1. NoRH Visit February, 2005Angelos Vourlidas, NRL On Deriving Mass & Energetics of Coronal Mass Ejections Angelos Vourlidas NRL A Tutorial

2. NoRH Visit February, 2005Angelos Vourlidas, NRL Overview The following questions will be addressed: –How can we derive information about CME mass/energetics? What assumptions enter in the calculations? What are the data analysis steps to extract quantitative CME information from white light images? –How good are the numbers? Can we estimate the errors? How? –What can we do with this information? What statistics tell us? What correlations can we find?

3. NoRH Visit February, 2005Angelos Vourlidas, NRL Preliminaries Height-time plots, online movies are constructed from UNCALIBRATED LASCO images. Calibrated images are rarely shown. All necessary calibration tools exist in the LASCO Solarsoft distribution. This talk is relevant to CME measurements ONLY. Coronal background densities, streamers and plumes must be treated differently. Remember, a white light CME is defined as an brightness increase relative to the background

4. NoRH Visit February, 2005Angelos Vourlidas, NRL Our Objective Raw C3 Image Calibrated C3 Image (Diff.) ?

5. NoRH Visit February, 2005Angelos Vourlidas, NRL CME Mass/Energy Derivation Flow C3_massimg.pro cme_massimg2total.pro

6. NoRH Visit February, 2005Angelos Vourlidas, NRL Mass Calculations Primer Assumptions: Emission is due to Thompson scattering of photospheric light from coronal electrons. All mass is on the sky plane. Plasma composition is 10% He, 90% H. Restrictions: The 3D distribution of the background and CME electrons, Ne, is unknown. The temperature of the ejected material is unknown (coronal should dominate). Emission is optically thin.

7. NoRH Visit February, 2005Angelos Vourlidas, NRL Method: A coronagraph measures the total brightness along the line of sight. We can only measure excess brightness (I CME - I PREEVENT ). Error Sources: exposure time (~0.15%) vignetting (~1%) photon noise (<1.4%) Phot. Calibration ( 0.73%) composition (6%)stars (cancel out) Cosmic rays (few pixels) solar rotation (not important for fast events ) Streamer deflections (difficult to estimate) 3D structure ( more on that later ) Mass Calculations Primer Excess DN calibration B total B e No. of e - composition Mass

8. NoRH Visit February, 2005Angelos Vourlidas, NRL Mass Calculation Methods Several ways to obtain a “mass” for an event. The choice depends on the objectives: –After the whole event? –After specific features (i.e., core)? –Flow measurements? “Typical” C3 Mass Image SECTOR Best for automated calculations: Extent & Upper boundary from CME lists/ht measurements TORUS Best for flow calculations: Position at fixed distance ROI Most common: Avoid streamers, planets, other CMEs

9. NoRH Visit February, 2005Angelos Vourlidas, NRL Example Results — Single Event EMEM EKEK EPEP E total Mass v esc v CM E mag E pot E kin E total v esc v CM or v front mass More examples in Vourlidas et al (2000), Subramanian & Vourlidas (2004)

10. NoRH Visit February, 2005Angelos Vourlidas, NRL How Good Are CME Mass Estimates? Real mass could be x2 larger

11. NoRH Visit February, 2005Angelos Vourlidas, NRL PA Corrected Sky-Plane Effect of CME-SkyPlane Distance on Mass Estimates? CME mass could be 5x larger CME mass could be 3x less Sky-Plane PA Corrected

12. NoRH Visit February, 2005Angelos Vourlidas, NRL CME Mass Database (Jan 1996 – Dec 2003) 1.Date/time 2.Width 3.Position Angle 4.Height of CME Front 5.Sector Area 6.Mass 7.Mass density 8.Kinetic Energy 9.Potential Energy 10.Velocity (H-t) 11.Acceleration 12.Escape Velocity. Thanks to the hard work of Ed Esfandiari an up-to-date CME database has been created: The CME information is taken from the CUA/NRL list. The database includes full-frame mass images for every h-t data point in the CUA list (6385 events so far). The mass is derived with the same method (sector) for all frames. Energy and other calculations are also provided. The following information is provided for every CME frame :

13. NoRH Visit February, 2005Angelos Vourlidas, NRL Results The analysis of the mass database is based on : Measurements at the point of maximum mass. ( Need for a single “representative” number for each event ). Does not include events with: < 5 h-t measurements (frames). Width > 120°. Negative mass. Zero pixels in sector.

14. NoRH Visit February, 2005Angelos Vourlidas, NRL Results – Distributions ParameterLASCOSolwind (ergs)4.3 10 30 3.5 10 30 (gr)1.7 10 15 4.1 10 15 Total Mass (gr)4.1 10 18 3.9 10 18 Mass Flux (gr/day)3.6 10 15 7.5 10 15 Duty cycle81.7%66.5%

15. NoRH Visit February, 2005Angelos Vourlidas, NRL Results – Average Mass The constant mass density suggests that: 1.Only the CME width is needed to derive the mass 2.The bulk of the CME material originates at high altitudes where the corona is more uniform. 3  10 10 gr/pix or 1.3  10 4 e/cm 3 /R s

16. NoRH Visit February, 2005Angelos Vourlidas, NRL Results – Bimodal Distribution? Do we have “failed” and “successful” CME populations?

17. NoRH Visit February, 2005Angelos Vourlidas, NRL Results – Yearly Variations

18. NoRH Visit February, 2005Angelos Vourlidas, NRL Review It is easy to calculate CME mass and energetics from the LASCO images (calibration/routines available since 1996). The accuracy of the mass values is difficult to estimate without 3D information. Simple simulations suggest that masses could be underestimated by x2 (on average, well-behaved (aka non-halo) events). Thousands of measurements of several dynamical parameters for almost all CMEs are now available. Mass images for almost all CMEs are also available (for DIYers). Preliminary analysis of the mass/energy data yielded a couple of very interesting results: CME mass density = constant! There may be 2 classes of CMEs; “failed” and “successful”. CME mass/energy distributions are power-laws (like flares!).

19. NoRH Visit February, 2005Angelos Vourlidas, NRL BACKUPS

20. NoRH Visit February, 2005Angelos Vourlidas, NRL Results – Mass Distribution Solwind Exponential Fit ( Jackson & Howard 1993 ) LASCO Power-law Fit,  =-1.8 ( Vourlidas & Patsourakos 2004 )

21. NoRH Visit February, 2005Angelos Vourlidas, NRL LASCO C3 Photometric Performance Courtesy of A. Thiernisien

22. NoRH Visit February, 2005Angelos Vourlidas, NRL Magnetic Energy Estimates Problem: Direct measurement is not (currently) possible except Radio gyrosynchrontron emission from energetic electrons within the CME (Bastian et al. 2001). Only a handful cases so far. Another Approach: 1. Select fluxrope-like CMEs. 2. Assume the fluxrope feature becomes the IP Magnetic Cloud. 3. Assume magnetic flux, Φ is conserved (in the fluxrope). 4. Use in-situ measurements of Φ to normalize the magnetic energy, E M. 5. Use the coronagraph measurements of the fluxrope area, A and “length”, l to derive the evolution of E M.

23. NoRH Visit February, 2005Angelos Vourlidas, NRL Magnetic Energy Estimates Relevant Equations: Assume fluxrope is cylindrical, B & A are measured/derived from in-situ observations  Φ. A is given by the no. of pixels in the LASCO images l is assumed equal to the height of the CM, l  r CM.