Solar Subsurface Fluid Dynamics Descriptors Derived from Global Oscillation Network Group and Michelson Doppler Imager Data

Abstract

We analyze Global Oscillation Network Group (GONG) and Michelson Doppler Imager (MDI) observations obtained during Carrington rotation 1988 (2002 March 30-April 26) with a ring-diagram technique in order to measure the zonal and meridional flow components in the upper solar convection zone. We derive daily flow maps over a range of depths up to 16 Mm on a spatial grid of 75 in latitude and longitude covering ±60° in latitude and central meridian distance and combine them to make synoptic flow maps. We begin exploring the dynamics of the near-surface layers and the interaction between flows and magnetic flux by deriving fluid dynamics descriptors such as divergence and vorticity from these flow maps. Using these descriptors, we derive the vertical velocity component and the kinetic helicity density. For this particular Carrington rotation, we find that the vertical velocity component is anticorrelated with the unsigned magnetic flux. Strong downflows are more likely associated with locations of strong magnetic activity. The vertical vorticity is positive in the northern hemisphere and negative in the southern hemisphere. At locations of magnetic activity, we find an excess vorticity of the same sign as that introduced by differential rotation. The vertical gradient of the zonal flow is mainly negative except within 2 Mm of the surface at latitudes poleward of about 20°. The zonal-flow gradient appears to be related to the unsigned magnetic flux in the sense that locations of strong activity are also locations of large negative gradients. The vertical gradient of the meridional flow changes sign near about 7 Mm, marking a clear distinction between near-surface and deeper layers. GONG and MDI data show very similar results. Differences occur mainly at high latitudes, especially in the northern hemisphere, where MDI data show a counter cell in the meridional flow that is not present in the corresponding GONG data.