Skip to content

Resources for papers published based on Helio4Cast software.

Notifications You must be signed in to change notification settings

helioforecast/Papers

Folders and files

NameName
Last commit message
Last commit date

Latest commit

author
Andreas J. Weiss
Feb 21, 2022
8c149bb · Feb 21, 2022

History

73 Commits
Apr 9, 2020
Jan 21, 2021
Jun 18, 2021
Nov 8, 2021
Nov 8, 2021
Nov 16, 2021
Oct 30, 2020
Jan 22, 2020
Feb 14, 2022

Repository files navigation

Papers

This repository contains the codes used and described in the following publications from April 2020 until February 2022 (from oldest to newest):

  1. Bailey2020_L5DstPrediction - Bailey, R. L., Möstl, C., Reiss, M. A., Weiss, A. J., Amerstorfer, U. V., Amerstorfer, T., et al. (2020). Prediction of Dst during solar minimum using In situ measurements at L5. Space Weather, 18, e2019SW002424. https://doi.org/10.1029/2019SW002424
  2. Moestl2020_PSP_rate - Möstl, C., Weiss, A. J., Bailey, R. L., Reiss, M. A., Amerstorfer, T., Hinterreiter, J., ..., Stansby, D. (2020, November). Prediction of the In Situ Coronal Mass Ejection Rate for Solar Cycle 25: Implications for Parker Solar Probe In Situ Observations. The Astrophysical Journal, 903(2), 92. https://doi.org/10.3847/1538-4357/abb9a1
  3. Weiss2020_3DCORE - Weiss, A. J., Möstl, C., Amerstorfer, T., Bailey, R. L., Reiss, M. A., Hinterreiter, J., ..., Bauer, M. (2021, jan). Analysis of coronal mass ejection flux rope signatures using 3dcore and approximate bayesian computation. The Astrophysical Journal Supplement Series, 252(1), 9. Retrieved from https://doi.org/10.3847/1538-4365/abc9bd
  4. Bailey2021_AmbSoWiML - Bailey, R. L., Reiss, M. A., Arge, C. N., Möstl, C., Henney, C. J., Owens, M. J., et al. (2021). Using gradient boosting regression to improve ambient solar wind model predictions. Space Weather, 19, e2020SW002673. https://doi.org/10.1029/2020SW002673
  5. Reiss2021_MLrope - Reiss, M. A., Möstl, C., Bailey, R. L., Rüdisser, H. T., Amerstorfer, U. V., Amerstorfer, T., et al. (2021). Machine learning for predicting the Bz magnetic field component from upstream in situ observations of solar coronal mass ejections. Space Weather, 19, e2021SW002859. https://doi.org/10.1029/2021SW002859
  6. Moestl2021_multipoint - Möstl, C., Weiss, A. J., Reiss, M. A., Amerstorfer, T., Bailey, R. L., Hinterreiter, J., ... Bale, S. D. (2022, jan). Multipoint interplanetary coronal mass ejections observed with solar orbiter, BepiColombo, parker solar probe, wind, and STEREO-A. The Astrophysical Journal Letters, 924(1), L6. https://doi.org/10.3847/2041-8213/ac42d0