1. Marlon Núñez and David A. Núñez Universidad de Málaga
A model for predicting the onset and intensity of well-connected SEPs and its evaluation by using solar data of cycles 22 and 23.
Marlon Núñez and David A. Núñez
Universidad de Málaga

2. Contents Introduction
Method for predicting well-connected SEPs (wcSEPs).
Statistical performance
Comparisons with other forecaster of wcSEPs
Tools of U. Málaga.
Conclusions

3. Solar proton events: an introduction
A Solar proton event occurs when protons emitted by the Sun accelerates to very high energy levels:
in interplanetary space by the shocks associated with coronal mass ejections.
by a solar flare accompanied by a coronal mass ejection.
Accelerated particles are finally guided by the interplanetary magnetic field lines.-

4. SEP events . Well connected SEP events Poorly connected SEP events
Flare/CME
Well connected
SEP events
Poorly connected
SEP events

5. Well-connected SEP events
Flare/CME
After escaping, particles follow the IMF spiral paths

7. Well-connected SEP events
Flare/CME
Well connected
SEP events .
Well-connected SEPs are approximately 45-50% of all SEPs.

8. .

9. Contents Introduction
Method for predicting well-connected SEPs (wcSEPs).
Statistical performance
Comparisons with other forecaster of wcSEPs
Tools of U. Málaga.
Conclusions

10. Magnetic connection detection.
Magnetic connection detection
We estimate the magnetic connection by correlating X-ray and proton flux data at 1 AU, serching for cause-consequence relations.
Search for Cause-Consequence candidate pairs, by correlating X-ray to Proton data (several energy channels)
The highest correlation found will be the magnetic connection estimation.
If the correlation is high and the X-flare peak is high,
then a SEP is expected.

11. Magnetic connection detection
Analysis of the beginning of a flare and proton data at 1AU:
¿Cause-consequence candidate pair?
¿X-ray vs Proton (several energy channels) correlation?
Search for Cause-Consequence candidate pairs, by correlating X-ray to Proton data
The highest correlation found will be the magnetic connection estimation.
IF the correlation is high and the X-flare peak is high,
THEN a SEP is expected.

12. Magnetic connection detection
Analysis of the beginning of a flare and proton data at 1AU:
(Nov 8th, 1987)
Correlated!
(use of specific signal processing technique)
Search for Cause-Consequence candidate pairs, by correlating X-ray to Proton data
The highest correlation found will be the magnetic connection estimation.
IF the correlation is high and the X-flare peak is high,
THEN a SEP is expected.

13. Forecasting the onset of a Well-connected SEP
Analysis of the beginning of a flare and proton data at 1AU:
(Nov 8th, 1987) .

14. Forecasting the peak intensity of the prompt component of well-connected SEPs
The goal is to predict the wcSEP prompt component (approx. 8 hours after the onset).
Regression analysis for predicting that value. Result of the regression analysis:
The main dependency is non-linear
Best predictor variables: X-ray peak of the associated flare and the magnetic connectivity estimation (discovered in the previous analysis)
Then, interpolate between that value (the peak) and the onset (at 10 fpu) discovered in the previous analysis.
Result: RMSError = 0.58 in the logarithmic scale.

15. Contents Introduction
Method for predicting well-connected SEPs (wcSEPs).
Statistical performance
Comparisons with other forecaster of wcSEPs
Tools of U. Málaga.
Conclusions

16. Contingency Table (Cycles 22 and 23).
Contingency Table (Cycles 22 and 23)
wcSEP occurred
83 wcSEPs (*)
wcSEP did not occurr
Forecasts of wcSEP
129 forecasts
Forecasts of
“non wcSEP”
19,515 forecasts
Every operative event forecaster is evaluated according to the contingency table.
It measures the number of obserserved events that were succesfully predicted. In our case
This contingency table is the output of the Statistical Evaluation Tool that I will explain later. This contingecy table shows, during cycles 22 and 23, there was 83 wcSEP and we succesfully predicted 70, therefore…
(*) SEPs with WCT of 8 (time betwen the peak of the associated flare and the SEP onset).

