Hiss in the Plasmasphere and Plumes: Global Distribution From Machine Learning Technique and Their Effects on Global Loss of Energetic Electrons

Abstract:

Whistler mode hiss waves are typically observed inside the plasmasphere and plumes, and are known to play an important role in energetic electron loss processes in the Earth’s inner magnetosphere. In particular, hiss in plumes is previously shown to be stronger than the waves inside the plasmasphere; however, it has been challenging to achieve the dynamic evolution of hiss inside the plumes on a global scale. We use machine learning technique, more specifically, artificial neural network (ANN) to construct the global evolution of total electron density and hiss wave amplitude inside the plasmasphere and plume and the associated hiss waves therein. These constructed hiss wave models are used to quantify the effects of hiss on the global electron loss at L < 6 using the 3D Fokker Planck simulation. We demonstrate that neural network is able to reconstruct the dynamic evolution of total electron density and hiss inside the plasmasphere and plume. Moreover, the simulation result indicates that plume hiss can cause an efficient loss of energetic electrons in the outer radiation belt.