The focus of the CGS project on stormtime geospace ensures the advancement of the Nation's space weather preparedness and resilience by building capabilities to nowcast and predict regional and global space weather, thus fulfilling priorities of the Space Weather Action Plan and the Decadal Survey. In particular, by building a comprehensive model of stormtime geospace coupling all of its key regions, the CGS addresses crucial space weather hazards, including communication (mesoscale ionospheric disturbances), satellite drag, radiation belt environment, and geomagnetically-induced currents.
Below we show some examples of space weather impacts and/or products resulting from the CGS models. These results show how the development of highly precise physics-based models can lead to predictive capabilities and yield a variety of space weather products at spatiotemporal scales that are important to and can be utilized by various user and stake holder communities.
MAGE simulation of the 17-18 March 2013 geospace storm. In the beginning of the movie, the pre-existing radiation belt is shown as a cloud of particles colored in yellow. As the storm develops, the pre-existing belt is wiped out but then it is replenished with injection of new energetic electrons from the magnetotail shown in cyan and pink colors.
This animation compares the simulated energetic electron intensity, shown on the left in the equatorial plane, with that measured by the two probes of the NASA Van Allen probes mission. The panels on the right show how particles are injected into the radiation belts in a very similar manner in the simulations and observations. These injections are very well correlated with spikes in high-speed plasma flows in the magnetotail shown in the bottom panel. The high-speed flows are also known as bursty bulk flows reproducing which requires highly precise numerical techniques, realized in MAGE. These flows enable mesoscale plasmasheet transport and acceleration of particles, and are one of the major scientific targets of CGS.
Recent observations (e.g., Engebretson et al., 2019a,b) showed that intense perturbations of the ground magnetic field, that generate significant geomagnetically induced currents, can be localized to within a couple hundred kilometers. Such structures are presumably driven by similarly localized ionospheric currents overhead. The CGS team has recently performed a global magnetosphere-ionosphere simulations using the GAMERA and REMIX MAGE components (Sorathia et al., 2020) at an unprecedented resolution (~30 km in the auroral zone). This simulation demonstrates the power of the highly resolved CGS models in reproducing localized structure potentially responsible of intense GICs.
The picture shows the three vector components of the magnetic perturbations computed from the GAMERA-REMIX simulation by Sorathia et al. (2020). The green arrows depict the equivalent ionospheric current flowing overhead. The nightside auroral electrojet current exhibits highly localized structure (for instance, between Greenland and Scandinavia in this particular snapshot), and the corresponding structure can be also seen in the magnetic perturbations on the ground. The figure is adapted and expanded from Laundal et al. (2020).
Thermospheric mass density changes greatly during geospace storms due to the intense energy and momentum deposition at high latitudes and the redistribution of this energy and momentum globally through dynamics and thermodynamics. The storm-time change in neutral mass density affects satellite orbits through the drag effect (e.g. Chen et al., 2012, 2014, Emmert, 2015). Neutral density changes can be of different scales from global to regional, mesoscale structures. One of the most significant mass density changes are associated with the excitation and propagation of large-scale and mesoscale atmospheric waves, also known as traveling atmospheric disturbances (TADs).
MAGE simulation of the 24 August 2005 geospace storm. The top panel shows MAGE simulated neutral densities at 400 km in the northern (left) and southern (right) hemispheres. The red dot and blue square give the location of the CHAMP and GRACE satellites, data from these two satellites are compared with MAGE predictions in the bottom panels. The density peaks in satellite data correspond to the density enhancements caused directly by Joule heating in auroral and cusp regions at high latitudes, as well as by TADs in low and mid latitudes. For instance, the large density peaks near 13:20 UT seen in the data of both satellites were caused by TADs in the equatorial region, and well-captured by the MAGE model. The model captured quantitatively most of the density peaks in satellite data, suggesting that the modeled Joule heating and ion drag were close to the reality, in magnitude, location and timing.
There is a wealth of mesoscale structures in the ionosphere, especially during geospace storms and at high latitudes. Mesoscale structures in high-latitude convection electric fields and the associated localized Joule heating and ion drag lead to neutral temperature, wind and composition structures of different spatial and temporal scales, which, in turn, result in ionospheric large and mesoscale structures. The dynamic plasma transport by the convection electric fields further complicates the situation and produces a more structured ionosphere. In In the movie above, storm-time expanded convection pattern cuts through the middle latitude solar radiation-produced ionization and transports the plasma to high latitudes and into the polar cap. During this transport process ionospheric mesoscale structures, such as storm enhanced density (SED), polar tongue of ionization (TOI) and polar cap patches, are formed and dynamically evolve in response to the changing solar wind conditions. Large TEC gradients are seen near the edges of these mesoscale structures where plasma instability is seeded and developed to cause scintillation to Global Navigation Satellite Systems (GNSS) signals and other severe space weather effects (e.g., Sun et al., 2013). Understanding and predicting horizontal gradients of TEC and its temporal variations are thus important for the availability and accuracy of GNSS navigation systems (e.g., Jakowski and Hoque, 2019).
