Solar Cycle Prediction Using Precursors and Flux Transport Models

We study the origin of the predictive skill of some methods to forecast thestrength of solar activity cycles. A simple flux transport model for theazimuthally averaged radial magnetic field at the solar surface is used, whichcontains a source term describing the emergence of new flux based onobservational sunspot data. We consider the magnetic flux diffusing over theequator as a predictor, since this quantity is directly related to the globaldipole field from which a Babcock-Leighton dynamo generates the toroidal fieldfor the next activity cycle. If the source is represented schematically by anarrow activity belt drifting with constant speed over a fixed range oflatitudes between activity minima, our predictor shows considerable predictiveskill with correlation coefficients up to 0.95 for past cycles. However, thepredictive skill is completely lost when the actually observed emergencelatitudes are used. This result originates from the fact that the precursoramplitude is determined by the sunspot activity a few years before solarminimum. Since stronger cycles tend to rise faster to their maximum activity(known as the Waldmeier effect), the temporal overlapping of cycles leads to ashift of the minimum epochs that depends on the strength of the followingcycle. This information is picked up by precursor methods and also by our fluxtransport model with a schematic source. Therefore, their predictive skill doesnot require a memory, i.e., a physical connection between the surfacemanifestations of subsequent activity cycles.Comment: Astrophys. Journal, in pres