project final report - cordis.europa.eu · atmospheric ghg observing system (geo carbon strategy,...

Doc: ICOS-INWIRE_final-report_v20160301.docx

Date: 01/03/2016

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INTERNAL www.icos-inwire.lsce.ipsl.fr 1/33

PROJECT FINAL REPORT

Grant Agreement number: 313169 Project acronym: ICOS-INWIRE Project title: ICOS Improved sensors, NetWork and Interoperability for GMES Funding Scheme: Period covered: from 1January2013to 31December2015 Name of the scientific representative of the project's co-ordinator, Title and Organisation: Dr Jean-Daniel Paris, Commissariat à l’Energie Atomique et aux Energies Alternatives Tel: +33 1 69 08 17 00 Fax: +33 1 69 08 77 16 E-mail: [email protected] Project website address: icos-inwire.lsce.ipsl.fr


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TABLEOFCONTENTS1.1 ExecutiveSummary........................................................................................................................................31.2 Summarydescriptionofprojectcontextandobjectives...................................................................41.3 DescriptionofmainS&Tresults/foregrounds....................................................................................6

1.3.1 WP2:AutonomousGHGatmosphericsensorsystems......................................................6

1.3.2 WP3:EnhancedoperationalcapabilitiesofICOSatmosphericnetwork..........................11

1.3.3 WP4:AutonomousGHGecosystemsensorsystems........................................................15

1.3.4 WP5:EnhancedoperationalcapabilitiesofICOSeddycovariancenetwork....................17

1.3.5 WP6:TowardsinteroperabilitybetweentheEuropeanICOSnetworkandotherGHGnetworks.......................................................................................................................................22

1.4 Potentialimpactandmaindisseminationactivitiesandexploitationresults........................271.4.1 Potentialimpact................................................................................................................27

1.4.2 Maindisseminationactivities...........................................................................................28

1.4.3 Exploitationofresults.......................................................................................................29

1.5 Addressofprojectpublicwebsiteandrelevantcontactdetails...................................................33


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1.1 ExecutiveSummaryGreenhousegases(GHG)aretheprimarydriversofclimatechange.Accuratequantificationoftheirfluxesisneededtotackletheclimatechangechallenge.Therequiredobservationsincludeessentialclimatevariablessuchascarbondioxide(CO2)andmethane(CH4)intheatmosphereaswellascomplementaryparametersdescribingthebiogeochemicalanddynamicenvironmentsuchastheatmosphericboundarylayerheight.Highprecisionsurfacemeasurementsactbothasprimarydatasourceandmetrologicalreference,whereassatelliteobservationsprovideacompletegeographicalmappingofthekeyvariables.

ThefundamentalobjectiveofICOS-INWIREwastoenhancecapabilitiesoftheICOSinfrastructureforGHG monitoring, in order to meet the needs of operational users in Copernicus (GMES in-situcoordination(GISCD2.1)requirements,EEA,2010). ICOS-INWIREaimedtodevelop1)standardizedsensors system that can be run with excellent autonomy in challenging environments, whileremainingcompliantwiththeICOShigh-accuracyrequirements,and2)softwareanddatabasetoolsthatwillintegrateICOSdatawithdatafromotherin-situGHGnetworksforCopernicususers.

Theprojecthasachievedthedevelopmentoftheecosystem(eddycovariance)andatmospheric(concentration)NearRealTime(NRT)measurementsprocessingandevaluation,includingthedevelopmentofunsupervisedalgorithmsforuncertaintyestimationandflagging.ThisworkledtothemodificationofthedatalifecycleanddefinitionoftheofficialICOSdataproducts.NewproductsdevelopedandtestedinICOS-INWIREalsoincludemulti-platformboundarylayerheightretrievalalgorithmandtotalcolumngreenhousegasmeasurementsfromTCCON(TotalCarbonColumnObservingNetwork)inrapiddelivery(3weeks)tomeettheCopernicusrequirements.ANRT(3daydelivery)TCCONproductdeliveredbytheCIOSAtmosphericThematicCenterhasbeendevelopedandshowcasedoverashortperiodof1month.

Thedevelopmentsforrobust,enhancedGHGatmosphericandecosystemmeasurementssystemsinextremeenvironmentshavebeenfullyimplementedandtestedinliaisonwithinstrumentmanufacturers.Anautomatedflasksamplerhasbeenimplementedandinitialfieldtestshavebeenperformed.

TowardstheinteroperabilitybetweentheEuropeanICOSnetworkandotherGHGnetworksanassessmentofcompatibilitygoalshasbeenmade,adesignassessmentfortheatmosphericnetworkhasbeenperformed,thecomparabilityofTCCONmeasurementswithin-situmeasurementshasbeenassessed,protocolsharmonizationhasbeenelaboratedanddisseminatedwithICOS,NEONandAmeriFluxrepresentativesalthoughICOSismoreadvancedlevelintermsofimplementingharmonizedprotocolsthantheseothernetworks.AdatadiscoverytoolhasbeenimplementedtoprovideaccesstoatmosphericGHGdatafromdifferentnetworksanditssustainabilityforCopernicususersisdiscussedinreportD6.9.

AllthisworkwasdoneinstrongliaisonwithkeystakeholderincludingECMWF,TCCONinternationalconsortium,theWMO,(andotherkeyplayersofCopernicus/MACC-II/III)andseveralotherusers(modellinggroups,datafordecisionmaking),aswellasinstrumentmanufacturers.Notably,WMO


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CIMOisnowwellengagedintheprocessleadingtoimplementofanewWMOstandardforeddycovarianceinfluxmeasurements.

Thesedevelopmentsweresuccessfullycompletedanddemonstrated,andtheydirectlybenefittoCopernicus,ICOSandthewidercommunity.ICOS-INWIREenabledandextendedtherobust,enhancedprovisionofGHGdatabymergingnew,in-situGHGobservations(ICOS)andsurfaceremotesensing(TCCON)tovalidatesatelliteretrievalsanddataassimilationresultswithinCopernicus.1.2 SummarydescriptionofprojectcontextandobjectivesGreenhousegases(GHG)aretheprimarydriversofclimatechange.Accuratequantificationoftheirfluxesisneededtotackletheclimatechangechallenge.Therequiredobservationsincludeessentialclimatevariablessuchascarbondioxide(CO2)andmethane(CH4)intheatmosphereaswellascomplementaryparametersdescribingthebiogeochemicalanddynamicenvironment.Measurementsstartedinthe1950’sinMaunaLoa,Hawaii;nowlargesurfacenetworksandspace-bornemissionsdocumenttheglobalGHGdistribution.Highprecisionsurfacemeasurementsactbothasprimarydatasourceandmetrologicalreference,whereassatelliteobservationsprovideacompletegeographicalmappingofthekeyvariables.Therehasbeenremarkableprogressoverthepastfifteenyearsinthedevelopmentofin-situGHGmeasurementtechniques,modelingapproachesandthecreationofaglobalterrestrialandatmosphericGHGObservingSystem(GEOCarbonStrategy,2010).Localecosystemfluxmeasurementsrecordedcontinuouslybyfluxtowers(Valentinietal.,2000),combinedwithconcentrationmeasurementsmadeatatmosphericstationsarenowusedtoderiveestimatesofGHGfluxesoverlargeregionsoftheglobe(Janssensetal.2003,Beeretal.2010,Xiaoetal.2008,2011,Chevallieretal.2010).GlobalmappingofgreenhousegasfluxesdeliversamajorimprovementinunderstandinghowthebiogeochemicalcyclesofgreenhousegasesregulatetheclimateoftheEarth.Importantly,thisprovidesthescientificbasisforthecrucialdevelopmentofemissionreductionpolicies.TheGMESAtmosphereCoreService(ImplementationGroup)hasidentifiedasitstwoprioritiestheconsolidationofin-situGHGatmosphericmonitoringthroughtheAtmosphericcomponentoftheICOSinfrastructureinEuropeandtheharmonizationofmultiple-sourcedatasets(GACS,2009;GISC,2011).In-situGHGdataareidentifiedascriticalinformationto“enablemonitoringoflongtermtrends”andto“ensurevalidationofglobalsatelliteretrievals”.TheworkingpaperontheGMESGlobalLandMonitoringCoreServices(Dolmanetal.,2010)identifiedamongkeyThematicServices“landdataassimilationsystemsforthecarbonandwatercycles”,andrecognizedthenecessitytovalidateglobaldataassimilationproductsusinginsitunetworkssuchasFLUXNET,CARBOEUROPE,nowintegratedattheEuropeanlevelintotheEcosystemcomponentoftheICOSInfrastructure(www.icos-infrastructure.eu).ICOSisalargescaleEuropeaninfrastructureselectedbytheEuropeanStrategicForumonResearchInfrastructures(ESFRI)roadmaprecentlysetupasaEuropeanorganization(ERIC).ICOSconsistsofanetworkofGHGmonitoringstationscoveringtheEuropeancontinent.Thestationsareequippedwithsensorsystemstomeasureonlineecosystemfluxes(andair-seafluxes)atlocalscale,oratmosphericGHGconcentrationandboundarylayerheight(usinglidars)toverifyGHGbudgetsover


