@misc{SmirnovKronbergDalyetal.2020, author = {Smirnov, Artem G. and Kronberg, Elena A. and Daly, Patrick W. and Aseev, Nikita and Shprits, Yuri Y. and Kellerman, Adam C.}, title = {Adiabatic Invariants Calculations for Cluster Mission: A Long-Term Product for Radiation Belts Studies}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {2}, issn = {1866-8372}, doi = {10.25932/publishup-52391}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-523915}, pages = {14}, year = {2020}, abstract = {The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes.}, language = {en} } @article{ShpritsDrozdovSpasojevicetal.2016, author = {Shprits, Yuri Y. and Drozdov, Alexander and Spasojevic, Maria and Kellerman, Adam C. and Usanova, Maria E. and Engebretson, Mark J. and Agapitov, Oleksiy V. and Zhelavskaya, Irina and Raita, Tero J. and Spence, Harlan E. and Baker, Daniel N. and Zhu, Hui and Aseev, Nikita}, title = {Wave-induced loss of ultra-relativistic electrons in the Van Allen radiation belts}, series = {Nature Communications}, volume = {7}, journal = {Nature Communications}, publisher = {Nature Publ. Group}, address = {London}, issn = {2041-1723}, doi = {10.1038/ncomms12883}, pages = {7}, year = {2016}, language = {en} } @article{LandisSaikinZhelavskayaetal.2022, author = {Landis, Daji August and Saikin, Anthony and Zhelavskaya, Irina and Drozdov, Alexander and Aseev, Nikita and Shprits, Yuri Y. and Pfitzer, Maximilian F. and Smirnov, Artem G.}, title = {NARX Neural Network Derivations of the Outer Boundary Radiation Belt Electron Flux}, series = {Space Weather: the international journal of research and applications}, volume = {20}, journal = {Space Weather: the international journal of research and applications}, number = {5}, publisher = {American Geophysical Union}, address = {Washington}, issn = {1542-7390}, doi = {10.1029/2021SW002774}, pages = {18}, year = {2022}, abstract = {We present two new empirical models of radiation belt electron flux at geostationary orbit. GOES-15 measurements of 0.8 MeV electrons were used to train a Nonlinear Autoregressive with Exogenous input (NARX) neural network for both modeling GOES-15 flux values and an upper boundary condition scaling factor (BF). The GOES-15 flux model utilizes an input and feedback delay of 2 and 2 time steps (i.e., 5 min time steps) with the most efficient number of hidden layers set to 10. Magnetic local time, Dst, Kp, solar wind dynamic pressure, AE, and solar wind velocity were found to perform as predicative indicators of GOES-15 flux and therefore were used as the exogenous inputs. The NARX-derived upper boundary condition scaling factor was used in conjunction with the Versatile Electron Radiation Belt (VERB) code to produce reconstructions of the radiation belts during the period of July-November 1990, independent of in-situ observations. Here, Kp was chosen as the sole exogenous input to be more compatible with the VERB code. This Combined Release and Radiation Effects Satellite-era reconstruction showcases the potential to use these neural network-derived boundary conditions as a method of hindcasting the historical radiation belts. This study serves as a companion paper to another recently published study on reconstructing the radiation belts during Solar Cycles 17-24 (Saikin et al., 2021, ), for which the results featured in this paper were used.}, language = {en} } @article{AseevShpritsDrozdovetal.2016, author = {Aseev, Nikita and Shprits, Yuri Y. and Drozdov, Alexander and Kellerman, Adam C.}, title = {Numerical applications of the advective-diffusive codes for the inner magnetosphere}, series = {Space Weather: The International Journal of Research and Applications}, volume = {14}, journal = {Space Weather: The International Journal of Research and Applications}, publisher = {American Geophysical Union}, address = {Washington}, issn = {1542-7390}, doi = {10.1002/2016SW001484}, pages = {993 -- 1010}, year = {2016}, abstract = {In this study we present analytical solutions for convection and diffusion equations. We gather here the analytical solutions for the one-dimensional convection equation, the two-dimensional convection problem, and the one- and two-dimensional diffusion equations. Using obtained analytical solutions, we test the four-dimensional Versatile Electron Radiation Belt code (the VERB-4D code), which solves the modified Fokker-Planck equation with additional convection terms. The ninth-order upwind numerical scheme for the one-dimensional convection equation shows much more accurate results than the results obtained with the third-order scheme. The universal limiter eliminates unphysical oscillations generated by high-order linear upwind schemes. Decrease in the space step leads to convergence of a numerical solution of the two-dimensional diffusion equation with mixed terms to the analytical solution. We compare the results of the third- and ninth-order schemes applied to magnetospheric convection modeling. The results show significant differences in electron fluxes near geostationary orbit when different numerical schemes are used.