Simulating and Predicting Solar Cycles Using a Flux-Transport Dynamo

By M. Dikpati, P. Gilman. Proceedings of the International Astronomical Union, 2006

231 citations recorded by the source corpus.

Subfields: Astronomy and Astrophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/22b6fde963a70613c704126900519730883c5423

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Astronomy and Astrophysics

1. Paul Charbonneau
2. Mark S. Miesch
3. M. Browning
4. A. Brun
5. J. Toomre
6. S. Solanki
7. Benjamin P. Brown
8. N. Krivova

In Molecular Biology

1. Paul Charbonneau
2. Mark S. Miesch
3. M. Browning
4. J. Toomre
5. A. Brun
6. Benjamin P. Brown
7. S. Solanki
8. N. Krivova

Citations in the corpus

• ON THE WEAKENING OF THE POLAR MAGNETIC FIELDS DURING SOLAR CYCLE 23 (2009, background): “…next cycle are generated by converting the pre-existing poloidal field into toroidal flux (Cameron & Schüssler 2007; Choudhuri et al. 2007; Dikpati 2008; Dikpati & Gilman 2006; Dikpati et al. 2006, 2008; Hathaway 2009; Schatten 2005; Svalgaard et al. 2005; Wang & Sheeley 2009; Yeates et al. 2008).”
• Sunspot Group Tilt Angles and the Strength of the Solar Cycle (2010, methodology): “A more physicsbased approach is offered by models of the evolution of the Sun’s magnetic field, although recent dynamo computations have given controversial results for cycle 24 (Dikpati & Gilman, 2006; Choudhuri et al., 2007; Jiang et al., 2007).”
• Exploring the Physical Basis of Solar Cycle Predictions: Flux Transport Dynamics and Persistence of Memory in Advection- versus Diffusion-dominated Solar Convection Zones (2007, background): “Dikpati & Gilman (2006), in their highly advection-dominated model, show that bands of latitudinal field from three previous cycles remain “lined up in the meridional circulation conveyor belt”.”
• Solar Dynamo Theory (2014, methodology): “Dikpati et al. (2006) have developed a novel, dynamo-based prediction scheme in which a parameterization of the zonally averaged observed surface magnetic flux is used as a surface boundary condition to a modified Babcock-Leighton model (see also Dikpati & Gilman 2006).”
• Solar activity forecast with a dynamo model (2007, methodology): “We found a decaying solution, in contrast to the oscillatory solution which Dikpati et al. (2004) reported.”
• MAGNETIC WREATHS AND CYCLES IN CONVECTIVE DYNAMOS (2012, result): “Our results tend to support the recent studies with mean-field dynamo models, which suggests that the differential rotation of the convection zone may play a greater role in the generation of toroidal magnetic field than the tachocline (e.g., Dikpati & Gilman 2006; Muñoz Jaramillo et al. 2009).”
• Solar Cycle Prediction Using Precursors and Flux Transport Models (2006, methodology): “Input model according to Dikpati et al.(2006) The DDG model (Dikpati et al. 2006) is described in some more detail in Dikpati & Gilman (2006).”
• MAGNETIC CYCLES IN A CONVECTIVE DYNAMO SIMULATION OF A YOUNG SOLAR-TYPE STAR (2011, background): “…solar dynamo models where the advection of toroidal flux by the meridional circulation regulates cyclic activity (e.g., Wang & Sheeley 1991; Dikpati & Charbonneau 1999; Küker et al. 2001; Nandy & Choudhuri 2001; Dikpati & Gilman 2006; Rempel 2006; Jouve & Brun 2007; Yeates et al. 2008).”
• Data Assimilation in the ADAPT Photospheric Flux Transport Model (2014, unknown): “Observations were combined with a physical model by [13] who used and assimilation technique consisting of a simple data-nudging method.”