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Towards Estimating the Solar Meridional Flow and Predicting the 11-yr Cycle Using Advanced Variational Data Assimilation Techniques

Published online by Cambridge University Press:  24 July 2018

Ching Pui Hung ,
Allan Sacha Brun ,
Alexandre Fournier ,
Laurène Jouve ,
Olivier Talagrand  and
Mustapha Zakari
Ching Pui Hung
Affiliation:
Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot UMR 7154 CNRS, F-75005 Paris, France email: [email protected] Laboratoire AIM Paris-Saclay, CEA/IRFU Université Paris-Diderot CNRS/INSU, 91191 Gif-Sur-Yvette, France
Allan Sacha Brun
Affiliation:
Laboratoire AIM Paris-Saclay, CEA/IRFU Université Paris-Diderot CNRS/INSU, 91191 Gif-Sur-Yvette, France
Alexandre Fournier
Affiliation:
Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot UMR 7154 CNRS, F-75005 Paris, France email: [email protected]
Laurène Jouve
Affiliation:
Laboratoire AIM Paris-Saclay, CEA/IRFU Université Paris-Diderot CNRS/INSU, 91191 Gif-Sur-Yvette, France Université de Toulouse, UPS-OMP, Institut de Recherche en Astrophysique et Planétologie, 31028 Toulouse Cedex 4, France
Olivier Talagrand
Affiliation:
Laboratoire de météorologie dynamique, UMR 8539, Ecole Normale Supérieure, Paris Cedex 05, France
Mustapha Zakari
Affiliation:
Institut de Physique du Globe de Paris, Sorbonne Paris Cité, Université Paris Diderot UMR 7154 CNRS, F-75005 Paris, France email: [email protected]
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Abstract

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We present in this work the development of a solar data assimilation method based on an axisymmetric mean field dynamo model and magnetic surface data. Our mid-term goal is to predict the solar quasi cyclic activity. We focus on the ability of our variational data assimilation algorithm to constrain the deep meridional circulation of the Sun based on solar magnetic observations. Within a given assimilation window, the assimilation procedure minimizes the differences between data and the forecast from the model, by finding an optimal meridional circulation in the convection zone, and an optimal initial magnetic field, via a quasi-Newton algorithm. We demonstrate the capability of the technique to estimate the meridional flow by a closed-loop experiment involving 40 years of synthetic, solar-like data. We show that the method is robust in estimating a (stochastic) time-varying flow fluctuating 30% about the average, and that the horizon of predictability of the method is ~ 1 cycle length.

Keywords

Dynamomeridional circulationdata assimilationnumerical
Type
Contributed Papers
Information
Proceedings of the International Astronomical Union , Volume 13 , Symposium S335: Space Weather of the Heliosphere: Processes and Forecasts , July 2017 , pp. 183 - 186
Copyright
Copyright © International Astronomical Union 2018 

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