The focus of Working Group A was to understand the issues involved in predicting long-term solar cycle variability over timescales of years to decades. Ultimately, levels of solar activity and magnetic variations of the Sun control the fluxes of solar energetic particles (SEPs) and galactic cosmic rays that are of key importance for human and robotic exploration of the Moon, Mars, and beyond.
Sunspot number is well correlated with several other measures of solar activity, including sunspot area, 10.7 cm radio flux, x-ray flares, total irradiance, the geomagnetic aa index, and cosmic ray flux. The long record of sunspot number helps in the characterization of features of past solar cycles. Feature-recognition techniques may help to better characterize magnetic structures on the Sun. This ability could, in turn, lead to the prediction of activity levels with a lead time of several years. Cycle 23 was accurately predicted using a curve-fitting technique that used the cycle properties for the first year or two from the prior solar minimum. Thus, this type of technique can give several-year forecasting capability once a given cycle is under way.
Dynamo models that incorporate deep meridional flow throughout the convection zone to transport magnetic flux (so-called flux-transport models) may have considerable predictive capability. These models transport flux toward the solar equator at the base of the convection zone. It is known that magnetic-field maps show the equatorward drift of active regions, Hale’s polarity law, differential solar rotation, and pole-ward meridional flow. “Magnetic persistence,” or the duration of the Sun’s memory of its own magnetic field, can be controlled by meridional circulation in the solar convection zone.
There is a flux-transport, dynamo-based prediction scheme for solar activity. It describes the poloidal source on the basis of sunspot areas. In other words, the time variation of the poloidal source function within each sunspot cycle is derived from observations of the sunspot areas during that cycle. A predictive