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10 - Data Assimilation in the Near-Earth Electron Radiation Environment

from Part II - ‘Fluid’ Earth Applications: From the Surface to the Space

Published online by Cambridge University Press:  20 June 2023

Alik Ismail-Zadeh
Affiliation:
Karlsruhe Institute of Technology, Germany
Fabio Castelli
Affiliation:
Università degli Studi, Florence
Dylan Jones
Affiliation:
University of Toronto
Sabrina Sanchez
Affiliation:
Max Planck Institute for Solar System Research, Germany
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Summary

Abstract: Energetic charged particles trapped by the Earth’s magnetic field present a significant hazard for Earth-orbiting satellites and humans in space. Application of the data assimilation tools allows us to reconstruct the global state of the radiation particle environment from sparse single-point observations. The measurements from different satellites with different observational errors can be blended in an optimal way with physics-based models. The mathematical formulation on the diffusion and diffusion-advection equations for the Earth’s Van Allen radiation belts and ring current is described. We further describe several recent studies that successfully applied the data assimilation tools to the near-Earth space radiation environment. The applications to the reanalysis of the radiation belts and ring current, real-time predictions, and analysis of the missing physical processes are described and motivation for these studies is provided. We further discuss various assimilation techniques and potential topics for future research.

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Publisher: Cambridge University Press
Print publication year: 2023

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References

Albert, J. (2005). Evaluation of quasi-linear diffusion coefficients for whistler mode waves in a plasma with arbitrary density ratio. Journal of Geophysical Research: Space Physics, 110(A3).Google Scholar
Aseev, N., and Shprits, Y. (2019). Reanalysis of ring current electron phase space densities using Van Allen Probe observations, convection model, and log-normal Kalman Filter. Space Weather, 17(4), 619–38.CrossRefGoogle Scholar
Aseev, N. A., Shprits, Y. Y., Drozdov, A. Y., and Kellerman, A. C. (2016). Numerical applications of the advective-diffusive codes for the inner magnetosphere. Space Weather, 14(11), 9931010.Google Scholar
Asikainen, T., and Mursula, K. (2011). Recalibration of the long-term NOAA/MEPED energetic proton measurements. Journal of Atmospheric and Solar-Terrestrial Physics, 73(2), 335–47.Google Scholar
Asikainen, T., and Mursula, K. (2013). Correcting the NOAA/MEPED energetic electron fluxes for detector efficiency and proton contamination. Journal of Geophysical Research: Space Physics, 118(10), 6500–10.Google Scholar
Baker, D., Belian, R., Higbie, P., Klebesadel, R., and Blake, J. (1987). Deep dielectric charging effects due to high-energy electrons in Earth’s outer magnetosphere. Journal of Electrostatics, 20(1), 319.Google Scholar
Baker, D. N. (2000). The occurrence of operational anomalies in spacecraft and their relationship to space weather. IEEE Transactions on Plasma Science, 28(6), 2007–16.Google Scholar
Baker, D. N. (2002). How to cope with space weather. Science, 297(5586), 1486–7.Google Scholar
Baker, D. N. (2005). Specifying and forecasting space weather threats to human technology. In Daglis, I. A., ed., Effects of Space Weather on Technology Infrastructure, NATO Science Series II: Mathematics, Physics and Chemistry, vol. 176. Dordrecht: Springer, pp. 125.Google Scholar
