CCMC has implemented a beta version of the "SEP scoreboard". Scoreboard planning was initiated together with Mark Dierckxsens (BIRA-IASB), Mike Marsh (UK Met Office) and the international research community. Recently in 2018, Johnson Space Center's Space Radiation Analysis Group has become involved in the SEP scoreboard as part of a 3-year project called ISEP.
The SEP Scoreboard builds upon the flare scoreboard and CME arrival time scoreboard. It will be an automated system such that model/method developers can have their predictions automatically uploaded to an anonymous ftp in a pre-defined JSON format, which will be parsed and databased by the system.
SEP forecasts can be roughly divided into three categories: (1) Continuous/Probabilistic (2) Solar event triggered (3) Physics-based/complex. The SEP scoreboard will focus on real-time forecasts but will also coordinate with the SEP working team to evaluate different models for a set of historical events. This is particularly useful for some physics-based models in the third category that are not yet relevant for real-time modeling.
Click here to go to the SEP Working Team page.
Please email Mark Dierckxsens, Mike Marsh, Masha Kuznetsova, and Leila Mays with your feedback which will be shared with the SEP scoreboard planning group.
Latest News:
➡ 2020-12: The beta SEP Scoreboard websites are now live!
➡ 2020-12: ESWS 2020 presentation and screenshots
➡ 2019-02: Final SEP Scoreboard JSON schema and helper script released
➡ 2020-10: Latest prototypes developed
➡ See the agenda/materials of the SHINE and ESWW15 2018 community campaign.
➡ The SEP scoreboard is part of the the SEP Working Team
in the Community-wide International Forum for Space Weather Modeling Capabilities Assessment.
➡ See the agenda of ESWW13 working meeting: Community-wide space weather Scoreboards: Research assessment of real-time forecasting models and techniques.
SEP scoreboard planning group:
Please contact us to join
Leads: Mark Dierckxsens (BIRA-IASB), Mike Marsh (UK Met Office)
JSC SRAG, Ian Richardson (UMD/GSFC), Jesse Adries, Veronique Delouille (SIDC), Nathan Schwadron (UNH), Marlon Nunez (U Malaga), Anastasios Anastasiadis, Olga Malandraki (National Observatory of Athens), A. Posner (NASA HQ), B. Heber (Univ. of Kiel), J. Labrenz (Univ. of Kiel), Masha Kuznetsova (CCMC), M. Leila Mays (CCMC)
Participating partners:
SEP Scoreboard and Data Access
- iSWA Webservice API, examples:
- MAG4: MAG4_LOS_FEr [HMI-NRT] | MAG4_LOS_r [WF-HMI-NRT] | MAG4_SHARP_FE [V-HMI-NRT] | MAG4_SHARP [VWF-HMI-NRT] | MAG4_SHARP_HMI [VPLUS-HMI-NRT]
- HESPERIA RELeASE: SOHO EPHIN 30 min | SOHO EPHIN 60 min | SOHO EPHIN 90 min | ACE EPAM 30 min | ACE EPAM 60 min | ACE EPAM 90 min
- SEPSTER: SEPSTER (Parker Spiral) | SEPSTER (WSA-ENLIL)
- UMASEP: UMASEP-10 | UMASEP-100 | UMASEP-500
- iSWA data tree
Submission File Format Information
SEP scoreboard JSON:- visual schema (PDF)
- comprehensive JSON example file (.json)
- example intensity profile text file (note format and units string in header)
- sep_json_writer.py (last updated on 2020.11.13)
- script documentation
- mapping of visual schema keys to helper script command line arguments (PDF)
- Sample python dictionary format (can be used with sep_json_writer.py, although this is the least recommended method for using the helper script)
SEP Scoreboard Probability Display Prototype
SEP Scoreboard Intensity Display Prototype
Feedback welcome!
Currently Registered Models
|
COMESEP SEPForecast COronal Mass Ejections and Solar Energetic Particles SEPForecast |
HESPERIA REleASE High Energy Solar Particle Events foRecastIng and Analysis Relativistic Electron Alert System for Exploration  
|
UMASEP-10 & 100 HESPERIA UMASEP-500 University of Malaga Solar energetic proton Event Predictor |
FORSPEF  Forecasting Solar Particle Events and Flares |
PREDICCS  Predictions of radiation from REleASE, EMMREM, and Data Incorporating CRaTER, COSTEP, and other SEP measurements |
MAG4  Magnetogram Forecast |
SPRINTS  Space Radiation Intelligence System |
Reports & Presentations
- Presentations from the ESWW13 working meeting: Community-wide space weather Scoreboards: Research assessment of real-time forecasting models and techniques.
- Agenda/materials of the SHINE and ESWW15 2018 community campaign.
How to get started with the SEP Scoreboard:
◦ Participating modelers will respond fill in the registration questionnaire below and CCMC model on-boarding questionnaire and email both to Leila Mays. We will then create a folder for the model on our anonymous ftp site and register your model metadata on the CCMC model registry.◦ Participants will produce SEP forecasts conforming to the file format (JSON; see above).