Ionospheric total electron content (TEC, left) and neutral temperature and winds in the F-region during the march 17, 2013 geospace storm. This movie was produced using the coupled magnetosphere ionosphere thermosphere (CMIT) model which was the predecessor of the MAGE model (coupling LFM with RCM and TIEGCM). In this simulation, a high-resolution version of TIEGCM (~100 km resolution) was used. Ionospheric mesoscale structures were primarily caused by the plasma transport by the dynamic varying high-latitude convection electric fields, while neutral temperature and wind structures are mostly associated with localized Joule heating and ion drag processes. Animation Credit: Tong Dang
Recently there has been a breakthrough in modeling plasma bubbles in the equatorial ionosphere (Huba and Liu, 2020). The first-principles whole atmosphere model WACCM-X was coupled to the global ionosphere model SAMI3 . A critical feature of this simulation was that a high-resolution grid (≲ 70 km) was used which allowed the model to capture equatorial plasma bubble onset and evolution on a global scale initiated by atmospheric gravity waves. In one case studied, a series of bubbles formed in the Atlantic sector with wavelengths in the range 400 - 1200 km, rose to over 800 km, and persisted until after midnight. These results are remarkably consistent with recent GOLD observations (Eastes et al., 2019).
In the movie, storm-time expanded convection pattern cuts through the middle latitude solar radiation-produced ionization and transports the plasma to high latitudes and into the polar cap. During this transport process ionospheric mesoscale structures, such as storm enhanced density (SED), polar tongue of ionization (TOI) and polar cap patches, are formed and dynamically evolve in response to the changing solar wind conditions. Large TEC gradients are seen near the edges of these mesoscale structures where plasma instability is seeded and developed to cause scintillation to Global Navigation Satellite Systems (GNSS) signals and other severe space weather effects (e.g., Sun et al., 2013).
Chen, G., J. Xu, W. Wang, J. Lei, and A. G. Burns (2012), A comparison of the effects of CIR- and CME-induced geomagnetic activity on thermospheric densities and spacecraft orbits: Case studies, J. Geophys. Res., 117, A08315, doi:10.1029/2012JA017782.
Chen, G.-M., J. Xu, W. Wang, and A. G. Burns (2014), A comparison of the effects of CIR- and CME-induced geomagnetic activity on thermospheric densities and spacecraft orbits: Statistical studies, J. Geophys. Res. Space Physics, 119, doi:10.1002/2014JA019831.
Eastes, R. W., S.C. Solomon, R.E. Daniell, D.N. Anderson, A.G. Burns, S.L. England, et al. (2019) Global- scale observations of the equatorial ionization anomaly, Geophysical Research Letters, 46, 9318, https://doi.org/10.1029/2019GL084199.
Emmert, J. T. (2015). Thermospheric mass density: A review. Advances in Space Research, 56(5), 773–824. https://doi.org/10.1016/j.asr.2015.05.038.
Engebretson, M. J., et al. (2019a), Nighttime Magnetic Perturbation Events Observed in Arctic Canada: 2. Multiple-Instrument Observations, Journal of Geophysical Research: Space Physics, 124(9), 7459–7476, https://doi.org/10.1029/2020JA028128.
Engebretson, M. J., et al. (2019b), Nighttime Magnetic Perturbation Events Observed in Arctic Canada: 1. Survey and Statistical Analysis, Journal of Geophysical Research: Space Physics, 124(9), 7442–7458, https://doi.org/10.1029/2020JA028128.
Huba, J.D. and H.-L. Liu (2020) Global modeling of equatorial spread F with SAMI3/WACCM-X, Geophys. Res. Lett., 47, e2020GL088258. https://doi.org/10.1029/2020GL088258.
Jakowski, N., & Hoque, M. M. (2019). Estimation of spatial gradients and temporal variations of the total electron content using ground‐based GNSS measurements. Space Weather, 17, 339–356. https://doi.org/10.1029/2018SW002119.
Krauss, S., Temmer, M., & Vennerstrom, S. (2018). Multiple satellite analysis of the Earth's thermosphere and interplanetary magnetic field variations due to
ICME/CIR events during 2003–2015. Journal of Geophysical Research: Space Physics, 123, 8884–8894. https://doi.org/10.1029/2018JA025778.
Laundal, Karl, et al. Electrojet Estimates from Mesospheric Magnetic Field Measurements. preprint, Earth and Space Science Open Archive, doi:10.1002/essoar.10504160.1.
Sorathia, K. A., Ukhorskiy, A. Y., Merkin, V. G., Fennell, J. F., & Claudepierre, S. G. (2018). Modeling the depletion and recovery of the outer radiation belt during a geomagnetic storm: Combined MHD and test particle simulations. Journal of Geophysical Research: Space Physics, 123, 5590– 5609. https://doi.org/10.1029/2018JA025506
Sorathia, K. A., Merkin, V. G., Panov, E. V., Zhang, B., Lyon, J. G., & Garretson, J., et al. (2020). Ballooning‐interchange instability in the near‐Earth plasma sheet and auroral beads: Global magnetospheric modeling at the limit of the MHD approximation. Geophysical Research Letters, 47, e2020GL088227. https://doi.org/10.1029/2020GL088227
Sun, Y.-Y., T. Matsuo, E. A. Araujo-Pradere, and J.-Y. Liu (2013), Ground-based GPS observation of SED-associated irregularities over CONUS, J. Geophys. Res. Space Physics, 118, 2478–2489, doi:10.1029/2012JA018103.