Beutier, T., and Boscher, D. (1995). A three-dimensional analysis of the electron radiation belt by the Salammbô code. Journal of Geophysical Research: Space Physics, 100(A8), 14853–61.Google Scholar
Bourdarie, S., and Maget, V. (2012). Electron radiation belt data assimilation with an ensemble Kalman filter relying on the Salammbô code. Annales Geophysicae, 30, 929–43.Google Scholar
Castillo, A. M., de Wiljes, J., Shprits, Y. Y., and Aseev, N. A. (2021). Reconstructing the dynamics of the outer electron radiation belt by means of the standard and ensemble Kalman filter with the VERB-3D code. Space Weather, 19(10), e2020SW002672.Google Scholar
Cervantes, S., Shprits, Y. Y., Aseev, N. et al. (2020a). Identifying radiation belt electron source and loss processes by assimilating spacecraft data in a three-dimensional diffusion model. Journal of Geophysical Research: Space Physics, 125(1), 116.Google Scholar
Cervantes, S., Shprits, Y. Y., Aseev, N. A., and Allison, H. J. (2020b). Quantifying the effects of EMIC wave scattering and magnetopause shadowing in the outer electron radiation belt by means of data assimilation. Journal of Geophysical Research: Space Physics, 125(8).Google Scholar
Cohen, D., Spanjers, G., Winter, J. et al. (2005). Design and Systems Engineering of AFRL’s Demonstration and Sciences Experiment. Proceedings of the GATech Space Systems Engineering Conference, 8–10 November 2005. Paper No. GT-SSEC.D.1, pp. 17. http://hdl.handle.net/1853/8037.Google Scholar
Daae, M., Shprits, Y. Y., Ni, B. et al. (2011). Reanalysis of radiation belt electron phase space density using various boundary conditions and loss models. Advances in Space Research, 48(8), 1327–34.Google Scholar
Drozdov, A. Y., Shprits, Y. Y., Orlova, K. G. et al. (2015). Energetic, relativistic, and ultrarelativistic electrons: Comparison of long-term VERB code simulations with Van Allen Probes measurements. Journal of Geophysical Research: Space Physics, 120(5), 3574–87.Google Scholar
Escoubet, C., Schmidt, R., and Goldstein, M. eds. (1997). Cluster-science and mission overview. In Escoubet, C. P., Russell, C. T., and Schmidt, R., eds., The Cluster and Phoenix Missions. Dordrecht: Springer, pp. 1132.Google Scholar
Evensen, G. (2003). The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dynamics, 53(4), 343–67.Google Scholar
Fok, M.-C., Glocer, A., Zheng, Q. et al. (2011). Recent developments in the radiation belt environment model. Journal of Atmospheric and Solar-Terrestrial Physics, 73(11–12), 1435–43.Google Scholar
Fok, M.-C., Horne, R. B., Meredith, N. P., and Glauert, S. A. (2008). Radiation belt environment model: Application to space weather nowcasting. Journal of Geophysical Research: Space Physics, 113(A3).Google Scholar
Friedel, R., Bourdarie, S., Fennell, J., Kanekal, S., and Cayton, T. (2003). ‘Nudging’ the Salammbo Code: First results of seeding a diffusive radiation belt code with in situ data: GPS, GEO, HEO and POLAR. Eos Transactions of the American Geophysical Union, 84(46), Fall Meeting, 8–12 December 2003, San Francisco, 476 Suppl., abstract, SM11D–06.Google Scholar
Friedel, R., Reeves, G., and Obara, T. (2002). Relativistic electron dynamics in the inner magnetosphere: A review. Journal of Atmospheric and Solar-Terrestrial Physics, 64, 265–82.Google Scholar
Galand, M., and Evans, D. S. (2000). Radiation damage of the proton MEPED detector on POES (TIROS/NOAA) satellites. NOAA Technical Memorandum. Boulder, CO. OAR 456-SEC 42.Google Scholar
Ganushkina, N. Y., Amariutei, O., Shprits, Y., and Liemohn, M. (2013). Transport of the plasma sheet electrons to the geostationary distances. Journal of Geophysical Research: Space Physics, 118(1), 8298.Google Scholar
Ganushkina, N. Y., Liemohn, M., Amariutei, O., and Pitchford, D. (2014). Low-energy electrons (5–50 kev) in the inner magnetosphere. Journal of Geophysical Research: Space Physics, 119(1), 246–59.Google Scholar
