B06 – Novel methods for the 3D reconstruction of the dynamic evolution of the Van Allen belts using multiple satellite measurements

Energetic particles in the near-Earth space pose a significant risk to Earth-orbiting satellites and humans in space. During geomagnetic storms the radiation in the near-Earth space can dramatically increase, and numerous anomalies have been reported by satellite operators. Satellite measurements are usually limited to a single location in space, which complicates the data analysis geared towards reproducing the global state of the ring current and radiation belts. Up until recently, most of the research concentrated on the analysis of data from individual spacecrafts, which does not allow for inferring the global evolution of the particle radiation environment.

Analysis of satellite measurements from different spacecraft is complicated by the fact that measurements are given at various locations in space, have different instrumental errors and often vary by orders of magnitude. During the first funding period, we focused on developing data-assimilative tools for the most energetic electrons called radiation belts. These highly energetic particles can produce deep dielectric charging in satellites. In the second funding period, we will focus on another population of electrons in the near-Earth space that is usually referred to as ring current. The name is derived from the current that is generated by this particle population and the magnetic field produced by it that can be measured on the ground. The hazardous effects of the ring current include charging of satellite surfaces that can damage them, degradation of satellite solar panels, and induction of currents in power grids that can damage transformers or result in voltage instability leading to a collapse of the power system. While there are a number of existing physics-based models of the ring current and a number of operational satellites providing in-situ measurements of the ring current in space, there have only been a few attempts to assimilate the measurements in the physics-based model and there is currently no operational model that is using data assimilation for predictions.

While we will be building upon the progress achieved during the funding period, there are also significant differences between the data assimilation for the radiation belts and for the ring current. In the case of the radiation belts, the description can be reduced to 3 variables and the evolution can be described by the diffusion equation. For the ring current (in the most general case), we need to specify the 4-dimensional distribution function, as the ring current has an asymmetry in the local time (4th variable). Another complication of modeling the ring current is the fact that the dynamics are described by the advection-diffusion equation and not just the diffusion equation, as is the case for radiation belts. The ring current also shows variability on much shorter time scales and exhibits very narrow spatial structures, which makes it difficult to judge whether the observed variability is produced by global changes of the ring current, local changes associated with small spatial structures or transient phenomena.

Data assimilation for the ring current will require the development of new methods and approaches. In collaboration with a number of projects within CRC, we will explore different methods and test the applicability of non-linear parameter estimation with the EnKF for determining unknown and unobserved parameters. We will also use the EnKF to directly assimilate fluxes into the code without first transforming them into Phase Space Density (PSD). Special attention will be paid to the set up and use of the Ensemble Kalman Filter (EnKF), including set up of errors and localisation, and comparison with the Kalman Filter (KF). The new approaches and methods developed within the CRC will be tested on space physics data for multi-dimensional diffusion and diffusion-convection equations.

Real time display shown at https://www.gfz-potsdam.de/sektion/magnetosphaerenphysik/daten-produkte-dienste. Two-day radiation belt forecast of 1 MeV electrons using the data-assimilative VERB code, real-time ARASE, ACE, POES and GOES data. (Top left) real-time satellite trajectories and geometry of the magnetic field lines used to calculate magnetic coordinates (adiabatic invariants) for data assimilation. (Bottom left) 3D snapshot of the radiation belts. (right panels) Top panel shows real-time satellite measurements. Second panel illustrates the measurements interpolated into the model grid in the equatorial plane at 1 MeV energy and 50° equatorial pitch angle. Third panel shows the reanalysis of the radiation belts and a two day prediction into the future. Last two panels show propagated solar wind parameters measured at L1 and the Kp index of geomagnetic activity, respectively. The dashed red line demarcates historical reanalysis from the forecast for 2 days ahead of real-time.
  • Castillo, A. M., de Wiljes, J., Shprits, Y. Y., and Aseev, N. A. (2020). Reconstructing the dynamics of the outerelectron radiation belt by means of the standard and ensemble Kalman filter with the VERB-3Dcode, ESSOAr. doi:10.1002/essoar.10504674.

