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Abstract 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 non-linear and high dimensional systems in the context of terrestrial weather prediction. In ...
YEAR: 2021   DOI: https://doi.org/10.1029/2020SW002672
AbstractWe present a reconstruction of the dynamics of the radiation belts from Solar Cycles 17 – 24 which allows us to study how radiation belt activity has varied between the different solar cycles. The radiation belt simulations are produced using the Versatile Electron Radiation Belt (VERB)-3D code. The VERB-3D code simulations incorporate radial, energy, and pitch angle diffusion to reproduce the radiation belts. Our simulations use the historical measurements of Kp (available since Solar Cycle 17, i.e., 1933) to mode ...
YEAR: 2021   DOI: https://doi.org/10.1029/2020SW002524
We describe a lightweight, accurate nowcasting model for electron flux levels measured by the Van Allen probes. Largely motivated by Rigler et al. , we turn to a time-varying linear filter of previous flux levels and Kp. We train and test this model on data gathered from the 2.10 MeV channel of the Relativistic Electron-Proton Telescope (REPT) sensor onboard the Van Allen probes. Dynamic linear models are a specific case of state space models, and can be made flexible enough to emulate the nonlinear behavior of particl ...
YEAR: 2018   DOI: 10.1029/2017SW001788