Glauert, S. A., and Horne, R. B. (2005). Calculation of pitch angle and energy diffusion coefficients with the PADIE code. Journal of Geophysical Research: Space Physics, 110(A4).Google Scholar
Godinez, H. C., Yu, Y., Lawrence, E. et al. (2016). Ring current pressure estimation with RAM-SCB using data assimilation and Van Allen Probe flux data. Geophysical Research Letters, 43(23), 11948–56.CrossRefGoogle Scholar
Green, J. C., and Kivelson, M. G. (2004). Relativistic electrons in the outer radiation belt: Differentiating between acceleration mechanisms. Journal of Geophysical Research: Space Physics, 109(A3).Google Scholar
Hamlin, D. A., Karplus, R., Vik, R. C., and Watson, K. M. (1961). Mirror and azimuthal drift frequencies for geomagnetically trapped particles. Journal of Geophysical Research (1896–1977), 66(1), 14.CrossRefGoogle Scholar
Jordanova, V., Kozyra, J., Nagy, A., and Khazanov, G. (1997). Kinetic model of the ring current–atmosphere interactions. Journal of Geophysical Research: Space Physics, 102(A7), 14279–91.Google Scholar
Jordanova, V., and Miyoshi, Y. (2005). Relativistic model of ring current and radiation belt ions and electrons: Initial results. Geophysical Research Letters, 32(14).Google Scholar
Kalman, R. (1960). A new approach to linear filtering and prediction problems. Trans. ASME Journal of Basic Engineering, 82(1), 3545.Google Scholar
Kalnay, E. (2003). Atmospheric Modeling, Data Assimilation and Predictability. Cambridge: Cambridge University Press.Google Scholar
Kennel, C., and Engelmann, F. (1966). Velocity space diffusion from weak plasma turbulence in a magnetic field. The Physics of Fluids, 9(12), 2377–88.Google Scholar
Kim, K., Shprits, Y., Subbotin, D., and Ni, B. (2012). Relativistic radiation belt electron responses to GEM magnetic storms: Comparison of CRRES observations with 3-D VERB simulations. Journal of Geophysical Research: Space Physics, 117(A8).Google Scholar
Koller, J., Chen, Y., Reeves, G. D. et al. (2007). Identifying the radiation belt source region by data assimilation. Journal of Geophysical Research: Space Physics, 112(A6).Google Scholar
Koller, J., Friedel, R., and Reeves, G. (2005). Radiation belt data assimilation and parameter estimation. LANL Reports, LA-UR-05-6700. http://library.lanl.gov/cgi-bin/getfile?LA-UR-05-6700.pdf.Google Scholar
Kondrashov, D., Ghil, M., and Shprits, Y. Y. (2011). Lognormal Kalman filter for assimilating phase space density data in the radiation belts. Space Weather, 9(11).CrossRefGoogle Scholar
Kondrashov, D., Shprits, Y. Y., Ghil, M., and Thorne, R. (2007). A Kalman filter technique to estimate relativistic electron lifetimes in the outer radiation belt. Journal of Geophysical Research: Space Physics, 112(A10).Google Scholar
Lanzerotti, L. J. (2001). Space weather effects on technologies. Washington DC American Geophysical Union Geophysical Monograph Series, 125, 1122.Google Scholar
Lyons, L. R., Thorne, R. M., and Kennel, C. F. (1972). Pitch-angle diffusion of radiation belt electrons within the plasmasphere. Journal of Geophysical Research, 77(19), 3455–74.Google Scholar
Maynard, N. C., and Chen, A. J. (1975). Isolated cold plasma regions: Observations and their relation to possible production mechanisms. Journal of Geophysical Research (1896–1977), 80(7), 1009–13.Google Scholar
McFadden, J., Evans, D., Kasprzak, W. et al. (2007). In-flight instrument calibration and performance verification. In Wüest, M., Evansvon, D. S. and Steiger, R., eds., Calibration of Particle Instruments in Space Physics, vol. SR-007. Bern: International Space Science Institute, pp. 277385.Google Scholar
