1. 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore Forecasting X-class, M-class, CMEs, and SPEs from active region magnetograms using previous flare activity 2011 October MURI Meeting

2. 2 Relation between size and twist of an active region’s magnetic field with free energy: Free Magnetic Twist Size Energy + - + - More Less ~(Twist x Size)

3. 3 MSFC Vector Magnetogram of a very Nonpotential Active Region: 25,000 km Observed-field upward (downward) vert. comp. is shown by solid contours or light shading (dashed contours or dark shading); red arrows show observed hor. comp. ; green arrows show hor. comp. of pot. field computed from obs. vert. comp. ; strong-observed-field (>150G) intervals of neutral lines are blue. An active-region field’s horizontal shear is concentrated along neutral lines where the field’s horizontal component is strong and the vertical component’s horizontal gradient is steep Observed Horizontal Field Potential Horizontal Field

4. WL SG Magnetic Measures Φ

5. 5 Active-Region Magnetic Measures Vector measures (SDO/HMI) Magnetic Size Φ=∫|B z | da (|B z | >100G) Free Magnetic Energy Proxy WL SG = ∫(  B z ) dl (potential B h >150G) Where B z is the vertical field and B h is the horizontal field. In the line-of-sight approximation (SOHO/MDI) B z is replaced by the line-of-sight field and B h is replaced by the potential transverse field which is calculated from the line-of-sight field

6. Only Big Twisted Active Regions Produce CMEs Proxy of Active-Region Magnetic Free Energy * Produced CMEs in 24 hours * No CMEs in 24 hours A Productive Active Region has: Large amount of free energy Large magnetic size Large magnetic twist Similar tendencies for production of X and M flares. Database 40,000 Magnetograms From 1,300 active regions 1996-2004 Known flare/CME/SPE history

7. Correlation of AR Production of Major Solar Events with Free-Energy Proxy Free-energy proxy histogram of all active regions(black curve), and those that produce an X or M flare or CME in the next 24 hours. Gray scale plot shows free- energy/magnetic size distribution of 40,000 magnetograms of 1,300 active regions. Red contours are 0.001, 0.01, and 0.1, and 0.5 event/day levels.

8. Forecasting Events: Basic approach From a vector magnetogram, in theory the free-energy of an active region can be measured. Present vector magnetograms though are not capable of making these measurements. Proxies of free-magnetic energy though do exist, and can be measured from line-of-sight magnetograms. From a large database, we have determined empirical forecasting curves to convert an active region’s free- energy proxy to its expected next-day event rates.

9. Empirical Forecasting Curves For Forecasting an Active Region’s Next-Day Event Rates from Its Present Free-Energy Proxy R=A( L WL SG ) B P(t)=100%(1-e -Rt ) L WL SG (G) Proxy of Free Energy We have determined next-day event rates as a function of the active region’s free- energy proxy, for several types of events. The sample is divided into 40 equally populated bins using the magnitude of our free-energy proxy. For each bin, the average observed next- 24-hour event rate is determined, with uncertainties. The event rates for bins with event rates of >0.01 events/day are fitted with a power law. This fit is used for converting our free- energy proxy to expected event rate. Event rate can be converted to the probability of an event.

10. 2011 Advancements Transitioned from MDI line-of-sight magnetograms to HMI line-of-sight magnetograms. Will discuss how. With Near-Real-Time HMI magnetograms, we are now producing Near-Real-Time Forecasts. The system was installed at NASA/SRAG in March 2011. NASA/SRAG do the radiation forecasts for the astronauts. The six ground-based GONG sites serve as a backup. Have identified how to improve event-chance forecasts by including previous flare activity.

11. Transitioning to HMI Line-of-Sight 1. Advantages of HMI over MDI MDIHMI pixels2”0.5” Cadence96 minutes45 sec LOS, 90 sec Vector LatencyApproximately a daytens of minutes Magnetograph TypeLine-of-sightVector Operational1996-Jan 2011 Now Turned off May 2010 to present Now Operating Transition Problem The value of our free-energy proxy is resolution dependent. Increase resolution results in both longer neutral lines, and steeper gradients. The amount of increase varies from active region to active region. There might be something predictive in these different resolution dependent free-energy proxies, but until enough active regions are included in the sample, this will not be known. L WL SG = ∫(  B los ) dl

12. 12 Transitioning to HMI Line-of-Sight 2. Solution to Using HMI for Forecasting For MDI resolution L WL SG (MDI)=1.31* L WL SG (HMI) Multiplicative uncertainty is 1.22 HMI Smoothed to MDI ResolutionUnsmoothed HMI 1.Convert HMI to MDI magnetic field strength. 2.Then apply MDI point spread function. 3.Then cross-calibrate using overlap era.

