flarecast: a project overviewflarecast.eu/wp-content/uploads/2017/01/flarecast_overview... · –...
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• FirstH2020fundingcall(PROTEC-1-2014– SpaceWeather)
– Scope:“Exploratoryworkstudyingnewideasfordataanalysis andmodellingofspaceweatherwithaviewtoenhancingtheperformanceofspaceweatherprediction”
– Expectedimpact:“…todelivernewinsightsintothedetailedprocessesthatgeneratespaceweather.Thisshouldcontributetonewservicesabletopredict,withasignificantlyhigherprecisionthantoday,spaceweathereventsaffectingtheEarth”
FLARECAST’sOrigins
• TheFlareLikelihoodAndRegionEruptionforeCASTing (FLARECAST)projectaimsto:
1. understandthedriversofflareactivityandimproveflareprediction
2. provideagloballyaccessibleflarepredictionservicethatfacilitatesexpansion
3. engagewithspace-weatherendusersandinformpolicymakersandthepublic
Aims and Objectives
Consortium Partners
Institution Country ExpertiseAcademy ofAthens(AA)ProjectCoordinator GR Solarphysics,flareforecasting
TrinityCollegeDublin(TCD) IE Solarphysics,flareforecasting
Università degli Studi diGenova (UNIGE) IT Mathematicaltechniques
Consiglio Nazionale delle Ricerche (CNR) IT Mathematicaltechniques
CentreNationaldelaRecherche Scientifique(CNRS)
FR Solarphysics,magnetic fieldsimulations
Université Paris-Sud (PSUD) FR Infrastructure(MEDOC)
Fachhochschule Nordwestschweiz (FHNW) CH Computerscience
MetOffice (MO) UK Operational SpWx,verification
NorthumbriaUniversity(UNN)Project Scientist UK Solarphysics,flareforecasting,verification
• ProjectManagementBoard
– PC,PS,WPleaders(min.1partnerrepresentative)• monthlytelecons;6monthlyphysicalmeetings
• SteeringCommittee
– NealHurlbert (USA– featureextraction/infrastructure)CHAIR– GrahamBarnes(USA– flareforecasting)– DougBiesecker (USA– operationalSpWx)– PedroRusso(NL– EPO)– SilviaVilla (IT– machinelearning)*beingapproached
• quarterlytelecons;2attendingtoday(Neal&Graham)
WP1:ProjectManagement
• CataloguedProperties• McIntoshandMt.Wilsonclasses
• Line-of-sight(LOS)MagneticProperties• spatialdistribution:Fourierpowerindex,(multi)fractaldimension• connectivity:B-effective• polarityinversionlines(PILs):Schrijver’s R value,Falconer’sLWLSG
• Vector-magneticProperties• localizedversionofSHARPheaderquantities(beyondjusttotalsandaverages)• helicity measures• refinedflowfieldmeasures(DAVE4VM)
• Propertyassociationwithflares• fullGOESsoftX-rayflarehistoryincludedinpropertydatabase
WP2:Active RegionProperties
• CataloguedProperties
– McIntoshandMt.Wilsonclasses
• Line-of-sightMagneticProperties
– spatialdistribution:Fourierpowerindex,(multi)fractaldimension
– connectivity:Beff
– polarityinversionlines (PILs):Schrijver’s R,Falconer’sLWLSG
WP2:Active RegionProperties
• Propertyassociationwithflares
– fullGOESflarehistoryincludedinpropertyDB
• Vector-magneticProperties
– localizedversionofSHARPheaderquantities(beyondtotals/averages)
– helicity measures
– betterflowfields(DAVE4VM)
WP2:Active RegionProperties
• PrimaryDataSources
– SDO/HMInearreal-timeSHARPvector-magnetograms
– NOAA/SWPC
• solarregionsummaries• GOESsoftX-rayevents
• SecondaryDataSources
– exploringground-basedline-of-sightandvectordata
WP2:Active RegionProperties
• ExistingAlgorithms
– Poissonaverageflarerate
• UnsupervisedClusteringMethods
– k-means– possibilistic C-means
• SupervisedLearningMethods
– multi-layerperceptron(MLP)– recurrentneuralnetwork(NN)
WP3:Flare Prediction Algorithms
– discriminantanalysis
– clusteringwithsimulatedannealing
– supportvectormachine(SVM)
WP4:DataStorageand Processing
• RESTful APIforDataTransfer
– allDBreading/writingviahttp
• Semi-structuredDataModel
– JSONdatatypes,extendable
WP4:DataStorageand Processing
• Docker Containers
– compatiblewithallmajorOS – pickandmixinstallation
• DataValidation
– checksofinputdataintegrityandcontinuity
• ForecastVerification:Benchmarking
– applicationofstandardverificationmetrics– assessmentofpredictionalgorithmsandtheirresults,feedingintoWP6to
improveactiveregionpropertiesandpredictiontechniques
• ForecastVerification:ErrorAssessment
– techniquestoassignuncertaintyestimatestoverificationmetrics
WP5:Dataand ForecastValidation
• UnderstandingMagneticEruptions
– exploitationofexistingMHDsimulations
– investigatethepropertiesandevolutionsthattriggereruptions
• ImprovingFlarePrediction
– testnewpropertiesaspredictors
– createnoveltimeseriespredictionalgorithms
WP6:ExplorativeResearch
• SuitabilityofForecastTimeScales
– studydifferingforecastwindows andforecastlatency
– needstobedrivenbytherequirementsofSpWx end-users
• AdvanceCMEPrediction
– gaininsightbycorrelatingactiveregionpropertieswithCMEoccurrence
– alignment/interactionwithexistingEUprojects(HELCATS)
WP6:ExplorativeResearch
• EducationandPublicOutreach– socialmediaactivity(e.g.,Twitter),pressreleases– participateatpublicevents– educationalmaterialforformal/informallearningandpublicitymaterials
• DisseminationtoScientificCommunity– publishpeer-reviewedliterature– participateindiversesciencemeetings,coordinatingthematicsessions– organizeinformationalsessionsforjuniorpost-gradstudents(PROGRESS)
• DisseminationtoIndustryandGovernment– raiseawarenessbypresentingatSpWx meetingswithindustrialfocus– highlightsocietalimpactstopolicymakersandGovernmentofficials– organise workshopsforendusers inindustryandGovernment
WP7:Dissemination
• Projectprogressingnominally
– propertyDB(designed);propertyextractionalgorithms(integrated)
– predictionDB(designed);predictionalgorithms(being integrated)
– forecastDB(undergoing design);verificationalgorithms(being tested)
• Crucialstageforrelevance/utilityofforecasts
– end-userrecommendationsrequiredtoguidetailoring
• BreakoutI:Userneedsandgoals
• BreakoutII:Roadmapforflareforecastdevelopments
FinalThoughts