}, language = {en} } @article{AseevShprits2019, author = {Aseev, Nikita and Shprits, Yuri Y.}, title = {Reanalysis of ring current electron phase space densities using van allen probe observations, convection model, and log-normal kalman filter}, series = {Space weather : the international journal of research and applications}, volume = {17}, journal = {Space weather : the international journal of research and applications}, number = {4}, publisher = {American Geophysical Union}, address = {Washington}, issn = {1542-7390}, doi = {10.1029/2018SW002110}, pages = {619 -- 638}, year = {2019}, abstract = {Models of ring current electron dynamics unavoidably contain uncertainties in boundary conditions, electric and magnetic fields, electron scattering rates, and plasmapause location. Model errors can accumulate with time and result in significant deviations of model predictions from observations. Data assimilation offers useful tools which can combine physics-based models and measurements to improve model predictions. In this study, we systematically analyze performance of the Kalman filter applied to a log-transformed convection model of ring current electrons and Van Allen Probe data. We consider long-term dynamics of mu = 2.3 MeV/G and K = 0.3 G(1/2) R-E electrons from 1 February 2013 to 16 June 2013. By using synthetic data, we show that the Kalman filter is capable of correcting errors in model predictions associated with uncertainties in electron lifetimes, boundary conditions, and convection electric fields. We demonstrate that reanalysis retains features which cannot be fully reproduced by the convection model such as storm-time earthward propagation of the electrons down to 2.5 R-E. The Kalman filter can adjust model predictions to satellite measurements even in regions where data are not available. We show that the Kalman filter can adjust model predictions in accordance with observations for mu = 0.1, 2.3, and 9.9 MeV/G and constant K = 0.3 G(1/2) R-E electrons. The results of this study demonstrate that data assimilation can improve performance of ring current models, better quantify model uncertainties, and help deeper understand the physics of the ring current particles.}, language = {en} } @article{SmirnovKronbergLatallerieetal.2019, author = {Smirnov, Artem G. and Kronberg, Elena A. and Latallerie, F. and Daly, Patrick W. and Aseev, Nikita and Shprits, Yuri Y. and Kellerman, Adam C. and Kasahara, Satoshi and Turner, Drew L. and Taylor, M. G. G. T.}, title = {Electron Intensity Measurements by the Cluster/RAPID/IES Instrument in Earth's Radiation Belts and Ring Current}, series = {Space Weather: The International Journal of Research and Applications}, volume = {17}, journal = {Space Weather: The International Journal of Research and Applications}, number = {4}, publisher = {American Geophysical Union}, address = {Washington}, issn = {1542-7390}, doi = {10.1029/2018SW001989}, pages = {553 -- 566}, year = {2019}, abstract = {Plain Language Summary Radiation belts of the Earth, which are the zones of charged energetic particles trapped by the geomagnetic field, comprise enormous and dynamic systems. While the inner radiation belt, composed mainly of high-energy protons, is relatively stable, the outer belt, filled with energetic electrons, is highly variable and depends substantially on solar activity. Hence, extended reliable observations and the improved models of the electron intensities in the outer belt depending on solar wind parameters are necessary for prediction of their dynamics. The Cluster mission has been measuring electron flux intensities in the radiation belts since its launch in 2000, thus providing a huge dataset that can be used for radiation belts analysis. Using 16 years of electron measurements by the Cluster mission corrected for background contamination, we derived a uniform linear-logarithmic dependence of electron fluxes in the outer belt on the solar wind dynamic pressure.}, language = {en} } @article{SmirnovBerrendorfShpritsetal.2020, author = {Smirnov, Artem and Berrendorf, Max and Shprits, Yuri Y. and Kronberg, Elena A. and Allison, Hayley J. and Aseev, Nikita and Zhelavskaya, Irina and Morley, Steven K. and Reeves, Geoffrey D. and Carver, Matthew R. and Effenberger, Frederic}, title = {Medium energy electron flux in earth's outer radiation belt (MERLIN)}, series = {Space weather : the international journal of research and applications}, volume = {18}, journal = {Space weather : the international journal of research and applications}, number = {11}, publisher = {American geophysical union, AGU}, address = {Washington}, issn = {1542-7390}, doi = {10.1029/2020SW002532}, pages = {20}, year = {2020}, abstract = {The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120-600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on >15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis.}, language = {en} } @article{SmirnovShpritsAllisonetal.2022, author = {Smirnov, Artem and Shprits, Yuri Y. and Allison, Hayley and Aseev, Nikita and Drozdov, Alexander and Kollmann, Peter and Wang, Dedong and Saikin, Anthony}, title = {Storm-Time evolution of the Equatorial Electron Pitch Angle Distributions in Earth's Outer Radiation Belt}, series = {Frontiers in astronomy and space sciences}, volume = {9}, journal = {Frontiers in astronomy and space sciences}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-987X}, doi = {10.3389/fspas.2022.836811}, pages = {15}, year = {2022}, abstract = {In this study we analyze the storm-time evolution of equatorial electron pitch angle distributions (PADs) in the outer radiation belt region using observations from the Magnetic Electron Ion Spectrometer (MagEIS) instrument aboard the Van Allen Probes in 2012-2019. The PADs are approximated using a sum of the first, third and fifth sine harmonics. Different combinations of the respective coefficients refer to the main PAD shapes within the outer radiation belt, namely the pancake, flat-top, butterfly and cap PADs. We conduct a superposed epoch analysis of 129 geomagnetic storms and analyze the PAD evolution for day and night MLT sectors. PAD shapes exhibit a strong energy-dependent response. At energies of tens of keV, the PADs exhibit little variation throughout geomagnetic storms. Cap PADs are mainly observed at energies < 300 keV, and their extent in L shrinks with increasing energy. The cap distributions transform into the pancake PADs around the main phase of the storm on the nightside, and then come back to their original shapes during the recovery phase. At higher energies on the dayside, the PADs are mainly pancake during pre-storm conditions and become more anisotropic during the main phase. The quiet-time butterfly PADs can be observed on the nightside at L> 5.6. During the main phase, butterfly PADs have stronger 90 degrees-minima and can be observed at lower L-shells (down to L = 5), then transitioning into flat-top PADs at L similar to 4.5 - 5 and pancake PADs at L < 4.5. The resulting PAD coefficients for different energies, locations and storm epochs can be used to test the wave models and physics-based radiation belt codes in terms of pitch angle distributions.}, language = {en} } @article{AseevShpritsWangetal.2019, author = {Aseev, Nikita and Shprits, Yuri Y. and Wang, Dedong and Wygant, John and Drozdov, Alexander and Kellerman, Adam C. and Reeves, Geoffrey D.}, title = {Transport and loss of ring current electrons inside geosynchronous orbit during the 17 March 2013 storm}, series = {Journal of geophysical research : Space physics}, volume = {124}, journal = {Journal of geophysical research : Space physics}, number = {2}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9380}, doi = {10.1029/2018JA026031}, pages = {915 -- 933}, year = {2019}, abstract = {Ring current electrons (1-100 keV) have received significant attention in recent decades, but many questions regarding their major transport and loss mechanisms remain open. In this study, we use the four-dimensional Versatile Electron Radiation Belt code to model the enhancement of phase space density that occurred during the 17 March 2013 storm. Our model includes global convection, radial diffusion, and scattering into the Earth's atmosphere driven by whistler-mode hiss and chorus waves. We study the sensitivity of the model to the boundary conditions, global electric field, the electric field associated with subauroral polarization streams, electron loss rates, and radial diffusion coefficients. The results of the code are almost insensitive to the model parameters above 4.5 RERE, which indicates that the general dynamics of the electrons between 4.5 RE and the geostationary orbit can be explained by global convection. We found that the major discrepancies between the model and data can stem from the inaccurate electric field model and uncertainties in lifetimes. We show that additional mechanisms that are responsible for radial transport are required to explain the dynamics of ≥40-keV electrons, and the inclusion of the radial diffusion rates that are typically assumed in radiation belt studies leads to a better agreement with the data. The overall effect of subauroral polarization streams on the electron phase space density profiles seems to be smaller than the uncertainties in other input parameters. This study is an initial step toward understanding the dynamics of these particles inside the geostationary orbit.}, language = {en} } @article{SmirnovKronbergDalyetal.2020, author = {Smirnov, Artem G. and Kronberg, Elena A. and Daly, Patrick W. and Aseev, Nikita and Shprits, Yuri Y. and Kellerman, Adam C.}, title = {Adiabatic Invariants Calculations for Cluster Mission: A Long-Term Product for Radiation Belts Studies}, series = {Journal of Geophysical Research: Space Physics}, volume = {125}, journal = {Journal of Geophysical Research: Space Physics}, number = {2}, publisher = {John Wiley \& Sons, Inc.}, address = {New Jersey}, pages = {12}, year = {2020}, abstract = {The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes.}, language = {en} }