Prediction and warning system of SEP events and solar flares for risk estimation in space launch operations

García-Rigo, Alberto; Núñez, Marlon; Qahwaji, Rami; Ashamari, Omar W; Jiggens, Piers; Pérez, Gustau; Hernández‐Pajares, Manuel; Hilgers, A.

doi:10.1051/swsc/2016021

Cited by 22 publications

(23 citation statements)

References 50 publications

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“…Since 2010, the NASA's integrated Space Weather Analysis (iSWA) system redistributes UMASEP-10's forecasts, which have obtained successful results on an operational level (Tsagouri et al 2013). The UMASEP-10 tool was also included as a real-time forecasting module in the European Space Agency's SEPsFLAREs system (García-Rigo et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Predicting well-connected SEP events from observations of solar soft X-rays and near-relativistic electrons

Núñez

2018

J. Space Weather Space Clim.

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-This paper studies the use of electron data from the Electron Proton Alpha Monitor (EPAM) on board the Advanced Composition Explorer (ACE) in the UMASEP (University of Málaga Solar particle Event Predictor) scheme [Núñez, Space Weather 9 (2011) S07003; Núñez, Space Weather 13 (2015)] for predicting well-connected >10 MeV Solar Energetic Proton (SEP) events. In this study, the identification of magnetic connection to a solar particle source is done by correlating Geostationary Operational Environmental Satellites (GOES) Soft X-Ray ( These results show that the use of ACE EPAM electron data in the UMASEP scheme obtained a better anticipation time (additional 41 min on average) but a lower performance in terms of POD and FAR. We also analyzed the use of a combined model, composed of WCP-electrons and WCP-protons, working in parallel (i.e. the combined model issues a forecast when any of the individual models emits a forecast). The combined model obtained the best POD (84%), and a FAR and AWT (34.4% and 1 h 34 min, respectively) which is in between those of the individual models.

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Section: Introductionmentioning

confidence: 99%

Predicting well-connected SEP events from observations of solar soft X-rays and near-relativistic electrons

Núñez

2018

J. Space Weather Space Clim.

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“…The European Space Agency (ESA) supported FORSPEF (Papaioannou et al, , ) and SEPsFLAREs (Garcia‐Rigo et al, ) systems have combined flare and SEP forecasting capabilities or preeruptive and posteruptive forecasting capabilities. Both systems leverage empirical models to establish flare and SEP predictions.…”

Section: Introductionmentioning

confidence: 99%

“…State‐of‐the‐art SEP forecasting models are empirical, physics based, or have a hybrid approach of combining empirical and physics‐based forecasting capabilities. See Garcia‐Rigo et al () and references therein for a SEP prediction summary.…”

Section: Introductionmentioning

confidence: 99%

SPRINTS: A Framework for Solar‐Driven Event Forecasting and Research

et al. 2017

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Capabilities to predict onset and time profiles of solar‐driven events, including solar X‐ray flares; solar energetic particles (SEP); coronal mass ejections; and high‐speed streams, are critical in mitigating their potential impacts. We introduce the Space Radiation Intelligence System (SPRINTS). This NASA‐invested technology integrates preeruptive metadata and forecasts from the MAG4 system with posteruptive metadata in order to produce high fidelity and preeruptive to posteruptive transitional forecasts for solar‐driven events. To catalog start and end times of the four solar‐driven events, SPRINTS is capable of generating posteruptive forecasts based on automatic detections employed on 30+ years of GOES X‐ray and particle data as well as 20+ years of ACE and DSCOVR solar wind data. The prediction results for 1986–2016 presented here are from the SPRINTS posteruptive capability for forecasting SEPs leveraging GOES X‐ray metadata. We present onset, peak flux, and time profile SEP forecast metrics and results based on expert‐guided, statistical, and machine‐learned decision tree models. Operating on data from a 20 year period, a machine‐learned decision tree model provided the best results for predicting an S1 event (on the NOAA Space Weather Prediction Center Solar Radiation Scale): 86% probability of detection and 37% false alarm rate. Five flare‐related metadata sets were leveraged in the decision tree modeling. Consistently, flare‐integrated flux, flare heliolongitude, and flare decay‐phase duration were found to be the top three forecasting parameters, while flare magnitude and flare latitude had little to no impact on the SEP forecast model. For the solar‐driven events of March 2012, we demonstrate SPRINTS abilities to forecast solar flares, SEP onset, and SEP evolution.

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“…4 UMASEP-10 was also included as a module in the European Space Agency's SEPsFLAREs system (García-Rigo et al 2016). Section 2.2 describes the UMASEP scheme, and Section 2.4 the adaptation of this scheme to build the tool UMASEP-10mw using microwave data.…”

Section: Introductionmentioning

confidence: 99%

Exploring the potential of microwave diagnostics in SEP forecasting: The occurrence of SEP events

Zucca

Núñez

Klein

2017

J. Space Weather Space Clim.

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Solar energetic particles (SEPs), especially protons and heavy ions, may be a space-weather hazard when they impact spacecraft and the terrestrial atmosphere. Forecasting schemes have been developed, which use earlier signatures of particle acceleration to predict the arrival of solar protons and ions in the space environment of the Earth. The UMASEP (University of MAlaga Solar particle Event Predictor) scheme forecasts the occurrence and the importance of an SEP event based on combined observations of soft X-rays, their time derivative and protons above 10 MeV at geosynchronous orbit. We explore the possibility to replace the derivative of the soft X-ray time history with the microwave time history in the UMASEP scheme. To this end we construct a continuous time series of observations for a 13-month period from December 2011 to December 2012 at two microwave frequencies, 4.995 and 8.8 GHz, using data from the four Radio Solar Telescope Network (RSTN) patrol stations of the US Air Force, and feed this time series to the UMASEP prediction scheme. During the selected period the Geostationary Operational Environmental Satellites (GOES) detected nine SEP events related to activity in the western solar hemisphere. We show that the SEP forecasting using microwaves has the same probability of detection as the method using soft X-rays, but no false alarm in the considered period, and a slightly increased warning time. A detailed analysis of the missed events is presented. We conclude that microwave patrol observations improve SEP forecasting schemes that employ soft X-rays. High-quality microwave data available in real time appear as a significant addition to our ability to predict SEP occurrence.

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Prediction and warning system of SEP events and solar flares for risk estimation in space launch operations

Cited by 22 publications

References 50 publications

Predicting well-connected SEP events from observations of solar soft X-rays and near-relativistic electrons

Predicting well-connected SEP events from observations of solar soft X-rays and near-relativistic electrons

SPRINTS: A Framework for Solar‐Driven Event Forecasting and Research

Exploring the potential of microwave diagnostics in SEP forecasting: The occurrence of SEP events

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