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GNET2017Forward:ThefutureshapeofaGreenlandGNSS

observationnetwork

AwhitepaperproducedbytheparticipantsoftheNSF-supportedGNETworkshop,NASAGSFC,26-27January2017

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ExecutiveCommittee:

RobertHawley,DartmouthCollege

ErikIvins,NASAJetPropulsionLaboratory

TomNeumann,NASAGoddardSpaceFlightCenter

ContributingAuthors:SurendraAdhikari,NASAJetPropulsionLaboratoryLaurenAndrews,NASAGoddardSpaceFlightCenterGregBabonis,UniversityofBuffaloMikeBevis,TheOhioStateUniversityDavidBromwich,TheOhioStateUniversityClaraChew,NASAJetPropulsionLaboratorySorenChristensen,AgencyforDataSupplyandEfficiency,DenmarkReneeCrain,NationalScienceFoundationBeaCsatho,UniversityofBuffaloReneForsberg,TechnicalUniversityofDenmarkRonniGrapenthin,NewMexicoInstituteofMiningandTechnologyRobertHawley,DartmouthCollegeErikIvins,NASAJetPropulsionLaboratoryAbbasKhan,TechnicalUniversityofDenmarkKristianKjeldsen,UniversityofCopenhagenPerKnudsen,TechnicalUniversityofDenmarkEricLarour,NASAJetPropulsionLaboratoryFinnBoMadsen,TechnicalUniversityofDenmarkGlenMattiolli,UNAVCOTomNeumann,NASAGoddardSpaceFlightCenterThomasNylen,UNAVCOKeshavDevSingh,UniversityofCalifornia,DavisTonieVanDam,UniversityofLuxembourgMikeWillis,UniversityofColorado

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TableofContentsExecutiveSummary...................................................................................................................................4

1 Currentstateofthenetwork.........................................................................................................6

2 CurrentandfuturescienceusingGNETdata...........................................................................72.1 SolidEarthandIsostaticAdjustment................................................................................72.2 IceMassBalance......................................................................................................................92.2.1 Surfacemassbalance...........................................................................................................................92.2.1.1 Background...................................................................................................................................92.2.1.2 Theconnectionofincreasedmeltondischarge.........................................................112.2.1.3 SMBAnalysiswithGNETData...........................................................................................132.2.1.4 UseofGNETDataforFundamentalImprovementinSMBModeling...............142.2.1.5 GNETZenithTotalDelay:UseforRegionalAtmosphericModels......................152.2.1.6 ChangesinGrISdrivenbybothglacierdischargeandSMB.................................172.2.1.7 OtherpossiblesurfacemassbalancestudiesbenefitingfromGNET...............21

2.2.2 SupportforInterpretationofAltimetry...................................................................................222.2.3 SupportforGRACEandtheTotalMassBalanceTimeSeries.........................................23

2.3 Ionosphere,Troposphere...................................................................................................232.4 Largescalegeodesy...............................................................................................................252.4.1 GNSScoordinatetimeseriesandreferenceframes............................................................252.4.2 MakingITRFavailabletotheusers............................................................................................262.4.3 GNSSreflectometry...........................................................................................................................27

3 DataManagement...........................................................................................................................273.1 GeneralBackground.............................................................................................................273.2 AncillaryData.........................................................................................................................283.3 GenerationofTimeSeries..................................................................................................283.4 DataStreamandArchivingFundedbyNSF..................................................................29

4 Bestconfigurationmovingforward..........................................................................................304.1 EvaluationofGNETstations...............................................................................................304.2 Addingstationstotheexistingnetwork........................................................................324.3 Detailedsitecharacterizationofexistingsites,additionalmeasurements.......334.4 Expandedskycoverageanddataaccessforexistingsites......................................33

5 REFERENCES:....................................................................................................................................34

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GNET2017forward:ThefutureshapeofaGreenlandGNSSobservationnetwork

AwhitepaperproducedbytheparticipantsoftheNSF-supportedGNETworkshop,NASAGSFC,26-27January2017

ExecutiveSummaryAninternationallycoordinatedresearchcampaign,theInternationalPolarYear(IPY)2007-2008,initiatedacoordinatedefforttostudythepolarregionsusingmodernobservationaltechniques,includingamajorinvestigationusinggeodeticandseismicinstrumentation.Thiseffortisformallyknownandfundedunderthename“POLENET”,orthePolarEarthObservingNetwork.InGreenland,theGNETprojectwasdevelopedtoestablishanetworkofGPSreceiversoperatingcontinuouslyandautonomouslyonstablebedrockaroundGreenland.ThemostprominentinstitutionsinvolvedinsupportingthisefforthavebeenTheOhioStateUniversity,theUniversityofLuxembourg,UNAVCO(Boulder,CO)andtheInstitutforRumsforskningogRumteknologi(DTUSpace,Copenhagen).ThepurposeoftheJanuary26-27,2017workshopwastodiscussthefutureofthisnetworkfromageodeticperspective.WewereespeciallyfocusedondocumentinghowGNETdataarebeingusednow,toprobehowthenetworkcouldevolve,andtoaskwhatscientificquestionsmotivateitsfuture.GNETdatahaveservedavarietyofusefulscientificpurposes,suchasprovidinggroundtruthforpredictivemodelsforpostglacialrise/fallofbedrockadjacenttotheicesheetthatinturn,playanessentialroleincorrectingsatellitegravityandaltimetrybasedestimatesoficemassbalanceondecadaltimescales.Adecadeofobservationsnowindicatethatverticalmotionstendtobedominatedbythemassunloadingcausedbysecularicesheetmasslosstotheocean.InadditiontoenumeratingpastsuccessesofGNET,theworkshopparticipantssoughttoexaminetheyetunexploitedvaluethatthenetworkmayprovideforachievingnewscienceobjectives,suchastroposphericandionosphericmapping,gainingnewinsightsconcerningsurfacemassbalance,icedynamicsandoceantidalmapping,amongothers.Thisworkshopreportisdesignedtocapturesomeofthesenewexplorations,butwillhardlyserveasacomprehensivesurveyofallofthedetailsorallofthenewscientificdiscoveryanewdecadeofGNEToperationcouldenable,howeverthenetworkmayevolve.Thereisanemphasisplaceduponthecomponentsoficesheetsurfacemassbalanceinthisreport.Surfacemassbalanceisessentiallythenetinputmasscomponent.Thisisdrivenprimarilybytheatmosphereandnear-surfaceicesheettemperaturestructure.Theemphasisismotivatedbythreerecentsciencebreakthroughs:(i)sinceabout2006thenegativemassbalanceoftheGreenlandicesheetisdominatedbymeltprocesses(andsinceabout1997dominatedbysurfacemassbalanceingeneral);(ii)recentfindingsdemonstratethatGNEThavesensitivitiestotheloadingcomponentsofthevariouselementsofthesurfacemassbalance;(iii)the

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zenith-delaysmeasuredinthecarrierphaseoftheelectromagneticpulsesreceivedatthestationsarecapableofsignificantlyimprovinghindcastmodelsofprecipitation,afundamentalcomponentofthesurfacemassbalance.Theprimaryrecommendationsofthisreportare:

1. ContinuetosupportthecontinuousandautonomousoperationofthecurrentconfigurationofGNET.Thespatialdistributionandlongtimeseriesofobservationsfromthecurrentnetworkhasenabledawealthofscientificdiscovery,andextendingthesetimeseriesintothefuturewillenablenewscience.

2. Maximizetheutilityofthecurrentdatabypromotingtheexistingdatadistributionmodel,whichencourageslow-latencyaccesstodata.Theseeffortsshouldbeaugmentedwithreadilyavailabledoinumberstoenableproperdatacitation.

3. EncouragingnewusesofGNETdata,suchastroposphericzenithdelayanalyses

toimproveatmosphericmodelsinGreenlandanduseofthesedataformodelingtheionosphere.Thisisoneexampleofmanyofnewsciencethatcouldbesupportedbytheexistingdata.

4. Ifpossible,densifythecurrentnetworktobetterresolvethoseareasof

maximumgradientinGIA,and/orregionsofrapidglacierchange.

5. Givenfiniteresources,weconsiderascoringschemeforevaluatingtherelativeimportanceofexistingstations.Consideredaretheroleofexistingstationsforfosteringanimprovedunderstandingof(i)GIA,(ii)surfacemassbalanceminusdischarge(SMB-D)and(iii)resolvingthelargerdiscords(>4.5mm/yr)revealedincomparisonofGIAmodelsbasedonrelativesea-leveldataversusthosemorereliantonGNETupliftratedata.TheultimatedecisionregardingtherelativeimportanceofthesecompetingscienceobjectivesshouldbeguidedbytheacceptanceofviablescienceprojectsselectedbytheNationalScienceFoundation.