Miyoshi, Y., Shinohara, I., Takashima, T. et al. (2018). Geospace exploration project ERG. Earth, Planets and Space, 70(1), 113.Google Scholar
Naehr, S. M., and Toffoletto, F. R. (2005). Radiation belt data assimilation with an extended Kalman filter. Space Weather, 3(6).Google Scholar
Nakano, S., Ueno, G., Ebihara, Y. et al. (2008). A method for estimating the ring current structure and the electric potential distribution using energetic neutral atom data assimilation. Journal of Geophysical Research: Space Physics, 113(A5).CrossRefGoogle Scholar
Ni, B., Shprits, Y., Nagai, T. et al. (2009a). Reanalyses of the radiation belt electron phase space density using nearly equatorial CRRES and polar-orbiting Akebono satellite observations. Journal of Geophysical Research: Space Physics, 114(A5).Google Scholar
Ni, B., Shprits, Y., Thorne, R., Friedel, R., and Nagai, T. (2009b). Reanalysis of relativistic radiation belt electron phase space density using multisatellite observations: Sensitivity to empirical magnetic field models. Journal of Geophysical Research: Space Physics, 114(A12).Google Scholar
Ni, B., Shprits, Y. Y., Friedel, R. H. et al. (2013). Responses of Earth’s radiation belts to solar wind dynamic pressure variations in 2002 analyzed using multisatellite data and Kalman filtering. Journal of Geophysical Research: Space Physics, 118(7), 4400–14.Google Scholar
Podladchikova, T. V., Shprits, Y. Y., Kellerman, A. C., and Kondrashov, D. (2014a). Noise statistics identification for Kalman filtering of the electron radiation belt observations: 2. Filtration and smoothing. Journal of Geophysical Research: Space Physics, 119(7), 5725–43.Google Scholar
Podladchikova, T. V., Shprits, Y. Y., Kondrashov, D., and Kellerman, A. C. (2014b). Noise statistics identification for Kalman filtering of the electron radiation belt observations: 1. Model errors. Journal of Geophysical Research: Space Physics, 119(7), 5700–24.Google Scholar
Reeves, G. D., McAdams, K. L., Friedel, R. H. W., and O’Brien, T. P. (2003). Acceleration and loss of relativistic electrons during geomagnetic storms. Geophysical Research Letters, 30(10).Google Scholar
RobinsonJr., P. A. (1989). Spacecraft environmental anomalies handbook. Technical report, Jet Propulsion Lab, Pasadena, CA.Google Scholar
Roederer, J. G. (2012). Dynamics of Geomagnetically Trapped radiation, vol. 2. Berlin: Springer Science & Business Media.Google Scholar
Rosen, A. (1976). Spacecraft charging by magnetospheric plasmas. IEEE Transactions on Nuclear Science, 23(6), 1762–68.CrossRefGoogle Scholar
Saikin, A. A., Shprits, Y. Y., Drozdov, A. Y. et al. (2021). Reconstruction of the radiation belts for solar cycles 17–24 (1933–2017). Space Weather, 19(3), e2020SW002524.CrossRefGoogle Scholar
Schiller, Q., Li, X., Koller, J., Godinez, H., and Turner, D. L. (2012). A parametric study of the source rate for outer radiation belt electrons using a Kalman filter. Journal of Geophysical Research: Space Physics, 117(A9).Google Scholar
Schulz, M., and Lanzerotti, L. (1974). Particle Diffusion in the Radiation Belts. New York: Springer-Verlag.Google Scholar
Shprits, Y., Daae, M., and Ni, B. (2012). Statistical analysis of phase space density buildups and dropouts. Journal of Geophysical Research: Space Physics, 117(A1).Google Scholar
Shprits, Y., Elkington, S., Meredith, N., and Subbotin, D. (2008a). Review of modeling of losses and sources of relativistic electrons in the outer radiation belts: I. Radial transport. Journal of Atmospheric and Solar-Terrestrial Physics, 70(14), 1679–93.Google Scholar
Shprits, Y. Y., Kellerman, A. C., Drozdov, A. Y. et al. (2015). Combined convective and diffusive simulations: VERB-4D comparison with 17 March 2013 Van Allen Probes observations. Geophysical Research Letters, 42(22), 9600–8.Google Scholar