◦ SEP forecast .json files will be accepted by anonymous ftp, each model has an assigned folder.
◦ All information will be stored in a database and the JSONs are made accessible to users via an API
CCMC Rules of the Road apply: CCMC requests that users notify the CCMC, SEP model/technique developers and submitting forecasters before performing validation studies with the SEP Scoreboard database. It is recommended that such validation studies be performed with the knowledge and collaboration of developers and submitting forecasters/researchers.
◦ SEP forecasts will be displayed side by side on the "SEP Scoreboard" website - currently in development (beta version coming in 2019).
Model/Technique Registration (*=required):
Information about your group/project:Name(s) and e-mail (s) (please list primary contact first)*:
Associated Institution/Project name/Group name*:
Website url(s):
Logo(s):
Information about your method:
Forecasting method name*:
Shorthand unique identifier for your method (methodname_version, e.g. ModelName_1 or ModelName_201201):
Short description*:
Model Inputs*:
Model Outputs*:
References:
Further Model Details:
(1)* Is the forecast made continuously (e.g. probability for the next 24 hours, or a time series), or event-triggered (e.g. by a flare or CME).
(2)* Is the forecast human generated, human generated but model-based, model-based, or other.
(3)* If model-based: is the model empirical, physics-based or both.
SEP Models in the Community and Literature (compiled by Mike Marsh)
| Model Type | Model Name | Principal Developer(s) | Observational Inputs | Outputs | |
| Empirial | AER SEP model | Lisa Winter (LANL) | Type II, Type III, and Langmuir wave properties measured from Wind/WAVES | probability of a > 10 MeV proton event (> 10 pfu) | |
| Empirial | AFRL PPS | Stephen Kahler (AFRL) | GOES x-ray peak flux & location | E>5 MeV intensities | |
| Empirial/Machine learning | Boubrahimi model | Soukaina Boubrahimi (GSU) | GOES x-ray and proton flux | E>100 MeV intensities | |
| Physics | SEP modeling with EUHFORIA | Nicolas Wijsen, Angels Aran | Coupled with the EUHFORIA MHD model | ||
| Physics | EPREM | Nathan Schwadron (UNH) | Can be driven by in-situ proton observations, can be coupled with MHD | User defined flux range, also dose calculations within EMMREM framework | |
| Physics | FLAMPA (SWMF) | University of Michigan | SWMF module coupled with MHD | ||
| Empirical | FORSPEF | Anastasios Anastasiadis (NOA) | Magnetograms, x-ray flares, or CMEs | E > 30,60,100 MeV integral proton energy flux and fluence | |
| Physics | Kota SEP (SWMF) | University of Michigan | SWMF module coupled with MHD | ||
| Empirical | ESPERTA | Monica Laurenza (INAF) | |||
| Physics | Luhmann Model | Janet Luhmann (UCB SSL) | Coupled with WSA-ENLIL+Cone (magnetograms, coronagraphs) | User defined flux range | |
| Empirical | MAG4 | David Falconer (NASA/MSFC, UAH) | Magnetograms, x-ray flares | 24 hour event probabilistic forecast | |
| Physics | iPATH | Gang Li, Gary Zank (UAH) | |||
| Physics & Empirical | PREDICCS | Nathan Schwadron (UNH) | (coupled version of EMMREM and REleASE) | ||
| Empirical | REleASE | Arik Posner | SOHO/COSTEP-EPHIN high energy electron flux. ACE/EPAM in new version | E=4-9, 9-16, 16-40, 28-50 MeV proton flux | |
| Empirical | SEPForecast (COMESEP) | Mark Dierckxsens (BIRA IASB) | GOES x-ray peak flux & location, CME width & velocity, GLE observations | E>10 MeV and >60 MeV integral proton energy peak flux and probability | |
| Physics | SOLPENCO | Angels Aran (Univ. Barcelona) | CME/Flare location & shock velocity estimate | User defined flux range | |
| Physics | SPARX | Silvia Dalla (UCLan) Mike Marsh (UK Met Office) |
Flare location, peak x-ray flux | User defined flux range | |
| Empirical/Machine learning | SPRINTS | Alec Engel (NextGen Federal Systems) | x-ray flares | 10 MeV onset and peak flux (10, 30, 50 and 100 MeV possible) |
|
| Empirical | SWPC PPM | Christopher Balch (NOAA/SWPC) | GOES x-ray, SEON radio burst, H-alpha/EUV imaging | E>10 MeV integral peak proton flux, peak time, and probability | |
| Empirical | SWPC | NOAA/SWPC | Day 1-3 event probabilistic forecast | ||
| Empirical | UMASEP | Marlon Nuñez (Univ. Malaga) | Goes x-ray & proton fluxes | E>10 MeV integral proton flux. E>100 MeV proton flux in new version. | |
| Empirical | UK Met Office | UK Met Office | Day 1-4 event probabilistic forecast | ||
| Physics | Zhang model | Ming Zhang (FIT) |