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1 CurrentstateofthenetworkTheGreenlandGeodeticNetwork(GNET;Figure1)currentlyconsistsof58geodetic-gradeGlobalPositioningSystem(GPS)receivers,locatedonfixedbedrocksitesaroundthecoastofGreenland[Bevisetal.,2012].ThecapabilityoftheextendedGlobalNavigationSatelliteSystem(GNSS)hasnowsurpassedtheprecisepositioningperformanceoftheolderGPSduetoincorporationofmoresatellitesandadvancesinon-boardtechnology.Thenetworkhasthefullcapabilityformmlevelgeodesy.GNEThasgrownovertheyears,andisoperatedincooperationbetweenseveralgroups.Currentlythereare36stationsoperatedbytheOhioStateUniversity(OSU),1operatedbyNASA’sJetPropulsionLab(JPL),1operatedbyUNAVCO,15byDenmark(DTU),and5bytheUniversityofLuxembourg.Itisimportanttonotethatthoughthereareavarietyof‘owners’ofvariousGNETstations,thereiswidespreadcooperationbetweenthenetworkpartners,intermsofsharingoflogistics,datamanagement,andcollaboratingonbestpracticesforstationinstallation.MaintenanceissharedandcoordinatedbyOSU,UNAVCO,andDTU.Eachstationconsistsofageodetic-gradeGPSantennamountedonapermanently-anchoredmonumentonbedrock,aGPSreceiver,anextensivepowerandpower-managementsystem(solarpanels,windgenerators,batteries),andatelecommunicationssystemfortelemeteringdata-thiscanbewiredorwireless,andisfrequentlyprovidedbytheiridiumnetwork.Thesestationshavethefullcapabilitytomonitorveryprecisecrustalmovements,asforexample,recentlydescribedbyHerringetal.[2016].Eachstationinthenetworkfacesitsownspecificchallengestolongevity.Simplewearandtearonequipmentcancausefailures,butextremeweatherconditionsatsomesitescanalsoposeproblems,withhighwinds,icingandheavysnowloadsdamagingstations.Satellitecommunicationfordataretrievalcanfailformultiplereasons.Somestationsarevisitedbywildlife;polarbearsareanobviouspotentialproblem(theyarenaturallycuriousandverystrong),butequallydamagingtodatareturncanbethesharpteethandbeaksofArcticfoxesandravens.Inspiteofthesepotentialproblems,regularmaintenanceofthestationshas,overtheyears,produceda92%rateofdatareturnforthenetworkandgapsinthedatastreamshavesteadilyreducedovertheyears.Currently,inanygivenyear,manystationsmustbevisitedforroutinemaintenance,upgrades,andrepairs.Thecostofthesemaintenancevisitsislargelydrivenbythehelicoptertimerequiredtoaccess

GNET 2007-2009 (-2014)

• 2007– 23 new stations– 3 field team– Ad-hoc charter helicopters

• 2008– 11 new stations– 1 field team– Long-term fixed charter

helicopter

• 2009– 12 new stations– 1 field team– Long-term fixed charter

helicopter

• 2010-2014– 3 new stations

Figure1.Mapof58currentGNETsitesandinstallationdate.

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mostGNETsites.Continuedmaintenance,upgrades,andadditionstothenetworkwillrequiretheinvestmentofresourcesbynationalfundingagencies.Althoughexpensive,GNETdatasupportsasubstantialbodyofscienceinGreenland,acrossmanydisciplines,asoutlinedinSection2.

2 CurrentandfuturescienceusingGNETdata

2.1 SolidEarthandIsostaticAdjustmentTheelevationofEarth’scrustiscontinuallychangingowingtothecontinuummechanicalresponseofthesolidEarthtotheredistributionofmassontheEarth’ssurface.Oneoftheprimarycausesofsuchchangesisthegrowthandmeltofthegreaticesheets,suchastheGreenlandicesheet.Thechangesincrustalelevationduetotheinterrelatedchangesingroundedicemassandoceanloadingisbroadlytermedglacialisostaticadjustment(GIA)whenthesechangeshavelongtimescales,generallyoforder100-10,000years.However,veryimportantcrustalresponsesalsooccuronelastictimescales,essentiallythesametimescalesasseismicwavepropagationandabasicobservationofferedbyGNETisthatpresent-dayicemassvariabilitytendstodominatemanyoftherecordedverticalsignals[Bevisetal.,2012].OurgeophysicalandobservationalunderstandingofGIAprocesseswerenurturedbystudyoftheemergenceofthecoastlinealongtheBalticSeainSwedenandFinlandmorethan100yearsago[e.g.,Ekman,1991;Peltier,1998].Landtodayrisesatratesof2-15mm/yearnearthecentersoftheformergreaticesheetsoftheLatePleistocene,causinglocalsea-levelstorecede,producingaclearobservationalrecordofsea-leveldrop.Thisphenomenonwascalledpost-glacialrebound(PGR),yetasitbecameunderstoodthattheprocessinvolvedtheentiresphericalearthduetothe125metersofsea-levelloadchange,andassociatedgeoidchanges,theprocessisnowtermedglacialisostaticadjustment(GIA).TheoriginaldesignofGNETwasprimarilyfocusedonthemeasurementofverticallandmotionsassociatedwithdirectpasticeloadandviscoelasticresponses. ForsolidEarthapplications,werecommendcontinuedoperationofexistingGNETsitesforaslongaspossible.Thisallowsustoseparateelasticandviscoelasticcrust-mantleresponses.Theselengthenedtimeserieswillaidinaccomplishingthisgoal,especiallyastheyoverlapwithaltimetrymissions(CryoSat-2andICESat-2(launchingin2018)),WorldViewimagingsatellites,aswellasthethreeSentinelsatellitesofESA’sCopernicusprogram.Inaddition,theNASA-ISROjointNISARmission,launchingin2020thatwillenablespace-baseddischargeobservationsofGreenland’soutletglacierstobetterresolvemassbalancetimeseries.ThisperiodoftemporallycoincidentobservationswillgreatlyimprovetheelasticcorrectionforsolvingforGIA.ItisimportanttoemphasizethatGIAisatime-invarianttrend,andmoreover,thataGIAcorrectionisusedtocorrectsatelliteobservationsthatmonitorthestateoftheicesheet.GreatdiscrepanciesremaininourcurrentpredictionsofviscoelasticGIA[cf.,Lecavalieretal.,2014;Khanetal.,2016](seeError!Referencesourcenotfound.).

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Figure2.Relativesea-level-basedreconstruction(a;Lecavalieretal.,2014)andpredictionofpresent-dayupliftrate.GIAmodelwithGPS-basedupliftdata(b;Khanetal.,2016)andrevisedicehistoryreconstruction.Thediscrepancybetweenthetwopredictionsislargeenoughtobeanimpedimenttoproperlydiscriminatingbetweenalternativeicehistoryreconstructions.ReconciliationwillallowGIAmodelsthatproperlypredicttheGPStrendstobeusedinpaleoclimatemodels.

Inaddition,thecombinationofseismicimagingdataalongwithGPS-basedcrustalupliftdataenablesimprovedunderstandingofEarthstructureproperties.TheNSF-fundedGreenLandIceSheetmonitoringNetwork(GLISN)project(e.g.,Murrayetal.,2015)willprovideimprovedseismicdata.CombiningresultsofGLISNandGNETwillhelpbetterdefinebasalice-rockinteractions,lithosphericthickness,asthenosphericstructure,lateralheterogeneitiesintheEarth’scrustandprovideanimprovedbasisfortheheatfluxboundaryconditionusedinicesheetmodels[Rogozhinaetal.,2012].EachoftheseimagingfeaturesallowsbetterconstraintsforforwardmodelingtheGIAresponsetopastloadingfromicechanges.

Figure3:MapofcurrentstationswithGIAestimates.Currentstations(blackdots)andsuggestednewstations(yellowdots)areplacedtoconstrainGIA.

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AllGNETstations,shownasblackpointsinFigure3,arecurrentlyprovidingdatarelevanttoconstrainingGIA.Additionalstations,shownasyellowpointsinFigure3,arelocatedinplacesthatwouldenhanceourunderstandingofGIAinareashavingnotablespatialheterogeneityinsolidearthstructure.SeismicconstraintsfromprojectslikeGLISNbetterconstrainthestructureofthesolidearthparametersusedincrustalmotionmodelsofbothlongandshorttimescales.CombinationsofseismicandGPSgeodesycanbeimportantforconstrainingvariousimprovementsinEarthstructureandconstitutiveproperties[e.g.,Bosetal.,2015].

2.2 IceMassBalanceTherearetwoessentialphysicalcomponentsthatcontrolannualandinter-annualicemassbalance.Theseareinput,estimatedfromsurfacemassbalancemodels,andoutput,thatisgenerallycomputedfromicedrainagevelocitydata[Shepherdetal.,2012].Oneapproachtodeterminingtheongoingmassbalanceofanicesheetistoindependentlyestimateeachofthese,i.e.,changesinthe1)surfacemassbalanceand2)theicedischarge.Asecondapproachistoestimatetheinter-seasonalheightchangesovertheicesheet(estimatingthevolumechange)andfindanappropriatedensityscalingtodeterminemasschange.Athirdapproachistomeasurethegravitychangesfromspace.Thislatterapproachdeterminesmasschangesdirectly.Eachmethodhasadvantagesandpitfalls.Inwhatfollows,weaddresshowGNEThassupportedthegoalsofthesethreemethods,butdonotdiscussthemoreadvancedspeculationthatGNETmightofferawaytoadvancemassbalanceonitsown[e.g.Khanetal.,2010;Yangetal.,2013].

