Applications

UMASEP, a scheme for making real-time predictions of solar radiation storms (SEPs)

Main references about the UMASEP scheme:

• • Núñez M. (2022), Evaluation of the UMASEP-10 version 2 tool for predicting all >10 MeV SEP events of solar cycles 22, 23 and 24, Universe, 8(1), 35.

  • Núñez M. (2015), Real-time prediction of the occurrence and intensity of the first hours of > 100 MeV solar energetic proton events, Space Weather, 13, 11.

  • Núñez M. (2011), Predicting solar energetic proton events (E > 10 MeV), Space Weather, 9, S07003.

Real-time forecasts from the tools based on the UMASEP scheme are presented at the following websites:  

• • NASA's space weather system (iSWA) (UMASEP-10, UMASEP-30, UMASEP-50, UMASEP-100 and HESPERIA UMASEP-500 forecasts)

    • Some real forecasts of UMASEP-10 in iSWA:  April 2014,  June 2015 

  • National Observatory of Athens (HESPERIA Project site)  (HESPERIA UMASEP-500 forecasts)

  • ESA's Space Radiation Expert Service Centre (HESPERIA UMASEP-500 forecasts)

  • Universidad de Malaga Space Weather site (UMASEP-10 and UMASEP-100 forecasts)

Projects that have implemented new tools based on the UMASEP scheme:

• • NASA's project ISEP (UMASEP component)

  • European H2020 project HESPERIA 

  • ESA's project SEPsFLAREs 

SARM, a model for predicting interplanetary shock speeds and arrival times at locations from 0.72 to 8.7 AU

Reference about the SARM model:

• • Núñez M., T. Nieves-Chinchilla, and A. Pulkkinen (2016), Prediction of Shock Arrival Times from CME and Flare Data, Space Weather, 14, 2016, doi: http://dx.doi.org/10.1002/2016SW001361.

Applications of the SARM model:

• • Near real-time predictions of SARM v2.0 for the Earth for today are shown in http://spaceweather.uma.es/shock_predictions.html

  • Execution of SARM v2.0 with manually provided input CME/flare data in http://spaceweather.uma.es/sarm_v2/index.html

Real-time SARM forecasts are submitted to the NASA's CME scoreboard, where forecasts of other models may be viewed at once.

Projects that have used the SARM model:

• • ESA's project SEPsFLAREs:

  • ESA's project SAWS

SAIRT and OnlineTree2, machine learning algorithms for mining time-changing data streams:

• SAIRT (Tool for constructing Regression Trees from data streams), Fidalgo-Merino R., Núñez, M. (2011)

• OnlineTree2 (Tool for constructing Decision Trees from data streams), Nuñez M., R. Fidalgo-Merino, R.Morales (2007)