FLARECAST: A project overviewflarecast.eu/wp-content/uploads/2017/01/FLARECAST_Overview... · – Doug Biesecker(USA – operational SpWx) – Pedro Russo ... – NOAA/SWPC • solar

FLARECAST:Aprojectoverview

D.ShaunBloomfield(NorthumbriaUniversity,UK)FLARECASTConsortium(Europe)

• 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

Consortium Locations

ProjectStructure

WP1

WP2 WP3

WP4

WP5

WP6

WP7

• 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

Website:http://flarecast.eu

Twitter:@FLARECAST_EU

WebResources