2.2.1 Surfacemassbalance

2.2.1.1 Background

Thesurfacemassbalance(SMB)referstothefactorsthatdeterminehowtheatmospherecandeliverrainandsnowtoreplenishthewatersupplyfortheGrIS,whileotherfactorsareablationbymeltingandrunoffwhilealsoaccountingforrefreezing.Greenlandalsohasnon-icesheetsurfaceswhichalsoparticipateinthemassbalancethataremeasuredbybothGRACE(directly)andbyGPScrustaldisplacements(indirectly).Figure4showsthemodelrepresentationofSMBforGreenlandthatcanbereconstructedfromthecurrentlymostsophisticatedSMBmodelrunningfrom1958-2015byvandenBroekeetal.[2016].IcemassbalanceisessentiallyestimatedasSMB-D,whereDistheicedischargeduetooutletglaciersexitingtothesurroundingocean.Thisisalsocalledtheinput-outputmethod(IOM)[Shepherdetal.,2012;Hurkmansetal.,2014].Technically,thisisnottheentiremassbalancesinceoneothercomponent,groundinglinemigration(GLM)alsomaycomeintoplay[Rosenauetal.,2013].ThemotivationtostudythetwocomponentsoftheIOM(SMBandD)isprovidedbytheimportantrelationshipoftheicesheetmassbalancetoongoingandfuturesea-levelrise[Hannaetal.,2013;vandenBroekeetal.,2016].SMBuncertaintiesaredifficulttoquantify,buttheyareoftenreportedat15-20%Tedescoetal.[2017],

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thoughlocallyandtemporallytheymaybemuchlarger[Schlegeletal.,2016;Alexanderetal.,2016].ChangesinSMBarenowaccountingforroughly2/3oftotalmassbalance[Enderlinetal.,2014;vandenBroekeetal.,2016],reducingtheuncertaintiesassociatedwithSMBestimatesisofconsiderablepracticalimportance.Inthissection,weaddressthevariouswaysinwhichGNETmighthelptoimproveSMBestimatesand/orgaugetheiruncertainty.Thesub-componentsofSMB,andtheimportanceofthesubtlephysicsthatcontroltheirbehaviorcannotbeunderemphasized.Forexample,ithasrecentlybeenarguedthatthenegativemassbalanceofGreenlandowestotheenergybalancehavingreachedatippingpoint,whereinthefirnlayerbegantoloseitscapabilitytorefreezenearsurfacemeltwater[Nöeletal.,2017].

Figure 4. Cumulative surface mass balance (SMB) for the full land area of Greenland (orange line),cumulativeicedischargeD(blueline)andresultingcumulativemassbalanceMBGreenland(redline).GRACEtimeseriesincluded(greyline)hasbeenoffsetby1000Gtforclarity.NotethatanincreaseinslopeforD(t),anddecreaseinslopeforSMB(t)eachacttopushthemassbalanceofGreenlandintoanegativestate[vandenBroekeetal.,2016].

ItisworthwhiletodisaggregatetheconstituentsofSMBandalsotheirspatialandtemporalvariability.Long-termmassstabilityofglaciercomplexesisuniversallydeterminedbyknowingthestabilityoftheannualaccumulationandablationzones.

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Figure5.Modelbasedannualvaluesfor1958-2012.25ofSMBconstituentsforGrIS:totalprecipitation(Ptot),melt(ME),runoff(RU),refreezing(RF)andrainfall(RA).Dashedlinesindicate1991–2015trends[vandenBroekeetal.,2016].

2.2.1.2 Theconnectionofincreasedmeltondischarge

AccumulationandablationzonesofanicesheetaredefinedastheareaswherethesignofannualSMBdiffer(positiveandnegative),respectively,withthetwozonesbeingseparatedbytheequilibriumlineatwhichSMB=0.InFigure5weshowthe5mostimportantconstituentsasreconstructedina regionalatmosphericclimate(RACMO2.3)SMBmodelfrom1958throughwinterof2012[vandenBroekeetal.,2016].Notethatmelting(ME)hasthestrongestestimatedslopeduring1991-2012,andalsohasthelargestexcursionsfromthenorm.Meltisalsoacriticalcomponentofchangesindischarge,D,aswatermovementtothebaseoftheicesheetcancauselubricationandglacierspeedup[alsoseeFigure4,andthechangesinslopeafter2005].Somewhatparadoxically,overtime,extensivemeltwateratthebasemayleadtosubsequentdecreaseinglacierspeed[vandeWaletal.,2008;Soleetal.,2011].Theseprocessesarenoteasilymodeled[e.g.,Dasetal.,2008;PimentelandFlowers,2011]andcanseeevolutionarycomplexitythatarepoorlypredictedinmodels[e.g.,Tedstoneetal.,2015].Observationsofice-flowenhancementbysuchlubricationindicatesabroad-scaleinfluenceasthemeltwaterspreadsoverthebed.Thepatternofspeedupisalsoquitecomplex,reflectingthecontrolbybottomtopographyatsub-kmscales,sedimententrainment,subglaciallakefillingandflushing,andconduitreorganizations[e.g.,HewittandFowler;2008;Joughinetal.,2013].Emphasisshouldbeplacedondatasetsofhighqualityandresolutioninspaceandtime.Duringthepastdecade,Arcticsummershavebeentrendingtowardearliermeltingonsetandextrememaximumheatandduration[CrawfordandSerreze,2015].ThisfactwasevidencedmostprofoundlyonGrISbythesummer2012summermelt.AninteractivewebsiteattheNationalSnowandIceDataCenter(NSIDC)currentlytracks

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theareaextentofmelting.Figure6showsasummaryofthemeltextentof2012(orangecurve)incomparisontothedailymedianvaluesandtheirtypicaldeviancefromthemedian.Theplotclearlyshowssummer2012tobeextraordinaryinarealextent.Wenotethattheareaisfairlyeasytomeasurefromspaceusingemissivityorscatterometry.However,thevolumeofmelt,itssubglacialroutingandtime-scaleforflushingfromthesystemispoorlyknown,atbest.ModelsthatderiveIOM,assume,generally,thatwaterwillrunthroughthesysteminstantaneously,sinceroutingmodelsarenotdevelopedforoperationalSMBmodels.Thismeansthatwhileannualerrorsmaystaybelow20-25%,duringanygivenweek,orevenmonth,themelt(ME),run-off(RU)andre-freeze(RF)maybeinerrorbymorethan100%.Asweseekfuturesea-levelriseestimates,thismaybecomeanincreasingproblem,andthereisadesiretogetabettercontrolonthespace-timeevolutionoftheseroutingsystems.

Figure6.MeltextentmeasuredfromspaceduringSpringtoFallmonthsforGrIS(1980-2010)median,withsingleyear2012showninorangeand2017inblue(fromNSDICinteractivewebsite).NotethatinJuly2012themeltextentquadruplesoverthe30-yearmedian.

Arcticsummershavebegunearlier,lastedlongerandreachedmoreextremesurfacetemperaturesduringthepasttwodecadesCrawfordandSerreze[2015].Asaconsequence,wearelikelytoseetheroleofME,anditsfeedbackonD,andthepartitioningofRUandRFcomeunderincreasedscrutinyforthepurposesofmakingcorrectmodel-basedprojectionsoffuturesea-levelrise.TypicalevaluationsofthequalityofMEinSMBmodelsarequantifiedthroughinter-comparisonofspace-based

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melt-daysobservedinsatelliteimagestothosecapturedinthereanalysismodel.Suchinter-comparisonisshowninFigure7.Hereweseethatmelt-daysmaybediscrepantby±15days(thesearedaysinwhichmodelandobservationonanygivenpixeldisagree).Whilethemodelsinter-compareinareasonableway,theuncertaintyinroutingpath,time-lagandultimatepercentofexpulsiontotheseaisnottested.

Figure7.SummaryofcomparisonoftwoSMBmodelsandsatellite-detectedannualmeanofthetotalnumberofmeltdays(toppanel;basedonspacebornepassivemicrowavedata).BottompanelshowsthedifferencebetweenmodelsandtheT19HmeltandExtXPGRalgorithmsusedforprocessingspace-baseddatasets[Fettweisetal.,2011].ThemeannumberofGrISpixelswhenRCMandthealgorithmsdetectmelt(RCM=SAT),whenRCMdetectsmeltbuttheretrievingalgorithmsdonot(RCM>SAT)andwhenRCMdoesnotdetectmeltwhilethealgorithmsdo,(RCM<SAT)isalsolistedasapercentageofthenumberofGrISpixels°—summerdays.[ReproducedfromFettweisetal.,2011].

2.2.1.3 SMBAnalysiswithGNETData

Regardlessofthemethodsofconstruction,SMBconstituentswillcontributetoanytimeseriesrepresentationonmass-bearinggridsformedbysummingestimatesofSMB.TemporalchangestototalmassbalanceareusuallydominatedbySMB.GNETcanbeusedtotestbothtypes(intra-seasonalandsecular)ofmasschange.Insomeareas,wecanactuallytestSMBestimatesbycomparingelasticdisplacementtimeseriescomputedfromthemassgridstotheactualdisplacementsmeasuredbyGNETasinarecentpaperbyLiuetal.[2017].Forexample,amajorsnowfallevent,orrapidsequenceofevents,shouldproduceapredictablesignalintheelastictimeseriesatnearbyGPSstations.However,forthelengthscalesknownforsuchevents,thesignalislikelynotdetectedabovethenoiselevelatdistantstations.Giventwosuchmajorsnow

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falleventsamonthapartinthesamearea,onecanroughlypredictthecorrespondingsignalsinthede-trendedelasticdeflectionscomputedfromdailyorweeklySMBgridstobesimilarlyreflectedinthede-trendedGPStimeseries.Intheory,anysustainedchangeinSMBshouldhaveacorrespondingsignaturerecordedintheGNETtimeseriesfromwhichaloadingmassmaybeinvertedfor.Inpractice,allgeophysicalsourcesofloadingofthesolidEarthmustbecarefullyaccountedfor,suchastheatmosphere,oceanandlargescaleglobalhydrology[vanDametal.,1997;Bevisetal.,2012;AdhikariandIvins.,2016;Liuetal.,2017]

2.2.1.4 UseofGNETDataforFundamentalImprovementinSMBModeling

OneobviouswaytoimproveSMBestimatesistoincreasethepredictionskillofhybridnumericalweatherandsnowmodels.WenotethatoneofthelargeuncertaintiesinFigure5isthetotalprecipitation.Coupledweather-snowmodelsarebuiltaroundhigh-resolution,regionalnumericalweatherprediction(NWP)modelsthatareembeddedwithinaglobalmodel.Typically,thisisanECMWFmodel,suchasitslatestglobalreanalysis,ERA-InterimorERA-5.

