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CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters B.V. Jackson Center for Astrophysics and Space Sciences, University of California at San Diego,

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Presentation on theme: "CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters B.V. Jackson Center for Astrophysics and Space Sciences, University of California at San Diego,"— Presentation transcript:

1 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters B.V. Jackson Center for Astrophysics and Space Sciences, University of California at San Diego, LaJolla, CA, USA Masayoshi http://smei.ucsd.edu/ http://ips.ucsd.edu/ The Ability of Radio Heliospheric Remote Sensing Observations to Provide Global Solar Wind Parameters ftp://cass185.ucsd.edu/Presentations/2013_jeju

2 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters More Details IPS (three site- one site)

3 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters IPS Radio Systems The Ootacamund (Ooty), India off-axis parabolic cylinder 530 m long and 30 m wide (15,900 m 2 ) operating at a nominal frequency of 326.5 MHz. New STELab IPS array in Toyokawa (3,432 m 2 array now operates well – year-round operation began in 2011)

4 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters A model of the power spectra of density fluctuations To calculate solar wind velocities using a single IPS station, we use a theoretical power spectrum: an integration of scattering layers along the line of sight (z). The spectrum depends on: λ, ε, v, Θ, α (isotropic medium). Frequency of intensity fluctuations Diffractive function (Fresnel function) Visibility function of the source Heliocentric distance at the region of IPS (point P) Wave number of solar wind irregularities q x ² + q y ² =q² Turbulence spectrum follows a potential law α ≈ 3.5 ± 0.5 Solar wind velocity Example of the model (log-log): MEXART and STEL observing frequencies. Fresnel knee Mejia-Ambriz, J., et al., 2013, AGU 2013 Presentation, May, Cancoon, Mexico.

5 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters Comparison between Spectrum Fitting and Cross Correlation Methods Spectrum Fitting Method (Single-station meas.) Speed V 1st. =459km/s Axial Ratio=1.07 Spectral Index=3.8 3C273 2012/9/3 Cross Correlation Method (3-station meas.) Speed V 3st. = 457±13 km/s from IPS obs. for 3C273 in 2012 V3st. (km/s) V1st. (km/s) Correlation ~0.47 V 1st /V 3st =1.04±0.24 (Courtesy of M. Tokumaru) Tokumaru, M., et al., 2013, AOGS 2013 Presentation, June, Brisbane, Australia.

6 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters

7 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters

8 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters

9 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters The Marquardt Method 1) Inverse Hessian Method –A * x m = b –A * x i = -Grad(chiSq) + b –x m – x i = A -1 * (-Grad(chiSq) ) 2) Gradient Descent Method –dx = C * Grad(chiSq)

10 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters STEL: 298.000 Single Site: 303.437 Diff: -5.43671 3.1060 2.2460 24.6000 327.0000 0.0001 AlphaARElong.theta 3.10602.246024.60000.0001 STELSSDiff. 298.000303.437-5.43671

11 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters AlphaARElong.theta 3.61561.525527.50000.0028 STELSSDiff. 253.000249.5653.43510

12 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters AlphaARElong.theta 3.68880.664432.40000.0005 STELSSDiff. 307.000305.4061.59369

13 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters v0 = 600

14 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters V0=344.229

15 CASS/UCSD IPS 2013 Remote Sensing Solar Wind Parameters


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