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largerregions.ThenetworkofstationsiscomplementedandsupportedfordataprocessingandsensorssystemtestingbyThematicCentres,forAtmosphericandEcosystemdata,respectively.ThesensorssystemsthatequipeachICOSstation(intakeline,calibrationstandards,instruments,anddatatransmissionhub)requiredtobestandardized,withallthestationssharingthesameinstrumentsandprotocols.ThedataprocessingfromrawmeasurementstoelaboratedGHGconcentrationorfluxproductsisstandardizedattheAtmosphericandtheEcosystemThematicCentreoftheinfrastructure.PrototypedataprocessingchainsattheAtmosphericandEcosystemThematicCentreswheresignificantlyenhancedinICOS-INWIRE.ACentralAnalyticalLaboratory(Germany)willprovideflaskairsamplesanalysisforcarboncycletracers.ThepreparatoryphaseofICOSinfrastructuresettinguptheconceptwasfinishedin2013,andtheICOSnetworkswillbeformallyoperationalin2016.ICOS-INWIREactedlikeabridgeforcontinuedtechnicalresearchanddevelopmentoverthisperiod.ThestrategicgoalofICOS-INWIREwastoenableandextendtheprovisionofGHGdatafromrelevantmonitoringnetworksasidentifiedintheGISC(2011)reporttotheGMESAtmosphereandLandCoreServices.Thisincludesenablingharmonizedin-situGHGmeasurementsfrommultiplenetworks,includingfromstationsinpoorlycoveredregions,andfromground-basedremotesensingstationsoftheTotalColumnCarbonObservingNetwork(TCCON).TheconceptwastoenhancethecapabilitiesoftheICOSResearchInfrastructurejointlywiththeTCCONnetwork,bydevelopingnewsoftwareanddatabasetools,andautonomousGHGstationswithintelligentsensorsystemscapabletocollectandtransmitcontinuousdatafromchallengingenvironmentstoidentifiedusers,i.e.operationalcentersanddataassimilationsystems(e.g.ECMWF).Theconvergencebetweenin-situandspaceGHGobservationshastobedemonstratedinICOS-INWIREthrough1)combiningground-basedremotesensing(TCCON)andsurfacein-situmeasurements(ICOS)availabletocalibrationandvalidationneedsand2)providingthesedatatotheECMWFassimilationsystem,thatmergestheinsitu,totalcolumnandsatellitedata-streamsinitsforecastservices.ThefundamentalobjectiveoftheICOS-INWIREprojectwastoenhancecapabilitiesoftheICOSinfrastructureforGHGmonitoring,inordertomeettheneedsofoperationalusersintheGMESAtmosphereandLandCoreServiceElements.Itachievedthisby:1. Developingandtestingautonomousstationsequippedwithgreenhousegasconcentration(WP2)andfluxes(WP3)sensorsystemsabletooperateautonomouslyinremoteareasandintechnicallychallengingenvironments.2. EnhancingthecapabilitiesoftheICOSatmosphericandecosystemnetworksthroughtheICOSThematicCentersforproducingnewtimelydeliveryandnearrealtimedataproductsaswellasofGHGsurface(ICOS)andtotalcolumn(TCCON)concentration,boundarylayerheightfromlidar(WP3),andeddy-covarianceGHGfluxes(WP5)3. Developingintegrateddata-productscombiningground-basedupwardlookingremotesensingandsurfacein-situmeasurementstovalidatesatelliteretrievals(WP5andWP6)4. Improvinginter-operabilitybetweenICOSandotherin-situGHGmonitoringnetworks,throughthedevelopmentofinnovativesoftwareanddatabasetools(WP6)thatwilldeliverdatatotheGMESCoreservices


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TheEuropeancontributiontoglobalGHGin-situmonitoringTheconstructionofaglobalcoordinatedGHGObservingSystemisapriorityoftheGrouponEarthObservation(GEO),anda5-yearimplementationstrategyhasbeendrawnup(GEO-CommunityofPractice,2010).Thein-situcomponentiscoordinatedbytheWorldMeteorologicalOrganization(WMO)foratmosphericstations,andtoamuchlesserextentbytheGlobalTerrestrialObservingSystem(GTOS)forecosystemfluxtowers.TheWMOhasalsorecentlylaunchedaninitiativetowardanIntegratedGlobalGreenhouseGasInformationSystem(https://www.wmo.int/pages/prog/arep/gaw/ghg/IG3IS-info.html).In-situGHGmonitoringisalsoapriorityintheUS,wheretheNEONecosystemmonitoringnetworkisbeingbuildsince2011onabudgetof$430M(www.neoninc.org),andinChinawherecarbonmonitoringisanationalsciencepriority.TheCopernicuspriorityforin-situdataasdescribedbytheGISCreport(GISC,2011)includessurfacevalidated(“essential”)andtotalcolumn(“desirable”)GHGmeasurements,includingCO2andCH4.ICOSisaEuropeancontributiontoglobalGHGObservingSystems.ICOSunitesecosystem,marineandatmosphericresearchcommunitiesacrossmorethan15countries.ICOSregroupsallpre-existingGHGresearchnetworksinEuropesuchasCHIOTTO,CARBOEUROPE,EUROFLUX.Inaddition,EuropeanresearcherscontributetotheTCCONinternationalnetwork(www.tccon.caltech.edu)whichprovidesanemergentbutalreadycrucialvalidationresourceforspaceinstruments,theOrbitingCarbonObservatory(OCO-2),IASIandGOSAT.ICOScomplementedwithTCCONsites,andreinforcedthroughICOS-INWIRE,isabletoaddresstheinsituGHGdatarequirementsasestablishedbytheGISCreport.Weanticipate,onthefaceoftheachievementsinICOS-INWIRE,thatICOSissoonabletoprovideroutinein-situGHGdatafromallgloballyavailablenetworksoperationallytotheCopernicusprogram.1.3 DescriptionofmainS&Tresults/foregrounds1.3.1 WP2: Autonomous GHG atmospheric sensor systems The goal of WP2 was to carry out the necessary R&D for the development of robust, lowmaintenance atmospheric GHG monitoring stations suitable for harsh environments, and theconsolidationoftheexistinginstrumentalpackageattheatmosphericstationsoftheICOSnetwork,withtheobjectivetoenablearealtimetransmissionofthedatatothecentraldatabaseandthenaseamlessdataprovisiontoCOPERNICUS.Theworkperformedinthisprojectconcernsnotonlythehigh precision GHG analysers, but also the associated infrastructure needed for the datatransmission,powersupply,airinlet,etc….As a first step we have analysed the major troubleshooting problems encountered in GHGmonitoringstationsbasedontheexperienceacquiredfromseveralyearsatsiteslocatedinEurope,Arctic, and tropical regions. Threemains categories of problems have been identified linkedwithenvironmentalconditions,humanbeingsandinstrumentsandsensors.Asaresultoftheanalysisofthose problems, we have proposes recommendations and solutions to prevent and solve them(D2.1).ThisanalysisgavethefoundationforaknowledgebasisabouttroubleshootingissuesatGHG


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monitoringstations.Inordertosustainthedevelopmentofthisbasiswehavedevelopawebbasedtool, called WEBOBS, giving the possibility to users to describe all the problems, their identifiedcauses symptoms and solutions. Then a research by keyword enables the community to find allproblemswhichhavebeenalreadyencounteredforagivendevice(Figure1).

Figure1:Left:Exampleofproblems,withtheircausesandproposedsolutionsascompiledinthis

activity.Right:exampleoftheinformationcentralizedinWEBOBSforoneGHGanalyser.Asexpected,oneoftheissuesidentifiedinthisanalysisoftroubleshootingistheneedforarobustsystemtoensurereal timedatatransmissionaswellasremotecontrolof theanalyzers,especiallyforisolatedsites.Alargepercentageoftheproblemscanbediagnosesorevensolvedthankstotheremotecontrol.Asaconsequenceof thedeployment in the fieldofanalyzerswhicharemoreandmorereliablewithlimitedmaintenance,wecanexpecthavinglesshighlyqualifiedoperators.Inthiscontext it will be essential to provide a remote access to a central laboratory, and/or to themanufacturers, where more expertise will be available. In many cases the troubleshootingperformedremotelybyanexpertcouldidentifiedasimplemaintenancefeasiblebylocaltechnicians,insteadofshippingbacktheanalysertothemanufacturer.WehavecollaboratedwithaSMEinorderto propose an integrated package (Figure 2) which can interact with the sensors installed at thestation (GHG,meteorological, webcam, etc…) to gather and then transmit dataset using differentway of transmission (RS232, RS485, Ethernet, NMEA; CAN BUS). A detailed description of thissolutionaswellasacostestimateisprovidedinthedeliverableD2.2.


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Figure2:DiagramoftheDIABOXsystemset-upatErsastationforthedatacollectionandtransmission.

In addition to the in-situmeasurements of greenhouse gases the ICOS Class 1 stationsmust alsoorganize regular flask sampling program. The sampled flaskswill serve as a quality control of thecontinuousmeasurements,andwillprovidemeasurementsofadditional tracegases likeN2O,SF6,isotopes, etc…). As part of ICOS-INWIREwe had set-up the ambitious objective to develop a newflasksamplingsystemthatmeetsthehighstandardoftheICOSflasksamplingstrategy.Namelythespecificationoftheflasksamplerincludesthefollowingpossibilities:• Installationofatleast24flasksforallowingdiurnalcyclesampling• Simultaneoussamplingofatleast2flasksforthecomparisonexerciseswithotherlaboratoriesaspartoftheICOSQAstrategy

• Samplingflasksviaabuffervolumeorinalowflowscenariothatintegratesairsamplesoverca.1hourtogetmorerepresentativevalues

• InstallationofflaskswithdifferentsizesinonesamplerforallowingbothtracegasanalysisattheCentral Flask Laboratory (CFL) whichwill be carried outwith 2L flasks and 14C analysis at theCentralRadiocarbonLab(CRL)usinglarger3Lflasks.

Aprototypehasbeendesignedandbuiltduringtheproject(Figure3).Thenewflasksamplerhasthepotentialtosetanewstandardinautomatedsamplingsincetheinstrumentprovidesasetofuniquefeatures,whichcannotbeprovidedbyotherautosamplingdevices.The largesetof24 flasks thatcanbeprocessedmakes itpossible to run the instrument6monthswithoutanyuser interventionprovidedthat2flasksgetfilledonabi-weeklyscheduleasitisforeseenfortheICOSflasksamplingprogram.FurtherinnovativefeatureslikepurgingthesamplinglinebetweensamplingintervalshelptoensuretheambitiousaimswithrespecttotheenvisagedICOSflasksamplequality.Althoughthemechanicaldesignof the instrument is finishedandthemanufacturingprocess is fullyestablished,thework on the development of the sampler control software is not yet completed. Features forintegrated sampling requiring the mass flow controller setup are still under implementation. Inaddition to this, experiments have indicated a malfunction in the individual control of the valvemotors.Thisrequiresapartlyrevisionofthemotorcontrolconcept.


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Figure3:Left:pictureoftheautomaticflasksamplerprototype.Right:Flaskoverviewscreenofthe

samplercontrolsoftwareDuring the duration of the ICOS-INWIRE projectmany specific tests have been performed both inlaboratoryandfieldconditions.Theresultsofthosetestshavebeenexploredbythepartnersoftheproject,aswellasthescientificcommunitythankstopresentationatinternationalmeetings,andthemanufacturersoftheanalyserswithwhomcollaborativeeffortswereestablished.Asanexampleofthe industry liaisondevelopedwithonemanufacturer theFigure4 shows the improvementof theCH4 repeatability thanks to the redesigned of one electronic board used for the cell pressureregulation. The performance degradation on the CH4 measurement of the new generation ofanalyzer(G2401,G2301)comparedtotheoldergenerations(ESP1000,G1301)wasidentifiedbyYverKwoketal,2015,andtheimprovementimplementedbyPicarrowaspresentedattheGGMT/WMOinternationalconference(Leggettetal.2015).

