Summary
Short- and long-term prediction of solar activity and space weather are long-standing problems, affecting the society at a large scale: being able to issue a prediction earlier and more reliably will prevent economic losses for industries, space sector, and governments. During our ongoing ERC CoG project UniSDyn, we have numerically and observationally demonstrated the potential of a novel data product, the internal surface gravity oscillation mode, tracing the sub-surface magnetic field in the Sun, and here formulated methodologies to build prediction tools based on it both over short and long timescales. Earlier prediction methods have relied on magnetic fields on the solar surface or in the interplanetary space, while now we propose to use the solar internal oscillations as basis of the predictions - hence our ideas are novel and ground-braking. Innovation potential is augmented by the demonstrated capacity of the team to perform the demanding data analysis of the required data products for the proof-of-concept tools. Large innovation potential is also contained in new type of data service to be built: they augment the sustainability and re-usability of generic scientific data products, and enhance the renewal of science.
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| Web resources: | https://cordis.europa.eu/project/id/101101005 |
| Start date: | 01-02-2023 |
| End date: | 31-10-2024 |
| Total budget - Public funding: | - 150 000,00 Euro |
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Original description
Short- and long-term prediction of solar activity and space weather are long-standing problems, affecting the society at a large scale: being able to issue a prediction earlier and more reliably will prevent economic losses for industries, space sector, and governments. During our ongoing ERC CoG project UniSDyn, we have numerically and observationally demonstrated the potential of a novel data product, the internal surface gravity oscillation mode, tracing the sub-surface magnetic field in the Sun, and here formulated methodologies to build prediction tools based on it both over short and long timescales. Earlier prediction methods have relied on magnetic fields on the solar surface or in the interplanetary space, while now we propose to use the solar internal oscillations as basis of the predictions - hence our ideas are novel and ground-braking. Innovation potential is augmented by the demonstrated capacity of the team to perform the demanding data analysis of the required data products for the proof-of-concept tools. Large innovation potential is also contained in new type of data service to be built: they augment the sustainability and re-usability of generic scientific data products, and enhance the renewal of science.Status
SIGNEDCall topic
ERC-2022-POC2Update Date
09-02-2023
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