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Credits

This ML pipeline or parts thereof is open source and can be used by anyone for their research. However, this does not mean that credits shouldn't be given to the main developers.

If you want to use this ML pipeline or parts thereof for your own research, please provide credits to the developers in the following way:

  1. For the first two publications resulting from the use of this ML pipeline or parts thereof

  • Please add the following authors to the list of authors: Rüdisser Hannah T., Austrian Space Weather Office, GeoSphere Austria, Graz, Austria

  • Please add the following sentence to the acknowledgements: Europlanet 2024 RI has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149.

  1. For the third and all following publications resulting from the use of this ML pipeline or parts thereof
  • Please add the following sentences to the acknowledgements: The used ML pipeline was developed in the course of Europlanet 2024 RI by Hannah T. Rüdisser (Austrian Space Weather Office, GeoSphere Austria, Graz). Europlanet 2024 RI has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149.

IWF - ICME detection

This project is about the science case proposed by the IWF, entitled "Detection and classification of ICMEs in in-situ solar wind data". The publication about this project can be found here:

  • Rüdisser H.T., Windisch A., Amerstorfer U.V., Möstl C., Amerstorfer T., Bailey R.L., and Reiss M.A. (2022), Automatic detection of interplanetary coronal mass ejections in solar wind in situ data, Space Weather 20, e2022SW003149, doi:10.1029/2022SW003149.

Useful links and resources

  1. in situ solar wind data (only numbers in numpy structured arrays): https://doi.org/10.6084/m9.figshare.12058065.v7

  2. the same in situ solar wind data as datetime objects in recarrays: https://doi.org/10.6084/m9.figshare.11973693.v7

  3. jupyther notebook for reading the data of (2) and from an ICME catalogue (first two code cells): https://github.com/cmoestl/heliocats/blob/master/cme_rate.ipynb

  4. to install the conda environment to run the code for (3): https://github.com/cmoestl/heliocats/blob/master/README.md

  5. the ICMECAT catalogue in different formats (see section below ICME CATALOGUE v2.0): https://helioforecast.space/icmecat

  6. solar wind forecast: https://helioforecast.space/solarwind

Further literature:

  • Luhmann J.G., Gopalswamy N., Jian L.K., and Lugaz N. (2020), ICME evolution in the inner heliosphere, Solar Phys. 295:61, doi:s11207-020-01624-0
  • Möstl C., Farrugia C.J., Temmer M., Miklenic C., Veronig A.M., Galvin A.B., Leitner M., and Biernat H.K. (2009), Linking Remote Imagery of a Coronal Mass Ejection to Its In Situ Signatures at 1 AU, Astrophys. J. Lett. 705, L180-L185, doi:10.1088/0004-637X/705/2/L180
  • Möstl C., Temmer M., Rollett T., Farrugia C.J., Liu Y., Veronig, A.M., Leitner M., Galvin, A.B., and Biernat H.K. (2010), STEREO and Wind observations of a fast ICME flank triggering a prolonged geomagnetic storm on 5-7 April 2010, Geophys. Res. Letters 37, L24103, doi:10.1029/2010GL045175
  • Richardson I.G. (2018), Solar wind stream interaction regions throughout the heliosphere, Living Reviews in Solar Physics 15, doi:10.1007/s41116-017-0011-z
  • Zurbuchen T.H. and Richardson I.G. (2006), In-Situ Solar Wind and Magnetic Field Signatures of Interplanetary Coronal Mass Ejections, Space Sci. Rec. 123, 31-43, doi:10.1007/s11214-006-9010-4