Understanding Coronal Heating through Time-Series Analysis and - - PowerPoint PPT Presentation

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Understanding Coronal Heating through Time-Series Analysis and - - PowerPoint PPT Presentation

Nov 17, 2023 513 likes •670 views

Understanding Coronal Heating through Time-Series Analysis and Nanoflare Modeling Kristine M. Romich 1 and Nicholeen M. Viall 2 1 Harold Washington College (Chicago, IL) 2 NASA Goddard Space Flight Center (Greenbelt, MD) Background image courtesy

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SLIDE 1

Background image courtesy of NASA/SDO and the AIA, EVE, and HMI science teams.

Understanding Coronal Heating through Time-Series Analysis and Nanoflare Modeling

Kristine M. Romich1 and Nicholeen M. Viall2

1 Harold Washington College (Chicago, IL) 2 NASA Goddard Space Flight Center (Greenbelt, MD)

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Basic solar anatomy

Credit: NASA / Jenny Motar

  • Solar surface features

caused by the Sun’s magnetic field

  • Temperature of

photosphere: ~ 5800 K


  • Temperature of corona: 


1 - 3 MK

Source: https://www.nasa.gov/sites/default/files/images/462977main_sun_layers_full.jpg

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Why is the corona so hot?

(Answer: We don’t know!)

Image: https://apod.nasa.gov/apod/ap060407.html

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How do we study the corona?

All images courtesy of NASA/SDO and the AIA, EVE, and HMI science teams.

The Atmospheric Imaging Assembly (AIA) aboard NASA’s Solar Dynamics Observatory spacecraft continually monitors the corona across a variety

  • f wavelengths.

Each channel is sensitive to a different temperature.

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Intensity fluctuations:

a signature of temperature evolution

(June 5-8, 2012)

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Nanoflares

  • Impulsive bursts of energy release in the solar

atmosphere — too small (and too numerous) to resolve using current instruments

  • EBTEL (Enthalpy-Based Thermal Evolution of

Loops) simulates plasma response to energy input

  • My job: model nanoflares, run through EBTEL,

compare with real data

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Modeling nanoflares

  • Individual nanoflares

represented as triangular bursts (duration: <100 s); energy in each burst = area of triangle


  • Distribution follows a

power law
 


Hudson (1991), Cargill (2014), Bradshaw & Viall (2016)

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EBTEL: single nanoflare

Klimchuk et al. (2008), Cargill et al. (2012)

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EBTEL: sequence of nanoflares

Compare with real data: if nanoflares cause the intensity fluctuations, results should be similar.

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Fourier analysis: time → frequency

Significance

  • Basic idea: every time

series can be expressed as the sum of embedded sinusoids


  • Helps us identify patterns

in data

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Preliminary results

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Background image courtesy of NASA/SDO and the AIA, EVE, and HMI science teams.

We have developed a method of approximating the energy released by a sequence of nanoflares. Our simulations can help determine the characteristics of the nanoflares that are responsible for heating the corona.

Conclusion

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Acknowledgments

  • AIP/SPS
  • GSFC: Nicholeen Viall, Larry Kepko, Jim

Klimchuk, Emily Mason

  • The SDO/AIA science team

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Questions?

Image: https://apod.nasa.gov/apod/ap060407.html

kristine.romich@gmail.com https://www.spsnational.org/programs/internships/2017/kristine-romich

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References

  • Bradshaw, S. J., & Viall, N. M. 2016, The Astrophysical

Journal, 821:63.

  • Cargill, P. J., Bradshaw, S. J., & Klimchuk, J. A. 2012, The

Astrophysical Journal, 752:161.

  • Cargill, P. J. 2014, The Astrophysical Journal, 784:49.

  • Hudson, H. S. 1991, Solar Physics, 133:357.
  • Klimchuk, J. A., Patsourakos, S., & Cargill, P. J. 2008, The

Astrophysical Journal, 682:1351.

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