Figure8.Illustrationofanensembleanalysiswith(green)andwithout(yellow)minimizationonthestatisticalrangeofanyindividualatmosphericmodelvariable.Theexampleanalysisexampleillustratestheimportanceforthe“forecastcycle”.TheuseoftheGNSSphasedelayinformationinthemodelthatisdataassimilative(“4D-Var”)hasthepotentialtogreatlytightenhindcastmodelsthatarecriticalforSMBmodelslikeRACMOandMAR.The50+GNETstationsolutionsfortroposphereparameterscansupplydatarequiredforvariationalminimizationinfourdimensions.Itisimportanttonotethatrelativelygreaterimprovementoccursinmodelestimates(4DVartrajectories)asthedistancetoobservationsisreduced.[Baueretal.,2015].

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Coupledweather-snowmodelslikeRACMO2andMARarequitesophisticatedintheircaptureoftheappropriatephysics,aweaknessisthattheylackdirectassimilationofthemeteorologicalobservationsacquiredwithintheirmodeldomains.GlobalmodelssuchasthoseoftheECMWFdoassimilateallavailablemeteorologicaldata,includingGPSdelaydata,usingvariationaldataassimilationmethodsknownas4DVarandensemble4DVar(En4DVar)Baueretal.[2015].AgeneralillustrationisshowninFigure8.WeadvocatethatconsiderableimprovementinSMBcanberealizedbyupgradingcoupledweather-snowmodelcodesthroughimplementationof4DVarmodulesthatdirectlyassimilategroundincludingGPSdelay,upperairandsatelliteobservations.BelowwegiveasynopsisofthegainsshouldberealizedusingGNETdata:

• improvedpredictionskillintheNWMcomponent• morereliableboundaryconditionsforthemulti-layeredsnowmodel• improvedmodelsofthestateofthesnow/firn/icelayersbeneaththesurface.

Towardthesegoalsthefollowingactionsarerequired:

• RoutinegenerationandassimilationofGPSdelayparametersfromGNET• DemonstratetheimpactofassimilatingGPSdelaydataintohighresolution,

regionalNWMs• GPSdelayparametersshouldberoutinelyestimated,innearly-real-timeand

usedtodemonstratethatthedelaydataimprovesthewatervaporfieldsandpredictionsforprecipitation

• Addressissuesthatarepertinenttoweather-snowassimilation.Asmanyoftheseissuesmaybeobscuretothoseunfamiliartoatmosphericprofilinganditsconsequencesforoperationalmodels,weofferthefollowingsectiononthetechnique.

2.2.1.5 GNETZenithTotalDelay:UseforRegionalAtmosphericModels

ThegoalistouseGNETGPSobservationstogenerateandassimilatezenithtotaldelay(ZTD;BennittandJupp,2012)togreatlyimprovethepredictionofsurfacemassbalance(SMB)overtheicesheetproducedbyregionalatmosphericmodels,likeMAR,RACMO,orWRFthatshowlargedifferences(Figure7).ZTDobservationsimplicitlyyieldtheverticallyintegratedwatervaporamount(precipitablewater)nottheverticalprofileofwatervaporlikeradiosondes.However,watervaporisconcentratedinthelowerpartoftheatmosphere–moisturecontent(specifichumidity)typicallydecreasesexponentiallywithheight.ZTDisavailableat~10minuteintervalsifdesiredincontrasttothetwicedailyradiosondeascents,sopotentiallydetailedtemporalbehaviorofmoistairintrusionsintoGreenlandcanbecapturedfromZTDusage.ZTDvaluesaffectedbysensoricingandsnowaccumulationwillhavetobescreenedoutbyarobustqualitycontrolprocedure.TheaccuracyofZTDvaluesinnorthernGreenland

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duringwintermaybeanissuewithannualprecipitablewatervaluesbeing4-5mmthere(RobaskyandBromwich,1994),withmuchsmallervaluesinwinter,comparabletotheuncertaintyattachedtovaluesinferredtoZTD.AtmosphericmotionfieldsofcomparableaccuracytothewatervaporinformationprovidedbytheGPSZTDwillbeneeded.ThisisgoingtobeachallengeforGreenland,largelysurroundedbydatasparseocean.ThedrydelayderivablefromZTDcorrespondstosurfacepressuresotheseobservationsimprovetheatmosphericcirculationdepiction.OneapproachthatwillhelpistousetheGPSobservationsinconjunctionwiththeautomaticweatherstations(GC-Net)ontheicesheet.TheGNETandGC-Netshouldbeviewedasanintegratednetwork.Additionalcomplementarydeploymentsmaybeneeded.Also,allavailablenon-AWSsurfaceobservationswillbeneeded.ZTDvaluesmaybeasignificantchallengetoassimilateaccuratelyasthesitesarelocatedinthecomplexcoastalenvironmentforgeodeticapplicationsratherthanmeteorologywheresamplingofbroadscaleconditionsisdesired.Mahfoufetal.[2015]hasstudiedthechallengesofZTDassimilation.Thesearepartlyresolutiondependent.Modelgridspacingofafewkmmayberequiredtoresolvethenecessaryterraindetailsandmaynotbeadequateforallsites.Consequently,adetailedevaluationoftheGPSsitesisneededtodeterminethosebestsuitedtocharacterizingatmosphericbehavior.TheMahfoufetal.[2015]studyofEuropeisforacasewhereinsummerthunderstormsshowthatGPSZTDassimilationimprovespredictionoflargeprecipitationevents–morethan0.5cm(waterequivalent)perday.Greenlandisaverydifferentenvironment.TheeventsofconcernforGreenlandaresynopticscalecyclones,frontsandhurricaneremnantsthatresultinlargemoistureflowsintotheisland.Thegreatestimpactseemslikelytobefromsitesonthewest,southandeastcoastsofGreenlandprobablyinthewarmerpartoftheyear.Multi-layeredairflowsassociatedwithmoistureintrusionsasaresultoflow-levelterrainblockingwillcomplicateeffectiveuseofZTDvalues.ThequestionofanassimilationapproachusedtoincorporateZTDobservationsintoregionalatmosphericmodelsisbeingdebated,themuchmorecomplex4DVARversussimplerapproacheslike3DVARand/orensembleapproaches.Perhapsthemostcompellingargumentfor4DVARcomesfromMahfoufetal.[2015]where4DVAR,likethatusedbytheglobalARPEGEmodelwitha6-hourassimilationwindow,wouldinclude10timesmoreZTDobservations(orequivalent)thantheir3DVARapproach.However,thereareotherstrategiesforsimplerdataassimilationapproachestoincorporatemoreZTDobservations.Ofequal,orgreater,importanceisthecarewithwhichZTDvaluesneedtobetreatedtoachieveaccurateassimilation.OurrecommendationisthatdataforZTD(andGC-Netvalues)fromGreenlandbeassimilatedfrom2007onwardintotheArcticSystemReanalysisversion3(ASRv3)for1979-2020at15kmwith71verticallevels.Ithasapan-Arcticdomainandextendsfrom~45°NtotheNorthPole.Theprimaryfocusistoexamineextremeweatherand

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climateconditionsinthePanArctic.AsecondarygoalistoachievebettersurfacemassbalanceestimatesfortheGreenlandicesheetforthelast14ofthe42yearstobecoveredbyASRv3.ProspectsforusingtheHIRLAMregionalmodel(Christensenetal.,2007)andits4DVARassimilationcapabilitytoperformaveryhighresolution(gridspacingofafewkm)ofGreenlandfrom2000onwardisquitepromising.AlldatawithinthedomainwillbeassimilatedincludingGNETZTDalsowiththegoalofbettersurfacemassbalanceestimatesfortheicesheet.Tosummarizeweemphasizetwokeyrecommendationsinthiswhitepaper:

1. ZTDobservationsfromthecomprehensiveGNETarrayaroundGreenlandshowgreatpromiseforimprovingsurfacemassbalance(andfirndensity)estimatesfromregionalatmosphericmodels.Thesedatahavehardlybeenexaminedbytheatmosphericsciencecommunityandtheirspatialandtemporalbehaviorarenotwellcharacterized;andthisknowledgeisneededtomakeeffectiveuseoftheseobservationsviadataassimilationintoatmosphericmodels.TwoormoregraduatestudentsshouldbesupportedtoevaluateGNETZTDdata,theirassimilationintoregionalatmosphericmodels,andcomparisonswithsimulationsproducedwithMARandRACMO2andreanalysisresultsproducedbyASRversion2.

