Search

In this study, field‐aligned currents (FACs) and ionospheric electric fields on different spatial scales are investigated through the analysis of FAC data from the Swarm satellites and electric field data from the Dynamic Explorer 2, respectively, from all seasons and under all solar wind conditions and varying levels of solar activity. Distributions of the average and variable components of FAC and electric field are the main focuses of this study, where the FAC variability is represented by the standard deviation of FAC in each magnetic latitude/magnetic local time bin and electric field variability is represented by the square root of the sum of squares of standard deviations of magnetic eastward and equatorward components of the electric field. We found that the mean patterns of the FAC and electric field are mainly contributed by the large‐scale (wavelength: ⩾500 km) FAC and electric field. Unlike the average, in addition to the large scale, variabilities of FAC and electric field are not negligible on mesoscale (wavelength: 100–500 km) and small scale (wavelength: 8–100 km), while the FAC variability shows a different scale dependence from the electric field variability. Specifically, for decreasing scale sizes, the FAC variability increases while the electric field variability decreases, suggesting that the strong FACs on small scale and mesoscale do not necessarily correspond to strong ionospheric electric fields on those scales. Further, FAC variabilities on large scale and mesoscale are included into the Global Ionosphere Thermosphere Model (GITM) and the corresponding impacts on Joule heating have been assessed. It was found that, for the conditions studied here, the large‐scale FAC variability may significantly increase the Joule heating (~160% globally) and that the enhancement due to the mesoscale FAC variability is not negligible (~36% globally). FACs and ionospheric electric fields are investigated on different scalesStrong FACs on small scale and mesoscale do not necessarily correspond to strong ionospheric electric fields on those scalesThe Joule heating can be enhanced by ~36% associated with the mesoscale FAC variability for the conditions studied here

We report a new modeling capability that self‐consistently couples physics‐based magnetospheric electron precipitation with its impact on the ionosphere. Specifically, the ring current model RAM‐SCBE is two‐way coupled to an ionospheric electron transport model GLOW (GLobal airglOW), representing a significant improvement over previous models, in which the ionosphere is either treated as a 2‐D spherical boundary of the magnetosphere or is driven by empirical precipitation models that are incapable of capturing small‐scale, transient variations. The new model enables us to study the impact of substorm‐associated, spectrum‐resolved electron precipitation on the 3‐D ionosphere. We found that after each substorm injection, a high‐energy tail of precipitation is produced in the dawn sector outside the plasmapause, by energetic electrons (10 < E< 100 keV) scattered by whistler‐mode chorus waves. Consequently, an ionospheric sublayer characterized by enhanced Pedersen conductivity arises at unusually low altitude (∼85 km), with its latitudinal width of ∼5–10° in the auroral zone. The sublayer structure appears intermittently, in correlation with recurrent substorm injections. It propagates eastward from the nightside to the dayside in the same drift direction of source electrons injected from the plasma sheet, resulting in global impact within the ionosphere. This study demonstrates the model's capability of revealing complex cross‐scale interactions in the geospace environment. Understanding the variability within the near‐Earth magnetosphere‐ionosphere‐thermosphere system is not only a scientific goal but also a critical need for reliable nowcasting and forcasting of hazardous space weather. The system is fully coupled in a variety of ways that challenge our current modeling and observational capabilities. In order to unify the ionospheric and magnetospheric dynamics and their interactions, we report a latest modeling effort that self‐consistently couples the magnetospheric particle precipitation with its impact on the ionosphere. This model significantly advances the consistency of the models, providing the opportunity to study the 3‐D ionospheric variability and associated transient magnetospheric drivers. With this new tool, we find that earthward particle injections in the magnetosphere result in energetic electron precipitation with 10 < E< 100 keV, which cause intense ionization and a transient sublayer with enhanced electric conductivity at unusually low altitudes near 85 km. The layer develops in a global manner that may change the traditional pattern of current closure within the geospace system. Our new model demonstrates a capability of revealing the complex cross‐scale interactions within the near‐Earth environment. Ring current model RAM‐SCBE is coupled to an ionospheric electron transport code GLOW to study the impact of precipitation on the ionosphereElectron precipitation with high‐energy tail produced by chorus wave scattering during substorms creates Dregion conductivity sublayerThe sublayer intermittently arises, correlated with recurrent substorms; it propagates eastward along with the drifting sources

