The Forecasting Solar Particle Events and Flares (FORSPEF) Tool

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Meredith Wiggins
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Hilgers 3 1 IAASARS, National Observatory of Athens, Greece 2 Academy of Athens, Research Center for

1 .. The Forecasting Solar Particle Events and Flares (FORSPEF) Tool A. Anastasiadis 1, I. Sandberg 1, A. Papaioannou 1, M. K. Georgoulis 2, K. Tziotziou 1, G. Tsiropoula 1, D. Paronis 1, P. Jiggens 3, A. Hilgers 3 1 IAASARS, National Observatory of Athens, Greece 2 Academy of Athens, Research Center for Astronomy and Applied Mathematics, Greece 3 European Space Agency, European Research and Technology Center, The Netherlands

2 Background Solar Energetic Particle (SEP) events Desai and Burgess, 2008

methods (Georgoulis, 2013) PPS (Shea & Smart, 1989) PROTONS (Balch, 1999; 2008) RELeASE (Posner, 2007) Laurenza s method

3 Background How to forecast Solar flares and SEP events? Solar Particle Events Solar Flares Machine learning (Qahwaji & Colak 2007) Statistical methods (Wheatland, 2001) Morphological methods (Georgoulis, 2013) PPS (Shea & Smart, 1989) PROTONS (Balch, 1999; 2008) RELeASE (Posner, 2007) Laurenza s method (Laurenza, 2009) UMASEP (Nunez, 2011) COMESEP (comesep.eu, 2013) Probability of Occurrence Prediction of the max. flux Projected CME char. Probability of Occurrence Prediction of the max. flux SEP Flux profile

4 The FORSPEF system

the effective connected magnetic field strength (B eff ) prediction metric

5 The FORSPEF system Solar Flares (& Projected CME) Forecasting Magnetic connectivity matrix > The Solar Flare Prediction will rely primarily on the effective connected magnetic field strength (B eff ) prediction metric SDO/HMI Georgoulis & Rust, 2007; Gerogoulis, 2008; Tziotziou et al., 2012; 2013

6 > Flare & (Projected) CME prob. A pictorial output of the range of probabilities for different flare classes (red histogram). Also shown is the respective CME likelihood curve (blue histogram). The FORSPEF system Solar Flares (& Projected CME) Forecasting

The FORSPEF system SEP Forecasting & Nowcasting + >

velocity) identify the probability that an SEP event

flares and CMEs that do produce SEP events, how do the

7 The FORSPEF system SEP Forecasting & Nowcasting + > Given specific solar parameters (flare mag, CME width, velocity) identify the probability that an SEP event will occur Onset Peak Duration > Given a subset of flares and CMEs that do produce SEP events, how do the characteristics of the SEP event relate to those of the parent solar event?

8 The FORSPEF database SEP Forecasting & Nowcasting > The FORSPEF SEP database includes 314 SEP events, SFs ( C1.0) (from ) and 3680 CMEs (from 1997 to 2013). Flares CME Sandberg et al., 2014; Papaioannou et al., 2015a 6 Indicators: Flares: flux, longitude, rise time, duration / CMEs: velocity, width; 2 Physical quantities: peak flux, fluence 4 Energy ranges: > 10; > 30; > 60; > 100 MeV

9 Actual Work Scheme The FORSPEF system Forecasting mode AR12157 AR12157 AR12157 Probabilities for Solar Flare Occurrence

10 Actual Work Scheme The FORSPEF system Forecasting mode AR FORSPEF database The FORSPEF database Probabilities folded with the FORSPEF database

11 Actual Work Scheme The FORSPEF system Nowcasting mode > SEP Nowcasting, offers - Probability of SEP occurrence for a given SF - The expected SEP characteristics

12 Actual Work Scheme Flux The FORSPEF system Nowcasting mode N=30/314 SEP events Time > SEP Nowcasting, offers - For a given SF, 30 historical SEP events from the FORSPEF database, closest in terms of the flare longitude and within one order of magnitude in the flare flux are chosen. - All SEP characteristics are calculated on the basis of this SEP events sub sample. > SEP Nowcasting, offers - Probability of SEP occurrence for a given SF - The expected SEP characteristics

13 Results Outputs of the system > Solar flare forecasting Pictorial outputs of the flare-prediction process with a 24- hour forecast window on a recent full-disk SDO/HMI magnetogram.

14 Results Outputs of the system >SEP Nowcasting Illustrations of the derived SEP characteristics for a given flare.

15 Conclusions > The FORSPEF system > Incorporates a novel method for the solar flare prediction and a new database of SEP events, solar flares and CMEs. > Provides forecasting of SEPs based on solar flare & projected CME characteristics (e.g. speed) > Offers a 24-hour forecast of SEP events, up to 70 o EW covering practically the entire course of the AR toward the limb (up to ~85 o ), under the assumption that the AR does not change significantly over this course. > FORSPEF has been released in April 2015 /

16 Thank you [web] Acknowledgments: The research leading to these results has received funding from the European Space Agency, ESA Contract No /13/NL/AK

17 Back-up slides

18 The SOHO/MDI database Solar Flares (& Projected CME) Forecasting Magnetic connectivity matrix > The SOHO/MDI magnetogram sample used for the Solar Flare Prediction. > It covers Solar Cycle 23 and includes observations of 2736 days, 1416 ARs and individual magnetograms. Georgoulis, 2015

19 Actual Work Scheme The FORSPEF system l Using CMEs Nowcasting mode Without CME With CME

20 The FORSPEF database Statistical analysis l Solar Flares > X-ray flare flux versus flare longitude. The flares associated with SEP events are presented by the filled black circles and all other (non SEP flares) by the open red circles Belov et al., 2005 Papaioannou et al., 2015a

21 The FORSPEF database Statistical analysis l Solar Flares > Distribution of solar flare latitude (in degrees) as a function of the flare longitude (in degrees).the flares associated with SEP events are presented by the filled black circles and all other (non SEP flares) by the open red circles Papaioannou et al., 2015a

22 The FORSPEF database Statistical analysis l CMEs Med. < ~500 Km/s Med. > ~1000 Km/s > Distribution of the events as a function of the CME velocity [km/s] events 158 events Kahler & Vourlidas, 2004 Gopalswamy et al., 2002

23 The FORSPEF database Statistical analysis l CMEs > Distribution of the events as a function of the CME width [degrees]. > Halo CMEs are better correlated to SEP events 3522 events 158 events Kahler, 2001 Kahler & Vourlidas, 2013 Shea and Smart, 1989

Cross-calibration of solar proton detectors

Cross-calibration of solar proton detectors I. Sandberg, I.A. Daglis Institute of Accelerating Systems and Applications, Greece Department of Physics, University of Athens, Greece P. Jiggens, P. Nieminen,