Nikita Alexandrovich Aseev

Understanding the dynamics of energetic electrons in the radiation belts is key to protect space borne equipment and astronauts on-board spacecraft missions. Therefore, global reconstruction of the near-Earth radiation environment should be available at all times, radial distances and geomagnetic latitudes. Low Earth Orbit (LEO) satellites provide a large data set of rapid observations of the radiation belt region over a wide range of magnetic local times (MLT). However, the use of this data set is rather complicated due to possible proton contamination of electron fluxes and the observation of electron precipitation, leading to high variability of electron measurements, considerable instrumental errors and the need for background correction. In this study, we present a new intercalibration method for satellite measurements of energetic electrons in the radiation belt region using a data assimilation approach. Our aim is to intercalibrate the electron flux measurements of the POES satellites NOAA-15,-16,-17,-18,-19 and MetOp-02 against RBSP observations for the period October 2012 to December 2013. For this, we use a reanalysis of the radiation belt region, obtained by assimilating RBSP and GOES electron data into 3-D Versatile Electron Radiation Belt (VERB-3D) code simulations via a standard Kalman filter. Since the reanalysis provides global reconstruction of the state of the system. We compare the POES/MetOp data with our reanlysis and estimate the flux ratios at each time, location and energy. These ratios are averaged over time and space to obtain energy dependent recalibration coefficients. In order to validate our results, we perform a traditional conjunction study between POES/MetOp satellites and the Van Allen probes. Similarly, we estimate flux ratios for all the found conjunctions and calculate the corresponding energy dependent recalibration coefficients. The conjunction coefficients and the DA estimated coefficients show very good agreement. Additionally, the use of data assimilation allows for improved statistics, as the number of possible ratios is considerably improved. The recalibration coefficients estimated using the our data assimilation approach leads to good resemblance and agreement between the recalibrated POES/MetOp data set and the RBSP observations.

Low Earth Orbit satellites offer extensive data of the radiation belt region, but utilizing these observations is challenging due to potential contamination and difficulty of intercalibration with spacecraft measurements at Highly Elliptic Orbit that can observe all equatorial pitch‐angles. This study introduces a new intercalibration method for satellite measurements of energetic electrons in the radiation belts using a Data assimilation (DA) approach. We demonstrate our technique by intercalibrating the electron flux measurements of the National Oceanic and Atmospheric Administration (NOAA) Polar‐orbiting Operational Environmental Satellites (POES) NOAA‐15,‐16,‐17,‐18,‐19, and MetOp‐02 against Van Allen Probes observations from October 2012 to September 2013. We use a reanalysis of the radiation belts obtained by assimilating Van Allen Probes and Geostationary Operational Environmental Satellites observations into 3‐D Versatile Electron Radiation Belt (VERB‐3D) code simulations via a standard Kalman filter. We compare the reanalysis to the POES data set and estimate the flux ratios at each time, location, and energy. From these ratios, we derive energy and L* dependent recalibration coefficients. To validate our results, we analyze on‐orbit conjunctions between POES and Van Allen Probes. The conjunction recalibration coefficients and the data‐assimilative estimated coefficients show strong agreement, indicating that the differences between POES and Van Allen Probes observations remain within a factor of two. Additionally, the use of DA allows for improved statistics, as the possible comparisons are increased 10‐fold. Data‐assimilative intercalibration of satellite observations is an efficient approach that enables intercalibration of large data sets using short periods of data.

In this study, we present an empirical model of the equatorial electron pitch angle distributions (PADs) in the outer radiation belt based on the full data set collected by the Magnetic Electron Ion Spectrometer (MagEIS) instrument onboard the Van Allen Probes in 2012–2019. The PADs are fitted with a combination of the first, third and fifth sine harmonics. The resulting equation resolves all PAD types found in the outer radiation belt (pancake, flat‐top, butterfly and cap PADs) and can be analytically integrated to derive omnidirectional flux. We introduce a two‐step modeling procedure that for the first time ensures a continuous dependence on L, magnetic local time and activity, parametrized by the solar wind dynamic pressure. We propose two methods to reconstruct equatorial electron flux using the model. The first approach requires two uni‐directional flux observations and is applicable to low‐PA data. The second method can be used to reconstruct the full equatorial PADs from a single uni‐ or omnidirectional measurement at off‐equatorial latitudes. The model can be used for converting the long‐term data sets of electron fluxes to phase space density in terms of adiabatic invariants, for physics‐based modeling in the form of boundary conditions, and for data assimilation purposes.

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, https://doi.org/10.1029/2020sw002524), for which the results featured in this paper were used.

Measurements from the Van Allen Probes mission clearly demonstrated that the radiation belts cannot be considered as a bulk population above approximately electron rest mass. Ultra-relativistic electrons (~>4Mev) form a new population that shows a very different morphology (e.g. very narrow remnant belts) and slow but sporadic acceleration.We show that acceleration to multi-MeV energies can not only result of two-step processes consisting of local heating and radial diffusion but occurs locally due to energy diffusion by whistler-mode waves. Local heating appears to be able to transport electrons in energy space from 100s of keV all the way to ultra-relativistic energies (>7MeV) and is a dominant process for acceleration to ultra-relativistic energies. Acceleration to such high energies occurs only for the conditions when cold plasma in the trough region is extremely depleted down to the values typical for the plasma sheet.There is also a clear difference between the loss mechanisms at MeV and multi MeV energies. The difference between the loss mechanisms at MeV and multi-MeV energies is due to EMIC waves, that can very efficiently scatter ultra-relativistic electrons, but leave MeV electrons unaffected.These observations and modelling clearly show that cold plasma at eV energies has a controlling effect on the trapped electrons at energies seven orders of magnitude more energetic. Depletion in cold plasma is a requirement for acceleration while fast loss occurs only in the regions of high plasma density.We also present how the new understanding gained from the Van Allen Probes mission can be used to produce the most accurate data assimilative forecast. Under the recently funded EU Horizon 2020 Project Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) we will study how ensemble forecasting from the Sun can produce long-term probabilistic forecasts of the radiation environment in the inner magnetosphere.