2. SupporttheuseofGNETZTDinregionalreanalysesencompassingGreenland,ASRv3andtheHIRLAM-basedeffort.

2.2.1.6 ChangesinGrISdrivenbybothglacierdischargeandSMB

Inpractice,crustalmotionsrespondtothefullsetofloadchangesthatinevitablyinvolvebothicedischargeandSMB.WhiletheSMBchangeshavegreateramplitudesandclearcoherenceandfidelityintheirseasonality,changesinDoccursimultaneously,althoughthesechangestendtobeoflowerfrequencyintheirtemporaldomains.Observationsoficedischargevariationsaregovernedbychangesinglacierspeedandgeometry[Ahlstrømetal.,2013;Moonetal.2014;Joughinetal.,2013].However,itisaninescapablefactthattheSMBMEandDconstituentsareintimatelycoupled[e.g.,Palmeretal.,2011;PimentelandFlowers,2011;Schlegeletal.,2013].TherearerelativelynewandpromisingdirectionsthatGNETmightcontributetodisentanglingtheinterrelationshipsofcoupledicedischargesystems.IftheGNETtimeseriescanbeappropriatelyfiltered,theyshouldcontainsequentialloadsignalresponsesthataredrivenbythecouplingofMEandD.Approximately60%oftheGPSreceiversinGNETarecapableofmakingcontributionstoourunderstandingofthedischargeofGrISglaciersandicestreams.Khanetal.[2010]andLiuetal.[2017]recentlydiscussedcasesinwhichGPSdatahavebeenusedtoplaceconstraintsonglacierdynamics.Additionalresearchhasinvestigatedglacier

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flowbyusingGPStrackersonmovingglacierice.HeredatafromGNETstationsplayacriticalroleasreferencebasestationsAndersenetal.[2010].ThebestbedrockGNETreceiversforthisobservationareeitherveryclosetotheglacierterminusbeingstudied,orexistaspairsofreceivers,whereinoneisclosetotheterminusoftheglacier,andoneisatadistancefarenoughawaytobeunaffectedbyglacierchanges.AsimilargeodeticstrategywasusedbyDietrichetal.[2007]forJakobshavnIsbræ.

InFigure9,stationSRMPhasaverytightradiusofsensitivitywithrespectto4adjacentoutletglaciers,whileUPVK,havingacoastalbedrocklocation,ismoresensitivetobroad-scaleSMBfeaturessuchasPtot(seeFigure5).AnewtreatmentofGNETdatasensitivitybyAdhikarietal.[2017]employedthe3-DcrustalmotionstostudycoupledSMB-DonseasonaltimescalesforeachGNETstation.OneexamplefortheRinkGlacierinwestcentralGreenlandusedtheGPS-determined3-Dbedrockmotiontounambiguouslyisolatemasstransportinasolitarywavethatoccursonlyduringtheintensemeltseasonsof2010and2012(seeFigures5and6).Someofthebasicconceptsofemploying3-DmotionsaredescribedbyWahretal.[2013].Inthelatterpapertwofeatureswerehighlighted:horizontalmotionsdropoffmorequicklythandoverticalmotionsasonemovesawayfromthewater-iceloadcenter.Additionally,horizontalmotiondatacontaindifferentdiagnosticinformationaboutthelocationoftheloadsource(seeFigure9).Forstudyingglacier-specificSMB-Dcouplingthelatterfeatureiscritical.AsubtlefeaturetobeextractedfromtheWahretal.[2013]example(Figure9)isthefactthatthereisaninherentdirectionalanisotropytothehorizontaldisplacements,andthesecanbeusedtolocate,undercertainconditions,thephysicallocationandsizeofthechangingwaterload.Thisisnotanewdiscovery,asSauberetal.[2000]haspointedthisoutinregardstochangesinglaciermassinAlaska,andHekietal.[2004]hasusedthedensenetworkinJapantomeasuremountainsnowloadchanges,withtheadvantageofthelaterstudybeingboththeexistenceofdenseGPSnetworkandknowledgeoftheapproximatelocationandtimingoftheload.

Figure9.AnalysisofanormalizedSMBcontributiontoverticalcrustaldisplacementforSRMP(thickline)andUPVK(thinline)stations.Theinsetshowsazoom-indistancerangeof0–100km.ThisstudyconcludedthatmodeledSMBloadingbasedonRACMO2.3actuallyincreasedtheannualvarianceoftheGPSresiduals,whichmadeitdifficulttoestimatecontributionsfromtheannualvariabilityofglacialdynamicstothetotalicemassbalance.ThestudyrevealsthepotentialuseofGNETonevaluationofSMBmodels.(FromLiuetal.,2017).

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GNETstations,beingoriginallyplacedtomeasureGIA,arenotnecessarilyclosetotherapidlychangingoutletglaciers.Forthepurposesofusing3-Dcrustalmotions,thestationsclosesttooutletglaciersarethemostpromisingforprovidingnewconstraints.Adhikarietal.[2017]usedallthestationsthathadprocessed3-Dtime-seriesavailableandderivedasensitivitygradientmap(seeFigure10)forthesestations.Themainprinciplefollowsfromthatusedingeophysicalmodeldataassimilationforadjointsystems[e.g.,Trompetal.,2005;Larouretal.,2016].Eachstationmaybeinfluencedbyon-landmasschangesinitsimmediatelocalarea,includingatmosphericloadingandloadingfromice-snow-watermasssystems.Thelatterchanges,whentheyarelargeinamplitude,dominantlyoccurwithintheoutletglaciersystems,yetthefullSMBloading,includingthatoccurringonbedrockmustbealsocomputed.ItispossiblethatstationsmayhaveallthreeoftheircrustaldisplacementssensitivetomasschangesassociatedwithME-Dcoupledevents,ortolocalRUorPEinduced-changes.Figure10shows33stationswithmappedsensitivitytomassloadinginthevicinityofeachoftheGNETstationreceiversthathave3-componentdisplacementdataavailable.Hereathree-colorwheelisused.Cooltohotcolorsrepresentprogressivelyhighersensitivityzonesforthestations,suchthatatleast1%ofmaximumdisplacementinducedbyaunitloadappliedoveraunitareainthesezoneswouldberecordedinone(blue),two(green)andthree(red)componentsofthedisplacementvector,respectively.Thesearereferredtoaszonesofinfluence(ZOI)byAdhikarietal.[2017],anditisimportanttounderstandthatthesefullyaccountforloadvariationsoccurringata2-kmscale,sothesecanshowwhereapotentiallyMElubricatedicestreammightquicklylooseorgainmass.ForthemarineterminatingRinkGlacier,the3-Dmotionscapturealargewavetransitingdown-glacierduringsummer-to-wintermonthsduringtheintensemeltyearof2012(seeFigures5,6).Figure11showsthetrajectoryofthehorizontaldisplacementvectoroftheRINKstationduringthedown-

Figure10.Apredictionof3-Dcrustalmotionsfromasimplesinglediskwaterloadremoval.(a)showsthevertical(positiveupward)andhorizontal(positiveawayfromthedisccenter).Crustaldisplacementsarecausedbyremovingauniformdiscloadofradius20kmhavinga1-mwaterthickness.Predictionsaregivenasafunctionofthedistancetothecenterofthedisc.Theverticaldot-dashedlinemarkstheedgeofthedisc.ResultsarecomputedusingseismologicallyrealisticEarthmodel.(b)Theratiooftheverticaltohorizontaldisplacementsshownin(a).Notethedifferentpositioninframe(a)ofthepeakvalueswithrespectto0.[Wahretal.,2013].

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glaciertransitoftheME-Dmassejectionduringsummertowinterof2010and2012.NotethatthereisnoevidenceofthewaveduringyearsofnominalME.

Verticalmotionstendtoreflectmassgainsandlossesoverlargerregions,whilehorizontaloversmallerones.ThisisreflectedattheRinkGlacierbytheexcellentcomparisonof3°GRACE-masconbasedloading,Schlegeletal.[2016](redlineinFig.12a)andthe90-daymeanoftheverticalGPStime-series.Horizontalmotionsshownoclearcorrelation(lowertwoframesinFigure12a),beingmoresensitivetothe10-50

Figure11.ZOIsfor33GNETstations.Thecentermapinthetoppanelshowsmeasuredicesurfacevelocities,locationsofall54GNETstations(redcircles),and5regionsofGreenland(blackboxesdisplayingZOIs.TheZOIsarecomputedusinghigh-resolution(~2km,seeAdhikarietal.,2016)gradientmaps.Blue,green,andredsignifytheprogressivelyhighsensitivityzonesforthecorrespondingGPSstations,suchthatatleast1%ofmaximumdisplacementinducedbyaunitloadappliedoveraunitareainthesezoneswouldberecordedinone,twoandthreecomponentsofthedisplacementvector,respectively.Foreachregion,stationIDsarelisted(fromNorthtoSouth)onlyforthosestationsthathaveZOIs.Majoroutletglaciersarealsoshown[Adhikarietal.,2017].

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kmscaleloadingeventsandmorerapidshiftsinloadingstructurethan3months.The2-DplotofhorizontalpositionisshowninFigure12b,forallyearsofRINKdata,withamplitudestandoutatthe0.5–1.0cmlevelduringtheintensemeltyears.DuringthetwoyearsofintensemeltthetrajectoryisnorthingandeastingfromaboutJunetoOctober,andthenreversinginlateFalltoearlySpringofthefollowingyear.ThespatialdistributionoftheMARSMBloadingisshownbythebackgroundcolorsoftheframes(c)and(d)ofFigure12.

2.2.1.7 OtherpossiblesurfacemassbalancestudiesbenefitingfromGNET

InadditiontothefamiliaruseofGNETstationsasGPSreferencepointsforon-icestudiesandthemotionoftheGNETstationstoinfericedischargeandchangesiniceloadingofthecrust,thereareanumberofas-yetunexploitedtopicsthatcouldbenefitfromGNETGPSdata.

1. TousethetimeseriesofhorizontalGPSstationpositionstodeterminemassloss

overanunknownareathatwouldaffectaGPSstationatacertaindistancefromthelocusofmassloss.