Figure4:Left:watervaporcorrectionbiascomparisonbetweenfactory(built-in)andATCcoefficients;

dottedlinerepresentshalfoftheWMOcompatibilitygoal[Laurentetal.,2015].Right:Picarroanalyzerperformancewith(inredandorange)andwithoutthehardwareupgrade(ingreenand

blue)[Leggettetal.,2015].From the numerous tests performed in laboratory and in the field (tropical, arctic, desertenvironments and ship platforms) we have proposed an assessment of the sensibility of thegreenhousegasesanalyserstothetemperature,pressure,wateranddustcontent,icingconditions,powersupplyquality.Accordingtotheresults,itappearsthattheGHGanalyserselectedinICOSdonot present a strong sensitivity to either the ambient temperature or pressure. Actually someanalyzerswere showinga strongCO sensitivity to theatmosphericpressure,but theproblemwascorrected by the manufacturer thanks to a hardware upgrade. Recommendations have beenprovidedinthedeliverableD2.5tohandlethedustandpoorqualitypowersupply(Figure6).AlotofeffortandtestshavebeendedicatedtothesensitivityofCO2/CH4measurementstothewatervapor,


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which has been identified as a major potential source of bias. All the results which have beenpresented in ICOS and GGMT/WMO meetings and synthetized in the deliverable D2.5 will bepublishedin2016.Theimportanceoftheevaluationoftheanalyzersensitivitytowatervaporbothbeforeoperations(testsperformedattheICOSATCMetrologyLab),andregularly inthefieldhavebeendemonstrated(Figure4)andprotocolshavebeenproposed(Figure5).

Figure5:Protocolofthewatervaporcorrectionassessmentwithdropletmethod.

AlltheresultsandrecommendationsaresynthetizedinthedeliverableD2.5(Reportonnewsensorpackagecapability inextremeenvironment)and inthefollowingtable(Figure6). It is importanttonotethatnotonlytheresultsarecrucialforthemonitoringnetwork,butalsotherigorousapproachwhichhavebeenproperlydocumented,andwhichwillshouldbefurtherpursuedtoguaranteetheoptimizationofthemeasurementprotocolsinthelongterm.

Figure6:Summaryoftheissueswhichhavebeenevaluated,withrelatedsolutionsand/or

recommendations.

Condition Natureofproblem

Solution Test(field,lab) Status

Highvariabilityandrangeofroomtemperature

Dependencyofsignaltotheroomtemperature

Correctionapplied;coefficientstobedetermined

Controlledchamber

NowsystematicallyimplementedbyICOSATC

HighHumidity GHGmeasurementneedtobecorrectedfromthedilutionandthespectroscopicbroadeningeffectofH2O

EitherdryingairorimprovingthedeterminationoftheH2Ocorrectioncoefficients

ATChumidifyingbench.Nafiondryerbiasassessmenttest.Nafionsetupwithbypasssystem.

NowaccurateH2OcorrectionsystematicallydeterminedatATCMetrologyLab.NafionwithbypasssetupsuccessfullytestedinCorsica.

Dust Cloggingoftheanalyserresultsindamage

FilterwithlargesurfacewithoutinducingartefactonGHGmeasurement

GHGmeasurementcompliancytest.Efficiencytestinthefield.

NowwidelyusedintheICOSnetwork

Icing Cloggingthesamplinglines

Insulatingand/orheatingthesamplinglines

GHGmeasurementcompliancytestoftheinsulated/heatedsamplinglines

ImplementedinNorunda.RequiredfurtherinvestigationsforissuerelatedtoH2O

Poorqualityofpowersupply

Riskofdamage Useof“online”UPS.UPSmanagementSystemforappropriateinstrumentshutdown/start

TestoftheUPSmanagementsysteminthefieldinrealconditions.

SuccessfullyimplementedinCorsica.


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1.3.2 WP3: Enhanced operational capabilities of ICOS atmospheric network Tomeet the needs of the GMES Global Atmospheric Core Service/Copernicus as prepared in theframe of MACC-II and MACC-III, high data availability rate and seamless in-situ Greenhouse gas(GHG)datatransmissionwasrequired.CentraltoWP3’sobjectiveswasthetimelydeliverytoMACC-II/III(ECMWFandpartners)oftherequiredparameters.ThetimelinessobjectivesetinWP3wasonemonth. Estimates of the contribution from lidar (boundary layer height) and TCCON data (totalcolumnCO2andCH4)wereidentifiedascrucial.The general goal of this work-package was to consolidate the data flow coming from the ICOSatmospheric network through the ICOS Atmospheric Thematic Center (ATC) with enhancedmeasurement and data transmission/exchange capabilities of in-situ stations or networks. Groundbased FTS (Fourier transform spectroscopy) measurements from TCCON were integrated in thatpackage, updated at first, at a monthly frequency. The contribution of lidar and ceilometer wasdemonstratedtodiagnoseboundarylayerheight,acriticalvariablethatdefinesthedilutionofCO2andCH4surfacesourcesandsinksintheatmosphere.Adatastreamwasimplementedtoprovideanintegrateddatapackagewith1)NearRealTime(1-day)ICOSdata,2)Rapiddelivery(1-month)ICOSdataand3)RapidDelivery(1-month)TCCONdatatotheGMESMACC-IIandotheroperationalusers.This was possible with the development of new capabilities for operational data processingenhancing the capabilities of theATC, and a different approach to data processingwithin existingnetworksandcommunities.

Figure7-schematicviewofmeasurementprotocolatICOSstations.AsfirststepGHGconcentrationdataprocessingwasimproved.InordertoimplementanautomaticdatafilteringofGHGmeasurementsinnearreal-time,possibleparametersthatcanbeusedinnon-human supervised data screening were identified, and data pre-processing with some automaticflagswasapplied,relayingonautomaticthresholdingduringapre-processingphase.Inparticular,aso-called “questionable data” flag (set on qualify in-situ data by PIs) has been added in dataworkflow. To facilitate PI’s work at qualifying data, an automaticmail service on data processingwhenerrorsoccurhasbeen implemented. ItallowsalertingPIswhensuspiciousmeasurementareacquiredatstationanddetectedinthepre-processingphaseofdata.In a concern for transparency and measurement traceability, full automatic processing ofatmospheric CO2 and CH4 mole fractions at the ICOS Atmospheric Thematic Center has been


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documented (seeFigure 7) and is currently being reviewed for scientific publication [Hazan et al.,2016].

Figure8–Box-and-whiskerplotsof thevalidatedminusnear-real timedifferencesofhourlymeansCO2(left)andCH4(right)molefractionsfor2014.ThispaperdescribesthecomputingfacilitydedicatedtotheICOS-ATCatLSCE,thedifferentstepsoftheprocessingofCO2andCH4molefractionsincludingtheautomaticqualitycontroloftherawdataandthecorrectionsduetowatervapourinterferenceandcalibrationinWMOreferencescale.MostoftheprocessingprotocolsandparametersareillustratedwithfewexamplesofinstrumentcurrentlyprovidingrawdatatotheICOS-ATCaspartoftheICOSextendedDemoExperiment.Inparticular,thedifferencebetweenvalidatedandnearreal-timemeasurementofCO2andCH4wasassessed(Figure8).Forthestudyofestimationofrepeatability'sbasedontargetgasmeasurements,thecalculationinnearreal timeof thecontinuousmonitoringrepeatability (CMR)andthe longtermrepeatability(LTR)havebeenimplementedintheICOSdataprocessingandrepresentativenesserrorassessmentthroughhourlymeanshasbeencalculatedfromdiscontinuousmeasurements

Figure9-Exampleofflaggedandun-flaggeddataatPicduMidiusingthespikedetectionalgorithm.Lastpartofdataprocessingimprovementtask3.1inthisworkpackagewastoimplementamethodto identify the periods when measurements are strongly influenced by local emissions, typicallywithin1or2kmaroundthestation.Such influenceof localsources ischaracterizedbyshort-termvariations, which it was proposed to detect using spike detection algorithm. Two peak selection


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methods,namelythecoefficientofvariationmethodandthestandarddeviationmethod(Brantleyetal.,2014)usedtoevaluateinsituemissions,localairqualitytrends,andairpollutantexposureweretested. The proposed algorithm detects CO2 and CH4 peaks, which are randomly emitted fromunidentifiedsources(seeFigure9forCO2).Onecentraltaskofworkpackage3wasalsotohaveabetterestimateofplanetaryboundarylayerheight (PBL), or better:mixing height (MH),which is a key parameter to link ground-based in-situmeasurements of atmospheric trace gases to transport model results or total-columnmeasurements.Becausemixingheightcanusuallynotbemeasureddirectly,thegoalofTask3.2wastodevelopanalgorithmthatcouldbeused toderiveMH fromopticalbackscatterprofilesof lidarsystemsaswellasthelesspowerfulbutmorecost-efficientceilometers.

Figure10–PlanetaryBoundaryLayerheightretrievedfromaJenoptikCeilometer(cyanpoints)andcomparedtothoseestimatedfromanearradiosonde(blackstars)atSIRTAObservatory,Palaiseau,FranceduringoneweekofMay2015.Twoatmosphericboundary layer retrievalalgorithmswere selected (resp.PyBL&STRAT), and thechoice was made to have them improved by their developers (resp. MPG & LMD) to meet thespecificneedsofICOS-INWIREintermsofBLHrestitutionandimplementationonsiteintheICOS.Itresults in two tuned versions (PyBL_ICOS& STRAT+) of original algorithmswhichwere comparedover a common dataset of measurement, thanks to standard data format for backscatter signalsfrom lidar/ceilometers also developed in this work package (see Figure 10 ). In order to assessalgorithmandinstrumentalprecisionandvariation,asetof12co-locatedceilometers(sixdifferenttypes)andalidarsystemwerecomparedbyapplyingSTRAT+onmeasurements(seeFigure11).Theresultsshowsthatthedetected-to-potentialBLHpercentageforallsystemsisbetween91%and97%of thepotential10-minBLHduring thewholeperiodof comparison (i.e.2months).Regarding theinstrumentvariability,allmodelof ceilometer showsimilarbehaviour since thepercentageofBLHdeviationlowerthan250m(𝑃<250)amongtheco-locatedceilometersduringthecomparisonwasbetter that 80%. Comparison with collocated radiosondes showed 𝑃<250𝑚 during night time islarger than 80% for all ceilometers. For daytime𝑃<250𝑚 drops to 25%-45% due to low signal tonoiseratios.SinceopticalsystemsarenotnecessarilybeexactlycollocatedwithatmosphericstationsintheICOSnetwork, spatial and temporal interpolations of mixing heights were investigated. Nevertheless


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obtainedresultsconcerninginterpolationofBLHvaluewerestillnotmatureenoughtobeusedandmorestudiesshouldbeperformed inorder tocombine radiosondeprofiles,opticalmeasurementsandmodeldata.BothtunedalgorithmsareavailableforpotentialusersandICOScommunityuponrequest.