For the first time we derive an analytical expression for energy deposition by propagating monochromatic Alfvén waves in the collisional ionosphere‐thermosphere (IT). Based on empirical models of IT parameters, we show an approximately 10% increase in efficiency of energy deposition at high latitudes and about 150 km altitude by Alfvén waves at 5 Hz as compared to static fields of the same magnitude. We analyze the dependence of the wave energy deposition on geomagnetic activity through a Global Ionosphere‐Thermosphere Model (GITM) simulation of IT conditions during the 13–14 October 2016 geomagnetic storm. The peak Alfvén wave contribution occurs in the Elayer and lower part of the Flayer. Wave‐induced heating is shown to increase in the daytime and postdusk high‐latitude Flayer during the storm due to increased wave‐modified conductivity. We estimate that the Alfvén wave contribution to the IT energy budget can reach about 30% of the value of static Joule heating during a strong storm and that the actual percentage increase is dependent on latitude and altitude. This effect carries important implications for ionospheric dynamics, especially for density enhancement in the daytime cusp, heating in the vicinity of auroral arcs and ion outflow. An analytical expression for energy deposition by propagating Alfvén waves in the collisional ionosphere‐thermosphere is derivedThe relative efficiency of energy deposition rate of Alfvén wave (up to 5 Hz in frequency) to static field is estimated to be ∼10% at high latitudes and below 250 km altitudeWe show that Alfvén wave energy deposition can reach about 30% of the value of static Joule heating during a strong storm

The challenges faced by science, engineering, and society are increasingly complex, requiring broad, cross-disciplinary teams to contribute to collective knowledge, cooperation, and sensemaking efforts. However, existing approaches to collaboration and knowledge sharing are largely manual, inadequate to meet the needs of teams that are not closely connected through personal ties or which lack the time to respond to dynamic requests for contextual information sharing. Nonetheless, in the current remote-first, complexity-driven, time-constrained workplace, such teams are both more common and more necessary. For example, the NASA Center for HelioAnalytics (CfHA) is a growing and cross-disciplinary community that is dedicated to aiding the application of emerging data science techniques and technologies, including AI/ML, to increase the speed, rigor, and depth of space physics scientific discovery. The members of that community possess innumerable skills and competencies and are involved in hundreds of projects, including proposals, committees, papers, presentations, conferences, groups, and missions. Traditional structures for information and knowledge representation do not permit the community to search and discover activities that are ongoing across the Center, nor to understand where skills and knowledge exist. The approaches that do exist are burdensome and result in inefficient use of resources, reinvention of solutions, and missed important connections. The challenge faced by the CfHA is a common one across modern groups and one that must be solved if we are to respond to the grand challenges that face our society, such as complex scientific phenomena, global pandemics and climate change. We present a solution to the problem: a community knowledge graph (KG) that aids an organization to better understand the resources (people, capabilities, affiliations, assets, content, data, models) available across its membership base, and thus supports a more cohesive community and more capable teams, enables robust and responsible application of new technologies, and provides the foundation for all members of the community to co-evolve the shared information space. We call this the Community Action and Understanding via Semantic Enrichment (CAUSE) ontology. We demonstrate the efficacy of KGs that can be instantiated from the ontology together with data from a given community (shown here for the CfHA). Finally, we discuss the implications, including the importance of the community KG for open science.