17. Contingency Table (Cycles 22 and 23)
Summary: Probability of detection of wcSEPs: 84%
wcSEP occurred
83 wcSEPs (*)
wcSEP did not occurr
Forecasts of wcSEP
129 forecasts 70
Forecasts of
“non wcSEP”
19,515 forecasts
(*) SEPs with WCT of 8 (time betwen the peak of the associated flare and the SEP onset).

18. Examples of succesful forecasts.
Oct 26th, 2003 (Halloween I)
Anticipation: 0:45 hours
Prompt component: predicted
Sept. 24th. 2001
Anticipation: 0:50 mins
July 7th, 2002
Anticipation: 5:15 hours
Now lets see examples of succesful forecasts.
This is a simulation of how our forecaster would have performed with the wcSEP occurred during Oct 26th, 2003.
In this case, there is no apparent evidence that a SEP was going to occur, but our F would have detected a strong magnetic connection and it would have generated this forecast in red.
As you see, it shows the expected evolution, the onset and the expected intensity peak of a prompt component of a wcSEP. and
Let’s see other succesful forecast.

19. Examples of succesful forecasts
Oct 26th, 2003 (Halloween I)
Anticipation: 0:45 hours
Prompt component: predicted
Sept. 24th. 2001
Anticipation: 0:50 mins
July 7th, 2002
Anticipation: 5:15 hours .

20. Examples of succesful forecasts
Oct 26th, 2003 (Halloween I)
Anticipation: 0:45 hours
Prompt component: predicted
Sept. 24th. 2001
Anticipation: 0:50 mins
July 7th, 2002
Anticipation: 5:15 hours .

21. Examples of succesful forecasts
Oct 26th, 2003 (Halloween I)
Anticipation: 0:45 hours
Prompt component: predicted
Sept. 24th. 2001
Anticipation: 0:50 hours
July 7th, 2002
Anticipation: 5:15 hours .

22. Examples of succesful forecasts
Oct 26th, 2003 (Halloween I)
Anticipation: 0:45 hours
Prompt component: predicted
Sept. 24th. 2001
Anticipation: 0:50 hours
July 7th, 2002
Anticipation: 5:15 hours .

23. Examples of succesful forecasts
Oct 26th, 2003 (Halloween I)
Anticipation: 0:45 hours
Prompt component: predicted
Sept. 24th. 2001
Anticipation: 0:50 hours
July 7th, 2002
Anticipation: 5:15 hours

24. Contingency Table (Cycles 22 and 23)
Summary: Probability of detection of wcSEPs: 84%
wcSEP occurred
83 wcSEPs (*)
wcSEP did not occurr
Forecasts of wcSEP
129 forecasts 70
Forecasts of
“non wcSEP”
19,515 forecasts 13
(*) SEPs with WCT of 8 (time betwen the peak of the associated flare and the SEP onset).

25. Examples of missed wcSEPs.
June 30th, 1988
It detected a magnetic connection before onset.
Oct 19th, 1989

26. Contingency Table (Cycles 22 and 23)
Summary: Probability of detection of wcSEPs: 84%
Missed event rate: 16%.
False alarm rate: 45%
wcSEP occurred
83 wcSEPs (*)
wcSEP did not occurr
Forecasts of wcSEP
129 forecasts 70 58
Forecasts of
“non wcSEP”
19,515 forecasts 13
(*) SEPs with WCT of 8 (time betwen the peak of the associated flare and the SEP onset).

27. Examples of false alarms
June 2nd, 2003
Nov 29th, 1992
A proton enhacement occurred did not surpass the threshold.

28. Contingency Table (Cycles 22 and 23)
Summary: Probability of detection of wcSEPs: 84%
Missed event rate: 16%.
False alarm rate: 45%
True-negative rate: 99.93%.
wcSEP occurred
83 wcSEPs (*)
wcSEP did not occurr
Forecasts of wcSEP
129 forecasts 70 58
Forecasts of
“non wcSEP”
19,515 forecasts 13
19,502
(*) SEPs with WCT of 8 (time betwen the peak of the associated flare and the SEP onset).