Figure 11 - List of 12 ceilometers and lidar systems participating in CEILINEX2015 at Lindenberg(Germany), on which BLH retrieval algorithmwas applied and detection score as seen as STRAT+detected-to-potentialBLHpercentagein%.Alongwith lidar/ceilometersBLHproducts tocompletedataoffering forCopernicus,oneaspectofdataprovision in ICOS-INWIREwas to improvedataworkflow forTCCONstations, inorder to fulfilGISC requirements in termofdelay (i.e.1month).WithinTCCONthe routineprocessingofdata isdoneinbatchesona6monthsbasisandmostoftheTCCON-dataitisfreelyaccessibleonlyoneyearafter the measurement. Within ICOS-INWIRE, data from four TCCON sites, including Ny Alesund(Spitsbergen), Trainou (France), Bialystok (Poland) and Réunion (France), are now processed andprovided through the ICOS-ATCdata server asRapidDelivery TCCONproducts. For these sites theprocessinganddatatransferhasbeenautomatedanddataisnowavailableatleastonemonthafterthemeasurement,andmostofthetimetheweekafter(seeFigure12).

Figure 12 – TCCON Rapid Delivery Product availability at ICOS ATC data center andmean uploadfrequencyfromstationtodatacenter.TCCONrapiddeliverydataareaccessibleviathelandingpagehttps://icos-atc.lsce.ipsl.fr/tccon hosted on ICOS ATC website. Access is subject to authentication.LoginandpasswordcanbeobtainedbycontactingICOSATC.Lasttaskofworkpackage3wastoimprovedata,metadataformat,anddatastreamwithMACC-II/IIIfor Copernicus. Data protocols and formats for data distribution to MACC-II were defined and 3open-ended datasets for CO2 and CH4 species weremade available for ECMWF users. In 2015, 7


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datasetsfromICOSstationsarepushedtoCopernicusservers,innearreal-time.Notethataccessisalso given via ICOS ATC website, using https protocol (user and login on request). In order tocharacterizedata transmissionefficiency, short termand long termdataavailabilityare taken intoaccount as performance indicator. Short term availability is ~70% because it is subjected to thestresses of operation and transmission in near real timeoperationmode. Long termavailability isbetter,asexpected,sincePIscanresolvemeasurementissues(transfer,communication,calibrationetc.…),andis~90%postdataprocessingandQA/QC(seeFigure13).

Figure 13 – Short term and long term availability for data provision for Copernicus. Short termindicatoriscomputedfrommeasurementsactuallytransmittedtoCopernicusthedayafter.Thelongterm indicator is computed from hourly measurements of air availability, transmitted every sixmonths.Itdoesnottakeintoaccountflaggingofdata.NotethatlongtermavailabilityatOPEstation(atalltowerstation,with3measurementslevels)is85%.Thisisduetothefactthatinletlineshavetobeflushedbetweeneachlevel.CoveredperiodisJanuary2015–November2015.1.3.3 WP4: Autonomous GHG ecosystem sensor systems ThepurposeofWP4wastofurtherstandardisethemethodologyoftheeddycovariance(EC)techniquetomonitorecosystemgreenhousegas(GHG)fluxesanditsassociatedqualitycontrol.TowarrantafullcoverageoftheICOSECnetwork,anautonomousandheavydutyECecosystemfluxsensorssystemasbedesigned.ThissystemshouldmeasurewithsimilarqualityandstandardsastheICOSsite1and2systems,inplacestoharshorremoteforthesemoreconventionalECsystems.Aspartofthisdesignawirelesssystemforauxiliaryvariableswasdevelopedcapableofmeasuringfrom-400Cto+700C.Thesystemwastestedinremoteconditions.WefurtherdevelopedaprocessforaninternationallyagreedprotocolforeddycovariancemeasurementsfortheGMES,thatispartofaUN(WMO-FAO)setofstandardsRobusteddycovariancedesignandtestsOneofthedesignchoiceswastheuseofof-the-shelftechnologysothirdpartiescanreadilyimplementthesystemsdesigns.Thisdesignchoicehadtobewaiveredforthewirelesssensorcommunicationasthestateofcurrentlycommerciallyavailableradiomotesisnotsufficientforscientificuseunderextremeenvironments.Thuswirelessmoteshavebeendesignedanewthatcanfunctionunderextremeconditions(-40oCto+70oC),areaccurateenoughforscientificdatacollectionandareeasytouseinthefield.AusermanualisavailableforpotentialuserswithinICOS.


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Alldesignchoicesandthesystemscharacteristicscanbefoundindeliverable4.1aReportoninitial‘heavy-duty’ECfluxsensorssystemdesign.

Fig8.Designdiagramfortherobusteddycovariancesystem.Thesystemblockatthelowerrightcorneristhewirelesssystemsoilmoisture,temperature,andrainfall.Thesystemwasbuiltatsuccessfullytestedat4locations,fromSpaintoNorthernSweden.Someminordesigndetailswerecorrectedduringthistest,butoverallthetestprovedsatisfactory.Inremotecoldconditionswesuccessfullytestedacameradesignthatuploaded10timesadaytocheckwhetheritwasfrozen.Througharemotetelephoneconnectionwewerethenabletodefrostit.

Fig9SonicanemometeraboveSwedishforestbeforeandafterdefrosting.AnautonomouspowersupplydevelopedbyInSituInstrumentABwasinstalledinmidOctober2025ataneddycovariancefluxsiteinnorthernSwedeninmid-October.Thesystemismonitored


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continuouslyanditisworkingasplanned.Thisopensupthepossibilityofusingtheeddycovariancesystemwiththepowersystemforremoteconditions,withverylowmaintenance.standardizationoffuturemeasurementsWewereinvitedataCIMO(WMOCommissiononMeteorologicalObservations)NewTechnologyWorkshopfrom10-13September2014inGenevatopresenttheecologicalobservatory/eddycovariance.DevelopmentofanECstandardwasconsideredhighutilityandwouldbeuseful,andCIMOistheappropriateentitytomanagethestandardonceithasbeendraftedbyagroupofexpertsdrawnfromtheglobalECcommunity.TherepresentativesmetduringAGUinSanFranciscoinDecember2014andagreedtoproceedandtaskedVUAtoprepareaninitialdraftofthestandard.ThiswasscheduledtobereadybytheendofJuly2015,withassistanceofNEONmanagement.Thisdraftstandard,largelybasedonexistingICOSandNEONprotocolsisavailableandiscurrentlyunderreviewbyNEON.AfterthatiswillbemadeavailabletoallFLUXNETorganizationsandopenforreview.AfterthataversionwillbesubmittedtoCIMOforapproval.1.3.4 WP5: Enhanced operational capabilities of ICOS eddy covariance network TheICOSEcosystemNetworkmonitorsandmeasuresalargenumberofparametersusingstandardizedmethodsandapproaches.Thegoalisclearlytoservethelargestpossiblenumberofuserswithhighqualitydatathatcanbeusedandintegratedinparticularinmodellingactivities.InthiscontexttheICOS-InwireactivitiesinWP5havebeenfocussedonthedataqualityimprovementandidentificationoftheproductscharacteristicsrequestedinordertofacilitateaccessandusetonewpotentialusers.Thetasksperformedcoveredsomeofthemostcriticalaspectsinthedatadisseminationanduse,such:

1) Theidentificationofthekeyecosystemvariablesneededinmodeldataassimilationandremotesensingdatavalidation,theircharacteristicsandfrequency;

2) ThetestoftheNearRealTimefluxesmeasurementprocessinganduncertaintyestimationinordertoevaluatetheirqualityandpotentialuseinmodellingactivities;

3) TheverificationofthecomplianceoftheICOSETCmetadatastructurewiththeGEOSSrequirementsinordertoincreasethevisibilityoftheICOSdata;

4) Thedevelopmentanddefinitionofnewmetricstoevaluatetheassimilationofthekeyecosystemvariablesinlandsurfacemodels,inordertosuggestnewapproachesinthemode-dataintegration.

Characteristicsofthevariablesneededinmodel-dataassimilationWhicharethecharacteristicsthatmodelersandremotesensingcommunitywantintheecosystemmeasurements?ThiskeyquestioniscrucialforacorrectdevelopmentoftheecosystemcomponentinICOSandtheactivitiesperformedinTask5.1havebeenfocusedonfindingthebestpossibleanswers.ThefirststephasbeentheanexpertmeetingorganizedinAmsterdambyVUAinMay2013whereECMWFmodellers(GianpaoloBalsamoandAntonBeljaars)participatedaskeyCopernicususerstogethertoICOSandICONS-Inwirepeople.ThesummaryofthemeetingresultshasbeenreportedinMilestoneMS16.thevariablesandsitescharacteristicsneededtoperformamodeldataassimilationexercisewereidentified,includingtheirformatandcharacteristics(qualityfiltering,uncertainty).Oneofthemainoutcomehasbeenthedefinitionoftwodifferentmaintypeof


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activitiesbasedonecosystemdata:• Retrospectivedataanalysis• NearRealTime(NRT)dataingestionThedifferencebetweenthetwoapproachesisinthetimeframeandlengthofthedatarecordsused:inthefirstcasethedatahavebeenacquiredbysitesinthepastyearswhileintheNRTdataingestionthemeasurementsusedinthemodellingactivityareacquiredandmadeavailablealmostinrealtimeandfortheprevious5to10days.Inboththeactivitiesthesamevariablesarerequestedandused(carbon,waterandenergyfluxes,netradiationandsoilwatercontent),althoughthequalityoftheNRTdataislowerduetoanumberofcorrectionsandfilteringactivitiesthatarepossibleonlywhenalong-timeseriesisacquiredandprocessed.Ithasbeenalsoclarifiedthatwhatismoreimportantistheclearindicationofquality,uncertaintyandmeasuredversusgapfilleddataandtheuseofastandardformatstableintime.Startingfromtheserequirementsonthevariablesitwassuggestedtoidentifydatasetswherethemodel-datafusioncouldbebasedonecosystemandatmosphericmeasurementsatthesametime.Inadditionalsotheclimateregionswheredataarelessavailableformodelvalidationhavebeenidentifiedwiththeaimtoanalyzetheavailabilityofdatacollectedintheseregions(tropical,sub-tropical,artic).Thesespecificrequirements(locatedinkeyareas,closetoatmosphericmeasurementtowers,collectionoftherequestedvariables,easyandopensharingofthedata)havebeenusedtosearchforpossiblestudycasesthatrespectedallthecharacteristicsrequested.TheseareashavebeenidentifiedandreportedinDeliverableD.5.1

Fig10:identificationofthesitesinthekeyclimaticregionsthatmatchestherequirementsintermsofkeyvariablesavailability.ThemainresultobtainedhasbeentheidentificationoftheneedsfrompotentialusersoftheICOSinfrastructurethatcanbeusedbyICOSinthedesignoftheproductsandvariablesmeasured.