We present the first complex network theory‐based analysis of high‐latitude total electron content (TEC) data, including dependencies on interplanetary magnetic field (IMF) clock angle and hemisphere. We examine several network measures to quantify the spatiotemporal correlation patterns in the TEC data for winter and summer months in 2016. We find that significant structure exists in the correlation patterns, distinguishing the dayside and nightside ionosphere, and specific features in the high latitudes such as the polar cap and auroral oval, including the cusp and ionospheric foot points of magnetospheric boundary layers. These features vary with the IMF, exhibiting a strong dependence on the north‐south direction and generally larger variations during the winter months in both hemispheres. Our exploratory results suggest that network analysis of TEC data can be used to study characteristic ionospheric spatial scales at high latitudes, thereby extending the utility of these data. We explore mesoscale and large scale (greater than tens of kilometers and greater than hundreds of kilometers, respectively) as a function of winter/summer season, hemisphere, and IMF direction and conclude that the relative importance of different ionospheric scales is not a constant relationship. Together with an identification of important areas of future work, our findings provide a foundation for the application of network analysis techniques to ionospheric TEC. Our results suggest that network analysis can reveal new physical connections in the ionospheric system. Network analysis is a methodology used to investigate the structure and dynamics of a system by identifying objects (nodes) and connections between objects (edges). These methods originated in the social sciences in which people are the objects and connections are defined by the presence of a predefined relationship between people. Network analysis has since flourished and been used to provide new scientific discovery in a broad range of disciplines, including biological, engineering, and geophysical systems. We use this approach to investigate the near‐Earth ionized space environment, the ionosphere. Performing a novel network analysis of total electron content (TEC) data, significant structure emerges. Notably, dayside and nightside ionospheric TEC effects are distinct. Further, within the dayside and nightside systems distinct regions emerge in response to space weather activity. We suggest that network analysis can provide significant new, and complementary, understanding of the Earth's space environment and outline important future directions. This work illustrates the importance of data‐driven discovery to improve understanding of our space environment and underscores the broader theme of embracing data science in the discipline of heliophysics. New approach can increase the utility of TEC data and enhance efficiency of analysis of diverse geospace observational system in the futureFor a given season the Southern Hemisphere exhibits correlations over larger distances, but the Northern Hemisphere is more spatially uniformImportant characteristic ionospheric‐scale sizes in TEC data vary across season and hemisphere

We perform the first ever global‐scale, altitude‐dependent analysis of polar ionospheric conductivity variability using spectrally resolved in situ satellite particle measurements. With an empirical orthogonal function analysis we identify three primary modes of three‐dimensional variability related to ionospheric footprints of the quiet and disturbed geospace environment: (1) perturbation of the quasi‐permanent auroral oval, (2) differing projections of electron precipitation during southward and northward interplanetary magnetic field, and (3) a likely imprint of variation in Alfvénic Poynting flux deposition. Together, these modes account for >50% of the total conductivity variability throughout the Eregion ionosphere. Our results show that height‐integrated conductance and height‐dependent conductivities are distinctly different, underscoring the importance of studying the ionosphere in three dimensions. We provide the framework for future three‐dimensional global analysis of ionosphere‐magnetosphere coupling. First characterization of the primary modes of variability of E region, height‐dependent conductivities over the entire polar regionThree‐dimensional modes reveal the particle precipitation‐controlled conductivity responses to IMF Bz and Poynting fluxTwo‐dimensional and 3‐D representations of conductivity variability are distinctly different

We have developed a new optimal interpolation (OI) technique to estimate complete high‐latitude ionospheric conductance distributions from Defense Meteorological Satellite Program particle data. The technique combines particle precipitation‐based calculations of ionospheric conductances and their errors with a background model and its error covariance (modeled with empirical orthogonal functions) to infer complete distributions of the high‐latitude ionospheric conductances. We demonstrate this technique for the 26 November through 2 December 2011 period and analyze a moderate geomagnetic storm event on 30 November 2011. Quantitatively and qualitatively, this new technique provides better ionospheric conductance specification than past statistical models, especially during heightened geomagnetic activity. We provide initial evidence that auroral images from the Defense Meteorological Satellite Program Special Sensor Ultraviolet Spectrographic Imager instrument can be used to further improve the OI conductance maps. Our OI conductance patterns allow assimilative mapping of ionospheric electrodynamics reconstructions driven separately by radar and satellite magnetometer observations to be in closer agreement than when other, commonly used, conductance models are applied. This work (1) supports better use of the diverse observations available for high‐latitude ionospheric electrodynamics specification and (2) supports the Cousins et al. (2015b) assertion that more accurate models of the ionospheric conductance are needed to robustly assimilate ground‐ and space‐based observations of ionospheric electrodynamics. We find that the OI conductance distributions better capture the dynamics and locations of discrete electron precipitation that modulate the coupling of the magnetosphere‐ionosphere‐thermosphere system. A new inverse procedure for ionospheric conductances is presentedNew technique provides better conductance specification than past statistical models, especially during geomagnetic activityNew conductances bring SuperDARN and AMPERE data into closer agreement