29. Examples of forecasts: “No wcSEP is expected”.
Example: Dec 13th and 14th (4 M flares and 1 X flare)

30. Examples of forecasts: “No wcSEP is expected”
Example: Dec 13th and 14th (4 M flares and 1 X flare)
No forecast were issued and …
Success !
No wcSEP occurred .

31. Contingency Table (Cycles 22 and 23)
Summary: Probability of detection of wcSEPs: 84%
Missed event rate: 16%.
False alarm rate: 45%
True-negative rate: 99.93%.
wcSEP occurred
83 wcSEPs (*)
wcSEP did not occurr
Forecasts of wcSEP
129 forecasts 70 58
Forecasts of
“non wcSEP”
19,515 forecasts 13
19,502 .
(*) SEPs with WCT of 8 (time betwen the peak of the associated flare and the SEP onset).

32. Contents Introduction
Method for predicting well-connected SEPs (wcSEPs).
Statistical performance
Comparisons with other forecaster of wcSEPs
Tools of U. Málaga.
Conclusions

33. Posner’s approach
It is based on the fact that relativistic electrons arrive at 1 AU ahead of non-relativistic SEPs.
This approach is based on the instrument COSTEP (SOHO) which provides relativistic electrons and < 50 MeV proton (1 AU)
Specialized in forecasting wcSEPs in the range MeV
Data gaps due to limited DSN coverage, data link priority to the SOHO satellite and keyhole periods of SOHO at L1.

34. Comparison, predicting 30-50 MeV wcSEPs
Posner’s
(2003)
UMA SEP F.
Precision (wc-SEPs)
False/alarm rate
3/4 (*)
5/9
3/4 (*)
3/9
Max. anticipation
74 mins
78 mins

35. Comparison, forecasting SEPs (>10MeV) Halloween storm, 2003.
Posner’s
forecasts
SEP (>10 MeV)
Integral proton flux > 10 fpu
Threshold (10 fpu)
Oct. 26th
Anticipaction time
Posner’s approach UMA SEP Forecaster
SEP 26th Oct: mins mins
SEP 28th Oct: missed mins
SEP 2th Nov: missed missed

36. Comparison, forecasting SEPs (>10MeV) Halloween storm, 2003.
Posner’s
forecasts
SEP (>10 MeV)
Integral proton flux > 10 fpu
Threshold (10 fpu) .
Oct. 26th Oct. 28th
Anticipaction time
Posner’s approach UMA SEP Forecaster
SEP 26th Oct: mins mins
SEP 28th Oct: missed mins
SEP 2th Nov: missed missed

37. Comparison, forecasting SEPs (>10MeV) Halloween storm, 2003.
Posner’s
forecasts
SEP (>10 MeV)
Integral proton flux > 10 fpu
Threshold (10 fpu) .
Oct. 26th Oct. 28th
Anticipaction time
Posner’s approach UMA SEP Forecaster
SEP 26th Oct: mins mins
SEP 28th Oct: missed mins
SEP 2th Nov: missed missed

38. Comparison, forecasting SEPs (>10MeV)
Posner’s
(2003)
UMA SEP F.
Precision (wc-SEPs)
False/alarm rate
2/5 (*)
4/9
4/5 (*)
3/9
Max. anticipation
31 mins
95 mins
In order to compare both methods, we simply compare the Onset time forecasted by both methods with the NOAA SEP onset of the SEP event given by NOAA.
(*) This comparison is not conclusive (only one year of forecasts).
A more in-depth comparison should be made.

39. Comparison, forecasting SEPs (>10MeV)
Posner’s
(2003)
UMA SEP F.
Precision (wc-SEPs)
False/alarm rate
2/5 (*)
4/9
4/5 (*)
3/9
Max. anticipation
31 mins
95 mins
Availability
~53%
COSTEP (SOHO)
>99%
Goes satellites:
Primary, secondary .
(*) This comparison is not conclusive (only one year of forecasts).
A more in-depth comparison should be made.

