The most dynamic electromagnetic energy and momentum exchange processes between the upper atmosphere and the magnetosphere take place in the polar ionosphere, as evidenced by the aurora. Accurate specification of the constantly changing conditions of high-latitude ionospheric electrodynamics has been of paramount interest to the geospace science community. In response this community’s need for research tools to combine heterogeneous observational data from distributed arrays of small ground-based instrumentation operated by individual investigators with global geospace data sets, an open-source Python software and associated web-applications for Assimilative Mapping of Geospace Observations (AMGeO) are being developed and deployed (https://amgeo.colorado.edu). AMGeO provides a coherent, simultaneous and inter-hemispheric picture of global ionospheric electrodynamics by optimally combining diverse geospace observational data in a manner consistent with first-principles and with rigorous consideration of the uncertainty associated with each observation. In order to engage the geospace community in the collaborative geospace system science campaigns and a science-driven process of data product validation, AMGeO software is designed to be transparent, expandable, and interoperable with established geospace community data resources and standards. This paper presents an overview of the AMGeO software development and deployment plans as part of a new NSF EarthCube project that has started in September 2019.

The Tonga volcano eruption of 15 January 2022 unleashed a variety of atmospheric perturbations, coinciding with the recovery phase of a geomagnetic storm. The ensuing thermospheric variations created rare display of extreme poleward-expanding conjugate plasma bubbles seen in the rate of total electron content index (ROTI) over 100-150°E. This is associated with fluctuations in FORMOSAT-7/COSMIC-2 (F7/C2) ion-density measurements and spread-F signatures in ionograms, reaching ~40°N geographic latitude. This was preceded by an unusually strong pre-reversal enhancement (PRE) in the global ionospheric specification (GIS) electron density profiles derived from F7/C2 observations. The GIS further revealed a decrease of equatorial ionization anomaly (EIA) crest density due to the storm impact. A sharp decrease of E-region conductivity by volcano-induced waves, combined with enhanced F-region wind over EIA with less ion-drag apparently intensified the PRE. The strong PRE and seed perturbations from the volcano-induced waves likely further triggered super plasma bubble activity.

Far ultraviolet (FUV) imaging of the aurora from space provides great insight into dynamic coupling of the atmosphere, ionosphere and magnetosphere on global scales. To gain quantitative understanding of these coupling processes, the global distribution of auroral energy flux is required, but the inversion of FUV emission to derive precipitating auroral particles’ energy flux is not straightforward. Furthermore, the spatial coverage of FUV imaging from Low Earth Orbit (LEO) altitudes is often insufficient to achieve global mapping of this important parameter. This study seeks to fill these gaps left by the current geospace observing system using a combination of data assimilation and machine learning techniques. Specifically, this paper presents a new data-driven modeling approach to create instantaneous, global assimilative mappings of auroral electron total energy flux from Lyman-Birge-Hopfield (LBH) emission data from the Defense Meteorological System Program (DMSP) Special Sensor Ultraviolet Spectrographic Imager (SSUSI). We take a two-step approach; the creation of assimilative maps of LBH emission using optimal interpolation, followed by the conversion to energy flux using a neural network model trained with conjunction observations of in-situ auroral particles and LBH emission from the DMSP SSJ and SUSSI instruments. The paper demonstrates the feasibility of this approach with a model prototype built with DMSP data from February 17-23 2014. This study serves as a blueprint for a future comprehensive data-driven modeling of auroral energy flux that is complementary to traditional inversion techniques to take advantage of FUV imaging from LEO platforms for global assimilative mapping of auroral energy flux.

Availability of far ultraviolet observations of Earth’s dayglow by the NASA Global-scale Observations of the Limb and Disk (GOLD) mission presents an unparalleled opportunity for upper atmosphere data assimilation. Assimilation of the observed dayglow emissions can be formulated in a similar fashion to lower atmosphere radiance data assimilation approaches using the sensitivity of the Lyman-Birge-Hopfield (LBH) band emission to thermospheric temperature. To demonstrate such an approach, we present a proof-of-concept implementation of an ensemble square-root filter measurement update step using ensemble simulation of the thermosphere and LBH emission by the NOAA’s Whole Atmosphere Model (WAM) and NCAR’s Global Airglow model. With help of a new assimilation approach, the utility of GOLD observations can be extended to reveal the global, time-dependent, altitude-resolved thermospheric structure, offering the key to addressing a number of outstanding questions such as origins of traveling atmospheric disturbances.

The most dynamic electromagnetic coupling between the magnetosphere and ionosphere occurs in the polar upper atmosphere. It is critical to quantify the electromagnetic energy and momentum input associated with this coupling as its impacts on the ionosphere and thermosphere system are global and major, often leading to considerable disturbances in near-Earth space environments. The current general circulation models of the upper atmosphere exhibit systematic biases that can be attributed to an inadequate representation of the Joule heating rate resulting from unaccounted stochastic fluctuations of electric fields associated with the magnetosphere-ionosphere coupling. These biases exist regardless of geomagnetic activity levels. To overcome this limitation, a new multiresolution random field modeling approach is developed, and the efficacy of the approach is demonstrated using SuperDARN data carefully curated for the study during a largely quiet 4 hours period on February 29, 2012. Regional small-scale electrostatic fields sampled at different resolutions from a probabilistic distribution of electric field variability conditioned on actual SuperDARN LOS observations exhibit considerably more localized fine-scale features in comparison to global large-scale fields modeled using the SuperDARN Assimilative Mapping procedure. The overall hemispherically integrated Joule heating rate is increased by a factor of about 1.5 due to the effect of random regional small-scale electric fields, which is close to the lower end of arbitrarily adjusted Joule heating multiplicative factor of 1.5 and 2.5 typically used in upper atmosphere general circulation models. The study represents an important step towards a data-driven ensemble modeling of magnetosphere-ionosphere-atmosphere coupling processes.

The equatorial electrojet (EEJ) is an important manifestation of ionospheric electrodynamics. Day-to-day changes of the EEJ result from E-region dynamo processes that are primarily driven by highly variable atmospheric waves propagating up from the lower and middle atmosphere. Progress has been made in our understanding that upward propagating tides are one of the major contributors to the day-to-day variability in the EEJ, however current models are limited in their ability to capture the vertical propagation of tides from the lower and middle atmosphere to the upper atmosphere due to difficulties to adequately represent many processes that influence it. In this study, we thus propose a new data-driven approach to modeling day-to-day variability by taking advantage of widely available ground-based magnetic field measurements. The new approach based on an ensemble transform adjustment method is applied to the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM) lower boundary conditions (LBCs) at about 97 km altitude in order to make the model’s tidal characteristics to be more consistent with observed magnetic perturbations associated with the EEJ. In this method, TIE-GCM ensemble simulations are driven by high-latitude ionospheric convection and auroral particle precipitation patterns specified by the AMGeO and by atmospheric waves and tides based on MERRA meteorological reanalysis. As part of forward modeling, the 3D Dynamo electrodynamic module is used to calculate magnetic perturbations on the ground and at low Earth orbit altitudes. A detailed analysis of the 21-day period from March 1 to 22, 2009 has shown that the modeled EEJ with the LBCs adjusted using ground-based magnetic perturbation data improves the agreement of the model to independent magnetic field observations from CHAMP. The use of routinely available ground-based magnetometer data to constrain the TIE-GCM LBCs could provide an opportunity to investigate how day-to-day tidal variability drives equatorial electrodynamics variability.

Previous studies have shown that Strong Thermal Emission Velocity Enhancement (STEVE) events occur at the end of a prolonged substorm expansion phase. However, the connection between STEVE occurrence and substorms and the global high-latitude ionospheric electrodynamics associated with the development of STEVE and non-STEVE substorms are not yet well understood. The focus of this paper is to identify electrodynamics features that are unique to STEVE events through a comprehensive analysis of ionospheric convection patterns estimated from SuperDARN plasma drift and ground-based magnetometer data using the Assimilative Mapping of Geospace Observations (AMGeO) procedure. Results from AMGeO are further analyzed using principal component analysis and superposed epoch analysis for 32 STEVE and 32 non-STEVE substorm events. The analysis shows that the magnitude of cross-polar cap potential drop is generally greater for STEVE events. In contrast to non-STEVE substorms, the majority of STEVE events investigated accompany with a pronounced extension of the dawn cell into the pre-midnight subauroral latitudes, reminiscent of the Harang reversal convection feature where the eastward electrojet overlaps with the westward electrojet, which tends to prolong over substorm expansion and recovery phases. This is consistent with the presence of an enhanced subauroral electric field confirmed by previous STEVE studies. The global and localized features of high-latitude ionospheric convection associated with optical STEVE events characterized in this paper provide important insights into cross-scale magnetosphere-ionosphere coupling mechanisms that differentiate STEVE events from non-STEVE substorm events.

Earth’s thermosphere is driven by a combination of meteorological, magnetospheric, and solar forcing that exhibits significant variation from day-to-day. The relative importance of these drivers and their combined affects in determining daily thermospheric variability on global and local scales is an important science question particularly under solar minimum conditions. Far-ultraviolet, satellite-based airglow observations are a valuable tool to probe the thermosphere and can provide the spatial coverage and temporal resolution required to improve our understanding of thermospheric day-to-day variability in response to driver variability. This paper presents first results from principal component analysis and ensemble sensitivity analysis to quantify the major modes of dayglow variability in both OI 135.6 nm emissions and N2 Lyman-Birge-Hopfield emissions and the sensitivity of these modes to geomagnetic and lower atmosphere drivers. The ensemble simulations are performed with NOAA’s Whole Atmosphere Model that extends from Earth’s surface to the exobase and NCAR’s Global Airglow Model for a recent period with low-to-moderate levels of geomagnetic activity and low solar activity. The ensemble simulations are compared to thermospheric observations over the same period by the NASA Global-scale Observations of the Limb and Disk (GOLD) mission.