Improving Solar and Geo-dynamo predictability: towards advanced integrated data assimilation techniques
The main goal of the project is to improve our physical understanding, and our capability to predict, the long-term magnetic activity of the Sun and the Earth. This understanding will be based on the analysis of 3D simulations that will be parameterized and implemented in low dimensional models amenable to data assimilation experiments.
Three-dimensional, self-consistent numerical simulations of solar and Earth interior magnetic field generation have made tremendous progress over the past 15 years, due to the dramatic increase in computational power.
In parallel advanced data assimilation pipelines have been implemented in geo and solar magnetohydrodynamics (MHD) to better constrain the short-term evolution of the magnetic field B. However, predictions of the long-term magnetic variations on the Earth and the Sun are intractable with 3-D simulations. This imposes to develop more conceptual, lower dimensional models in order to support (by objective comparison with data) our 3-D studies of the origin of the long-terms variations of B, such as rare and irregular polarity reversals, or solar grand minima. Our group has developed such models (of the mean-field flux transport type) together with a variational assimilation scheme to predict solar activity over one solar cycle (11 yr). We propose here to improve these models, and to propose new models, to be able to characterize the long term behavior of the Earth and the Sun.
The questions that we wish to address are :
- What are the physical mechanisms responsible for the long-term magnetic variability of the Sun and the Earth?
- What is the predictability of the low-frequency/rare events such as solar minima and geomagnetic reversals?
- Can we make robust forecasts of these events using, eg., partly simplified (parameterized) models?
These questions, whose answers must rely on the available observational evidence, can be cast in the general framework of data assimilation. Utilizing data assimilation techniques to study the long-term behaviour of the magnetism of the Sun and the Earth is currently out of reach if one wishes to resort to high-resolution 3-D models based on first-principles (the cost of assimilation is 10 to 100 times that of a single model integration). Our goal is to analyze complex, 3-D simulations of the solar- and geo-dynamo in order to extract the fundamental mechanisms which control the long-term magnetic variability of these objects, and to test these mechanisms against observations by placing them at the core of conceptual models of moderate size well-suited for data assimilation. These observations will include systematic sunspot count since the early 1600s for the Sun (encompassing the Maunder minimum) and geomagnetic intensity for the past 2 Myr (covering 5 reversals of polarity).
POSITION NAME SURNAME LABORATORY NAME GRADE, EMPLOYER WP leader Alexandre Fournier IPGP Professor (IPGP) WP co-leader A. Sacha Brun AIM Senior researcher (CEA) WP member Ching Pui Hung IPGP / AIM Post-doctoral researcher WP member Laurène Jouve IRAP / AIM Maître de conférences (U Toulouse) WP member Gauthier Hulot IPGP Senior Researcher (CNRS) WP member Thomas Gastine IPGP Junior Researcher (CNRS)
- Design of an operational tool for the prediction of solar activity
- Labex funded post-doc Ching-Pui Hung made considerable development which is likely to have the broader impact.
- Assimilation tool whose backbone is a mean-field model of the solar dynamo and which can convincingly estimate the deep circulation within the sun, based on the observation of sunspots and surface magnetograms.
- A paper submitted in February 2017 for publication in the Astrophysical Journal.
C. P. Hung, A. S. Brun, A. Fournier, L. Jouve, O. Talagrand, and M. Zakari, Variational estimation of the large scale time dependent meridional circulation in the Sun: proofs of concept with a solar mean field solar dynamo model, accepted for publication in the Astrophysical Journal.
C. P. Hung, A. S. Brun, A. Fournier, L. Jouve, O. Talagrand, and M. Zakari , Estimating the Solar Meridional Flow and Predicting the 11-yr Cycle Using Advanced Variational Data Assimilation Techniques, Space Weather of the Heliosphere: Processes and Forecasts, Proceedings IAU Symposium No. 335, 2017, Claire Foullon & Olga Malandraki, ed.
Coarse predictions of dipole reversals by low-dimensional modeling and data assimilation, by M. Morzfeld, A.Fournier, and G. Hulot, 262, 8-27, 2017. doi: 10.1016/j.pepi.2016.10.007 (in connection with WP2)
Sandpile models and solar flares: eigenfunction decomposition for data assimilation, by A. Strugarek, A. S. Brun, P.Charbonneau and N. Vilmer, Space Weather of the Heliosphere: Processes and Forecasts, Proceedings IAU Symposium No. 335, 2017, Claire Foullon & Olga Malandraki, ed. Submitted
Hung, C.P., Jouve, L., Brun, A.S., Fournier, A., and Talagrand O., Estimating the deep solar meridional circulation using magnetic observations and a dynamo model: a variational approach,The Astrophysical Journal, 814, 151 (21 pp), 2015. doi:10.1088/0004-637X/814/2/151
Svanda, M., Brun, A.S., Roudier, T., Jouve, L., Polar cap magnetic field reversals during solar grand minima: could pores play a role?, Astronomy and Astrophysics, 586, A123 (11 pp), 2016.
Brun, A.S., Browning, M.K., Dikpati, M., Hotta, H., Strugarek, A., Recent Advances on Solar Global Magnetism and Variability, Space Science Reviews, 196, 101 (35 pp), 2015
Réville, V., Brun, A.S., Strugarek, A., et al., From Solar to Stellar Corona: The Role of Wind, Rotation, and Magnetism, The Astrophysical Journal, 814, 99 (9 pp), 2015
Alvan, L., Strugarek, A., Brun, A.S., Mathis, S., Garcia, R.A., Characterizing the propagation of gravity waves in 3D nonlinear simulations of solar-like stars, Astronomy and Astrophysics, 581, A112 (13 pp), 2015.
Augustson, K., Brun, A.S., Miesch, M., Toomre, J., Grand Minima and Equatorward Propagation in a Cycling Stellar Convective Dynamo, The Astrophysical Journal, 809, 149 (25 pp), 2015