Dear Solar Physics Community,
We are writing to give advance notice (to add to your diaries) of a Royal Astronomical Society Specialist Discussion Meeting: “Future Solar and Heliospheric Assets for Space Weather Prediction: Instruments, Modelling and Machine-Learning” which will take place on Friday, April 22nd, 2022. Abstract submission details will be announced closer to the time.
This will likely be a hybrid in-person / virtual meeting, although this is still to be confirmed and subject to RAS policy at the time.
The UK has world leading heliophysics and space weather programmes with major involvement in operating space missions such as SOHO, STEREO and Solar Orbiter, ground-based facilities such as BISON and LOFAR, and the creation of the MET Office Space Weather Operations Centre. Notably, currently under development, is the Lagrange operational space weather mission to the Lagrange L5 point in which the UK has invested heavily via ESA’s Space Safety Programme. In tandem with further L1 missions under development, Lagrange will underpin a wave of new research opportunities aimed at increasing predictive capabilities for space weather forecasting.
As we enter the era of satellite mega-constellations and domestic rocket launches, and with the NASA/ESA Lunar Gateway Space Station due to be stationed outside the protective influence of the Earth’s magnetic field, there is a strong need to better understand the fundamental link between solar and interplanetary space weather and the near-Earth environment. As we observe increasing solar activity in Solar Cycle 25, a community wide effort is required to coordinate and synergise current and future developments.
We invite contributions from academic and space weather communities on all aspects of solar- and helio-physics starting from the solar surface, extending out through the solar corona, into the solar wind, and out to Earth’s orbit and beyond. The meeting will focus on three key themes:
1) Space-, ground-based and in-situ observations of the photosphere, corona and inner heliosphere;
2) Physical models which solve the relevant physics to make best use of sparse observations in space and to fill gaps where observations are unavailable; and
3) Data assimilation and machine learning techniques which are now understood to be fundamental for many regimes of space weather forecasting.
Dr. Enrico Camporeale (NOAA, University of Colarado)
Dr. Eftyhia Zesta (NASA Heliospherics Division)
Prof. Dr. Stefaan Poedts (Katholieke Universiteit Leuven)
Prof. Dr. Jasmina Magdalenić (Royal Observatory of Belgium)
We look forward to welcoming you at this meeting next year,
Ravindra Desai (Imperial College London)
Siegfried Gonzi (UK MET Office)
Jackie Davies (RAL Space)
Matthew Lang (University of Reading)