A5064642116- Ionosphere and magnetosphere dynamics
- Earthquake Detection and Analysis
- Solar and Space Plasma Dynamics
- Geomagnetism and Paleomagnetism Studies
- Neural Networks and Applications
- Geophysics and Gravity Measurements
- GNSS positioning and interference
- Radiation Therapy and Dosimetry
- Gamma-ray bursts and supernovae
- Advanced Image Processing Techniques
- Seismic Waves and Analysis
- Blind Source Separation Techniques
- Image Enhancement Techniques
- Advanced X-ray and CT Imaging
- Image Retrieval and Classification Techniques
- Laser-Plasma Interactions and Diagnostics
- Atmospheric and Environmental Gas Dynamics
- Precipitation Measurement and Analysis
- Advanced Image and Video Retrieval Techniques
- Plasma Diagnostics and Applications
- Energy Load and Power Forecasting
- Geophysics and Sensor Technology
- Spacecraft Design and Technology
- Atmospheric Ozone and Climate
- Nuclear Physics and Applications
Huawei Technologies (China)
2024
GFZ Helmholtz Centre for Geosciences
2016-2023
Huawei Technologies (Sweden)
2023
University of Potsdam
2017-2022
Skolkovo Institute of Science and Technology
2014-2022
Harbin Institute of Technology
2021
Czech Academy of Sciences, Institute of Physics
2020
Planetary Science Institute
2016-2018
University of California, Los Angeles
2016-2018
Vavilov Institute of General Genetics
2015
The dipole configuration of the Earth's magnetic field allows for trapping highly energetic particles, which form radiation belts. Although significant advances have been made in understanding acceleration mechanisms belts, loss processes remain poorly understood. Unique observations on 17 January 2013 provide detailed information throughout belts energy spectrum and pitch angle (angle between velocity a particle field) distribution electrons up to ultra-relativistic energies. Here we show...
Periods of low plasma density allow chorus waves to accelerate radiation belt electrons ultrarelativistic energies.
Abstract The Earth’s ionosphere affects the propagation of signals from Global Navigation Satellite Systems (GNSS). Due to non-uniform coverage available observations and complicated dynamics region, developing accurate models has been a long-standing challenge. Here, we present Neural network-based model Electron density in Topside (NET), which is constructed using 19 years GNSS radio occultation data. NET tested against situ measurements several missions shows excellent agreement with...
Abstract We present the Neural‐network‐based Upper hybrid Resonance Determination (NURD) algorithm for automatic inference of electron number density from plasma wave measurements made on board NASA's Van Allen Probes mission. A feedforward neural network is developed to determine upper resonance frequency, f uhr , electric field measurements, which then used calculate density. In previous missions, bands were manually identified, and there have been few attempts do robust, routine automated...
Abstract Geomagnetic indices are convenient quantities that distill the complicated physics of some region or aspect near‐Earth space into a single parameter. Most best‐known calculated from ground‐based magnetometer data sets, such as Dst, SYM‐H, Kp, AE, AL, and PC. Many models have been created predict values these indices, often using solar wind measurements upstream Earth input variables to calculation. This document reviews current state geomagnetic methods used assess their ability...
Abstract We present the PINE (Plasma density in Inner magnetosphere Neural network‐based Empirical) model ‐ a new empirical for reconstructing global dynamics of cold plasma distribution based only on solar wind data and geomagnetic indices. Utilizing database obtained using NURD (Neural‐network‐based Upper hybrid Resonance Determination) algorithm period 1 October 2012 to July 2016, conjunction with indices, we develop neural network that is capable globally 2≤ L ≤6 all local times....
Abstract Chorus waves play an important role in the dynamic evolution of energetic electrons Earth's radiation belts and ring current. Using more than 5 years Van Allen Probe data, we developed a new analytical model for upper‐band chorus (UBC; 0.5 f c e < ) lower‐band (LBC; 0.05 waves, where is equatorial electron gyrofrequency. By applying polynomial fits to wave root mean square amplitudes, regression models LBC UBC as function geomagnetic activity (Kp), L , magnetic latitude ( λ ),...
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 electron flux both for low relativistic energies have been developed, behavior medium energy (120–600 keV) especially in MEO region, remains poorly quantified. At these energies, electrons are driven by convective diffusive transport, their prediction usually requires sophisticated 4D modeling codes. In...
Abstract Van Allen Probes measurements revealed the presence of most unusual structures in ultra‐relativistic radiation belts. Detailed modeling, analysis pitch angle distributions, difference between relativistic and ultra‐realistic electron evolution, along with theoretical studies scattering wave growth, all indicate that electromagnetic ion cyclotron (EMIC) waves can produce a very efficient loss electrons heart Moreover, detailed profiles phase space densities provides direct evidence...
Electron flux in the Earth's outer radiation belt is highly variable due to a delicate balance between competing acceleration and loss processes. It has been long recognized that Electromagnetic Ion Cyclotron (EMIC) waves may play crucial role of electrons. Previous theoretical studies proposed EMIC account for relativistic electron population. However, recent observations showed while are responsible significant ultra-relativistic electrons, population almost unaffected. In this study, we...
