Modeling the source temperature of fast and slow winds using a 16 moments multi-species model

Understanding the general properties of the various solar winds requires an understanding of the phenomena at their source. The properties of the solar wind are influenced by the exchange of energy at the base of the solar corona. For example, the speed of the solar wind is strongly influenced by the level of heating below the sonic point. The heating that occurs in the collisional part of the atmosphere modifies the ionisation level of the heavy elements and therefore their charge state. This is why the charge state ratios of heavy ions measured in the solar wind are good parameters for distinguishing between fast and slow solar winds. In this study, we use the new Irap solar atmospheric model (ISAM) to study the level of ionisation of heavy ions transported in fast and slow solar winds. ISAM is a 16-moment multi-species model that self-consistently couples the transport equations for neutral and ionised particles (H, p, e, He, O and Mg) from the lower chromosphere through the solar corona to the solar wind. The lower corona is a region that is strongly coupled to the transition region by the downward heat flux.

By solving first for H, p and e, we recover the results of previous modelling showing that variations in the source temperature modify the pressure of the transition region which, in turn, modulates the mass flux of the solar wind. Using an ad-hoc heating function characterised by a scale height inversely proportional to the expansion factor of the magnetic field lines channelling the solar wind, we first recover the general properties of the fast and slow solar winds, as well as the known observation that the source temperature of the slow wind is higher than that of the fast wind. We then solve explicitly the ionisation processes and the coupled transport of oxygen with the major species (H, p, e) in order to isolate the different processes that contribute to the ionisation level of the heavy ions. We compare the results of our modelling with spectroscopic and in situ data. This work was funded by the ERC SLOW SOURCE - DLV - 819189.