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NearRealTimeecosystemdataprocessingNearRealTimedata(NRT)canbedefinedasdatathatarereceived,processedandmadeavailabletotheusersinashorttime,generallylessthanoneday.TheneedofafastprocessingbasedonshortdatasetscanaffectthequalityoftheresultsandforthisreasonNRTdatahavebeeningeneralconsidered“lowquality”informationavailableonlyfordisseminationandgeneralcontrolofthemeasurements.AlsothankstoTask5.1resultsithasbeenconfirmedthathoweverthesedatahavepotentialscientificusersinterestedtoimprovemodeldatafusion(MDF)andinparticularlandsurfacemodel(LSM)tobetterunderstandthecomplexdynamicofterrestrialbiosphereexchangesofmatterandenergy.ThishoweverrequiresanimprovementofthedataqualityandthedevelopmentofanuncertaintyestimationthathasbeenthecoreactivityofTask5.2.TheNRTprocessingwasdevelopedfollowingthemostrecentrecommendationsonfluxescalculation(Fokenetal,2012),and the resultsobtained fromprevious researches (seeRichardsonetal,2012and reference therein). QA/QC procedures and uncertainty estimation are based on severalprocessingoptionschemes,withtheaimtoprovideinformationaboutbothrandom(stochastic)andsystematic(processingoptions)errors(Fig11).

Fig11:schemeofthestepsinvolvedintheNRTnewprocessingandoptionsselectedfortheuncertaintyestimationThemethodologydeveloped(fullydescribedinDeliverableD5.2)hasbeenimplementedontheICOSETCportal(www.icos-etc.eu/icos/nrt-data)andappliedinthelasttwoyearsoftheprojecttofivecandidateICOSEcosystemsites:- BE-Lcr,Lochristi,Belgium;IGBP:DBF- FI-Hyy,Hyytiala,Finland;IGBP:ENF- FR-Fon,France,Fontainebleau,IGBP:DBF- IT-SR2.SanRossore,Italy,IGBP:ENF- SE-Nor.Norunda,Sweden,IGBP:ENFTheresultsobtainedhavebeenofcrucialimportanceandimpactinICOS.NRTdatafromecosystemsiteswereoriginallyconsideredastemporary,lowqualitydatabutthankstothenewprocessing

Introduction NRT Work Flow Combining rules Quality Flagging Policy SWOT

NRT Work Flow

EC Raw Data Transfer

ECProcessing

Block AverageDouble Rotation

Block AveragePlanar Fit

Linear DetrendingDouble Rotation

Linear DetrendingPlanar Fit

Using results from pre-vious processing basedon historical long datasets(i.e. spectral correc-tion factors, planar fitcoefficients)

Combining Rules

Quality Flagging Policy

EC Fluxes Data Release


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strategytheyarenowincludedintheofficiallistofICOSproductsandconsideredhighqualitydatasuitableforresearchactivities.Assideresult,theactivityhelpedalsotobetterunderstandanddefinetheimportanceofthechoiceofasinglestandarddataformat.IntheICOS-Inwirecontexttherewasnostandardandtheconversiontoacommonformatwasperformedbythedatacentre.ThisapproachresultedtobetoocomplexandmoreimportantnotenoughrobustandfollowingtheseresultsICOSdecidedtostandardizetherawdataformat.ThisactivityhasbeenoneofthemostsuccessfulonthedeliverableandoftheprojectandinFig.12aresummarizedthemainconclusions.

Fig.12mainlessonslearnedwiththeNRTdataprocessingdevelopmentinICOSInwireCompliancewithGEOSSThemaincharacteristicsofthedata(intermsofvariablesbutalsoformat)werediscussedinthemeetingwiththemodelers(MilestoneM16)andtheanalysisofrequirementsdidnotevidenceparticularissues.ThecharacteristicsrequestedareingeneralalreadyavailableinthedataprovidedbyICOSandincludeandeasyidentificationofmeasuredandgapfilleddata,afullmetadatasettointerpretthedata,anumberofancillaryinformation(LAI,biomass,chambersetc.)thatalthoughnotusedinthefirstphasewillbeusefulinasecondstageandtohavebothalong-termandaNRTdataproduct.ToincreasethevisibilityoftheICOSdata,althoughtheactivityiscoveredbytheCarbonPortal,ithasbeendiscussedandtestedamethodtoincludetheICOSNearRealTimedataintheGENESIportalinordertotesttheinformationflowandcommunicationformat.TheworkhasbeendonefollowingaschemesuggestedbytheGENESIexpertsthroughsimpleXMLfilesthatinfuturecanbefurtherdevelopedtoincludemoreinformation.ThisexperiencehasbeenpresentedanddiscussedwiththeICOSCarbonPortalthatisinchargeofthisactivityandisdevelopingthestrategyconsideringalsotheexperiencefromICOS-Inwire.Asimilarsystem,basedonxmlfiles,hasbeenalsosetuptolinktheICOSEcosystemdatabasewiththeFLUXNETnetwork,aglobaldatabaseofmetadataonecosystemeddycovariancesites.Thexmlisautomaticallygeneratedattheaddresshttp://gaia.agraria.unitus.it/siteslist2.aspxanditisimportedintheFLUXNETdatabaseavailablehere:http://fluxnet.ornl.gov/NewmodelvalidationparametersThelastactivityintheWPhasbeenfocusedonthedefinitionofnewmetricstoevaluatemodeldataintegration.Infact,thebestuseofthedataisreachednotonlywhentheybecomeavailablewiththehighestpossiblequalitybutalsowheretheyareusedinthebestpossibleway.Inthiscontexta


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numberofpossiblealternativeevaluationsofthemmodelresultsagainstmeasurementshavebeencreatedandtestedusingexistingmodelsruns.Thegroupofmetricsapplied(describedinDeliverableD5.4)are:Descriptivestatistics:afteravisualinspectionofthedata,calculationofbasicdescriptivestatisticstosummarizethedatashouldgivetheresearcherinsightintotheirdata.SimpledescriptivestatisticsincludetheMean,MediaandMode.TheModeshouldbecalculatedasthevaluewheretheprobabilitydensityfunctionreachesitspeakandnotasthemostfrequentnumberduetotherandomcomponentindataandmodeloutputs.Whencomputingstatisticsformodeloutputswheneverpossiblebiomesshouldbeanalysedseparatelyduetotheirlargeheterogeneity.

Fig.13:exampleofdescriptivestatisticalanalysiswheredistribution,medianandpercentilesarecomparedbetweenamodel(purple)anddirectmeasurements(green)Regressionanalysis:alsoregressionanalysisbetweenvariablesisanotherimportantstep,easytofollowbecauseimplementedinallthesoftwarefordataanalysis.ItincludesforexampletheR2andtheRootMeanSquareError(RMSE)thatgiveinfoonthespreadofthemodelversusmeasurementdata.Theregressionanalysishowevershouldnotbeconsideredasonlyapplicabletothefinalmodeloutput;therearecaseswherepartialoutputofamodelcanbeverifiedagainstdataandinthiscasethisshouldbedone.Forexample,amodelpredictingforestbiomassstartingfromasimulationofthetreenumber,diametersandheightcouldbepossiblevalidatednotonlyonthefinalresultbutalsoontheintermediateproducts(diameter,treenumberandtreeheight)atthebasisofthecalculation(andoftenmoreeasilyavailableasdirectmeasurementsandwithloweruncertainty)Seasonalityandtrend:simulatingcorrectlytheannualbudgetdoesn’tmeanthatthemodeliscorrect.Itisalwayspossibletogettherightanswerforthewrongreasonandthisiswhyitisimportanttovalidatealsothemodeltemporalvariabilityatdifferentfrequencies.Asimplemethodcouldbelookingatmaximaofavariablethatissensitivetoseasonalvariationandanalyzingthetimingofthismaximabetweenmodelandobservation.However,othermethodsaretodayavailabletobetteranalyzethemodelbehaviorintime,likethedecompositionofthetimeseries.Theprinciplebehindthedecompositionofatimeseriesisthatatimeseriesconsistsof3elements:atrend,seasonalityandrandomvariance.TakingatmosphericCO2concentrationsasanexample,theyearlyincreaseinCO2concentrationasaresultofanthropogeniccarbonemissionsisalongtermpositivetrend.Theyearlycarbonfluctuationsasaresultofthegrowthseasonandwinterareaseasoncycle.


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Altheotherleftovervariationisquantifiedasrandomvariation.SeasonalcyclescanbeextractedbyforexampleaFouriertransformationfollowedbyassmoothingofthedataafterwhichthetransformationisreconstructedwithoutthesmoothedseasonalcycle.Anextstepwillthenbearegressiontoextractthetrendfromthedata.Subtractingthisextractedtrendwillleavetherandomvariation.Thedifferentcomponentsfrommodelanddatacanbethendirectlycomparedinordertocheckifthematchbetweenthetwoisconservedatallthetimescales.

Fig.14:exampleoftimeseriesdecompositioninthethreemaincomponents.HereasexampleNPPofdeciduousforestfromCasamodel.Asfinalconclusionofthistask,onthebasisoftheexampleofapplicationreportedinthedeliverableD5.4,isthatthetimedecompositionisoneofthemostpromisingapproaches.ThismayimplythatthecurrentICOSobservationschemesneedtobeadjustedtoaddressthereallycriticalissues,ratherthan“measureeverything”.Thiscallsforflexibilityinthestandardisationoftheprograminthelongterm.1.3.5 WP6: Towards interoperability between the European ICOS network and

other GHG networks Agrowingnumberofnetworksformonitoringatmosphericmixingratiosbytalltowersandsurface-atmospherefluxesofgreenhousegasesbyeddycovariancetowersareinoperationaroundtheworld.Intheatmosphericdomain,NOAA-GMDstartedintheearly1990swithatalltowerprogramacrosstheUS,andbynowoperatesabouteighttalltowerobservatories.VariouscountriesinEuropeoperateanetworkofnowabout30stations,manyofwhichwereintroducedwithinICOS,andadditionalstationstobestartedwithinthenextyears.ThecurrentEuropeannetworkincludesaround15talltowers,withtheremainingstationsatthecoastsorontopofmountains.EarthNetworks(EN),aprivatecompany,hasstartedinvestingintoameasurementnetworkforCO2andCH4inthebeginningof2011,withaplantoinstrument50towersintheUS.Furthermore,asubstantialnetworkisbeingimplementedinChina.TherapidgrowthofinsitunetworkswithinEuropeneedstobeaccompaniedbycarefulplanningofatmosphericsitelocationsinordertomaximizesynergies,toprovidethedesiredspatialcoveragerequiredforwall-to-wallmonitoringof