Figure12.MasstransportwavesdetectedinhorizontaldisplacementsatRINK.(a)Componentsofdetrendeddailycrustaldisplacement(circles)measuredatRINKstation,with90-dayrunningmeans(blacklines).Models(redlines)derivedfromGRACE-basedsurfaceloadingreconciletheobservationsofverticaldisplacement,notabledeviationsoccurduringintensemeltyears(grayshadows)forthehorizontalcomponents.(b)Map-viewtrajectoriesofhorizontals.(Largeonlyin2010and2012.)Circlesshowmonthlystationpositions.(c)PatternofmassdeficittransitingtheRinkGlacierduring2012summer.About-7.1mofmonthlythinningovertheoptimaldomain(bluefillwithintheglaciertrunkoutlinedbywhiteline)isrequiredtoexplainthemeanmonthlydisplacement(redarrow).Alsoplottedarethemagnitudesandfulcrumpositionsofmonthlymassanomalies(circles)thatsatisfythemonthlydisplacementdata(arrows).Adown-glacierpropagationof(negative)massanomalyrepresentsthenegativephaseofthemasstransportwave.MeanmonthlySMBloadsareshowninthebackground.(d)Sameas(c),butforthefall/mid-winterseasonthatfollows.Itrequires+2.8mmonthlythickeningovertheoptimaldomain(redfillwithintheglaciertrunk)toexplainthemeanmonthlydisplacement(bluearrow).(e)Summaryof(c)and(d),revealingthesolitaryseasonalwaveoficemasstransport.

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2. TousemultipathreflectionsofGPS/GNSSsignalstoobtainsurfaceparameters(snowdepth,oceantides).Larsonetal.[2009]providesaproof-of-conceptandSiegfriedetal.[submitted]presentareal-worldapplicationinAntarcticaofthismethodology.TheGNETarchiveprovidesameanstodothisonalargescale.

3. TouseGPSseismologytoprovideinformationaboutcalvingmechanicsresolvedathigh(~1Hz)frequencies[e.g.,Hollandetal.,2016]

4. TouseGPSonthesurfaceofmarineterminatingglacierstoobservegrounding/hingelineflexure.SuchstudieswouldbenefitfromfixedreferenceGPSstationssuchasGNET.

5. TouseburiedGPSantennatoobtainsnowwaterequivalentabovetheantennaemployingthewavepropagationprinciplesinsnow-ice,asforexampleoutlinedbyNievinskiandLarson(2014).

6. TofurthercoupleGPSobservationswithremotesensingtounderstandthenearsurfacerheologyofthecrustaroundGreenland.[e.g.,KucharandMilne,2015]

7. Examinetheinfluenceoftides(fromGPS-IR)oniceloadsandGPSresponse(e.g.,DeJaunetal.,2010).

Theabovelistofnewprojectswould,inseveralcases,requiretargeteddensificationoftheGNETnetwork.SuchadditionstoGNETwouldnecessarilybetheresultofproposal-drivenscienceinvestmentsfromNSF,NASAorotherfundingagency,andarethereforenotaprimaryrecommendationofthisreport.

2.2.2 SupportforInterpretationofAltimetryGNETcanalsohelptocalibrateorcorrectthealtimetryusedtoformSMBestimates.Althoughnotyetexploited,someICESattrackshaveverycloseapproachestoGNETstations.CrustalupliftmeasuredattheseGNETsitescouldbeusedtocorrecttheupliftofthesnowsurfacemeasuredbyICESat,allowinganassessmentofthechangeofthethicknessoftheicesheet.AsimilarstudycouldbedonewithICESat-2,followingits2018launch.Inaddition,thegroundtrackpatternofICESat-2isexpectedtobemuchdenserthanthatofICESat,expandingthenumberofGNETstationsthatcouldbeusedinaltimetryvalidation.StationsintheGNETnetworkareonexposedbedrockneartheicesheetperiphery,andrecordchangesintherocksurfaceheighttoafewmillimetersperyear.ICESat-2tracksinsomecaseswillnaturallypasswithinafewtensofmetersofaspecificstation,andinothercases,ICESat-2canbepointedtowithinafewtensofmetersofagivenGNETstation(thepointingcontrolofICESat-2being~40m).TheroughterrainandsteepslopesnearmanyoftheGNETstationswillbroadenthelaserpulsereturnofICESat-2comparedtothereturnoveraflatsurface,andshouldyieldelevationprecisiontowithinafewtensofcentimeters.Giventhelocallyroughterrain,anintermediateheightproductwouldbeneededinordertocomparethesub-centimeterprecisionfromGNETtothenearbyICESat-2measurements.Inordertobridgethisscalegap,GNETstationscouldbesurveyedusingLIDAR,stereophotography,and/oratotalstationsurvey.Withthesedata,itwillbepossibletodeterminelocationofthe

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GPSmonument,theGPSantenna(anditsphasecenter)relativetotherocksurfaceinwhichtheantennawasinstalled.Theselocalarea,geodeticgradeDEMs,withaperturesofhundredsofmetersorevenakilometer,wouldenablethegenerationofepoch-specificDEMsusingWorldViewsatelliteimageryadjustedtothelocalantennaandrocksurfaceDEM.TheWorldViewDEMcouldhaveanapertureof10km,forexample,andallowtheGNETstation’sfootprinttobeextendedontotheicesheet,characterizingtheheightofthesurfacecrossedbyICESat-2’strackwithinadayorsooftheICESat-2measurement.

2.2.3 SupportforGRACEandtheTotalMassBalanceTimeSeriesTheotherwayinwhichGNETcanimproveourestimatesofMBistosupplementthemasschangeestimatesinferredfromGRACEandGRACE-FollowOn.Improvementsaretwo-fold:GRACEhasverylowresolution(250kmx250kmattheverybest)andcannotdealwithcomplicatedcoastlines,snowcoveredareasandsmallglaciersvs.icesheet,etc.Secondly,GRACEmasschangedeterminationisheavilyreliantonanaccurate“GIAcorrection”thatcanonlybeprovidedbyacombinedmodelingandGPS-determinedverticalmotionretrievedfromthesecularcomponentofthetimeseries.GRACEmeasuresbothiceandrockmasschangesassociatedwithGIA.TheverticalrockmassfluxisestimatedusingaGIAmodel,andthisisremovedfromthetotalmasschangesensedbyGRACEtoisolatetheicemasschange.TheproblemswiththisGIAcorrectionarethat(1)itcanbelargerthantheresultingestimateoficemasschangeinsomeregions,and(2)thepotpourriofcurrentmodelspredictdifferentratesofGIA.TheonlywayoutofthisproblemistoimprovetheobservationalconstraintsonGIA,sothattheGIAmodelsarebetterconstrainedbyawiderrangeofobservations.ThiswasoneoftheoriginalgoalsofGNET,andtherecentworkbyKhanetal.[2016]hasdemonstratedthaterrorsintheGIAcorrectiontraditionallyusedbytheGRACEanalysisgroupshaveledtomajorerrorsinmasschangeestimatesforspecificdrainagebasins.

2.3 Ionosphere,TroposphereThe ionosphere and troposphere affect GNSS signals traveling from satellites toreceivers.The ionosphereextends fromabout50-1000kmabove theEarth’ssurfaceand acts as a dispersivemedium for GNSS signals. Thus, the phase delay of a radiosignalintheionosphereisfrequency-dependentanddeterminedbythenumberoffreeelectronsintheionosphere.Dual-frequencyGNSSobservationscanbeusedtoestimateionosphericdelayandalsodeterminethetotalelectroncontent(TEC)alongthesignalpath [MisraandEnge,2011;Komjathyetal.,2016].Processesaffecting the ionosphereincludespaceweathereffectsduetosolarandgeomagneticactivity,loweratmosphericcoupling(suchasstratosphericwarming,tidalsignatures),andnaturalandman-madehazards (tsunamis, earthquakes, rocket launches).Hence, themonitoring of TEChasuses ranging from space weather monitoring [Basu et al., 2001; Coster et al., 2003;CosterandKomjathy,2008], largeandsmall-scaleweathermonitoringsuchasstudiesof global stratospheric warming signatures Goncharenko et al. [2010] to tsunami

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trackingKomjathyetal.[2016],andthunderstormsLayetal.[2013],andevaluationofco-seismic[CalaisandMinister,1998]orco-eruptiveenergyrelease[Heki,2006].Spanning60-85° north latitude, GNETpresents a unique opportunity to observe thehigh-latitudeionospherewithpiercepointsrangingfromabout55-90°northlatitude.Ground-based GNSSmeasurements can provide a complete latitudinal profile of theArctic ionosphere. Geomagnetic processes are commonly observed with magneticstations that are co-located with GNSS stations in some places, and benefit fromsharingresourcesbetweenthetwostationtypes.Forseveralyears,GNEThasbeenusedforionosphericstudieswithafocusonstudiesof the polar cap and auroral oval processes via TEC and scintillation observations[Durgonicsetal.,2017].Routineprocessinggenerateshourly tosub-hourlyTECmapsover Greenland for near-real time application. However, insufficient data access tomost GNET stations limits this to only 10-15 stations, which impacts the spatialresolution of the results.While real-time streaming capabilities should be the long-term target for all sites, data access on a sub-hourly basis would be extremelybeneficial.Anincrease inresolutioncanbeachievedbyadditionof inlandstations inregions that move less than a few mm per day (this stability requirement can berelaxedforstationsthatonlyobservetheionosphere)andupgradingfromGPS-onlytomulti-GNSSconstellationobservationsthatincludeallavailablesatelliteconstellations.Samplingratesof1HzforTECand50-60Hzforscintillationstudiesareidealforsuchstudies. To minimize the bandwidth requirement for scintillation applications,scintillationindicescanbecalculatedlocallyandthentransmitted,instatedoftherawGNSSobservations.To fullyenable scienceduring strongscintillationconditions, therawdata shouldbe stored locally in a ring-buffer such that on-demanddownload ispossible.Thiswouldnotonlybenefitnavigationorpotentiallypowergridprotection,butenablestreamliningofthesciencesuchthatroutineanomalydetection,catalogingandanalysisispossible;ultimatelyexpandingionospherestudiesfromevent-basedtoacontinuum.The troposphere, ranging up to about 9 km high at the poles, is a non-dispersivemediumandassuchitsimpactonaradiosignalisfrequencyindependent(MisraandEnge, 2011). The effect of the troposphere on GNSS signal propagation can beseparatedintodryandwetphasedelays.TheformeriscausedbydrygasessuchasN2andO2,and the latter isdue towatervapor. InstandardGPSpositioningprocessing,these delays are corrected with models and obliquity mapping functions. Howevermaking use of observations from the global network of GNSS receivers and localmeasurements of pressure and temperature, the dry andwet terms of delay can bederived,andfromthem,parameterssuchasthezenithprecipitablewatercontentcanbeestimated[Bevisetal.,1992].Water vapor estimation should be a standard product for GNET and would benefitsatellite mission validation and calibration (e.g., improvements to the troposphericmodelsusedforICESat-2rangedelaycorrection).Thecurrentlowtemporal,buthighspatialresolutionMODISwatervaporestimatescanbemergedwithGNSSproductsto

