic variation for a specific hour of the day, into analytical formulas for the stationary spatial distribution of the turbulent electrode layer characteristics. The validity of using the quasi-stationary approximation is strictly substantiated by the significant difference (by more than two orders of magnitude) between the time scales of establishing electrical equilibrium in the medium and the period of the global current generator diurnal variation. It was established that the combined modeling mode adequately reproduces the synergistic expansion of the electric field strength (potential gradient) diurnal curve range and the deformation of its profile, characteristic of the summer season in the high mountains. The reliability of the obtained theoretical results was confirmed by their comparison with experimental data from in-situ measurements at the alpine station of Peak Cheget (430 16' N and 420 30' E), located in the Elbrus region at altitudes of 3040 m above sea level. The analysis demonstrated good quantitative and chronological agreement between the calculated extremes values and the observed diurnal variations in electric field during the summer season. The results obtained can be directly used to improve the accuracy of geophysical monitoring data interpretation
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