Machine Learning Interpretability of Outer Radiation Belt Enhancement \& Depletion Events

We investigate the response of outer radiation belt electron fluxes to different solar wind and geomagnetic indices using an interpretable machine learning method. We reconstruct the electron flux variation during 19 enhancement and 7 depletion events and demonstrate a feature attribution analysis on the superposed epoch results for the first time. We find that the intensity and duration of the substorm sequence following an initial dropout determine the overall enhancement or depletion of electron fluxes, while the solar wind pressure drives the initial dropout in both types of events. Further statistical results from a dataset with 71 events confirm this and show a significant correlation between the resulting flux levels and the average AL index, indicating that the observed "depletion" event can be more accurately described as a "non-enhancement" event. Our novel SHAP-Enhanced Superposed Epoch Analysis (SHESEA) method can be used as an insight discovery tool in various physical systems

Opening the Black Box of the Radiation Belt Machine Learning Model

Many Machine Learning (ML) systems, especially neural networks, are fundamentally regarded as black boxes since it is difficult to grasp how they function once they have been trained. Here, we tackle the issue of the interpretability of a high-accuracy ML model created to model the flux of Earth's radiation belt electrons. The Outer RadIation belt Electron Neural net model (ORIENT) uses only solar wind conditions and geomagnetic indices as input. Using the Deep SHAPley additive explanations (DeepSHAP) method, we show that the `black box' ORIENT model can be successfully explained. Two significant electron flux enhancement events observed by Van Allen Probes during the storm interval of 17 to 18 March 2013 and non storm interval of 19 to 20 September 2013 are investigated using the DeepSHAP method. The results show that the feature importances calculated from the purely data driven ORIENT model identify physically meaningful behavior consistent with current physical understanding.Comment: Under revie

Science return of probing magnetospheric systems of ice giants

The magnetospheric systems of ice giants, as the ideal and the unique template of a typical class of exoplanets, have not been sufficiently studied in the past decade. The complexity of these asymmetric and extremely dynamic magnetospheres provides us a great chance to systematically investigate the general mechanism of driving the magnetospheres of such common exoplanets in the Universe, and the key factors of influencing the global and local magnetospheric structures of this type of planets. In this paper, we discuss the science return of probing magnetospheric systems of ice giants for the future missions, throughout different magnetospheric regions, across from the interaction with upstream solar wind to the downstream region of the magnetotail. We emphasize the importance of detecting the magnetospheric systems of ice giants in the next decades, which enables us to deeply understand the space enviroNMent and habitability of not only the ice giants themselves but also the analogous exoplanets which are widely distributed in the Universe

Multiple conjugate observations of magnetospheric fast flow bursts using THEMIS observations

Magnetotail earthward fast flow bursts can transport most magnetic flux and energy into the inner magnetosphere. These fast flow bursts are generally an order of magnitude higher than the typical convection speeds that are azimuthally localised (1&ndash;3&thinsp;RE) and are flanked by plasma vortices, which map to ionospheric plasma vortices of the same sense of rotation. This study uses a multipoint analysis of conjugate magnetospheric and ionospheric observations to investigate the magnetospheric and ionospheric responses to fast flow bursts that are associated with both substorms and pseudobreakups. We study in detail what properties control the differences in the magnetosphere&ndash;ionosphere responses between substorm fast flow bursts and pseudobreakup events, and how these differences lead to different ionospheric responses. The fast flow bursts and pseudobreakup events were observed by the Time History of Events and Macroscale Interaction during Substorms (THEMIS), while the primary ionospheric observations were made by all-sky cameras and magnetometer-based equivalent ionospheric currents. These events were selected when the satellites were at least 6&thinsp;RE from the Earth in radial distance and a magnetic local time (MLT) region of &plusmn;&thinsp;5&thinsp;h from local midnight. The results show that the magnetosphere and ionosphere responses to substorm fast flow bursts are much stronger and more structured compared to pseudobreakups, which are more likely to be localised, transient and weak in the magnetosphere. The magnetic flux in the tail is much stronger for strong substorms and much weaker for pseudobreakup events. The Blobe decreases significantly for substorm fast flow bursts compared to pseudobreakup events. The curvature force density for pseudobreakups are much smaller than substorm fast flow events, indicating that the pseudobreakups may not be able to penetrate deep into the inner magnetosphere. This association can help us study the properties and activity of the magnetospheric earthward flow vortices from ground data. &nbsp;</p

