Airborne Atmospheric Electrical Measurements of the Variation of Ionospheric Potential and Electrical Structure in the Exchange Layer Over the Ocean

Abstract

The temporal variation of ionospheric potential was investigated by airplane potential gradient soundings and extended duration constant altitude potential gradient measurements to investigate the classical picture of atmospheric electricity. Soundings provided an estimate of ionospheric potential magnitude; constant level data indicated variation. In a low noise environment, above the inversion, utilizing one day’s data, diurnal change in potential gradient at constant altitude was clearly seen and in phase with the Carnegie curve. Typically, because of environmental noise, ground level measurements on land or sea must be averaged over many days for this pattern to emerge. A day-long comparison of potential gradient above the inversion with similar measurements of air-earth current density by R. V. Anderson, 7000 km away, showed high correlation. This suggests the ionosphere is an equi-potential surface in accordance with the classical picture. From 120 potential gradient profiles obtained mostly over the ocean, the average estimate of ionospheric potential was 241 kV; corrected for diurnal variation it was 219 kV. Measurements indicate that daily variation of ionospheric potential has not changed over the last four decades. Details of space charge densities over land and sea were also obtained. A relatively dense positive space charge layer existed in the lowest 150 m over the ocean; transported upward by convection, this establishes electric field variations from which circulation patterns in the exchange layer were deduced. Convection of positive space charge over large portions of the world’s oceans may help the global generator, thunderstorms, maintain the ionospheric potential.KeywordsPotential GradientScale HeightExchange LayerEquipotential SurfaceSpace Charge DensityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.