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SEP Scoreboard

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 multi-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

Beta SEP Scoreboard displays are now availble publicly: SEP Scoreboard forecast JSON file access:       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.

Submission File Format Information

SEP scoreboard JSON: A few tips on writting your data to to a JSON file.
Helper python script to create and validate JSON files: Further JSON file examples (.json): Contact CCMC software developer Joycelyn Jones with any JSON and script questions

View the SEP Scoreboard Change Log.

Current Models Implemented/Coming Soon

High Energy Solar Particle Events foRecastIng and Analysis

Relativistic Electron Alert System for Exploration
UMASEP-10 & 100
University of Malaga Solar energetic proton Event Predictor
SEP predictions inspired by STEReo
SPE Threat Assessment Tool

(available for historical events)
Magnetogram Forecast
SEPMOD (coming soon)  
ASPECS (coming soon)  

Advanced Solar Particle Events Casting System

Models who have registered their interest

COronal Mass Ejections and Solar Energetic Particles SEPForecast
Space Radiation Intelligence System

Reports & Presentations

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):

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*:

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)
National Aeronautics and Space Administration Air Force Materiel Command Air Force Office of Scientific Research Air Force Research Laboratory Air Force Weather Agency NOAA Space Environment Center National Science Foundation Office of Naval Research

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