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improve temporal resolution.While GNET’s spatial layout makes it difficult to fullycapture the heterogeneity of the troposphere, moving to full constellation GNSStracking at high data rateswill increase the number of troposphere piercing points.The network should be densified along the coast as most of the water vapor isexpected there. However, interior Greenland stations will allow tracking of watervaporintheinterior.Recentmeltingeventsthataffectedtheicesheetinteriorcanbeexpected to increase thewatervaporconcentration in theatmosphere.Forexample,thin, lowlevel liquidcloudswererecentlyshowntooccuroverGreenlandfrequentlyand enhanced the 2012melting event [Bennartzetal.,2013]. The additional interiorGNSSstationsproposedforionospherestudiescouldalsobenefitclimateresearchfortracking the atmospheric water content and, using GNSS-reflectometry Larsonetal.[2009],recordsnowheight/snowwatercontent.Meteorologyinstrumentationshouldbe included at all stations as these observations at high temporal resolution can beusedinvalidationeffortsofnumericalweathermodels.AlloftheseapplicationswouldbeacompletelynewuseofGNETdata.

2.4 LargescalegeodesyGNETGPSstationsplayanimportantroleinrealizationofaccurateandstableglobalinternationalreferencesthatcanbeusedforobservingchangesinthegeospheresuchaschangesintheicesheets,sealevel,theEarth’stectosphereandstrainfieldacrosstheNorthAmericaplate.Asdiscussedabove,GNETalsoservesasaconsistentreferenceforindividualsurveysandcampaignstherebylinkingsuchdatatogether.Theimportanceofanaccuratereliableinternationalreferenceframe(suchastheInternationalTerrestrialReferenceFrame;ITRF)forsupportingasustainabledevelopmentofinternationalsocietyandinternationalcollaborationhavebeenacknowledgedbytheUnitedNations(Resolution69/266),andallnationsbenefitfromwell-coordinatedreferenceframedetermination.

2.4.1 GNSScoordinatetimeseriesandreferenceframes.Thecomputationofcoordinatetimeseriesisafundamentalandnon-trivialtaskthatiscrucialforobtainingthebestresultsforsubsequenttimeseriesanalysis.InthecomputationofcoordinatetimeseriesfortheGNETstationsthereareissuesrelatedtohandlingofGPSclockandorbiterrors,ionosphericdelays,andrelatedtopics.Furthermore,suchcomputationsaredependentonthestabilityofthereferenceframe.Changesincomputationstrategiesandreferenceframeinstabilitiesanduncertaintiesaffecttheresultingcoordinatessubstantially.OftenthereferenceframeneedstoberedefinedwhencoordinatetimeseriesforGNETstationsarecomputed.SuchstudieshavebecomemorepowerfulastheGNSSsatellitenetworkhasexpanded(GPS,GLONASS,and/orGALILEO)andthecorrespondingprocessingstrategieshavematured.Thesedevelopmentsareongoingamongmanyresearchgroupsaroundtheworld.Inaddition,asthenumberandlocationofreferencestationsgloballyhasevolved,theselectionofstationsusedinsecuringastablerealizationofthereferenceframehasalsoevolved.

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Tosatisfythestringentrequirementsforreferenceframedetermination,potentialreferencestationsrequirecontinuousdataseriesfromgeodeticGNSSreceiversequippedwithchokeringantennasmountedonstablemonuments.Bydesign,GNETstationshavethatquality.TheobservablesfromallGNETstationsareconvertedtothestandardRINEXdataformat.TheGNETrawdatahasbeenarchivedastwosetsofdata:UNAVCOandLuxemburgdata.TheseareonlinethroughtheUNAVCOwebsite,andtheDTUSpaceGPSdata,whicharestoredatDTUSpaceandonlyavailableonrequest.Thedataportalsmaybeusedforpost-processingandestimationofcoordinatetimeseries,orusedasreferencestationsfortemporaryGPSstationinstallationsforawiderangeofapplicationsdescribedabove.InordertomaximizethebenefitoftheGNETnetworkforcoordinatesystemstudiesorreferenceframedetermination,stationsshouldlogGALILEOandGLONASSsignalsaswellasGPS.Furthermore,GNETstationsmayneedtobeaugmentedbyreferenceclocks,metsensors,andothergeophysicalequipmentsuchmagnetometers,radiationsensorsetc.

2.4.2 MakingITRFavailabletotheusers.Tosupportresearchanddevelopmentprojectsitisessentialthatthereferenceframeisrealizedlocallyandmadeaccessibletoend-users.Today,thereferenceframesarerealizedusingpermanentlyoperatingGNSSreferencestationsforwhichthereferencecoordinatesandGNSSdataareappliedforaccurateandconsistentpositioningofvehicles/platforms/payloadsmappingthequantityofinterest(e.g.icesheet/glaciergeometry,velocities,etc.).Currently,theSDFEandDTUareoperatingGNSSstationsinGreenlandtofulfillthistaskasthenationalauthoritytorealizenewITRFslocallyanddefinetransformationstotheofficialnationalframe.ThemainchallengestomakingITRFsavailabletousersarethatthefewon-linereferencestationsdonotprovidesufficientcoveragetodefineandmaintainasufficientlydetailedreferenceframeinallpartsofGreenlandtosupportresearchanddevelopmentprojectsandauthoritytasks,andthatdatafromallexistingreferencestationshasnotyetbeenmadeavailabletotheusersintherequiredrateandformat.ThistaskrequiresreferencecoordinatessupplementedbyhigherrateGNSSdatafromtheGNSSstations.Currently,theSDFEandDTUaresupportingthistaskasthenationalauthority.ReferencecoordinatesareavailableforallGNETstations.Onlyaminorsubsetofthestations,however,canprovidehigherratedata.GNETstationscouldpotentially,underanupgrade,providethereferencecoordinatesandhigherrateGNSSdataneededtosupportgroundandairborneoperationsinresearchanddevelopmentprojectsovertheentireisland.ByupgradingGNETstationswithhigherratereceiversandcommunicationlinksthegapscanbefilled.Furthermore,stationsmayneedtobeupgradedwithmultiGNSS(asopposedtoGPS-only)receivers.Optimally,near-real-timedatamaybeneeded.

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2.4.3 GNSSreflectometry.AnalysesofthereflectedGNSSsignalsshownewinterestingapplicationsofGNETdataforstudyingchangesinsealevelandsnowaccumulation.Bothapplicationsmayprovidevaluablesupplementstotheexistingobservationnetworks,especiallyinGreenlandwheredeploymentofsuchinstrumentationischallenging.OnechallengeinimplementingGNSSreflectometryforsealevelwork,isthatonlyafewstationsarelocatedneartheoceanscapableofobtainingsealevelinformation.Forsnowaccumulationwork,moststationsarelocatedonbedrockontheperipheryoftheisland,andassuchareoutsideofGreenland’saccumulationarea.However,valuableestimatesofsnowheightandmassofprecipitation(snow/firndensification)isimportanttoassessintheablationzone,thusaddingtoourknowledgeofSMBprocesses.Additionally,theseapplicationsrequirereflectionsatverylowanglethatarenormallyeliminatedfromthedatastreambyanelevationmask.

ThisisanewapplicationofGNSSrecentlypresentedatconferences,butatpresentonlyafewGNETstationscanbeused.However,applicationtoGNETdatamaybedevelopedusingexistingdataacquiredbythenetworkundercertainconditions.Forbestresults,stationslocatedclosetotheoceanmaybeusedformonitoringsealevelandsupporttidalstudiesandstudiesofsealevelrise.Stationslocatedcloseto,oractuallyon,theicesheetmaybeusedformonitoringchangesintheicesheetsandsupportstudiesoficesheetmassbalanceandofsnow/firnproperties.Tosupportthiswork,morestationsinclosevicinitytotheoceanandtotheicesheetareneeded.

3 DataManagement

3.1 GeneralBackgroundForbroaderuseofGNETrawdata,itisrecommendedthatalldatabemadeavailableonline,withaminimaldelay,asfarasfeasible(afewstationslikeStationNORDarenotroutinelydownloadedforhigh-ratedata).Withjusttwoagenciesinvolved,itisprobablyeasiesttomaintaintheseparateUNAVCOandDTUsites,aslongasdataformats,RINEXversionsandsitemaintenancelogsaresimilarandwelldocumented.Itisrecommendedthatbothofthedatacentersprovidedoinumbersfortheirrespectiverawdata,forpropercitation.Havingclearformatsandsimpleaccesstoalldatawouldbenefitnumerousotherapplicationsfornon-expertGPSusers,e.g.inthemeteorologydomain,andalsomakesurethattheGNETdataisusedmuchmorewidelyforlocalGreenlandsurveying,bothforsocietyuseandmining/resourcedevelopment(thisisessentiallynothappeningtoday,mainlybecauseoflacktrainingforlocalnon-expertusers).