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GHGemissionsandsinks,andtodevelopandagreeoncommonprotocolsandmethodsinecosystemmonitoringactivities.Networksforecosystemobservationshavebeendevelopedstronglyinthelast10yearsondifferentcontinents,followingdifferentstandardsandharmonizedcriteria.IntheUS,NEONdevelopedanetworkofhighlystandardizedecosystemsitesthatwillruninparalleltotheAmerifluxnetwork.Similarly,organizednetworksinthemajorcountriesinAsia(China,Japan,Thailand)andAustraliaareestablished.Allthesenetworks,includingICOS,arepartiallyintegratedundertheFLUXNETinternationalinitiative,butwithoutanyinter-operabilityoragreementaboutprotocolsandstandards.Dataacquisitionprotocols,methodsandstandardshavebeendevelopedorareunderdevelopmentindependentlyinthedifferentecosystemnetworks,butwithoutcoordination.Itisthuscrucialtoensurecompatibilityandinteroperabilityofmeasurementsacquiredbythesedifferentnetworks,bydevelopingcommonprotocolsandproductsdefinitionandcharacteristics.TheobjectivesoftheworkperformedunderWP6areto:•AssessthecompatibilityrequirementsofdifferentGHGatmosphericnetworks,usinghighresolutioninversemodellingtools•ProvideacoordinatedatmosphericnetworkdesignassessmentoverEurope,targetingmaximumreductionoffluxuncertainties•Ensurenetworkcompatibilitybetweenatmosphericin-situnetworksfromICOSandEN,andbetweenICOSandtheTotalCarbonColumnObservingNetwork(TCCON),anetworkforgroundbasedremotesensingofcolumns•Developanddocumentcommonprotocolsandmethodologiesthatensureinter-operabilitybetweenthedifferentecosystem(eddycovarianceGHGfluxes)networks.•DevelopdatabasesoftwaretoolsthatensurethedataavailabilitytotheGMESAtmosphereCoreServiceandotherusers•Demonstrateimprovementinthecal-valofsatellitedatausingTCCON6.1AssessmentofcompatibilityrequirementsThecompatibilityrecommendedbyWMOof0.1ppmforCO2and2ppbforCH4wasnotoriginallyintendedformeasurementsovercontinentalareaswithstrongandvariablefluxesofGHGsaffectingthemeasurements.ToassesstheusefulnessofthiscompatibilitytargetforICOSatmosphericobservations,targeteduncertaintiesforspatiallyresolvedland-atmospherefluxeshavebeenassumedforCO2(15gC/m2/ytoallowforresolvinginterannualvariationsinthebiosphericfluxsignals)andforCH4(5%ofemissions,correspondingtoyeartoyearvariationsinemissions),andtheJenaregionalinversionsystemSTILT-TM3wasappliedusingafullyearofsimulatedtransporttodeterminetheimpactofmeasurementbias.Theresultsshowthatmeasurementbiasesof0.1ppmforCO2and2ppbforCH4(i.e.withintheWMOcompatibilitygoal)arecompatiblewithuncertaintytargetsforretrievedspatiallyresolvedfluxesthatrequirefluxsignalstoberesolvedonannualtointer-annualtimescales(seeFig.15and16).However,forfuturemodellingsystemswithabetterrepresentationofatmosphericobservations(higherresolutiontransportandapriorifluxes),resultsreportedindeliverablereportD6.1indicatethatthecompatibilityrequirementsareausefulupperlimitformeasurementbiaseswithinthenetwork.TheseresultshavebeencommunicatedtoandtakenupbyICOS-ERIC,astheyunderpinthecurrentatmosphericstationrequirementssetupbyICOS.


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However,theassessmentalsoindicatedthatacleardefinitionofthetargetsforanymonitoringandverificationactivityaddressinggreenhousegasexchangeisofcrucialimportance.ThishasinitiatedastrongerinvolvementofthereportingcommunitywithinfutureprojectssurroundingtheICOS-ERIC,withtheintentiontogettheiradviceonhowtobestverifyGHGemissionreporting,i.e.toidentifythespatialandtemporalscalesatwhichinformationismostuseful.

Figure15:ImpactonfluxbiasforCO2inunitsofgC/m2/y,inthecaseofindependentbiaserrorsof0.1ppmateachstation(left),andincaseofa0.1ppmbiasinallICOSstationswithinGermany.Blackfilledcirclescorrespondtothestationlocations,andblackcirclesindicatetheareaaroundeachstationwithinonespatialcorrelationlengthoftheprioruncertainty(~66km).6.2CoordinatednetworkdesignoverEuropewithmesoscalemodelsInordertoassessthe(currentandfuture)ICOSatmosphericnetwork’sperformanceintermsoftheamountofinformationgainedthroughtheobservingnetwork,throughindividualstations,andregardingtheimpactofspatialgapsintheobservingnetwork,anetworkdesignstudywithdifferentregionalscaleinversionsystems(theSTILT-TM3systemandtheVUAregionalinversionsystem)focusingonCO2wasperformed.Forthis,thepriorfluxuncertaintywasharmonized,withanerrorstructurethatresemblesthemismatchbetweenpriorfluxesandeddycovariancefluxobservationsfromecosystemstations.Resultinguncertaintyreductions(Fig.17)showastrongspatialinhomogeneityintheuncertaintyreductionforseasonallyorannuallyintegratedfluxes,whichisaconsequenceoftheshortpriorerrorcorrelationscales.Typicaluncertaintyreductionsforseasonalfluxesarearound30-50%nearobservingsitesforthepixelscale(50km),andaround50%fornationalscales.Theregionalinversionsystemsgaveasimilaranswerregardingthepatternofuncertaintyreductionatthenationalscale.Acomparisontoacoarse-resolutionglobalinversionsystemclearlyindicatedthatsuchregionalsystemsareneededtoprovideinformationonsub-continentalscales.

Figure16:UncertaintyreductionmapsforthefutureICOSnetworkforsummer2007forSTILT-TM3(left)andtheVUAinversionsystem(right).


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Notethatmodel-datamismatchuncertaintiesarechosenthataretypicallyusedincurrentinversionsystems,suchthattheobservationalconstraintforfuture(improved)modelsislikelytoincrease.DifferencesintheuncertaintyreductionbetweentheSTILT-TM3andtheVUAinversionsystemsarepartiallyrelatedtothedifferingimplementationofalong-termfluxbiascomponent,resultinginlargerprioruncertaintyfortheVUAsystem(andthuslargeruncertaintyreduction)atlargespatiotemporalscales,butcouldalsoreflectdifferencesinoptimizationapproach.Theassessmentindicatesthatthedensityofstationsisacriticalparameterinobtainingahomogeneousuncertaintyreductioninsurface-atmosphereexchangefluxes.AnalysisofahypotheticalnetworkwithagapintheareaofGermanyindicatesasignificantimpactfortheimmediatearea,includingneighbouringcountries.ForthedevelopmentoftheICOSatmosphericnetworkthismeansthatitiscrucialtoexpandintocurrentlyunder-sampledregions,especiallySouthernandEasternEurope.

Figure17:DifferenceinuncertaintyreductionforseasonallyaveragedCO2fluxesforafullnetworkandonewithagapoverGermany,showingtheimpactofagaponuncertaintyreductionfordifferentcountries.6.3aQA/QCevaluationatTCCONsitesAsafirststeptowardscombiningground-basedremotesensingdatawithin-situobservationsfromICOS,TCCONobservationsofcolumn-averageddryairmolefractionsofCO2fortwosites(BialystokandOrleans)werecomparedwithacombinationoftall-towerbasedin-situprofileobservationsforthePBL,boundarylayerheightdata,andTM3-simulatedCO2mixingratiosforthefreetroposphere.Ingeneral,thedry-airmolefractionsretrievedbythedifferentmethods(TM3model,syntheticmodel+tall-towerin-situ,TCCON)agreedwithinlimits.Themodel-derivedcolumnsarelikelybiasedhighvs.TCCONduringwinterandalsopossiblyduringsummer,pointingtoatoolowageofairinthestratosphereintheTM3model.6.3bQA/QCevaluationforatmosphericstationsusingflasksamplingAnalysisofairsamplesarecollectedatthetwoAGAGEsitesJFJ(highaltituderesearchstationJungfraujoch)andCGO(CapeGrimObservatory)havebeencomparedtolocalcontinuousmeasurementsforthegasesCO2,CH4,CO,andN2Ofortimeperiodsfrom2003uptotheendof2013.Ingeneral,goodagreementwasfoundforthedifferentgases.However,insomecasesandforsometimeperiods,significantdifferences(bias)betweencontinuousandflasksampleanalysiswere


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foundthatexceedtheWMOrecommendedcompatibilitygoals.Thisshowsthatflasksamplingisanessentialelementofqualityassurance,asitprovidesacommonlinkbetweendifferentstationsandnetworksusingthesameflasksandanalysismethodsacrossallobservingstations.FutureregularflasksamplingusingtheautomatedsamplerwillsimplifythisprocedureforthecontinuousgreenhousegasmeasurementsmadeatICOSclass2stations,andregularintercomparisonsatsitesfromdifferentnetworks(suchasAGAGEorNOAA-GMD)willhelpensuringthatcompatibilitygoalsaccordingtoWMOaremetacrossdifferentnetworks.6.4HarmonizationandinteroperabilityofGHGecosystemnetworksHighaccuracyandqualityofcollecteddataisoneofthemainobjectivesoftheICOSecosystemnetwork,forwhichstandardshavetobedefinedfromtheselectionofthesitestothereleaseofthedata.Protocolsdefiningbestoptionsinthedifferentfieldsofresearchhavebeendevelopedtothisend,involvinganexpertsmeetingwithrepresentativesfromAmeriFluxandNEON.Eddycovariance(EC)methodologyplaysthelargestroleinthemonitoringactivity.FourprotocolshavebeendevelopedwithinICOScommunityrelatedtoEC,concerning:1–setupofthetower;2–sonicanemometer;3–gasanalyser;4–rawdataprocessing.TheseprotocolsaresummarizedinthereportD6.6,highlightingthecontributionofICOSINWIREintheirdefinition,andindicatingtheimportanceofstandardizationandtheroleofcollaborationwithotherexistingconsolidatedGHGnetworkssuchasAmeriFluxandNEON.TheofficialICOSprotocolsdistributionandpublicationisunderthecontrolofICOSanditsbodies,howevertheplanistopublishabookcontainingalltheprotocols,andreferenceandacknowledgmenttotheICOS-Inwirecontribution.Thefirststeptowardsinteroperabilityofdifferentnetworksisaconsistentandcommonsystemoflabellingofvariablesandprocessinglevels.Theproposedlabellingsystem,commontoICOSandAmeriFlux,anddevelopedwithinICOS-INWIRE,isdetailedinthereportD6.7.ThereportemphasizestheimportanceofacommonsystemoflabellingsharedbyinitiallytwodifferentGHGmonitoringnetworks,intheperspectiveofdevelopingfuturehigherstandardisationlevelsbetweenworldwideGHGnetworks.TheroleofcollaborationandinteroperabilitywithotherlargernetworkssuchasOzFluxinAustralia,ChinaFlux,andAsiaFluxiscrucial,andhasbeeninitiatedwithinICOS-INWIRE.6.5DatabaseandsoftwaretoolstoprovidedatafromdifferentGHGnetworkstoGMESservicesAnewdiscoverytoolhasbeenimplementedattheICOSATC(AtmosphereThematicCentre),accessibletousersthroughurlhttps://icos-atc.lsce.ipsl.fr/databrowser/.ItallowsuserssuchasCAMS(CopernicusAtmosphereMonitoringService)andinversemodellerstodiscoverandaccessatmosphericgreenhousegas(GHG)observationsfromdifferentnetworks,throughasimpleandeasy-to-useinterface.SustainabilityofthetoolisgrantedthroughthesupportbyICOS-ATC.


