Sequential Data-assimilation in a Flux-transport Dynamo Model

Details Sequential Data-assimilation in a Flux-transport Dynamo Model Sequential Data-assimilation in a Flux-transport Dynamo Model

May 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009spd....40.1114d&link_type=abstract

American Astronomical Society, SPD meeting #40, #11.14; Bulletin of the American Astronomical Society, Vol. 41, p.827

Astronomy and Astrophysics

Astronomy

Scientific paper

Applying a very simplified data-nudging technique in a flux-transport dynamo, Dikpati, de Toma and Gilman predicted solar cycle amplitude and onset-timing of cycle 24 seperately. In order to simultaneously predict cycle amplitude and timing we have developed a sequential data-assimilation technique, in a similar way used in atmospheric and oceanic prediction models. However two major difficulties in applying this technique in solar dynamo models are, (i) equatorward return meridional circulation is unknown, (ii) time-varying surface flow measurements have not been available for years prior to 1996. With recent progress of Mount Wilson Observatory's flow-data analysis by Ulrich and colleagues, we can now go back to 1985. We build sequential data-assimilation into a flux-transport dynamo model by (i) solving mean and perturbation equations by incorporating time-varying meridional flow since 1985; (ii) investigating transport of assimilated poloidal magnetic fields from surface to tachocline, where they are sheared by differential rotation to create spot-producing fields; (iii) updating model after a finite time-interval, by comparing model-output with observations; (iv) forecasting simultaneously cycle-amplitude, duration and shape. We form an ensemble of model-runs whose outputs calibrate best with surface magnetic observations. The ensemble-average gives the simultaneous prediction of solar cycle timing, amplitude and shape.
This work is partially supported by NASA grant NNX08AQ34G.

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