Shprits, Y., Kellerman, A., Kondrashov, D., and Subbotin, D. (2013). Application of a new data operator-splitting data assimilation technique to the 3-D VERB diffusion code and CRRES measurements. Geophysical Research Letters, 40(19), 49985002.Google Scholar
Shprits, Y., Kondrashov, D., Chen, Y. et al. (2007). Reanalysis of relativistic radiation belt electron fluxes using CRRES satellite data, a radial diffusion model, and a Kalman filter. Journal of Geophysical Research: Space Physics, 112(A12216).Google Scholar
Shprits, Y., Subbotin, D., Meredith, N., and Elkington, S. (2008b). Review of modeling of losses and sources of relativistic electrons in the outer radiation belts: II. Local acceleration and loss. Journal of Atmospheric and Solar-Terrestrial Physics, 70(14), 1694–713.Google Scholar
Shprits, Y., Subbotin, D., and Ni, B. (2009). Evolution of electron fluxes in the outer radiation belt computed with the VERB code Journal of Geophysical Research: Space Physics, 114(A11).Google Scholar
Shprits, Y., Subbotin, D., Ni, B. et al. (2011). Profound change of the near-Earth radiation environment caused by solar superstorms. Space Weather, 9(8).Google Scholar
Shprits, Y., Thorne, R., Friedel, R. et al. (2006). Outward radial diffusion driven by losses at magnetopause. Journal of Geophysical Research: Space Physics, 111(A11).Google Scholar
Shprits, Y. Y., Vasile, R., and Zhelavskaya, I. S. (2019). Nowcasting and predicting the Kp index using historical values and real-time observations. Space Weather, 17(8), 1219–29.Google Scholar
Sibeck, D., and Angelopoulos, V. (2008). THEMIS science objectives and mission phases. Space Science Reviews, 141(1), 3559.Google Scholar
Stern, D. P. (1975). The motion of a proton in the equatorial magnetosphere. Journal of Geophysical Research (1896–1977), 80(4), 595–9.Google Scholar
Stix, T. H. (1962). The Theory of Plasma Waves. New York: McGraw-Hill.Google Scholar
Subbotin, D. A. and Shprits, Y. Y. (2009). Three-dimensional modeling of the radiation belts using the Versatile Electron Radiation Belt (VERB) code. Space Weather, 7(10).Google Scholar
Subbotin, D. A. and Shprits, Y. Y. (2012). Three-dimensional radiation belt simulations in terms of adiabatic invariants using a single numerical grid. Journal of Geophysical Research: Space Physics, 117(A05205).Google Scholar
Subbotin, D., Shprits, Y., and Ni, B. (2011). Long-term radiation belt simulation with the VERB 3-D code: Comparison with CRRES observations. Journal of Geophysical Research: Space Physics, 116(A12).Google Scholar
Tsyganenko, N. (1989). A magnetospheric magnetic field model with a warped tail current sheet. Planetary and Space Science, 37(1), 5–20.Google Scholar
Turner, D., Shprits, Y., Hartinger, M., and Angelopoulos, V. (2012). Explaining sudden losses of outer radiation belt electrons during geomagnetic storms. Nature Physics, 8(3), 208–12.Google Scholar
UCS (2021). UCS Satellite Database, Union of Concerned Scientists. https://ucsusa.org/resources/satellite-database/.Google Scholar
Volland, H. (1973). A semiempirical model of large-scale magnetospheric electric fields. Journal of Geophysical Research (1896–1977), 78(1), 171–80.Google Scholar
Wang, D. and Shprits, Y. Y. (2019). On how high-latitude chorus waves tip the balance between acceleration and loss of relativistic electrons. Geophysical Research Letters, 46(14), 7945–54.Google Scholar
Wang, D., Shprits, Y. Y., Zhelavskaya, I. S. et al. (2020). The effect of plasma boundaries on the dynamic evolution of relativistic radiation belt electrons. Journal of Geophysical Research: Space Physics, 125(5), e2019JA027422.Google Scholar

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