  • Zhelavskaya, I., Aseev, N. A., Shprits, Y. Y., and Spasojevi, M. (2020). A combined neural network- and physics-based approach for modeling the plasmasphere dynamics, ESSOAr. doi:10.1002/essoar.10502691.1

  • Cervantes, S., Shprits, Y. Y., Aseev, N. A., and Allison, H. J. (2020). Quantifying the effects of EMIC wavescattering and magnetopause shadowing in the outer electron radiation belt by means of data as-similation. J. Geophys. Res.-Space, 125(8):e2020JA028208, doi:10.1029/2020JA028208

  • Ruchi, A., Dubinkina, S., and de Wiljes, J. (2020). Fast hybrid tempered ensemble transform filter for Bayesianelliptical problems. Nonlin. Processes Geophys., in press, doi:10.5194/npg-2020-24

  • Hamm, M., Pelivan, I., Grott, M., and de Wiljes, J. (2020). Thermophysical modelling and parameter esti-mation of small solar system bodies via data assimilation. Mon. Not. R. Astron. Soc., 496:2776–2785, doi:10.1093/mnras/staa1755

  • Cervantes, S., Shprits, Y. Y., Aseev, N., Drozdov, A., Castillo, A., and Stolle, C. (2020). Identifying radiation beltelectron source and loss processes by assimilating spacecraft data in a three-dimensional diffusionmodel. J. Geophys. Res.-Space, 125(1):1–16, doi:10.1029/2019JA027514

  • Castillo, A. M., Shprits, Y. Y., Ganushkina, N., Drozdov, A., Aseev, N., Wang, D. and Dubyagin, S. (2019). Simulations of the inner magnetospheric energetic electrons using the IMPTAM-VERB coupled model. Journal of Atmospheric and Solar-Terrestrial Physics. doi: 10.1016/j.jastp.2019.05.014 

  • Aseev, N. A. and Shprits, Y. Y. (2019). Reanalysis of ring current electron phase space densities using Van AllenProbe observations, convection model, and log-normal Kalman Filter. Space Weather, 17(4):619–638, doi:10.1029/2018SW002110

  • Aseev, N. A., Shprits, Y. Y., Wang, D., Wygant, J., Drozdov, A. Y., Kellerman, A. C., and Reeves, G. D. (2019). Transport and loss of ring current electrons inside geosynchronous orbit during the 17 March 2013 storm. J. Geophys. Res.-Space, 124(2):915–933. doi:10.1029/2018JA026031

  • Ni, B., Cao, X., Shprits, Y. Y., Summers, D., Gu, X., Fu, S. and Lou, Y. (2018). Hot Plasma Effects on the Cyclotron-Resonant Pitch-Angle Scattering Rates of Radiation Belt Electrons Due to EMIC Waves. Geophysical Research Letters, 45, 21-30. doi: 10.1002/2017GL07602

  • Zhelavskaya, I. S., Shprits, Y. Y. and Spasojevic, M. (2017). Empirical modeling of the plasmasphere dynamics using neural networks. Journal of Geophysical Research: Space Physics, 122, 11227–11244. doi:10.1002/2017JA024406

  • Aseev, N. A., Shprits, Y. Y., Drozdov, A. Y., Kellerman, A. C., Usanova, M. E., Wang, D. and Zhelavskaya, I. S. (2017). Signatures of Ultrarelativistic Electron Loss in the Heart of the Outer Radiation Belt Measured by Van Allen Probes. Journal of Geophysical Research, 122, 10102-10111. doi: 10.1002/2017JA024485

  • Borovsky, J. E. and Shprits, Y. Y. (2017). Is the Dst Index Sufficient to Define All Geospace Storms?. Journal of Geophysical Research: Space Physics, 122, 11543-11547. doi:10.1002/2017JA024679