Creating an index for Solar Energetic Particle (SEP) events using multivariate analysis

A. Papaioannou1, A. Anastasiadis1, M. Paassilta2, R. Vainio2, E. Valtonen2, A. Kouloumvakos1, A. Belov3, E. Eroshenko3, V. Yanke3,

A. Abunin3, M. Abunina3 1IAASARS, National Observatory of Athens, Penteli, Greece

2Departement of Physics, University of Turku, Finland 3IZMIRAN, Troitsk, Russia

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European Space Weather Week 14 (ESWW14) Session 10: ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and Data-

Driven Modeling 2017

Outline

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

> Solar Energetic Particle Events • The origin of SEP events

• Lessons learned

> Multivariate analysis • Principal Components Analysis (PCA)

> Results I • Coronal Mass Ejections

• Solar flares

> Results II • A possible new index

Solar Energetic Particle (SEP) events

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

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9 > Since the 90s:

Distinction of 2 classes of events:

-Impulsive (small, frequent, presumably flare related)

- Gradual (large, rare, presumably fast CME related)

Impulsive Gradual

Impulsive Gradual

Credit: SOHO / NASA / ESA

The origin of SEP events

Lessons Learned

Solar Energetic Particle (SEP) events

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

Belov et al, 2005

> Solar flares @ W45-W70 are associated to SEP events Magnetic connection

> The higher the flare flux the higher the probability of SEP occurrence @ all energies

2D

Solar Energetic Particle (SEP) events

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

Lessons Learned

Papaioannou et al, 2016

> Peak particle intensities are correlated to the SXR peak flux

Cane et al, 2010

2D

Solar Energetic Particle (SEP) events

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

Lessons Learned

Kahler, 2001 Reames, 1999; 2000

> Peak particle intensities are correlated with CME speeds -- Note that only 1-2% of CMEs are fast enough to accelerate SEPs

2D

Solar Energetic Particle (SEP) events

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

Lessons Learned

Miteva et al, 2017

> SEPs are associated to type III radio bursts (~100%) and type II radio bursts (~70%)

+

2D

Solar Energetic Particle (SEP) events

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

Lessons Learned

+

Papaioannou et al, 2016

3D

Solar Energetic Particle (SEP) events

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

Motivation

? D

> We now have several inter-related quantities (solar) that describe (map) SEP events Can we make use of a higher-order combination of these quantities ?

Multivariate Analysis

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

1. Principal Component Analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter-correlated quantities.

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2. PCA is a non-parametric analysis and the answer is unique and independent of any hypothesis about data distribution.

> These two properties can be regarded as weaknesses as well as strengths

+ Since PCA is non-parametric, no prior knowledge can be incorporated.

- PCA data reduction incurs loss of information.

Multivariate Analysis

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

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> Principal Component Analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter-correlated quantities.

> PCA rotates the original data space such that the axes of the new coordinate system point into the directions of highest variance of the data

Multivariate Analysis

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

> Principal Component Analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter-correlated quantities.

Ad

by

& W

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ms,

Will

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terd

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Figure credit: https://learnche.org/pid/

> Example of PCA

> PCA extracts the important information from the table, to represent it as a set of new orthogonal variables called principal components, and to display the pattern of similarity of the observations and of the variables as points in maps [score plots, loadings plot].

Multivariate Analysis

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

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> Interpretation of the results

Multivariate Analysis

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

> 126 SEP events

> 6 quantities > several different mappings

Results l Coronal Mass Ejections (CMEs)

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

> Radiation storms [S1 – S4] are closely related to:

> Fast and Halo CMEs

Papaioannou et al, Solar Physics, in preparation, 2017

non-halo

halo

slow

fast

minor S1 S2 S3 S4

Results l Solar Flares (SFs)

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

> Radiation storms [S1 – S4] are closely related to SFs:

> of M and X magnitude

> mostly gradual

> central, east & west

C-class M-class X-class

gradual impulsive

central east west

minor S1 S2 S3 S4

Results

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

> Radiation storms [S1 – S4] are closely related to the variables that significantly load on PC2

> Fast, Halo CMEs & strong SFs

PC2

PC1

> The variables that significantly load on PC1 are the:

> Flare duration and Flare Rise Time

> The variables that significantly load on PC2 are the:

> CME speed, CME width and log[SXRs]

minor S1 S2 S3 S4

A possible new index

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

Winter and Ledbetter, Astrophys. J., 2016

> It appears that index I is related to the occurrence of SEP events. For a time span of ~19 years [1997-2016], it was possible to identify 126 SEP events and 1423 non-SEP events for which all 6 variables were complete.

> 97% of the SEP events in our sample had I > 0.40

> 24% of the non-SEP events in our sample had I > 0.40

I = (0.626 x SFD)+(0.612 x SFRT)+(0.522 x VCME)+ (0.57 WCME) + (0.381 x log[SXRs])

SFD = Solar Flare Duration l SFRT = Solar Flare Rise Time l VCME = Velocity of the CME l WCME = Width of the CME l log[SXRs] = log of the Soft X-rays // Solar Flare

Summary

> We applied PCA to a set of 126 SEP events with complete solar information.

> It was shown that SEP events are associated to:

- fast and halo CMEs

- M and X SFs

- Mostly gradual SFs

- Flares located in the center, east and western part of the visible solar disk

> A new index - using SF+CME parameters - that may be used for the forecasting of the occurrence of SEPs was identified from the application of the PCA.

European Space Weather Week (ESWW) Session 10 ICME and SEPs throughout the heliosphere: Multi-spacecraft Observations and

Data-Driven Modeling

30.11.2017 Oostende

> Applying PCA to SEPs

PC2

PC1

> This work was funded from the State Scholarships Foundation of Greece (I.K.Y.) under the contract No 2016-050-0503-7338, in the framework of: "Funding Post-doctoral Researchers" (MIS:5001552) of the b.p.: "Human Resources Development, Education and Lifelong Learning" from ESPA (2014-2020). AA would further like to acknowledge the "SPECS: Solar Particle Events and foreCasting Studies” research grant of the National Observatory of Athens.

Acknowledgement: