All non peer-reviewed team publications on ADS since 2018.
SOHO community meeting list
Upcoming conferences and workshops
European Space Weather Week, 20-24 Nov 2023, Toulouse, France
Möstl, C., U. V. Amerstorfer, H. T. Rüdisser, E. E. Davies, E. Weiler, T. Amerstorfer, M. Bauer, J. Le Louëdec, A. J. Weiss, M. A. Reiss, R. L. Bailey, R. Laker, T. Horbury, Predicting the geomagnetic effects of solar coronal mass ejections, session SWR02
Amerstorfer, U. V., H.T. Rüdisser, A.J. Weiss, and C. Möstl, Predicting CME flux rope signatures using 3DCORE, session SWR02
Rüdisser, H. T., A. J. Weiss, U. V. Amerstorfer, C. Möstl, E. E. Davies, T. Amerstorfer, M. Bauer, 3DCOREapp: Reconstruct CMEs using the "3D Coronal Rope Ejection Model", session SWR02
Davies, E. E., U. V. Amerstorfer, H.T. Rüdisser, C. Möstl, M. Bauer, T. Amerstorfer, E. Weiler, P. Hess, A. J. Weiss, M. A. Reiss, L. Green, D.M. Long, T. Nieves-Chinchilla, S. Pal, D. Trotta, T. S. Horbury, H. O'Brien, E. Fauchon-Jones, J. Morris, C.J. Owen, S.D. Bale, J.C. Kasper, Flux rope modeling of the 2022 Sep 5 CME observed by PSP and Solar Orbiter from 0.07 to 0.69 AU, session SWR02
Weiler, E., E. E. Davies, C. Möstl, U. V. Amerstorfer, H. T. Rüdisser, A. J. Weiss, T. Amerstorfer, Identification of multipoint ICMEs to understand their large-scale magnetic field structure using in situ and imaging observations, session 100CD-03
Amerstorfer, T., J.A. Davies, D. Barnes, M. Bauer, J. Le Louëdec, E. Weiler, C. Möstl, Space Weather Prediction using Heliospheric Images: A Data Assimilation Approach, session 100CD-04
Le Louëdec, J., M. Bauer, T. Amerstorfer, C. Möstl, Enhancing STEREO-HI data with machine learning for efficient CME forecasting, session SWR06
Bauer, M., T. Amerstorfer, J. Le Louëdec, C. Möstl, H. Rüdisser, Automated Detection and Tracking of CMEs in HI, session SWR02
Reiss, M., B. Perri, K. Muglach, E. Samara, R. Mullinix, C. Wiegand, M. Miesch, Bottlenecks in space weather model validation: Where do we stand and how do we move forward?, session 100CD-03
co-author:
Lugaz et al., The Width of Magnetic Ejecta near 1 AU: Consequence for Space Weather Forecasting
Regnault et al., Discrepancies in the Properties of the 2021 November 3-5 Coronal Mass Ejection on Scales of 0.03 AU Revealed by Simultaneous Measurements at Solar Orbiter and Wind
Cardiff Space Weather Conference 12-15 Sep 2023, UK
Hodnett, R., S. Gonzi, D. Jackson, M. Reiss, C. Möstl, H. Rüdisser, R.-L. Bailey, Prediction of Bz of Coronal Mass Ejections from observations at Lagrange Point L1
Davies, J., Barnes D., Amerstorfer T., Barnard L., Calogovic J., Temmer M., Results of Use Case 4 (UC4) of the ESA-funded "Use of L5 data in CME propagation models" activity
Past conferences and workshops
ICTP-SCOSTEP-ISWI School and Workshop on the Predictability of the Solar-Terrestrial Coupling - PRESTO (29 May–2 June 2023), Trieste, Italy
Amerstorfer, T., Status and future outlook on predicting space weather from Sun to Earth (invited)
Amerstorfer, U. V., Using 3DCORE to predict ICME flux rope signatures
European General Assembly (23–28 April 2023), Vienna, Austria
Möstl, C. et al., Forecasting southward pointing magnetic fields in solar coronal mass ejections, ST1.6
Amerstorfer, U. V. et al., Short term forecast of CME flux rope signatures using 3DCORE, ST4.1
Rüdisser, H. T. et al., Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind in Situ Data, ESSI1.3
Amerstorfer, T. et al., CME real time prediction using HI beacon data confined by a Solar Orbiter arrival, ST4.1
Bauer, M. et al., Predicting CMEs Using ELEvoHI With STEREO-HI Beacon Data, ST4.1
Bailey, R. L. et al., Analysis of six years of GIC measurements in the Austria power grid, EMRP2.13
Davies, E. E. et al., The effect of magnetic reconnection on ICME-related GCR modulation, ST1.10
Sessions convening:
Amerstorfer, U. V., Rüdisser, H., ESSI1.3, Machine Learning in Planetary Sciences and Heliophysics
Bailey, R. L., EMRP2.13, Modelling and measuring Geomagnetically Induced Currents in grounded infrastructure
Amerstorfer, T., ST4.1, Space Weather Prediction of Solar Wind Transients in the Heliosphere