Evaluating the performance of empirical models of total electron density and whistler-mode wave amplitude in the Earth’s inner magnetosphere

Empirical models have been previously developed using the large dataset of satellite observations to obtain the global distributions of total electron density and whistler-mode wave power, which are important in modeling radiation belt dynamics. In this paper, we apply the empirical models to construct the total electron density and the wave amplitudes of chorus and hiss, and compare them with the observations along Van Allen Probes orbits to evaluate the model performance. The empirical models are constructed using the Hp30 and SME (or SML) indices. The total electron density model provides an overall high correlation coefficient with observations, while large deviations are found in the dynamic regions near the plasmapause or in the plumes. The chorus wave model generally agrees with observations when the plasma trough region is correctly modeled and for modest wave amplitudes of 10–100 pT. The model overestimates the wave amplitude when the chorus is not observed or weak, and underestimates the wave amplitude when a large-amplitude chorus is observed. Similarly, the hiss wave model has good performance inside the plasmasphere when modest wave amplitudes are observed. However, when the modeled plasmapause location does not agree with the observation, the model misidentifies the chorus and hiss waves compared to observations, and large modeling errors occur. In addition, strong (&gt;200 pT) hiss waves are observed in the plumes, which are difficult to capture using the empirical model due to their transient nature and relatively poor sampling statistics. We also evaluate four metrics for different empirical models parameterized by different indices. Among the tested models, the empirical model considering a plasmapause and controlled by Hp* (the maximum Hp30 during the previous 24 h) and SME* (the maximum SME during the previous 3 h) or Hp* and SML has the best performance with low errors and high correlation coefficients. Our study indicates that the empirical models are applicable for predicting density and whistler-mode waves with modest power, but large errors could occur, especially near the highly-dynamic plasmapause or in the plumes

Deep learning model of hiss waves in the plasmasphere and plumes and their effects on radiation belt electrons

Hiss waves play an important role in removing energetic electrons from Earth’s radiation belts by precipitating them into the upper atmosphere. Compared to plasmaspheric hiss that has been studied extensively, the evolution and effects of plume hiss are less understood due to the challenge of obtaining their global observations at high cadence. In this study, we use a neural network approach to model the global evolution of both the total electron density and the hiss wave amplitudes in the plasmasphere and plume. After describing the model development, we apply the model to a storm event that occurred on 14 May 2019 and find that the hiss wave amplitude first increased at dawn and then shifted towards dusk, where it was further excited within a narrow region of high density, namely, a plasmaspheric plume. During the recovery phase of the storm, the plume rotated and wrapped around Earth, while the hiss wave amplitude decayed quickly over the nightside. Moreover, we simulated the overall energetic electron evolution during this storm event, and the simulated flux decay rate agrees well with the observations. By separating the modeled plasmaspheric and plume hiss waves, we quantified the effect of plume hiss on energetic electron dynamics. Our simulation demonstrates that, under relatively quiet geomagnetic conditions, the region with plume hiss can vary from L = 4 to 6 and can account for up to an 80% decrease in electron fluxes at hundreds of keV at L &gt; 4 over 3 days. This study highlights the importance of including the dynamic hiss distribution in future simulations of radiation belt electron dynamics

Plasma Imaging, LOcal Measurement, and Tomographic experiment (PILOT): a mission concept for transformational multi-scale observations of mass and energy flow dynamics in Earth’s magnetosphere

We currently do not understand the fundamental physical processes that govern mass and energy flow through the Earth’s magnetosphere. Knowledge of these processes is critical to understanding the mass loss rate of Earth’s atmosphere, as well as for determining the role that a planetary magnetic field plays in atmospheric retention, and therefore habitability, for Earth-like planets beyond the solar system. Mass and energy flow processes are challenging to determine at Earth in part because Earth’s planetary magnetic field creates a complex “system of systems” composed of interdependent plasma populations and overlapping spatial regions that perpetually exchange mass and energy across a broad range of temporal and spatial scales. Further, the primary mass carrier in the magnetosphere is cold plasma (as cold as ∼0.1 eV), which is invisible to many space-borne instruments that operate in the inner magnetosphere. The Plasma Imaging LOcal and Tomographic experiment (PILOT) mission concept, described here, provides the transformational multi-scale observations required to answer fundamental open questions about mass and energy flow dynamics in the Earth’s magnetosphere. PILOT uses a constellation of spacecraft to make radio tomographic, remote sensing, and in-situ measurements simultaneously, fully capturing cold plasma mass dynamics and its impact on magnetospheric systems over an unprecedented range of spatial and temporal scales. This article details the scientific motivation for the PILOT mission concept as well as a potential mission implementation.AGS-1845151 - National Science FoundationPublished versio

