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

Nov 17, 2023 •513 likes •668 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

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 of NASA/SDO and the AIA, EVE, and HMI science teams.
Basic solar anatomy • Solar surface features caused by the Sun’s magnetic field • Temperature of photosphere: ~ 5800 K   • Temperature of corona:   1 - 3 MK Credit: NASA / Jenny Motar Source: https://www.nasa.gov/sites/default/files/images/462977main_sun_layers_full.jpg 2
Why is the corona so hot? (Answer: We don’t know!) 3 Image: https://apod.nasa.gov/apod/ap060407.html
How do we study the corona? The Atmospheric Imaging Assembly (AIA) aboard NASA’s Solar Dynamics Observatory spacecraft continually monitors the corona across a variety of wavelengths. Each channel is sensitive to a different temperature. All images courtesy of NASA/SDO and the AIA, EVE, and HMI science teams. 4
Intensity fluctuations: a signature of temperature evolution (June 5-8, 2012) 5
Nanoflares • Impulsive bursts of energy release in the solar atmosphere — too small (and too numerous) to resolve using current instruments • EBTEL ( E nthalpy- B ased T hermal E volution of L oops) simulates plasma response to energy input • My job: model nanoflares, run through EBTEL, compare with real data 6
  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) 7
EBTEL: single nanoflare Klimchuk et al. (2008), Cargill et al. (2012) 8
EBTEL: sequence of nanoflares Compare with real data: if nanoflares cause the intensity fluctuations, results should be similar. 9
Fourier analysis: time → frequency • Basic idea: every time series can be expressed as the sum of embedded sinusoids   • Helps us identify patterns in data Significance 10
Preliminary results 11
Conclusion 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. Background image courtesy of NASA/SDO and the AIA, EVE, and HMI science teams. 12
Acknowledgments • AIP/SPS • GSFC: Nicholeen Viall, Larry Kepko, Jim Klimchuk, Emily Mason • The SDO/AIA science team 13
Questions? kristine.romich@gmail.com https://www.spsnational.org/programs/internships/2017/kristine-romich Image: https://apod.nasa.gov/apod/ap060407.html 14
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. 15

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