Workshop on Machine Learning and Computer Vision in Heliophysics (April 19–21 2023), Sofia, Bulgaria
Bauer, M. et al., Automated CME detection and tracking in HI
Rüdisser, H. T. et al., Automatic Detection of Interplanetary Coronal Mass Ejections
Parker Solar Probe Science Working Group Meeting #23, (27–29 March, 2023), online
Talks:
Emma E. Davies, Flux rope modeling of the 2022 Sep 5 CME observed by PSP and Solar Orbiter from 0.07 to 0.69 AU
Parker Solar Probe – Solar Orbiter 5 Sep 2022 CME Workshop (13 February 2023), online
Talks:
Möstl, C., SolO/MAG & PSP/WISPR: CME evolution and flux rope modeling
PUNCH winter telecon (23 January 2023), online
Talks:
Möstl, C., Synergies between PUNCH and SOLO/HI
AGU Fall Meeting (12–16 December 2022), Chicago, USA
Talks:
Möstl, C., Weiss, A., Amerstorfer, U. V., Rüdisser, H. T., Amerstorfer, T., Bauer, M., Bailey, R. L., Reiss, M. A., Barnes, D., Davies, J. A., Harrison, R. A., Davies, E., Laker, R., Horbury, T. S., Heyner, D. and Bale, S., Multipoint In Situ and Imaging Observations of Interplanetary Coronal Mass Ejections with Solar Orbiter, BepiColombo, Parker Solar Probe, Wind, and STEREO-A
Reiss, M., Multi-spacecraft observations for enabling breakthroughs in space weather forecasting
Posters:
Bailey, R. L., Möstl, C., Reiss, M. A., Weiss, A., Amerstorfer, U. V., Amerstorfer, T., Eastwood, J., Leonhardt, J. and Magnes, W. The geomagnetic Vigil: How useful are Measurements at L5 for forecasting a Geomagnetic Index like Dst?
Weiss, A., Nieves-Chinchilla, T., Möstl, C., Reiss, C., Amerstorfer, T. and Bailey, R. L., Writhed Magnetic Flux Rope Model
Rüdisser, H., Reiss, M., Möstl, C., Amerstorfer, T., Amerstorfer, U. V., Weiss, A., Bailey, R., Windisch, A., Hinterreiter, J., Gonzi, S. and Jackson, D. Machine Learning for solving the Bz Problem in Space Weather Forecasting
European Space Weather Week (24–28 October 2022), Zagreb, Croatia
Talks:
Möstl, C., Weiss,A. J., Bailey, R. L., Reiss, M. A., Amerstorfer, T., Amerstorfer, U. V., Bauer, M., Rüdisser, H. T., Barnes, D., Davies, J. A., Harrison, R. A., Laker, R., Horbury, T., Heyner, D., Bale, S. Predicting the Bz magnetic field component in solar coronal mass ejections
Rüdisser, H. T., Windisch, A. , Amerstorfer, U. V., Möstl, C., Bailey, R. L., Amerstorfer, T., Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data
Posters:
Bailey, R. L., Leonhardt, R., Achleitner, G., Albert, D., Amerstorfer, T., Beck, P., Krauss, S., Latocha, M., Möstl, C., Nakamura, R., Reiss, M., Schachinger, P., Schönhuber, M., Schweitzer, S., Temmer, M., Veronig, A., SWAP: Establishing a network of space weather researchers and stakeholders in Austria
Reiss, M. A., Möstl, C., Bailey, R. L., Rüdisser, H., Amerstorfer, U. V., Amerstorfer, T., Weiss, A., Hinterreiter, J., and Windisch, A., Can Machine Learning solve the „Bz Problem” in Interplanetary Coronal Mass Ejections?
Session convening:
Gonzi, S., Pizzo, V., Adamson, E., Yordanova, E., Bailey, R. L., Session CD5: The Ensemble Method in Space Weather Forecasting: bridging the gap between expectation and reality (part 1)
Europlanet Science Congress (18–23 September 2022), Granada, Spain
Posters:
Amerstorfer, T., Bauer, M., Möstl, C., Barnard, L., Riley, P., Weiss, A. J., and Reiss, M. A., Morphological reconstruction of a multiple detected coronal mass ejection
Rüdisser, H. T., Windisch, A., Amerstorfer, U. V., Pisa, D., and Soucek, J., Automatic Detection and Classification of Boundary Crossings in Spacecraft in situ Data
Session convening:
Amerstorfer, U. V., Julka, S., Rüdisser, H. T., D'Amore, M., Rossi, A. P., Machine Learning in Planetary Sciences
Workshops:
Julka, S., Amerstorfer, U. V., Image Segmentation in planetary applications
Rüdisser, H., Soucek, J., Amerstorfer, U. V., Machine Learning Pipeline for Automated Detection of Magnetospheric Boundaries
Nodjoumi, G., Le Corre, D., Amerstorfer, U. V., MAPS and DeepLandforms: Open Source tools for landforms detection
European Conference on Machine Learning and Data Mining (18–23 September 2022), Grenoble, France
Talks:
Julka, S., Kirschstein, N., Granitzer, M., Lavrukhin, A., Amerstorfer, U. V., Deep Active Learning for Detection of Mercury’s Bow Shock and Magnetopause Crossings