Monitoring daily variations of atmospheric electric fields using data mining methods

The atmospheric electric field potential gradient is studied during snowfall, and the intensity of snowflakes electrifying depending on weather conditions is estimated. Applying modern data mining methods and high-mountain monitoring, where the anthropogenic factors on the electric field variations is insignificant, enables the identification of the influence of snowfall and snowstorms on the electric field's daily variations. Numerical data of the electrification process in the atmosphere are obtained, and relationships between electric field values and snowfall intensity, wind speed and temperature are demonstrated. Modern neural network techniques for data mining are applied in this context.