Reconstruction and prediction of the state of the near-Earth space environment is important for anomaly analysis, development of empirical models, and understanding of physical processes. Accurate reanalysis or predictions that account for uncertainties in the associated model and the observations, can be obtained by means of data assimilation. The ensemble Kalman filter (EnKF) is one of the most promising filtering tools for nonlinear and high dimensional systems in the context of terrestrial weather prediction. In this study, we adapt traditional ensemble-based filtering methods to perform data assimilation in the radiation belts. By performing a fraternal twin experiment, we assess the convergence of the EnKF to the standard Kalman filter (KF). Furthermore, with the split-operator technique, we develop two new three-dimensional EnKF approaches for electron phase space density that account for radial and local processes, and allow for reconstruction of the full 3D radiation belt space. The capabilities and properties of the proposed filter approximations are verified using Van Allen Probe and GOES data. Additionally, we validate the two 3D split-operator Ensemble Kalman filters against the 3D split-operator KF. We show how the use of the split-operator technique allows us to include more physical processes in our simulations and is a computationally efficient data assimilation tool that delivers an accurate approximation of the optimal KF solution, and is suitable for real-time forecasting.

Pitch angle distributions (PADs) of trapped particles play an important role in understanding the processes driving the dynamics of Earth’s radiation belts and ring current. The Van Allen Probes mission has provided electron observations of PADs with an unprecedented coverage in energy (from tens of keV to several MeV) and pitch angles during the mission’s lifespan. We approximate the equatorial electron PADs using the Fourier sine series expansion up to degree 5. The corresponding coefficients can be directly related to the main PAD shapes (pancake, butterfly, flat-top and cap), and the approximated PADs can be easily integrated and converted to omnidirectional flux. Using the entire Van Allen Probes MagEIS data set in 2012-2019, we analyze the response of the equatorial electron PAD shapes to 129 geomagnetic storms with minimum Dst< -50nT. At lower energies (<100 keV), the PADs are stable throughout geomagnetic storms and mainly exhibit a pancake shape. At higher energies, the storm-time PAD evolution depends on the magnetic local time (MLT). At dayside, the pancake distributions become steeper during the main phase and then recover to their original broader form during recovery phase, likely due to the inward radial diffusion. At nightside MLT, the butterfly distributions become more pronounced during the main phase due to the combination of drift-shell splitting and magnetopause shadowing. We present a simple polynomial regression model of PAD shapes driven by the solar wind dynamic pressure. The model allows reconstructions of the full equatorial PADs based on uni-directional measurements at low equatorial pitch angles (applicable to LEO satellite data), as well as from omnidirectional electron flux observations and significantly outperforms the standard sin(alpha) approximation.

The particle flux in the near-Earth environment can increase by orders of magnitude during geomagnetically active periods. This leads to intensification of particle precipitation into Earth’s atmosphere. The process potentially further affects atmospheric chemistry and temperature.In this research, we concentrate on ring current electrons and investigate precipitation mechanisms on a short time scale using a numerical model based on the Fokker-Planck equation. We focus on understanding which kind of geomagnetic storm leads to stronger electron precipitation. For that, we considered two storms, corotating interaction region (CIR) and coronal mass ejection (CME) driven, and quantified impact on ring current. We validated results using observations made by POES satellite mission, low Earth orbiting meteorological satellites, and Van Allen Probes, and produced a dataset of precipitated fluxes that covers energy range from 1 keV to 1 MeV.

Measurements from the Van Allen Probes mission clearly demonstrated that the radiation belts cannot be considered as a bulk population above approximately electron rest mass. Ultra-relativistic electrons (~>4Mev) form a new population that shows a very different morphology (e.g. very narrow remnant belts) and slow but sporadic acceleration.We show that acceleration to multi-MeV energies can not only result of a two-step processes consisting of local heating and radial diffusion but occurs locally due to energy diffusion by whistler mode waves. Local heating appears to be able to transport electrons in energy space from 100s of keV all the way to ultra-relativistic energies (>7MeV). Acceleration to such high energies occurs only for the conditions when cold plasma in the trough region is extremely depleted down to the values typical for the plasma sheet.There is also a clear difference between the loss mechanisms at MeV and multi MeV energies The difference between the loss mechanisms at MeV and multi-MeV energies is due to EMIC waves that can very efficiently scatter ultra-relativistic electrons, but leave MeV electrons unaffected.We also present how the new understanding gained from the Van Allen Probes mission can be used to produce the most accurate data assimilative forecast. Under the recently funded EU Horizon 2020 Project Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) we will study how ensemble forecasting from the Sun can produce long-term probabilistic forecasts of the radiation environment in the inner magnetosphere.