SEISOP: Space Environment Information System to Support Satellites Operations

Marco, Federico Di; Donati, Alessandro; Pantoquilho, Marta; Baumgärtner, Alexander; Ponz, D.

doi:10.2514/6.2008-3492

Cited by 1 publication

(1 citation statement)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…UMASEP is compared with other well‐known and operative forecasters [ Balch , 2008; Kahler et al , 2007; Laurenza et al , 2009; Posner , 2007], including a preliminary version of the presented system [ Núñez , 2009; Núñez and Núñez , 2009]. UMASEP's forecasts are currently downloaded every 5 min from users' space weather systems, such as the iSWA system [ Maddox et al , 2008] of NASA (http://iswa.gsfc.nasa.gov), the SEISOP system [ Di Marco et al , 2008] of the European Space Agency (ESA), and the European Space Weather Portal (http://www.spaceweather.eu/en/forecast/uma_sep).…”

Section: Introductionmentioning

confidence: 99%

Predicting solar energetic proton events (E > 10 MeV)

Núñez

2011

Space Weather

View full text Add to dashboard Cite

[1] A high level of proton radiation exposure can be dangerous to astronauts, satellite equipment, and air passengers/crew flying along polar routes. The presented solar energetic proton (SEP) event forecaster is based on a dual-model approach for predicting the time interval within which the integral proton flux is expected to meet or surpass the Space Weather Prediction Center threshold of J (E > 10 MeV) = 10 pr cm −2 sr −1 s −1 and the intensity of the first hours of well-and poorly connected SEP events. This forecaster analyzes flare and near-Earth space environment data (soft X-ray, differential and integral proton fluxes). The purpose of the first model is to identify precursors of well-connected events by empirically estimating the magnetic connectivity from the associated CME/flare process zone to the near-Earth environment and identifying the flare temporally associated with the phenomenon. The goal of the second model is to identify precursors of poorly connected events by using a regression model that checks whether the differential proton flux behavior is similar to that in the beginning phases of previous historically poorly connected SEP events and thus deduce similar consequences. An additional module applies a higherlevel analysis for inferring additional information about the situation by filtering out inconsistent preliminary forecasts and estimating the intensity of the first hours of the predicted SEP events. The highlevel module periodically retrieves solar data and, in the case of well-connected events, automatically identifies the associated flare and active region. For the events of solar cycles 22 and 23 of the NOAA/ SWPC SEP list, the presented dual-model system, called UMASEP, has a probability of detection of all well-and poorly connected events of 80.72% (134/166) and a false alarm rate of 33.99% (69/203), which outperforms current automatic forecasters in predicting >10 MeV SEP events. The presented forecaster has an average warning time of 5 h 10 min for the successfully predicted events, 1 h 5 min for wellconnected events and 8 h 28 min for poorly connected events, with a maximum warning time of 24 h for very gradual SEP events.

show abstract

Section: Introductionmentioning

confidence: 99%

Predicting solar energetic proton events (E > 10 MeV)

Núñez

2011

Space Weather

View full text Add to dashboard Cite

show abstract

SEISOP: Space Environment Information System to Support Satellites Operations

Cited by 1 publication

References 2 publications

Predicting solar energetic proton events (E > 10 MeV)

Predicting solar energetic proton events (E > 10 MeV)

Contact Info

Product

Resources

About