Mausumi Dikpati (HAO/NCAR) Giuliana De Toma (HAO/NCAR) Roger Ulrich (UCLA) Peter Gilman (HAONCAR)

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CYCLE 24 ONSET: WHY MORE DELAYED THAN
PREDICTED
Mausumi Dikpati (HAO/NCAR)
Giuliana De Toma (HAO/NCAR)
Roger Ulrich (UCLA)
Peter Gilman (HAONCAR)
High Altitude Observatory (HAO) – National Center for Atmospheric Research (NCAR)
The National Center for Atmospheric Research is operated by the University Corporation for Atmospheric Research
under sponsorship of the National Science Foundation. An Equal Opportunity/Affirmative Action Employer.
Issues:
Why polar field so weak in cycle 23?
Dikpati et al. 2004; Dikpati, de Toma & Gilman 2008 (ApJ):
Primarily due to weak source of polar fields, arising from Babcock-Leighton type decay
of cycle 23 active regions;
But also a slow-down in meridional flow during 1996-2002 contributed to some extent
Cameron & Schuessler 2007 (ApJ):
Primarily due to weaker surface polar field source
Hathaway & Rightmire 2010 (Science):
Indirectly attributed to speed-up of meridional flow (derived from magnetic feature
movement) during 2002-present
Dasi-Espuig, Solanki, Krivova, Cameron & Penuela 2010 (A&A):
Due to the product of weak amplitude and weak tilt-angle; in other words due to weak
poloidal source
Sensitivity of models to the strength of
meridional flow:
Are surface transport models and flux-transport
dynamo models in conflict?
Answer is NO
5-deg flow-peak enhances l/f annihilation
decreases polar fld with flow-increase
Poloidal fields evolving in the meridional cut undergo two
effects due to flow increase: (i) increased polar
40-deg flow-peak enhances separation between l/f
convergence effect due to flow increase and, (ii)
increases polar fld with flow-increase
decreased diffusive decay due to sinking of fields to
depth of lower diffusivity
What happens in a self-excited dynamo?
Dikpati & Charbonneau 1999)
Due to increase in flow-speed polar field should increase by polar
convergence effect, but bottom toroidal field decreases, leading to
weaker polar field source.
Net effect depends on which process wins competetion
What happens in a self-excited dynamo?
Surface poloidal source has a much more dramatic effect on polar field
amplitude – decreasing the source by 90% decreases the polar field
amplitude by 95%. This is due to the product of surface source and
decreased bottom toroidal fields.
What happens in a self-excited dynamo?
With increasing flow-speed in a self-excited dynamo, bottom toroidal field decreases much faster
(red curve), decreasing the polar field source, than the polar field can increase due to flowconvergence effect. So the net result can be an ultimate decrease of polar fields (blue curve).
If the source effect is factored out, the convergence effect alone would result in increasing the polar
fields (green curve).
Why Cycle 24 onset has been more delayed than predicted?
Long-term meridional flow data from MWO indicate, a reverse cell at highlatitudes persisted in major period of cycles 19-22, whereas a large
single-cell predominates in cycle 23
Flux-transport dynamos produce longer period for longer conveyor-belt
Physics of differences in meridional flow
measurement
VD
VP
VD
Because of magnetic diffusion we expect plasma velocities and magnetic feature
velocities to be different. Diffusion and plasma flow add in high latitudes and compete in
low latitudes
Snodgrass & Dailey 1996
Conclusions
 Flux-transport dynamos and surface-transport models are
NOT IN CONFLICT. Both are able to explain polar field
behaviors with the physics included in the model
 Changes in polar fields with changes in meridional flow in
flux-transport dynamos can only be determined by detailed
numerical simulation, because there are competing physical
processes
 Doppler meridional flow and meridional movement of
magnetic features are different, and should be different.
Former measures the plasma flow and therefore can be used as
input to any advective-diffusive transport model; the latter
measures the transport by advection and diffusion and
therefore should be compared with the output of any advectivediffusive transport model to determine diffusion coefficient
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