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Role of the Effective Prandtl Number on the Solar Convective Amplitude and Stratification, and Angular Momentum Transport

JAXA Supercomputer System Annual Report April 2017-March 2018

Report Number: R17EACA30

Subject Category: JSS2 Inter-University Research

PDF available here

  • Responsible Representative: Yuto Bekki, The University of Tokyo
  • Contact Information: Yuto Bekki bekki@mps.mpg.de
  • Members: Yuto Bekki, Takaaki Yokoyama, Hideyuki Hotta

Abstract

We have investigated a possible physical process to alleviate the huge discrepancy of the large-scale solar convective velocity between numerical simulations and local helioseismic observations (convective conundrum). It was shown for the first time that, if the solar convection is essentially magnetized and operates in an effectively high Prandtl number regime, the low wavenumber convective power can be efficiently suppressed owing to the enhanced subadiabatic layer in the deep convection zone. On the other hand, it was also found that the high-Prandtl number convection tends to transport the angular momentum radially inward, leading to a differential rotation inconsistent with observations. This study strongly suggests that the problems of convective heat transport and the angular momentum transport consists two sides of the same coin and must be solved integratedly.

Reference URL

N/A

Reasons for using JSS2

Large-scale convection simulations covering several tens of deep density scale heights were required to investigate the behavior of the low wavenumber convective power.

Achievements of the Year

To begin, we have developed a new numerical simulation code from scratch to solve the fully-compressible thermal convection in a three-dimensional cartesian box.

After the validity of the numerical code was verified, several sets of large-scale convection simulations were conducted using JAXA/JSS2 (Figure.1, Movie. 1).

It is shown that, in an effectively high-Prandtl number regime, the thermal convection is dominated by strong downflow plumes that can transport heat in a highly non-local manner. As a result, a subadiabatic (convectively-stable) layer formed near the base owing to the continuous deposition of low entropy meterials is enhanced and extended vertically upward.

Annual Reoprt Figures for 2017

Fig.1: Entropy structure of the high-Prandtl number thermal convection. The subsurface horizontal cut is shown at the bottom layer.

 

Fig.2(video): Upper panels: vertical velocity at (a) the surface, (b) middle convection zone, and (c) base. Lower panel: vertical cut of the entropy.

Publications

■ Peer-reviewed papers

1) Y. Bekki, H. Hotta, and T. Yokoyama., "Convective velocity suppression via the enhancement of the subadiabatic layer: Role of the effective Prandtl number", The Astrophysical Journal, 851;74 (2017)

■ Oral Presentations

1) Y. Bekki, H. Hotta, and T. Yokoyama., "Effects of the enhanced subadiabatic layer in effectively high-Prandtl number thermal convection", AAS 48th SPD Meeting, Portland, OR, USA. (2017. 8. 25).

2) Y. Bekki, H. Hotta, and T. Yokoyama., "Effects of Prandtl number on stratified thermal convection with and without rotation", Helicity Thinkshop 3, Tokyo, Japan. (2017. 11. 21).

■ Poster Presentation

1) Y. Bekki, H. Hotta, and T. Yokoyama., "Deep convective amplitude and stratification in an effectively high-Prandtl number thermal convection", IAU Symposium 340, Jaipur, India. (2018. 2. 19-24).

Usage of JSS2

Computational Information

  • Process Parallelization Methods: MPI
  • Thread Parallelization Methods: N/A
  • Number of Processes: 256 - 1024
  • Elapsed Time per Case: 120.00 hours

Resources Used

 

Fraction of Usage in Total Resources*1(%): 0.05

 

Details

Please refer to System Configuration of JSS2 for the system configuration and major specifications of JSS2.

Computational Resources
System Name Amount of Core Time
(core x hours)
Fraction of Usage*2(%)
SORA-MA 335,961.12 0.04
SORA-PP 0.00 0.00
SORA-LM 0.00 0.00
SORA-TPP 0.00 0.00

 

File System Resources
File System Name Storage Assigned
(GiB)
Fraction of Usage*2(%)
/home 100.14 0.07
/data 5,769.73 0.11
/ltmp 2,929.69 0.22

 

Archiver Resources
Archiver Name Storage Used
(TiB)
Fraction of Usage*2(%)
J-SPACE 0.00 0.00

*1: Fraction of Usage in Total Resources: Weighted average of three resource types (Computing, File System, and Archiver).

*2: Fraction of Usage:Percentage of usage relative to each resource used in one year.

JAXA Supercomputer System Annual Report April 2017-March 2018


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