Hiss in the plasmasphere and plumes: Global distribution from machine learning techniques and their effects on the loss of energetic electrons

Hiss is a broadband whistler mode emission that can pitch angle scatter electrons from tens of keV up to ~ 1 MeV, and thus is critical to the Earth's radiation belt dynamics. Hiss typically occurs in the Earth's plasmasphere and plume region. Contrary to what was shown in previous empirical models where the plasmasphere and the plume are not separately identified, recent studies show that hiss occurrence rates are higher and wave amplitudes are stronger in the plume than those inside the plasmasphere. As a result, without considering the dynamic evolution of both plume regions and hiss distribution, it is difficult to quantify the hiss effects on energetic electron dynamics on a global scale.

In this work, we use a Recurrent Neural Network (RNN) to construct the global evolution of electron density and hiss wave amplitude using geomagnetic indices and satellite location as inputs. We examine the model performance by comparing to the global electron density distribution inferred from the IMAGE EUV observation and GPS TEC observation. By explicitly taking time evolution into consideration, our model shows smooth and clear plume evolution, as well as enhanced plume hiss associated with it. We separately evaluate the hiss effects in the plasmasphere and the plume on the global energetic electron loss using the 3D Fokker Planck simulation, and discuss the importance of including plume hiss in the radiation belt modeling.