Space Climate 7 Meeting Abstract
An Attempt at Implementing Data Assimilation in a (Idealized) Radiative MHD Model of the Quiet Sun
Benoit Tremblay (Université de Montréal)
Alain Vincent (Université de Montréal)
Satellites and ground-based observatories probe the Sun's photosphere and atmosphere and are key in studying solar activity. Meanwhile, numerical models have attempted to bridge the gap between the physics of the solar interior and such observations. The following work explores how data assimilation, a notion widely used in meteorology, could be used in conjunction with these simulations to forecast short term solar activity for space-weather modelling purposes. Data assimilation adjusts the initial condition of a physical model so that the errors between the model prediction and observations within a window of time are minimized. The initial condition can then be used to forecast what comes beyond the assimilation window. But besides its use for predictions, data assimilation is on the whole an inversion technique. We attempt to implement data assimilation in a radiative MHD model of the Quiet Sun that ranges from the upper convection zone to the chromosphere. As a proof of concept, we present preliminary data assimilation experiments that were performed using synthetic data that was generated by a highly-idealized version of the physical model.
Mode of presentation: poster