40. Contents Introduction
Method for predicting well-connected SEPs (wcSEPs).
Statistical performance
Comparisons with other forecaster of wcSEPs
Tools of U. Málaga.
Conclusions

41. UMA SEP forecaster: network architecture
Goes 12
Goes 11
Goes 12
Universidad
de Málaga
Read every 5 minutes:
X-rays
Protons ( MeV)
UMA-SEP-Tool I N T E
UMA SEP
forecaster
NOAA
http requests

42. UMA SEP forecaster: network architecture
Goes 12
Goes 11
Goes 12
Universidad
de Málaga
Read every 5 minutes:
X-rays
Protons ( MeV)
UMA-SEP-Tool I N T E
UMA SEP
forecaster
NOAA
http requests
-Processing time:
Less than a minute
Users
ftp requests
SEIS (ESOC)
ESWP
Forecast
file and GUI
Forecasts are available every 5 minutes

43. .

44. Evaluation tools Operational evaluation tool
Users may go to a specific time and date to see how the UMA SEP Forecaster would have performed on that date.
Users may send files (X-ray and Proton data from other sources)

45. Evaluation tools Operational evaluation tool
Users may go to a specific time and date to see how the UMA SEP Forecaster would have performed on that date.
Users may send files (X-ray and Proton data from other sources)

46. Evaluation tools Operational evaluation tool
Users may go to a specific time and date to see how the UMA SEP Forecaster would have performed on that date.
Users may send files (X-ray and Proton data from other sources)
Statistical evaluation tool
Parallel processing for evaluating predictor performance (i.e. years, cycles)
It runs several UMA SEP forecasters in parallel, simulating 5 min. operations
Finally, the Statistical Evaluation Tool generates a performance summary based on the contingency table.

47. Contents Introduction
Method for predicting well-connected SEPs (wcSEPs).
Statistical performance
Comparisons with other forecaster of wcSEPs
Tools of U. Málaga.
Conclusions

48. Future of wcSEP forecasters (in general)
Become part of a Multi-model forecaster (wcSEP and pcSEPs):
No single numerical nor empirical model is able to predict all aspects of SEPs in real-time. Each forecasting model has its strengths / weaknesses.
A multi-model service should emphasize the aspect of the forecaster that proves to be the best according to its past performance.
Mid-term view: Onboard wcSEP forecasters (local warnings)
Sun-Earth magnetic connection might not be the same as interplanetary s/c magnetic connection.
Onboard wcSEP forecasters are possible. They are fast forecasters. They would allow s/c to take preparatory actions autonomously
We are very willling to participate in such projects (i.e. FPn-space calls).

49. UMA SEP forecaster output:
Conclusions
Characteristics of the UMA SEP forecaster:
Real-time prediction of the onset and intensity of the prompt component (first hours) of well-connected SEPs (wcSEPs).
Based on the estimation of the magnetic connectivity, which is deduced by correlating X-ray and Proton data at 1 AU.
Evaluation (solar cycles 22 and 23):
Probability of wcSEP prediction: 84%
Missed wcSEP rate: 16%
False alarm rate: 45%
Max. warning time: 6:10 hours
Intensity RMSError: (log. Scale) .
UMA SEP forecaster output:

50. Contact: mnunez@uma.es
Thank you!
Contact:

52. More wcSEP forecasts July 7th, 2002 Sept 13th. 1989
Forecast: 13:15 (UTC)
SEP onset: 18:30 (UTC)
Anticipation: 5 hrs.15
prompt component
pntensity peak: predicted
Sept 13th. 1989
Forecast: 13:25 (UTC)
SEP onset: 19:35 (UTC)
Anticipation: 6 hrs.10
intensity peak: Not predicted.

53. Fig. 3. This figure shows the predicted intensity of the first 8 hours compared with real SEP intensity values.

55. Fig. 5a. This chart shows that well-connected SEPs are approximately a half of all SEPs taking into account a Well Connection Time (WCT) ~ 8 hours. We think that if the WCT ≤ 9 hours and there is a high magnetic connectivity, the SEP is well connected.

56. Fig. 5b. This chart shows that the our system predict slightly better the relativistic SEPs with WCT ≤2 hours.