Rapid specification of ionization rates and ion densities in the upper atmosphere is essential when many evaluations of the atmospheric state must be performed, as in global studies or analyses of on‐orbit satellite data. Though many models of the upper atmosphere perform the necessary specification, none provide the flexibility of computational efficiency, high accuracy, and complete specification. We introduce a parameterized, updated, and extended version of the GLobal AirglOW (GLOW) model, called GLOWfast, that significantly reduces computation time and provides comparable accuracy in upper atmospheric ionization, densities, and conductivity. We extend GLOW capabilities by (1) implementing the nitric oxide empirical model, (2) providing a new model component to calculate height‐dependent conductivity profiles from first principles for the 80–200 km region, and (3) reducing computation time. The computational improvement is achieved by replacing the full, two‐stream electron transport algorithm with two parameterizations: (1) photoionization (QRJ from Solomon and Qian ([Solomon, S. C., 2005])) and (2) electron impact ionization (F0810 from Fang et al. ([Fang, X., 2008], [Fang, X., 2010])). We find that GLOWfast accurately reproduces ionization rates, ion and electron densities, and Pedersen and Hall conductivities independent of the background atmospheric state and input solar and auroral activity. Our results suggest that GLOWfast may be even more appropriate for low characteristic energy auroral conditions. We demonstrate in a suite of 3028 case studies that GLOWfast can be used to rapidly calculate the ionization of the upper atmosphere with few limitations on background and input conditions. We support these results through comparisons with electron density profiles from COSMIC. Fast, updated, extended version of GLobal AirglOW, GLOW, modelDrastic computational improvement from fully parameterized ionization treatmentAccurately reproduces upper atmosphere ionization, densities, and conductivities

This paper analyses magnetosphere‐ionosphere (M‐I) coupling from a perspective that is independent of inertial reference frame, and delineates how physical theories of M‐I coupling are affected by the principle of relativity. For the first time in the context of M‐I coupling, we discuss the literature from the 1970s on how the low‐velocity limit of the theory of special relativity is applied to electrodynamics. In most M‐I coupling theories, a particular low‐velocity limit applies, known as the “magnetic limit.” Two important consequences of this literature are: (a) significant displacement currents in Maxwell's equations break the Galilean invariance of the equations and (b) magnetic fields are not generated by currents created by a net charge density in motion. We show how reference frame‐independent descriptions of M‐I coupling require that ion‐neutral relative velocitiesand ion‐neutral collisions are key drivers of the physics. Currents are independent of reference frame whereas electric fields depend on reference frame. Starting with the same momentum equations that are typically used to derive Ohm's law, it is possible to express the perpendicular ionospheric current as depending on collisions between ions and neutrals, and electrons and neutrals, without reference to electric fields. Ignoring the relative motion between ions and neutrals results in errors exceeding 100% for estimates of high latitude Joule heating during significant geomagnetic storms, when ion‐neutral velocity differences are largest near the initiation of large‐scale ion convection. Interactions between the magnetized and ionized solar wind, the magnetospheric cavity surrounding Earth, and Earth's ionized upper atmosphere (ionosphere) can create rapid (∼1 km/s) large‐scale motions of the ionosphere during periods known as geomagnetic storms. We use the principle of relativity (PR) to gain insight into the complex physics of these interactions. Relativity states that the physics governing geospace must be independent of the velocity of an observer making measurements of the system. We write key equations governing interactions of the magnetosphere‐ionosphere system in terms of quantities that do not depend on the observer's motion. In doing so, we find that some previous theories had over‐emphasized the importance of a large‐scale electric field that grows during storms, while neglecting important physics related to collisions between the ionized portion of the atmosphere and the un‐ionized “neutral” component that contains much more mass. These collisional interactions create upper atmospheric heating and expansion, and cause large‐scale currents to flow between the ionosphere and magnetosphere, resulting in a multitude of impacts to our technological society. Using the PR, and isolating the physics that is independent of observer motion, led us to a deeper understanding of key physical processes during storms. Relativistic transformations applied to electrodynamics are analyzed in the context of magnetosphere‐ionosphere (M‐I) couplingWe present an “Ohm's law” relating horizontal ionospheric currents to quantities that do not vary with inertial reference frameElectrodynamic theories of M‐I coupling that do not account for the relative motion of ions and neutrals are not quantitatively accurate Relativistic transformations applied to electrodynamics are analyzed in the context of magnetosphere‐ionosphere (M‐I) coupling We present an “Ohm's law” relating horizontal ionospheric currents to quantities that do not vary with inertial reference frame Electrodynamic theories of M‐I coupling that do not account for the relative motion of ions and neutrals are not quantitatively accurate