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Figure18:Generalviewofthedatadiscoverytool,givingaccesstoatmosphericmeasurementsfromtheICOS,InGOS,andNOAA-GMDnetworks.6.6Demonstrationofimprovementinthecal-valofsatellitedatausingTCCONGround-basedcolumnmeasurementsfromTCCONsitesarevitalforvalidationofsatelliteretrievals.However,ithasbeenrealizedwithinthesatellitecommunitythatforvalidationtime-lagsofoneyear(asstandardTCCONprovision)arenotacceptable,andforfuturesatellitemissionssuchastheSentinel5precursor(S5p)rapiddelivery(RD-TCCON)dataisneeded.ThefeasibilityofRD-TCCONhasbeendemonstratedandimplementedfor4sites.

Figure19:LandingpageofdemonstrationexperimentatECMWFforveryfastdeliveryTCCONproduct,acknowledgingtheICOS-INWIREdataprovision.1.4 Potentialimpactandmaindisseminationactivitiesandexploitationresults

1.4.1 Potentialimpact

TheEU'stargetofreducinggreenhousegasemissionsby20%relativeto1990levelsby2020embodiesitsobjectivetofightclimatechangeandisattheheartoftheEuropestrategyforsustainablegrowth.Bothpolicy-inducedandvoluntaryactionscanhelpreducecarbonemissionsand


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increasecarbonsinks,butsignificantchangesinthecarbonbudgetarelikelytorequirepolicyinterventions.ThisiscalledforbyEuropeancitizens.TheimprovementoftheICOSresearchinfrastructurethroughICOSINWIREhaswide-rangingsocio-economicimplications:notonlyimprovingthemeasurementsystemsonregionalcarbonfluxesavailabletothepublicanddecisionmakers,butalsotechnologicalexternalities(innovationrequiredtomeettheneedsoftheinfrastructure’sdevelopment),generalsocio-economicbenefitofpublicinvestmentininfrastructureprojects,andpotentialimprovementtoclimatepredictionmodels.EuropeancompaniesservingtherequirementsoftheInfrastructurecanbenefitfromthedevelopmentofICOSbygainingcompetitiveadvantagesontheglobalmarket.ICOSINWIREsupportedtheresearchanddevelopmentneededtokeepICOSattheforefrontofcarbonobservations.NowthetaskwillbetosecuretheuptakeofICOS-INWIREresultsintheICOSdecisionmakingframe.

1.4.2 Maindisseminationactivities

TheICOSINWIREprojectmaintainedadedicatedwebsitewithaccesstodocuments,generated20publishedscientificpapers,and6morearegoingtobesubmitted.Thecoordinatorandotherparticipantsparticipatedinseveralconferencesandmeetingstopromotetheachievementsintheproject.Butmostimportantly,theconnectionwiththeICOSresearchinfrastructurehasbeenactivelymaintained.ClosecontactandcollaborationwiththeICOSHQ,ATC,ETCandCarbonPortalaswellasTCCONnetworkisensured.TheICOSdirector(DrW.Kutsch)participatedtoalltheICOS-INWIREannualmeetings.ThecoordinatorofICOS-INWIREhasbeennominatedtoparticipatetotheICOSResearchInfrastructuremanagementcommitteeteleconferencesonanadhocbasis.Inaddition,theICOS-INWIREExecutiveBoardincludesresponsiblepersonsfromtheICOSatmosphericandEcosystemThematicCenters.MoreactivitiesaredescribedinD7.3.ThecollaborationwithTCCONisclosethroughtheactivityofthebeneficiaryUBREMEN.WedemonstratedinICOS-INWIRE,thatTCCONdatacouldbedeliveredwithinoneweekorless.ThishasbeenvalidatedwiththedecisionbodyoftheinternationalTCCONnetwork,withtheestablishmentofadedicateddatafairusepolicyinWP3.Datadelivery3daysafterthemeasurementwouldbepossible.Thequalitycontrolforthisfastdataproductshouldbeenhancedinthefuture,pendingappropriateleveloffunding.Iffundingfortheoperationofthe4TCCONsitescanbeobtained,thefastdataproductcanbedeliveredbeyondthedurationofICOS-INWIRE.ItisstrikingthatatthelastICOSassemblyofPrincipalinvestigators,ICOS-INWIREwasdirectlyorindirectlyassociatedtohalfofthepresentations.3presentationswereentirelymadeofICOS-INWIREresults;thereforetheuptakeofICOS-INWIREresultsintheICOScommunityisnowconsideredastotallyengaged.Theprojecthasbeenpresentedatconferencesandassociatedinformationmaterialhasbeendevelopedanddistributed.Thesedisseminationactivitiesareexplainedinthereport.Theprojectwebsitehasbeenupdatedtofollowtheintermediatereview’srecommendations.AveryuserfriendlyDocumentManagementSoftware(webpageisWP7)hasbeeninstalledthroughthewebsiteandmadeavailabletothepartners.AfterthelifetimeofICOS-INWIRE,alldocumentation(reports,deliverables,material)willbetransferredtotheICOSdocumentmanagementsystem.


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1.4.3 Exploitationofresults

TheexpoitationofICOS-INWIREresultsintoICOSissecuredbyseveralelements:

- Adhesion: direct participation of key ICOS staff to ICOS-INWIRE (director of the ICOSEcosystemThematiccenterandseveralnationalnetworkscoordinatorsaremembersoftheICOS-INWIREexecutiveboard, the ICOSdirectorhasbeenparticipatingtothe last2annualmeetingsofICOSINWIRE)

- Community awareness: regular presentation of ICOS INWIRE results at internal ICOSmeetings(includingthePImeetings,thesciencemeetings)

- Decision-making: plans are under preparation to include several of the ICOS INWIREachievements into ICOS ina formalway.Anewactivity issetupto informthe inclusionofTCCON into ICOSwithina3yearhorizon.LidarBLHcharacterizationoperationalproduct isbeing prepared by the ICOS ATC. Webobs will be formally promoted as the networkinformationsysteminanewproposalinINFRADEV.

- In some cases the achievements of ICOS INWIRE will be promoted beyond ICOS to theResearch Infrastructure Cluster ENVRIPLUS. For example, robust instrument testingmethodology and power provision are being currently proposed as services to thecommunityofenvironmentalresearchinfrastructures.

Moredetailsaregivenhereafterforkeyachievements.

1.4.3.1 WP2:RobusttestinginharshenvironmentsATC/ICOSwillprofitfromtheworkdonetoevaluateseveraltechnicaloptionsintheatmosphericstations(e.g.Nafiondrying,CRDSanalysersfieldtesting,heatingofthesamplingline,datatransmission,etc.).TheresultsofthetestsperformedinICOS-INWIREwillbeusedtoimprovetheICOSAtmosphericStationsSpecificationsdocument,whichsummarizetheguidelinesfortheICOSsites.DetailscanbefoundinDeliverable2.1(RequirementspecificationsforGHGatmosphericstationsinextremeenvironments)andD2.4(Reportonthetestat4sites).

1.4.3.2 WP2:DevelopmentofWEBinterfacetomanagethestationandinstruments

TheWEBOBSinterfaceenablestocentralizethetroubleshootingofseveralstationsandinstruments.TheinformationcentralizedthroughthistoolwillbeusedbytheICOSatmosphericcommunityasaknowledgebaseoftheproblemswhichcanariseandhowtosolvethem.ThisWeb-basedsoftwarealsoservesasaninterfacetoexchangemetadatabetweenstationsandtheICOSdatabaseatATCandCP.ThissystemiscurrentlybeingproposedfordeploymentacrossICOSintheframeofanewproposal.

1.4.3.3 WP3:NRTdataprocessing

ICOS-INWIREhasimprovedtheICOSdataprocessingschemeinseveralpoints:warningsanderrorsinformationaresenttothestationPIsonadailybasis,calibrationinterpolationinterruptionsoftheregularschemearebettermanaged,automaticdetectionandflaggingoflocalexhaustplumeswith2methodsisundertestandwillbeimplementedintheICOSATCdatabase.Thankstodevelopmentsintask3.1,sufficientQCcannowbeappliedautomaticallyinalmostreal-timeandtheNRTdataisprocessedinamoreconsolidatedway.NRTdataarethereforereadytobe


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consideredasahigh-qualitydataproductthatwillbedistributedintheICOSofficialdataproductslist,asnowincludedintheICOSRIdatalifecycleplandocument.

1.4.3.4 WP3:BLHproductfromLIDARThroughtask3.2ICOS-INWIREprovidesasteptowardsareleasecandidateofaunifiedalgorithmforBLHretrieval,andaframeworkforlidar/ceilometerstestandperformanceevaluation,whichisessentialtocomplete“ICOSAtmosphericStationSpecifications”document.Onthisbasis,ICOSATCwillcontinueitscoordinatingroleinthedevelopmentofrobustalgorithmformixedlayerdepthcomputation.Recommendationhasbeenmadeanda2-yearroadmaptoimplementoperationallythebestalgorithmisnowavailablebasedonpropositionbytheCNRSpartner.

1.4.3.5 WP3:TCCONdataprocessingThroughTask3.3weachievedGISCrequirementintermofdatadelivery(i.e.1month)anddataprocessingimprovementon4experimentalTCCONstationstoCopernicus.InthecontextofCopernicus,TCCONandICOSATCareadditionallyabletodelivercolumnaveragedmolefractionsofCO2andCH4fromspecificTCCONsiteswithin3days,forspecificmodelassimilation,and/orsatellitevalidation.ICOS-INWIREbroughttogethertheseteamsanddevelopedanewservicebutlongtermsupporttothisactivityneedstobeendorsed.Tothiseffect,asciencerequirementandfeasibilitystudyforoperationalinclusionintoICOSwillbelaunchedin2016.

