THE PREDICTABILITY OF ADVECTION-DOMINATED FLUX-TRANSPORT SOLAR DYNAMO MODELS - INSU - Institut national des sciences de l'Univers Access content directly
Journal Articles The Astrophysical Journal Year : 2013

THE PREDICTABILITY OF ADVECTION-DOMINATED FLUX-TRANSPORT SOLAR DYNAMO MODELS

Abstract

Space weather is a matter of practical importance in our modern society. Predictions of forecoming solar cycles mean amplitude and duration are currently being made based on flux-transport numerical models of the solar dynamo. Interested in the forecast horizon of such studies, we quantify the predictability window of a representative, advection-dominated, flux-transport dynamo model by investigating its sensitivity to initial conditions and control parameters through a perturbation analysis. We measure the rate associated with the exponential growth of an initial perturbation of the model trajectory, which yields a characteristic timescale known as the e-folding time τ e. The e-folding time is shown to decrease with the strength of the α-effect, and to increase with the magnitude of the imposed meridional circulation. Comparing the e-folding time with the solar cycle periodicity, we obtain an average estimate for τ e equal to 2.76 solar cycle durations. From a practical point of view, the perturbations analyzed in this work can be interpreted as uncertainties affecting either the observations or the physical model itself. After reviewing these, we discuss their implications for solar cycle prediction.
Fichier principal
Vignette du fichier
Sanchez_2014_ApJ_781_8.pdf (2.75 Mo) Télécharger le fichier
Origin Publisher files allowed on an open archive
Loading...

Dates and versions

insu-01411576 , version 1 (07-12-2016)

Identifiers

Cite

Sabrina Sanchez, Alexandre Fournier, Julien Aubert. THE PREDICTABILITY OF ADVECTION-DOMINATED FLUX-TRANSPORT SOLAR DYNAMO MODELS. The Astrophysical Journal, 2013, 781 (1), pp.8. ⟨10.1088/0004-637X/781/1/8⟩. ⟨insu-01411576⟩
31 View
122 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More