We explore the characteristics, controlling parameters, and relationships of multiscale field‐aligned currents (FACs) using a rigorous, comprehensive, and cross‐platform analysis. Our unique approach combines FAC data from the Swarm satellites and the Advanced Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) to create a database of small‐scale (∼10–150 km, <1° latitudinal width), mesoscale (∼150–250 km, 1–2° latitudinal width), and large‐scale (>250 km) FACs. We examine these data for the repeatable behavior of FACs across scales (i.e., the characteristics), the dependence on the interplanetary magnetic field orientation, and the degree to which each scale “departs” from nominal large‐scale specification. We retrieve new information by utilizing magnetic latitude and local time dependence, correlation analyses, and quantification of the departure of smaller from larger scales. We find that (1) FACs characteristics and dependence on controlling parameters do not map between scales in a straight forward manner, (2) relationships between FAC scales exhibit local time dependence, and (3) the dayside high‐latitude region is characterized by remarkably distinct FAC behavior when analyzed at different scales, and the locations of distinction correspond to “anomalous” ionosphere‐thermosphere behavior. Comparing with nominal large‐scale FACs, we find that differences are characterized by a horseshoe shape, maximizing across dayside local times, and that difference magnitudes increase when smaller‐scale observed FACs are considered. We suggest that both new physics and increased resolution of models are required to address the multiscale complexities. We include a summary table of our findings to provide a quick reference for differences between multiscale FACs. Multiscale processes, or those which contain important features across multiple scales in time and/or space, characterize the near‐Earth space environment. Multiscale effects are particularly important to understand interactions between regions, where numerous processes contribute to the dynamics. In the solar wind‐magnetosphere‐ionosphere system, currents flowing along Earth's magnetic field lines, or field‐aligned currents (FACs), provide the dominant form of energy and momentum exchange. FACs are, therefore, a critical component of the space weather environment and are inherently multiscale. Though much progress has been made toward understanding FACs at large spatial scales (>250 km), smaller‐scale FACs and relationships between scales are not well understood. We take advantage of two different satellite missions to explore the repeatable spatial behavior (i.e., the characteristics) of FACs across scales, the dependencies on solar wind conditions, and the degree to which each scale differs from nominal large‐scale FACs. We specify differences in the spatial patterns of multiscale FACs and connect particularly strong differences at dayside local times to previously identified irregular space weather activity. We find that the relationships between scales are complex. We provide a summary table of our key findings and suggest areas of future work that will contribute to new multiscale understanding. Multiscale FACs exhibit strong local time and interplanetary magnetic field orientation dependenceFAC characteristics and dependence on controlling parameters do not map trivially across scalesDifferences between observed multiscale and nominal large‐scale FACs are characterized by horseshoe shape in local time, maximizing on dayside

Our understanding and specification of solar‐terrestrial interactions benefit from taking advantage of comprehensive data‐intensive approaches. These data‐driven methods are taking on new importance in light of the shifting data landscape of the geospace system, which extends from the near Earth space environment, through the magnetosphere and interplanetary space, to the Sun. The space physics community faces both an exciting opportunity and an important imperative to create a new frontier built at the intersection of traditional approaches and state‐of‐the‐art data‐driven sciences and technologies. This brief commentary addresses the current paradigm of geospace science and the emerging need for data science innovation, discusses the meaning of data science in the context of geospace, and highlights community efforts to respond to the changing landscape. Shifting data landscape of solar‐terrestrial system creates opportunity for a new frontier in geospace researchNew frontier should be created at intersection of traditional approaches and state‐of‐the‐art data‐driven science and technologySuggest actions to sustain and expand momentum that exists to utilize emerging field of data science for geospace discovery