1.4.3.6 WP3:DatauncertaintiesThecalculationoftime-varyingshortandlongtermrepeatability'sdevelopedduringICOS-INWIREhasbeenincludedrecentlyintheoperationalICOSdataprocessing.Spikedetectionalgorithmsarenowbeingevaluated,andtheresultswillbepresentedatthenextICOSMSAforcommunityuptake,withtheobjectivetoimplementthemostappropriateoneintheICOSprocessingchainsby2016-2017.

1.4.3.7 WP4:WirelesssensorssystemWirelessmotesallowforeasywirelesscommunicationbetweensensorsanddatalogger.TheyconstitutetheinnovativecoreoftheICOS-INWIREautonomousrobustecosystemeddycovariancesystem.Thesemoteshavebeendesignedtobeeasytouseandmatchmanytypesofinstruments.AttheendofthisprojectblueprintsoftheseradiomotesandassemblyserviceismadeavailabletoICOSpartners,withthefineelectronicsdepartmentoftheVUA.

Duringthesethreeyearsmanynewcomponentshaveappearedthatcanenhancetheinitialdesign.ThereforebeyondICOS-INWIREtheimprovementandfurtherdevelopmentoftheseradiomoteswillcontinueatVUA.Asanexamplewearecurrentlyinvestigatingpossibilitiestoreplacetheradiocomponentwithnewpartsthathaveonlyrecentlybecomeavailable,thesepartsshouldextendtherangeoftheseradiomotesevenfurther.Theinclusionofwirelesssensortechnologiesinenvironmentalscienceisrelativelynew,andwillinthefutureoffergreatfreedomandnewmethodsofcollectingdata.


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1.4.3.8 WP4:EddycovariancestandardwithWMO/CIMO

TheagreementwithWMOtodevelopanECstandardhasbeenmetearlyonintheprojectduringameetingwiththecommissionforinstrumentsandmethodsofobservation(CIMO),whichagreedthatacommonECstandardisdesirable.ThisneedforanECstandardofmeasurementshasbeenechoedbyalloftherepresentativesofECnetworksduringtheAGUfallmeetingin2014,wheretheparticipantsalsoexpressedtheirwillingnesstocooperateincreatingone.ThismeetingincludedmembersofICOS,NEON,Ameriflux,Chinaflux,INPE,OzfluxandICOS-INWIRE.

AfirstdraftforthisECstandardhasbeenwrittenwithinICOS-INWIREandiscurrentlyreceivingimprovementsbyselectedexpertstoformarobustdocumentthatcanformthebasisforafinalstandardtobeendorsedbythelargerfluxcommunity.Creatingastandardrequiresconsensusandtakestime,thisisreflectedintheD4.4deliverable:ReportonproposeddefinitionofinternationalWMO/FAOstandardoneddycovariance.Thisproposeddefinitionhasbeenwritten,howeverthecompletionofsuchastandardrequiresmoretimethanpossiblewithinthethreeyearsoftheICOS-INWIREproject.

BeyondthescopeofICOS-INWIREtheformationofthisECstandardwillcontinuetothebenefitofICOSandothernetworksglobally.ThepeopleresponsibleforthisECstandardarelongstandingmembersofthefluxcommunityandprominentmembersofICOSandarethusareinaperfectpositiontocontinuethedevelopmentofthisECstandardthathasalreadygainedsometraction.

1.4.3.9 WP4:Powersupply(fuelcell)

TheconceptanddesignofarobustandautonomouspowersupplysystemforeddycovariancefluxmeasurementsinharshwinterconditionshasbeendevelopedincooperationbetweenICOS-INWIREpartnerULUNDandasmallcompany,InSituInstrumentABlocatedinOckelbo,Sweden.ThepeopleatInSituInstrumentAB(www.insitu.se)areexpertsinenvironmentalmeasurementtechniqueswithaspecialtytointegratedifferentcomponentsintofunctioningstate-of-the-artsystems.Theyalsoperformfieldinstallationsandprovideservicesinmanagementofmeasurementsystemsaswellasdatahandling.

ThefinaldesignsolutionoftheICOS-INWIREpowersupplyisbasedonasystemconsistingofdualfuelcellsforproductionofelectricpowerandtoprovidebackupincaseoffailureofoneofthefuelcells.Thisisimportantsinceafuelcellbecomedamagedifitfreezes.Thereforeoneofthefuelcellsisdedicatedtothispreventivesafetyissue.Thetwofuelcellswillbeplacedinaspeciallydesignedweatherproofandinsulatedcontainerwithspeciallydesignedairintakesandwaterdrainagesystemtocopewithsnowdriftandlowtemperatures.Thesystemwillbecontinuouslymonitoredandcommunicationwiththeinternetwillbedonethroughflexiblecommunicationsolutions.Oneofthekeycomponentsofthesystemisabigmethanolfueltankthatwillprovidethenecessarycapacitytorunthesystemforminimum6monthsincoldclimates.FieldinstallationandtestsinthenorthofSwedenwillcommenceinOctober2015andcontinuethroughoutthewinter.

Sincewebelievethatitisimportanttomakeinnovationsavailabletothemarket,thesystemwillbefullyCEcertifiedandintroducedtothemarketafterfinalizationoftheICOS-INWIREfieldtests.


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1.4.3.10 WP5:DefinitionoftheGMESLandcoreservicesrequirements

DefiningtheneedsofgeneralICOSdatausersisakeysteptobetterdefinetheICOSproductsandtoprovidethebestpossibleservicefromtheResearchInfrastructure.TheactivitiesperformedintheWP5startedwithameetingwithexpertusersfromECMWFthathasbeenthebasisfortheDeliverables5.1,5.3and5.4wherethedatacharacteristicsandbestsitestouseinthemodellingactivitiesweredescribed.TheseelementswillbetransferredtotheICOSCarbonPortalandICOSEcosystemThematicCentre.ThemodellingactivitieswerealsoakeyresultfortheNRTdataproductiondescribedherebelow.

1.4.3.11 WP5:EcosystemNRTdataproduct

InthecontextofWP5anewmethodologytocalculateNearRealTimeeddycovariancefluxeshasbeendeveloped.Forthisfirsttimetherawdata(10Hz)weresubmitteddailytoacentralizedserverwhereacombinationofprocessingmethodsareappliedinastandardizedway.Theresultsarethenpublishedonlineeverydayanddirectlyaccessibletotheusers.Thedataincludeuncertaintyestimationandanumberofflagsforthemostimportantqualitytests(seeDeliverable5.2).Thesedatahavebeenalsousedinafirstdata-modelfusionactivitybyECMWF.Infact,thenewprocessingandqualitytests,inadditiontoapracticalexampleofscientificdatauserwerethebasisforadiscussionintheICOSInterimResearchInfrastructureCommitteethatrecognizedtheEcosystemNRTdataasICOSdataproducts(beforetheywereonlyenvisagedfordisseminationactivitiesandnotforscientificuse).ThisisanimportantstepforwardintheICOSdataproductsdefinitionandamajorICOS-INWIREcontributiontoICOS.

1.4.3.12 WP6:NetworkdesignandHarmonisation

ElementsofthenetworkdesignstudyperformedwithinWP6arebeingmadeavailabletouserssuchasstationPIsandalsothegeneralinterestedpublicthroughtheICOSCP(CarbonPortal).Specifically,thesensitivities(socalledfootprints)ofmeasurementsmadeatatmosphericstationstosurface-atmospherefluxesareusedtocreateinteractivevisualizationsofwhatthenetworkcan“see”.Forthis,theICOSCPhasstartedimplementingtheSTILTtransportmodelinawaythatallowsuserstointeractivelyvisualizestationfootprints.Thisway,stationPIsoralsotheinterestedgeneralpubliccanseehowatmospherictransportmodulatesthewayagivensiteisinfluencedbydifferentgeographicregions.Furthermore,biosphericfluxesandanthropogenicemissionsforCO2,CH4,andCO,usedasa-prioriemissionsforinversemodelling,arecombinedwiththesefootprintstogeneratetimeseriesinformationofsimulatedatmosphericsignalsandtheirpartitioningintoe.g.differentemissionsectorsandfueltypes.Thisenablesuserstoassessforeachstationtheexpectedcontributiontotheobservedsignalfromspecificsources,whichisusefule.g.forfurthernetworkplanning.ThenecessarycodemodulesandinventorydatahavebeenprovidedtoICOSCPbytheMPGgroupandtheEDGARemissioninventorygroupatJRC.ThiswillbeespeciallyusefultoevaluatealsopotentialnewsitesinthecontextofverificationofanthropogenicGHGemissionsreporting.

Theresultsfromthenetworkdesignactivities(ICOS-INWIRED6.1)werefrequentlycommunicatedtoICOSStationPIsandotherICOSparticipantsduringseveralICOSMonitoringStationAssembliesfor


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Atmosphere.Thisallowedforimprovedcoordinationwithinthenetworkregardingtherequirementofhomogeneousstationcoverageacrossthedomain,andregardingtheproximityofstationstoareasofstronglocalemissions(whicharemoreproblematictorepresentinmodels).TheresultsobtainedintheassessmentofcompatibilitygoalsforatmosphericGHGobservations(ICOS-INWIRED6.1)providedscientificallybasedreasoningtotherequiredmeasurementprecisionandaccuracyaswellastotherequiredcompatibilityofmeasurementsmadethroughouttheICOSatmosphericnetwork.

Acentralelementdevelopedinthisnetworkdesign,theso-called“footprints”arecurrentlybeingtransferredtotheICOSCarbonPortal(ICOS-CP).Footprintsrepresentsensitivitiesofmeasurementsmadeateachstationatagiventimetoupstreamsourcesandsinks,Thiswillallowforon-goingactivitiesregardingtheimpactofstationsontheestimationofsurface-atmosphereexchangefluxesinatmosphericinversions,andprovidesfurtherguidanceonstationselectionandnetworkdesign.

1.4.3.13 WP6:Protocolimprovements

Intheecosystemcomponent,itiscrucialtostandardizeandharmonizethemethodologies,definitions,andprotocolsasmuchaspossibleamongdifferentnetworks.ICOSaimstobeareferenceResearchInfrastructure.Thecomparisonofprotocolsandtheworkonsharingofprotocols,inparticularbetweenICOS,AmeriFlux,andNEON,contributedtoacommondevelopmentofthebasicstructureofthedataproductandthedefinitionvariables.ThishelpedsupportingthedevelopmentoftheICOSecosystemdefinitionsconsideringalsothecompatibilityandharmonizationwithotherRIs.

1.5 Addressofprojectpublicwebsiteandrelevantcontactdetailsproject'sco-ordinator:DrJean-DanielParis,Commissariatàl’EnergieAtomiqueetauxEnergiesAlternativesTel:+33169081700Fax:+33169087716E-mail:[email protected]:icos-inwire.lsce.ipsl.fr

project final report - cordis.europa.eu · atmospheric ghg observing system (geo carbon strategy,...

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