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Electron acceleration at Saturn due to whistler mode chorus waves has previously been assumed to be ineffective; new data closer to the planet show it can be very rapid (factor of 104 flux increase at 1 MeV in 10 days compared to factor of 2). A full survey of chorus waves at Saturn is combined with an improved plasma density model to show that where the plasma frequency falls below the gyrofrequency additional strong resonances are observed favoring electron acceleration. This results in strong chorus acceleration between approximately 2.5 R-S and 5.5 R-S outside which adiabatic transport may dominate. Strong pitch angle dependence results in butterfly pitch angle distributions that flatten over a few days at 100s keV, tens of days at MeV energies which may explain observations of butterfly distributions of MeV electrons near L = 3. Including cross terms in the simulations increases the tendency toward butterfly distributions. Plain Language Summary Radiation belts are hazardous regions found around several of the planets in our Solar System. They consist of very hot, electrically charged particles trapped in the magnetic field of the planet. At Saturn the most important way to heat these particles has for many years been thought to involve the particles drifting closer toward the planet. This paper adds to the emerging idea at Saturn that a different way to heat the particles is also possible where the heating is done by waves, in a similar way to what we find at the Earth. We use recent information from the Cassini spacecraft on the number and location of particles and also of the waves strength and location combined with computer simulations to show that a particular wave called chorus is excellent at heating the particles where the surrounding number of cold particles is low.
Pitch Angle Scattering of Sub-MeV Relativistic Electrons by Electromagnetic Ion Cyclotron Waves
(2019)
Electromagnetic ion cyclotron (EMIC) waves have long been considered to be a significant loss mechanism for relativistic electrons. This has most often been attributed to resonant interactions with the highest amplitude waves. But recent observations have suggested that the dominant energy of electrons precipitated to the atmosphere may often be relatively low, less than 1 MeV, whereas the minimum resonant energy of the highest amplitude waves is often greater than 2 MeV. Here we use relativistic electron test particle simulations in the wavefields of a hybrid code simulation of EMIC waves in dipole geometry in order to show that significant pitch angle scattering can occur due to interaction with low-amplitude short-wavelength EMIC waves. In the case we examined, these waves are in the H band (at frequencies above the He+ gyrofrequency), even though the highest amplitude waves were in the He band frequency range (below the He+ gyrofrequency). We also present wave power distributions for 29 EMIC simulations in straight magnetic field line geometry that show that the high wave number portion of the spectrum is in every case mostly due to the H band waves. Though He band waves are often associated with relativistic electron precipitation, it is possible that the He band waves do not directly scatter the sub-megaelectron volts (sub-MeV) electrons, but that the presence of He band waves is associated with high plasma density which lowers the minimum resonant energy so that these electrons can more easily resonate with the H band waves.
Current algorithms for the real-time prediction of the Kp index use a combination of models empirically driven by solar wind measurements at the L1 Lagrange point and historical values of the index. In this study, we explore the limitations of this approach, examining the forecast for short and long lead times using measurements at L1 and Kp time series as input to artificial neural networks. We explore the relative efficiency of the solar wind-based predictions, predictions based on recurrence, and predictions based on persistence. Our modeling results show that for short-term forecasts of approximately half a day, the addition of the historical values of Kp to the measured solar wind values provides a barely noticeable improvement. For a longer-term forecast of more than 2 days, predictions can be made using recurrence only, while solar wind measurements provide very little improvement for a forecast with long horizon times. We also examine predictions for disturbed and quiet geomagnetic activity conditions. Our results show that the paucity of historical measurements of the solar wind for high Kp results in a lower accuracy of predictions during disturbed conditions. Rebalancing of input data can help tailor the predictions for more disturbed conditions.
The Kp index is a measure of the midlatitude global geomagnetic activity and represents short-term magnetic variations driven by solar wind plasma and interplanetary magnetic field. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere and the radiation belts. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast Kp, based their inferences on the recent history of Kp and on solar wind measurements at L1. In this study, we systematically test how different machine learning techniques perform on the task of nowcasting and forecasting Kp for prediction horizons of up to 12 hr. Additionally, we investigate different methods of machine learning and information theory for selecting the optimal inputs to a predictive model. We illustrate how these methods can be applied to select the most important inputs to a predictive model of Kp and to significantly reduce input dimensionality. We compare our best performing models based on a reduced set of optimal inputs with the existing models of Kp, using different test intervals, and show how this selection can affect model performance.
Storm Time Depletions of Multi-MeV Radiation Belt Electrons Observed at Different Pitch Angles
(2019)
During geomagnetic storms, the rapid depletion of the high-energy (several MeV) outer radiation belt electrons is the result of loss to the interplanetary medium through the magnetopause, outward radial diffusion, and loss to the atmosphere due to wave-particle interactions. We have performed a statistical study of 110 storms using pitch angle resolved electron flux measurements from the Van Allen Probes mission and found that inside of the radiation belt (L* = 3 - 5) the number of storms that result in depletion of electrons with equatorial pitch angle alpha(eq) = 30 degrees is higher than number of storms that result in depletion of electrons with equatorial pitch angle alpha(eq) = 75 degrees. We conclude that this result is consistent with electron scattering by whistler and electromagnetic ion cyclotron waves. At the outer edge of the radiation belt (L* >= 5.2) the number of storms that result in depletion is also large (similar to 40-50%), emphasizing the significance of the magnetopause shadowing effect and outward radial transport.
