• Clicking on the title will open a new window with all details of the bibliographic entry.
  • Clicking on the DOI link will open a new window with the original bibliographic entry from the publisher.
  • Clicking on a single author will show all publications by the selected author.
  • Clicking on a single keyword, will show all publications by the selected keyword.

Found 2 entries in the Bibliography.

Showing entries from 1 through 2


Operational Nowcasting of Electron Flux Levels in the Outer Zone of Earth\textquoterights Radiation Belt

We describe a lightweight, accurate nowcasting model for electron flux levels measured by the Van Allen probes. Largely motivated by Rigler et al. [2004], 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 particle fluxes within the radiation belts. Real-time estimation of the parameters of the model is done using a Kalman Filter, where the state of the model is exactly the parameters. Nowcast performance is assessed against several baseline interpolation schemes. Our model demonstrates significant improvements in performance over persistence nowcasting. In particular, during times of high geomagnetic activity, our model is able to attain performance substantially better than a persistence model. In addition, residual analysis is conducted in order to assess model fit, and to suggest future improvements to the model.

Coleman, Tim; McCollough, James; Young, Shawn; Rigler, E.;

Published by: Space Weather      Published on: 04/2018

YEAR: 2018     DOI: 10.1029/2017SW001788

forecasting; Kalman Filter; Van Allen Probes


Intelligent Sampling of Hazardous Particle Populations in Resource-Constrained Environments

Sampling of anomaly-causing space environment drivers is necessary for both real-time operations and satellite design efforts, and optimizing measurement sampling helps minimize resource demands. Relating these measurements to spacecraft anomalies requires the ability to resolve spatial and temporal variability in the energetic charged particle hazard of interest. Here we describe a method for sampling particle fluxes informed by magnetospheric phenomenology so that, along a given trajectory, the variations from both temporal dynamics and spatial structure are adequately captured while minimizing oversampling. We describe the coordinates, sampling method, and specific regions and parameters employed. We compare resulting sampling cadences with data from spacecraft spanning the regions of interest during a geomagnetically active period, showing that the algorithm retains the gross features necessary to characterize environmental impacts on space systems in diverse orbital regimes while greatly reducing the amount of sampling required. This enables sufficient environmental specification within a resource-constrained context, such as limited telemetry bandwidth, processing requirements, and timeliness.

McCollough, J.; Quinn, J.; Starks, M.; Johnston, W.;

Published by: Space Weather      Published on: 10/2017

YEAR: 2017     DOI: 10.1002/2017SW001629

data sampling; magnetospheric plasma; measurement; Solar Energetic Protons; trapped electrons; trapped protons; Van Allen Probes