the need for physics-based inversions of sunspot structure and flows D. Braun, A. Birch, A. Crouch
Inversions from one of Konstantin’s Simulations Birch, Braun, & Crouch Data from Parchevsky &...
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Transcript of Inversions from one of Konstantin’s Simulations Birch, Braun, & Crouch Data from Parchevsky &...
Inversions from one of Konstantin’s Simulations
Birch, Braun, & Crouch
Data from Parchevsky & Kosovichev
Test of inversions for c2
• Start from simulated data “spot_model1” from Konstantin and Sasha
• Measure travel-time shifts using phase-speed filters and ridge filters
• Compute kernels in Born approx.
• Invert for change in c2
Measure travel-time shifts
• Surface focusing holography• Use phase-speed filters (first five from Couvidat et
al. 2006) or ridge filters (n=1,2,3,4)• Use one parameter fit (Gizon & Birch 2002) or
phase method (phase of covariance in Fourier domain). Difference between methods is very small compared to noise level.
2.5-3.0 mHz
3.0-3.5 mHz
3.5-4.0 mHz
4.0-4.5 mHz
4.5-5.0 mHz
5.0-5.5 mHz
Phase-speed filters+Frequency filters
12.8 km/s 14.9 km/s 17.5 km/s 24.8 km/s 35.5 km/s
Ridge filters + frequencyfilters
2.5-3.0 mHz
3.0-3.5 mHz
3.5-4.0 mHz
4.0-4.5 mHz
4.5-5.0 mHz
5.0-5.5 mHz
n=1 n=2 n=3 n=4
Born approx.
Horizontal integrals of sound-speed kernels for ridge-filtered measurements.
Kernels are all one sign (like global modes)
Kernels reflect mode structure.
Inversion method
• Look for fractional change in c2
• MCD
• 1D RLS at each k vector
• k-dependent regularization using norm of solution
• Use full noise covariance