Abstract Current algorithms for the real‐time prediction of K p index use a combination models empirically driven by solar wind measurements at L1 Lagrange point and historical values index. In this study, we explore limitations approach, examining forecast short long lead times using time series as input to artificial neural networks. We relative efficiency wind‐based predictions, predictions based on recurrence, persistence. Our modeling results show that short‐term forecasts approximately...
A machine learning technique is implemented for retrieving space-borne Global Navigation Satellite System Reflectometry (GNSS-R) wind speed. Conventional approaches commonly fit a function in predefined form to matchup data least-squares (LS) sense, mapping GNSS-R observations In this study, feedforward neural network trained TechDemoSat-1 (TDS-1) speed inversion. The input variables, along with the derived bistatic radar cross-section σ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...
Abstract Understanding the dynamic evolution of relativistic electrons in Earth's radiation belts during both storm and nonstorm times is a challenging task. The U.S. National Science Foundation's Geospace Environment Modeling (GEM) focus group “Quantitative Assessment Radiation Belt Modeling” has selected two time events that occurred second year Van Allen Probes mission for in‐depth study. Here, we perform simulations these GEM challenge using 3D Versatile Electron code. We set up outer L...
Abstract Over the last 20 years, a large number of instruments have provided plasma density measurements in Earth's topside ionosphere. To utilize all collected observations for empirical modeling, it is necessary to ensure that they do not exhibit systematic differences and are adjusted same reference frame. In this study, we compare satellite from Gravity Recovery Climate Experiment (GRACE), Constellation Observing System Meteorology, Ionosphere, (COSMIC), CHAllenging Minisatellite Payload...
Abstract Up until recently, signatures of the ultrarelativistic electron loss driven by electromagnetic ion cyclotron (EMIC) waves in Earth's outer radiation belt have been limited to direct or indirect measurements precipitation narrowing normalized pitch angle distributions heart belt. In this study, we demonstrate additional observational evidence that can be resonant interaction with EMIC waves. We analyzed profiles derived from Van Allen Probe particle data as a function time and three...
Abstract The Kp index is a measure of the midlatitude global geomagnetic activity and represents short‐term magnetic variations driven by solar wind plasma interplanetary field. one most widely used indicators for space weather alerts serves as input to various models, such thermosphere radiation belts. It therefore crucial predict accurately. Previous work in this area has mostly employed artificial neural networks nowcast Kp, based their inferences on recent history measurements at L1. In...
Space weather driven atmospheric density variations affect low Earth orbit (LEO) satellites during all phases of their operational lifetime. Rocket launches, re-entry events and space debris are also similarly affected. A better understanding processes impact on is thus critical for satellite operations as well safety issues. The Horizon 2020 project Weather Atmosphere Model Indices (SWAMI) project, which started in January 2018, aims to enhance this by: Developing improved neutral...
Abstract In recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These network‐based models capture large‐scale of plasmasphere, such as plume formation and erosion on nightside. However, their performance depends strongly availability training data. When data coverage is limited or non‐existent, occurs during geomagnetic storms, NNs significantly decreases, inherently cannot learn from number...
Abstract We present two new empirical models of radiation belt electron flux at geostationary orbit. GOES‐15 measurements 0.8 MeV electrons were used to train a Nonlinear Autoregressive with Exogenous input (NARX) neural network for both modeling values and an upper boundary condition scaling factor (BF). The model utilizes feedback delay 2 time steps (i.e., 5 min steps) the most efficient number hidden layers set 10. Magnetic local time, Dst, Kp , solar wind dynamic pressure, AE, velocity...
We introduce a new family of deep neural networks, where instead the conventional representation network layers as N-dimensional weight tensors, we use continuous layer along filter and channel dimensions. call such networks Integral Neural Networks (INNs). In particular, weights INNs are represented functions defined on hypercubes, discrete transformations inputs to replaced by integration operations, accordingly. During inference stage, our can be converted into traditional tensor via...
Abstract We present a reconstruction of the dynamics radiation belts from solar cycles 17 to 24 which allows us study how belt activity has varied between different cycles. The simulations are produced using Versatile Electron Radiation Belt (VERB)‐3D code. VERB‐3D code incorporate radial, energy, and pitch angle diffusion reproduce belts. Our use historical measurements Kp (available since cycle 17, i.e., 1933) model evolution L* = 1–6.6. A nonlinear auto regressive network with exogenous...
Abstract We have compared the location of mid‐latitude trough observed in two dimensional vertical total electron content (vTEC) maps with four plasmapause boundary models, Radiation Belt Storm Probes (RBSP) observations, and IMAGE extreme ultraviolet (EUV) observations all mapped to ionosphere pierce point using Tsyganenko (1996) magnetic field line model. For this study, we examine events over North America: one just after October 13, 2012 storm, during April 20, 2002 double another a...
Abstract Using over‐5‐year EMFISIS wave measurements from Van Allen Probes, we present a detailed survey to identify the controlling factors among geomagnetic indices and solar wind parameters for 1‐min root mean square amplitudes of lower band chorus (LBC) upper (UBC). A set important features are automatically determined by feature selection techniques, namely, Random Forest Maximum Relevancy Minimum Redundancy. Our analysis results indicate AE index with zero‐time‐delay dominates...