1. Empirical Forecasting of CMEs from a Free-Energy Proxy: Performance and Extension to HMI David Falconer, Ron Moore, Abdulnasser F. Barghouty, & Igor Khazanov 2010 October MURI Meeting ExtractMeasure Forecast CME Active Region Active Region Rates R=f(x) Our method forecasts threat level (high or low/All-Clear). Verifying forecast performance is being done. Transitioning to SDO/HMI has started.

2. Relation between Size, Twist, and Free Energy of an Active Region’s Magnetic Field Free Magnetic Twist Size Energy + - + - More Less ~(Twist x Size)

3. WL SG WL SS Magnetic Measures

4. 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

5. 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

6. Empirical Conversion Functions R=A( L WL SG ) B P(t)=100%(1-e -Rt ) L WL SG (G) Proxy of Free Energy We have determined event rates as a function of our 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 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 rates can be converted into a event probability.

7. Forecasting Tool A beta tool has been delivered to NASA SRAG, for MDI data. AFRL is looking at the tool. Paper submitted to Space Weather When there are no active regions on the disk that is threatening to produce a powerful, earthward directed CME, then solar wind modeling at L1 is easiest. L WL SG (G) Proxy of Free Energy

8. Verification of Forecasting Curve using our Database We obtain forecast curves from the first three fourths of the active regions to forecast the performance of the remaining fourth of the active regions, and compare the forecast to actual performance. We have binned our test sample into 10 bins of expected event rates. For each bin, we plotted the average forecasted and actual event rates. The plot shows the actual rates in the five bins having event rates above 0.01 events/day along with the statistical uncertainties. The five data-points fall along the unity line, verifying the forecast technique. Test 1: X&M flare forecast rates versus actual rate Expected Rate Actual Rate

9. Truth Tables Test 2: Predictive Skill Scores and comparison to present McIntosh method “ Free Energy” EventNo Event Predict Yes319302 Predict No38511578 “McIntosh”EventNo Event Predict Yes180412 Predict No52411468 Same division as previous EventNo Event Predict YesAB Predict NoCD X and M flares are used since they are the most frequent kind of event, and best identified with individual active regions.

10. Skill Scores from Truth Table Expression“Free Energy”“McIntosh”Best Possible Score Probability of Detection A/(A+C)0.450.261 False Alarm RateB/(A+B)0.490.700 Percent correct(A+D)/N0.950.931 Heidke Skill(A+D-E)/(N-E)0.450.241 Quadratic Score1/N)∑(f i -σ i ) 2 0.140.160 SS(QR*-QR)/QR*0.200.061 E=((A+B)(A+C)+(B+D)*(C+D))/N Skill scores are various measures of how reliable a forecast is. The first four scores are based on yes/no forecast, with a forecasted event rate of 0.5/day or greater being counted as a yes forecast, while an event rate of less than 0.5 events/day is counted as a no forecast. The quadratic (Brier) score and SS are a comparison between the forecasted rates (f i ) and the observed flare rate (σ i ), while QR* is the quadratic score if the average flare rate is used (Balch, 2008, Spaced Weather Vol 6). QR*=(1/N)∑(σ-σ i ) 2 =0.17 Our skill scores are always significantly better than McIntosh skill scores.

11. Steps in Transitioning from MDI to HMI 1.HMI to “MDI” conversion of free-energy proxy. 2.Deproject active region to accurately measure further from disk center, than is possible with MDI. 3.Use HMI’s higher resolution, higher cadence and full- vector measurements to improve forecast. MDIHMI Magnetograph TypeLine-of-sightVector Cadence96 minutes45/90 second LatencyDayMinutes Pixel size2”0.5”

12. Using HMI to Forecast CME Rate from MDI Forecast Curve Knowing that R CME =F(WL SG-MDI ) and WL SG-MDI =G(WL SG -HMI ) we can use HMI to predict CME rate. To determine G, we first calibrate HMI to MDI Gauss units. Then determine G. Preliminary result is that we can estimate WL SG MDI to within 10% using HMI.

13. Summary Free-energy proxies are strong predictors of future flare and CME activity. Initial verification has been done. Misty Crown at AFRL is conducting an independent verification. Transitioning to HMI from MDI has begun, the preliminary results indicate negligible increase in uncertainty in forecast event rates. Not shown, adding GONG as a backup instrument has begun, forecast uncertainties will be larger, but GONG’s global-network of 6 ground based sites will guarantee backup capability to forecasters.

14. Forecasting Tool Work to do