1 real-time cme forecasting using hmi active- region magnetograms and flare history david falconer,...

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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

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Page 1: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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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

Page 2: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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Relation between size and twist of an active region’s magnetic field with free energy:

Free Magnetic Twist Size Energy

+-

+-

Mor

e

L

ess

~(Twist x Size)

Page 3: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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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 (dashedcontours 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’shorizontal component is strong and the vertical component’s horizontal gradient is steep

Observed Horizontal Field Potential Horizontal Field

Page 4: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

WLSG

Magnetic Measures

Φ

Page 5: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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Active-Region Magnetic Measures

Vector measures (SDO/HMI)

Magnetic Size

Φ=∫|Bz| da (|Bz| >100G)

Free Magnetic Energy Proxy

WLSG= ∫(Bz) dl (potential Bh>150G)

Where Bz is the vertical field

and Bh is the horizontal field.In the line-of-sight approximation (SOHO/MDI)

Bz is replaced by the line-of-sight field and

Bh is replaced by the potential transverse field which is calculated from the line-of-sight field

Page 6: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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

Page 7: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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.

Page 8: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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.

Page 9: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

Empirical Forecasting CurvesFor Forecasting an Active Region’s Next-Day Event Rates from Its Present Free-

Energy Proxy

R=A(LWLSG)B

P(t)=100%(1-e-Rt)

LWLSG(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.

Page 10: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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.

Page 11: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

Transitioning to HMI Line-of-Sight

1. Advantages of HMI over MDIMDI HMI

pixels 2” 0.5”

Cadence 96 minutes 45 sec LOS, 90 sec Vector

Latency Approximately a day tens of minutes

Magnetograph Type Line-of-sight Vector

Operational 1996-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.

LWLSG= ∫(Blos) dl

Page 12: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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Transitioning to HMI Line-of-Sight 2. Solution to Using HMI for Forecasting

For MDI resolution• LWLSG(MDI)=1.31*LWLSG (HMI)

• Multiplicative uncertainty is 1.22

HMI Smoothed to MDI Resolution Unsmoothed

HMI HMI HMI

1. Convert HMI to MDI magnetic field strength.

2. Then apply MDI point spread function.

3. Then cross-calibrate using overlap era.

Page 13: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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

Page 14: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

Forecast based on Free-Energy Proxy and Flare History 1. Importance of Flare History

Major flares in Last 24 hours

Yes No

Actual Number of X&M Flares 1092±130 1387±144

Number of X&M Flares Predicted from Free-Energy Proxy Alone

750±110 1780±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.

Page 15: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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.

Page 16: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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 Yes Actual NoForecast Yes 544 540Forecast No 1231 37662

Contingency Table

Actual Yes Actual No

Forecast Yes 689 563Forecast No 1086 37639

Decision Matrix

Actual Yes Actual No

Forecast Yes Hit50%

False Alarm1.4%

Forecast No Miss Rate69%

Correct Null97%

Decision Matrix

Actual Yes Actual No

Forecast Yes Hit55%

False Alarm1.5%

Forecast No Miss Rate61%

Correct Null97%

Free-Energy Proxy Only Free-Energy Proxy and Last 24 hour Flare History

Page 17: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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 ScoresFree-energy proxy only Free-energy proxy and

last 24 hour flare historyBest

Probability of Detection 31% 39% 100%

False Alarm % 50% 45% 0%

Heidke Skill Score 0.36 0.43 1

Percent Correct 95.6% 95.9% 100%

Page 18: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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.

Page 19: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

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 WLSG

– Waiting for automated ambiguity resolution

– Will incorporate de-projecting of ambiguity-resolved active-region tiles

• Does HMI’s higher resolution give WLSG 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.

Page 20: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

Statistic backup slide

Skill Score Formula BestProbability 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 Yes Actual No Marginal Total

Forecast Yes A B A+B

Forecast No C D C+D

Marginal Total A+C B+D A+B+C+D=N

Decision Matrix Equations Actual Yes Actual No

Forecast Yes HitA/(A+B)

False AlarmB/(B+D)

Forecast No Miss RateC/(A+C)

Correct NullD/(C+D)

Page 21: 1 Real-Time CME Forecasting Using HMI Active- Region Magnetograms and Flare History David Falconer, Abdulnasser F. Barghouty, Igor Khazanov, and Ron Moore

Transitioning to HMI Line-of-Sight 2. Solution to Using HMI for Forecasting

For MDI resolution• LWLSG(MDI)=1.31*LWLSG (HMI)

• Multiplicative uncertainty is 1.22

Multiplicative uncertainty due to different instruments and their spatial resolutions

Event Type MDI HMI-lowres HMI-full resX and M Flares 1.07 1.48 2.71

X Flares 1.29 1.60 2.86CMEs 1.10 1.36 2.16

Fast CMEs 1.17 1.41 2.24SPEs 1.32 1.51 2.33

HMI Smoothed to MDI Resolution Unsmoothed

HMI HMI HMI

1. Convert HMI to MDI magnetic field strength.

2. Then apply MDI point spread function.3. Then cross-calibrate using overlap era.