13. 13 Transitioning to HMI Line-of-Sight 3. Display of Recent Forecast from HMI (October 25, 2011)

14. Forecast based on Free-Energy Proxy and Flare History 1. Importance of Flare History Major flares in Last 24 hours YesNo Actual Number of X&M Flares1092±1301387±144 Number of X&M Flares Predicted from Free-Energy Proxy Alone 750±1101780±163 Number of Active Region Magnetograms (% of sample) 1780(4%)38197(96%) Active regions that recently produced X&M class flares are ~50% more likely to produce X&M class flares in the near future, than free-energy proxy only would predict.

15. Forecast based on Free-Energy Proxy and Flare History 2. Recently Flaring and non-flaring forecast curves Result: Active regions that have recently flared, show a significantly greater flare rate in the future. Divide sample into flaring (have produced an X or M class flare in last 24 hours), and non-flaring (have not produced an X or M class flare in last 24 hours). Develop separate forecast curves for both sets, by binning in a similar manner, but requiring at least 50 active-region magnetograms of the set in the bin. Top Log-Log Bottom Log-Linear Dashed line Free-energy proxy forecast only.

16. Forecast based on Free-Energy Proxy and Flare History 3. Forecast Table Forecast an event if the event rate is above 0.5 events/day, and forecast no event if the rate is less than 0.5 events/day. Contingency Table Actual YesActual No Forecast Yes544540 Forecast No123137662 Contingency Table Actual YesActual No Forecast Yes689563 Forecast No108637639 Decision Matrix Actual YesActual No Forecast Yes Hit 50% False Alarm 1.4% Forecast NoMiss Rate 69% Correct Null 97% Decision Matrix Actual YesActual No Forecast Yes Hit 55% False Alarm 1.5% Forecast NoMiss Rate 61% Correct Null 97% Free-Energy Proxy Only Free-Energy Proxy and Last 24 hour Flare History

17. Forecast based on Free-Energy Proxy and Flare History 4. Improvement to Forecast The combination of flare history and free-energy proxy lead to improvements in probability of detection, Heidke skill score, and the false alarm rate, over free energy only. The Probability of Detection (The percent of Major flares, for which a yes forecast). The Heidke skill score ( skill score, 1 perfect forecast, 0 chance, -1 always wrong). The false alarm rate (the percentage of forecast events, that turn out to be false). Skill Scores Free-energy proxy onlyFree-energy proxy and last 24 hour flare history Best Probability of Detection31%39%100% False Alarm %50%45%0% Heidke Skill Score0.360.431 Percent Correct95.6%95.9%100%

18. Forecast based on Free-Energy Proxy and Flare History 5. To Do Need to determine dependence of forecast accuracy on width of forward time window. Determine if using last 24 hours flare history is optimal for forecast accuracy. Determine if more accurate forecast curves can be obtained for both sets by other curve-fitting methods. Perform these studies for the other event types (X&M flares were studied first for best statistics). Quantify how sample size affects results. Incorporate the combination in the forecast tool.

19. Future Work: Tool upgrades to be done using HMI Determine best way to implement combined flare and free- energy forecast Extend to CME, Fast CME, X-class Flare, and SPE. Use deprojected vector magnetograms to measure WL SG – Waiting for automated ambiguity resolution – Will incorporate de-projecting of ambiguity-resolved active- region tiles Does HMI’s higher resolution give WL SG values that are more strongly correlated with AR major-event production than does the lower resolution of MDI? – This will need a large HMI database to determine.

20. Statistic backup slide Skill Score Formula Best Probability of Detection A/(A+C)*100% 100% Heidke Skill Score 2(AD-BC)/[(A+C)*(C+D)+(A+B)*(B+D)] 1 False Alarm Rate B/(A+B)*100% 0% Percent Correct(A+D)/N 100% Actual YesActual NoMarginal Total Forecast YesABA+B Forecast NoCDC+D Marginal TotalA+CB+DA+B+C+D=N Decision Matrix Equations Actual YesActual No Forecast Yes Hit A/(A+B) False Alarm B/(B+D) Forecast NoMiss Rate C/(A+C) Correct Null D/(C+D)

21. Transitioning to HMI Line-of-Sight 2. Solution to Using HMI for Forecasting For MDI resolution L WL SG (MDI)=1.31* L WL SG (HMI) Multiplicative uncertainty is 1.22 Multiplicative uncertainty due to different instruments and their spatial resolutions Event TypeMDIHMI-lowresHMI-full res X and M Flares1.071.482.71 X Flares1.291.602.86 CMEs1.101.362.16 Fast CMEs1.171.412.24 SPEs1.321.512.33 HMI Smoothed to MDI ResolutionUnsmoothed HMI 1.Convert HMI to MDI magnetic field strength. 2.Then apply MDI point spread function. 3.Then cross-calibrate using overlap era.