Understanding of wave environments is critical for the understanding of how particles are accelerated and lost in space. This study shows that in the vicinity of Europa and Ganymede, that respectively have induced and internal magnetic fields, chorus wave power is significantly increased. The observed enhancements are persistent and exceed median values of wave activity by up to 6 orders of magnitude for Ganymede. Produced waves may have a pronounced effect on the acceleration and loss of particles in the Jovian magnetosphere and other astrophysical objects. The generated waves are capable of significantly modifying the energetic particle environment, accelerating particles to very high energies, or producing depletions in phase space density. Observations of Jupiter's magnetosphere provide a unique opportunity to observe how objects with an internal magnetic field can interact with particles trapped in magnetic fields of larger scale objects.
We present the PINE (Plasma density in the Inner magnetosphere Neural network‐based Empirical) model ‐ a new empirical model for reconstructing the global dynamics of the cold plasma density distribution based only on solar wind data and geomagnetic indices. Utilizing the density database obtained using the NURD (Neural‐network‐based Upper hybrid Resonance Determination) algorithm for the period of 1 October 2012 to 1 July 2016, in conjunction with solar wind data and geomagnetic indices, we develop a neural network model that is capable of globally reconstructing the dynamics of the cold plasma density distribution for 2≤L≤6 and all local times. We validate and test the model by measuring its performance on independent data sets withheld from the training set and by comparing the model‐predicted global evolution with global images of He+ distribution in the Earth's plasmasphere from the IMAGE Extreme UltraViolet (EUV) instrument. We identify the parameters that best quantify the plasmasphere dynamics by training and comparing multiple neural networks with different combinations of input parameters (geomagnetic indices, solar wind data, and different durations of their time history). The optimal model is based on the 96 h time history of Kp, AE, SYM‐H, and F10.7 indices. The model successfully reproduces erosion of the plasmasphere on the nightside and plume formation and evolution. We demonstrate results of both local and global plasma density reconstruction. This study illustrates how global dynamics can be reconstructed from local in situ observations by using machine learning techniques.
We present the dependence of the magnetosonic wave amplitudes both outside and inside the plasmapause on the solar wind and AE index using Van Allen Probe-A spacecraft during the time period of 1 October 2012 to 31 December 2015, based on a correlation and regression analysis. Solar wind parameters considered are the southward interplanetary magnetic field (IMF B-S), solar wind number density (N-SW), and bulk speed (V-SW). We find that the wave amplitudes outside (inside) the plasmapause are well correlated with the preceding AE, IMF B-S, and N-SW with time delays, each corresponding to 2-3 h (3-4 h), 4-5 h (3-4 h), and 2-3 h (8-9 h), while the correlation with V-SW is ambiguous both inside and outside the plasmapause. As measured by the correlation coefficient, the IMF B-S is the most influential solar wind parameter that affects the dayside wave amplitudes both outside and inside the plasmapause, while N-SW contributes to enhancing the duskside waves outside the plasmapause. The AE effect on wave amplitudes is comparable to that of IMF B-S. More interestingly, regression with time histories of the solar wind parameters and the AE index preceding the wave measurements outside the plasmapause shows significant dependence on the IMF B-S, N-SW, and AE: the region of peak coefficients is changed with time delay for IMF B-S and AE, while isolated peaks around duskside remain gradually decrease with time for N-SW. In addition, the regression with magnetosonic waves inside the plasmapause shows high coefficients around prenoon sector with preceding IMF B-S and V-SW.
Electromagnetic ion cyclotron (EMIC) waves play an important role in the dynamics of ultrarelativistic electron population in the radiation belts. However, as EMIC waves are very sporadic, developing a parameterization of such wave properties is a challenging task. Currently, there are no dynamic, activity-dependent models of EMIC waves that can be used in the long-term (several months) simulations, which makes the quantitative modeling of the radiation belt dynamics incomplete. In this study, we investigate Kp, Dst, and AE indices, solar wind speed, and dynamic pressure as possible parameters of EMIC wave presence. The EMIC waves are included in the long-term simulations (1year, including different geomagnetic activity) performed with the Versatile Electron Radiation Belt code, and we compare results of the simulation with the Van Allen Probes observations. The comparison shows that modeling with EMIC waves, parameterized by solar wind dynamic pressure, provides a better agreement with the observations among considered parameterizations. The simulation with EMIC waves improves the dynamics of ultrarelativistic fluxes and reproduces the formation of the local minimum in the phase space density profiles.
Up until recently, signatures of the ultrarelativistic electron loss driven by electromagnetic ion cyclotron (EMIC) waves in the Earth's outer radiation belt have been limited to direct or indirect measurements of electron precipitation or the narrowing of normalized pitch angle distributions in the heart of the belt. In this study, we demonstrate additional observational evidence of ultrarelativistic electron loss that can be driven by resonant interaction with EMIC waves. We analyzed the profiles derived from Van Allen Probe particle data as a function of time and three adiabatic invariants between 9 October and 29 November 2012. New local minimums in the profiles are accompanied by the narrowing of normalized pitch angle distributions and ground‐based detection of EMIC waves. Such a correlation may be indicative of ultrarelativistic electron precipitation into the Earth's atmosphere caused by resonance with EMIC waves.