Apoptotic Engulfment Pathway and Schizophrenia

Background: Apoptosis has been speculated to be involved in schizophrenia. In a previously study, we reported the association of the MEGF10 gene with the disease. In this study, we followed the apoptotic engulfment pathway involving the MEGF10, GULP1, ABCA1 and ABCA7 genes and tested their association with the disease. Methodology/Principal Findings: Ten, eleven and five SNPs were genotyped in the GULP1, ABCA1 and ABCA7 genes respectively for the ISHDSF and ICCSS samples. In all 3 genes, we observed nominally significant associations. Rs2004888 at GULP1 was significant in both ISHDSF and ICCSS samples (p = 0.0083 and 0.0437 respectively). We sought replication in independent samples for this marker and found highly significant association (p = 0.0003) in 3 Caucasian replication samples. But it was not significant in the 2 Chinese replication samples. In addition, we found a significant 2-marker (rs2242436 * rs3858075) interaction between the ABCA1 and ABCA7 genes in the ISHDSF sample (p = 0.0022) and a 3-marker interaction (rs246896 * rs4522565 * rs3858075) amongst the MEGF10, GULP1 and ABCA1 genes in the ICCSS sample (p = 0.0120). Rs3858075 in the ABCA1 gene was involved in both 2- and 3-marker interactions in the two samples. Conclusions/Significance: From these data, we concluded that the GULP1 gene and the apoptotic engulfment pathway are involved in schizophrenia in subjects of European ancestry and multiple genes in the pathway may interactively increase the risks to the disease. © 2009 Chen et al

Configuration and Generation of Substorm Current Wedge

The substorm current wedge (SCW), a core element of substorm dynamics coupling the magnetotail to the ionosphere, is crucial in understanding substorms. It has been suggested that the field-aligned currents (FACs) in the SCW are caused by either pressure gradients or flow vortices, or both. Our understanding of FAC generations is based predominately on numerical simulations, because it has not been possible to organize spacecraft observations in a coordinate system determined by the SCW. This dissertation develops an empirical inversion model of the current wedge and inverts midlatitude magnetometer data to obtain the parameters of the current wedge for three solar cycles. This database enables statistical data analysis of spacecraft plasma and magnetic field observations relative to the SCW coordinate. In chapter 2, a new midlatitude positive bay (MPB) index is developed and calculated for three solar cycles of data. The MPB index is processed to determine the substorm onset time, which is shown to correspond to the auroral breakup onset with at most 1-2 minutes difference. Substorm occurrence rate is found to depend on solar wind speed while substorm duration is rather constant, suggesting that substorm process has an intrinsic pattern independent of external driving. In chapter 3, an SCW inversion technique is developed to determine the strength and locations of the FACs in an SCW. The inversion parameters for FAC strength and location, and ring current strength are validated by comparison with other measurements. In chapter 4, the connection between earthward flows and auroral poleward expansion is examined using improved mapping, obtained from a newly-developed dynamic magnetospheric model by superimposing a standard magnetospheric field model with substorm current wedge obtained from the inversion technique. It is shown that the ionospheric projection of flows observed at a fixed point in the equatorial plane map to the bright aurora as it expands poleward, suggesting that auroral poleward expansion is mainly a consequence of magnetic dipolarization caused by the SCW. Chapter 5 shows that increased plasma pressure caused by flow braking has a temporal pattern similar to that of the currents in the SCW. In contrast, flow vortices vanish quickly, suggesting that pressure gradient is an important factor in generating the SCW. The measured pressure gradients are found to be organized relative to SCW central meridian. Nonalignment between pressure gradient and flux tube volume gradient lead to the generation of an SCW with quadrupole FACs (inner and outer loop of FACs). Because the inner current loop is weaker than the outer loop, the combined magnetic effect of the two current loops is similar to a classic SCW. The final chapter studies the magnetic flux transport by earthward flows, and accumulated inside the SCW and enclosed within auroral poleward boundary. Their good agreement suggests that flux accumulation causes magnetic dipolarization and auroral poleward expansion. The strength of the SCW is positively correlated with the amount of magnetic flux accumulated