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3.2 AncillaryDataAbsoluterepeatedgravitydata,observedirregularlybothbyULuxandDTUSpace,shouldsimilarlybeassigneddoi’s,andalsobepostedwithinashortintervaloftheobservations(ideally<1year)onDTUSpaceandULuxwebsite,respectively.Theurgencyforthiskindofdataislower,andonlyscienceoriented.Thefinalprocessedgravityvaluesshouldbeprovidedalongwithestimatedstandarderrors,tidalcorrections,operatorissues,hardwaretype,andverticalgravitygradientused(ifany).Itislikelynotrelevanttoincludeindividualdropdataandsimilar,butimprovedaccesstodatawouldstimulatemorescientificinvestigationsofGNETandgravitychanges,andthusbetterGIAunderstanding.

3.3 GenerationofTimeSeriesAcentralGNETwebpageshouldprovidethenecessarydatalinkstoalldata,bothrawandprocessedGPSdata,aswellasgravity.Itcouldalsolinktoother3rdpartyrelevantwebsites,suchasthenationalGreenlandmonitoringsitewww.promice.dkandotherGreenlanddataportals.Itwouldalsoberelevanttoincludesomeresourcematerialforlocalnon-expertusers.Inadditiontotherawdataaccessdescribedabove,processedGPSdataintheformoftimeseriesofstandardizedlatitude,longitudeandheightsate.g.30secresolutionarerecommendedforprovisionbyoneormore“official”dataprocessingcenters.IthasbeenamajorlimitingfactorforthewidespreaduseofGNETdatathatonlythe“raw”GPSdataareavailable.Processingsuchdataarebeyondthecapabilityofmanyusers,e.g.forglaciologistsandothergeoscientistsprimarilyinterestedinusingGNETfordirectGreenlandmassbalanceestimation.A“level2”GNETproductshouldberoutinelyprovidedbyoneormoredatacenters(e.g.OSU,UNevada,UNAVCOand/orDTUSpace),usingawell-describedanddocumentedmethodology.Onlybyprovidingthe“Level-2”coordinateproductwillabroaderusercommunityreallybeabletoutilizeGNET(andANET)dataforinnovativescience.TheavailabilityofL2-datawouldnourishnewscientificadvances,possiblylendinggreaterstrengthforannualmassbalance,especiallywheninterwovenwithothersatellitedata.WiththehightemporalresolutionofGNET,itwouldthenalsobepossibletoturnthisupsidedown,andimprovesatellitemonitoringoficesheetchangesbyGRACE,altimetryandiceflowvelocitymapping.Thereisaparalleltosatellitemissionshere:imaginethattheGRACEteamonlyprovidedLevel-1data(satelliterangeandrange-ratedata);thiswouldhaveseverelylimiteduseofGRACEdatatoahandfulofusers.ForGRACEthe“competition”inprovidingthebetterLevel-2databyimprovedmethodologyhasindeedhelpedtogeneratebetterLevel-2products,forthebenefitsofallusers.Tobeabletobenefitfromthesatellite/phonelinedatacommunicationtomostGNETstations,theLevel-2processingshouldideallybesetupinanearreal-timefashion,

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withalatencyoffewdays,tomatchthepresent6-daynear-realtimeprocessingofSentinel-1iceoutletglaciervelocitydata,alreadyrunningroutinelyaroundtheentireGreenlandicesheet(e.g.,http://cryoportal.enveo.at/).Also,thereferencesystemandtidal/atmosphericcorrectionsappliedshouldbeagreeduponbetweenallprocessingcenters,tothedegreepossible.TheLevel-2GNETdataprovidersshouldbeprovidedsecurelong-termfundingforrunningtheroutineprocessingservice,justlikeUniversityofTexas,JPL,andGFZ(Germany)doesforGRACE.Givingthe10-yearexperienceinanalysingGNETdatabykeyPI’s,thisshouldnotrequirelargeresources(comparede.g.totheGNETmaintenancecosts),asstandardprocessingtoolssuchasGIPSY,GAMITandBerneseareavailableandapplicationsfornetworkanalysisproven.TheLevel-2processingcouldalsobeaugmentedwithotherparameters,suchasionosphereandatmosphericrelatedprocessing,butthismightbeabiggerchallenge(andpotentiallyfewerusers)thanthe“clean”L2coordinateproducts.Derivedhigher-levelproducts,suchasimprovedGIAmodels,wouldstillbe“pure”scienceandkeptoutoftheL2-service,althoughlinksandrecommendationsshouldbeprovidedontheGNETdataportal/website.

3.4 DataStreamandArchivingFundedbyNSFDatafromtheNationalScienceFoundation(NSF)-fundedGNETnetworkisdownloadedeitherthroughTeleGreenlandADSLmodems(3sites)orthroughIridiumsatellitemodems(38sites).GNETmakesuseoftwodifferenttypesofIridiummodemstoconnecttotheremoteGPSreceivers.Onetypeinvolvesdialing29remotesitesfromanIridiumdownloadhubbasedinBoulder,Colorado.Thisdownloadhubconsistsofonebasemodemforapproximatelyevery6remotesites.ThesecondinvolvesusingIridiumRouter-BasedUnrestrictedDigitalInternetworkingConnectivitySolutions(RUDICS)modem,whichusesmulti-protocolMobileOriginated(MO)andMobileTerminated(MT)circuitswitcheddataconnectivity.InthecaseofRUDICSmodem,dataareroutedthroughanethernettunnelmaintainedatUNAVCO.TheRUDICSmodemprovidesahigherbandwidthconnection,andthuscanpassthroughhigherGPSdatarates.Themaintradeoffisthetwo-foldincreaseincostfortheRUDICSmodem.Thedial-upandRUDICSIridiummodemsrequireaserverandautomatedscriptstoaccesstheGPSdataandreceiverstateofhealthinformation.Onceconnected,ascriptlooksforthelastsuccessfullyarchivedfile,andproceedstoretrieveallremainingwholedatafiles.Iftheconnectionisinterrupted,thedownloadscriptwillreattempttheretrievalonthenextconnection,whichoftenoccursmultipletimesperday.Enoughbandwidthoverheadismaintainedtocatchupondatathatmighthavebeenmissedordelayedduetotechnicalissueswiththesite,regardlessofthedurationofthecommunicationsoutage.

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Rawdatainreceiver-specific,binarycompressedformatfilesdownloadedfromtheGPSreceiversthroughtheIridiumnetworkorADSLmodemsarepromptlyarchivedatUNAVCO.Additionally,therawdataareconvertedtoRINEX2.11andpostedasdailyfilesontheUNAVCOpublicftpserver,whichisaccessibleviaanonymousftp.DataqualitychecksareperformedwithTEQC[EsteyandMeertens,1999],andresultingsummaryfilesarearchivedalongwiththeobservationandnavigationfiles.OngoingdataprocessingisperformedbythePIteamatOhioStateUniversity,whichyieldspositionestimatesandotherancillaryinformation.UnliketheGeodesyAdvancingGeosciencesandEarthScope(GAGE)Facilityprocessingsystem,whichproducesdailyGNSSsolutionsfor>1700continuousstationsincludingtheNSF-fundedPlateBoundaryObservatory,TLALOCNet(Mexico),andCOCONet(panCaribbean),neitherdailypositionestimatesandtheirassociateduncertaintiesnorvelocityestimatesandtheiruncertaintiesareprovidedbyOSUtoUNAVCOforpublicationonitswebsite.IridiumserviceisprovidedatsubsidizedDepartmentofDefenseratestotheNSF.Iridiumcostsareapproximately$285/monthperdevice.Thiscostisnotcurrentlybasedondatausage,butinsteadisasetcosttoNSFthatisdividedequallyamongusers.TheDODratesarecurrentlyunderreviewandweanticipatechangesittheratestructureinthecomingmonths.

4 Bestconfigurationmovingforward

4.1 EvaluationofGNETstationsAnecessarydetailofthisreportistoestablishtherelativemeritsoftheGNETstationsastheyhaverecordedscientificdatasince2007.GiventhattheoriginalscientificgoalofGNETwastoretrievetheGIAsignalandimprovemodels,thismustbeoneofthemaincriteriaweusetowardaquantitativeevaluationofperformance.Additionally,asthedataclearlyhaveshown,apresent-daymassbalancecomponentispresentinthetimeseriesofcrustalmotionsrecordedateachofthestationsthatisusefulformakingconnectionstoSMBandD,orin-other-words,theongoingmassbalanceofcoastalGreenland[Jiangetal.,2010;Bevisetal.,2012].Inordertomakethiscomparisoninabothstraightforwardandintelligibleway,werelyheavilyonthreerecentanalysesofGIAandSMB-Dresponses.ApowerfulsourceofconstraintonGIAmodelscomesfromrelativesea-level(RSL)datasets,asthesesamplethecrustalandsea-levelresponsesatdifferenttimesduringtheGIAprocess.ArecentmodelofthistypeisthemodelbyLecavalieretal.[2014](seeFigure2a).AnalternativemodelforcomparisonisonethathasbeenheavilyinfluencesbytheGPSdatafromGNETbyKhanetal.[2016](Figure2b).WealsorelyontheZOIanalysisofAdhikarietal.[2017](Figure11).Weadoptthefollowingscoringtechniquefor40oftheGNETstationsandpresenttheseresultsonTable1.GIAisevaluatedintwoways.First,thestationhasanintrinsicrelativevalueinisolatingtheviscoelasticsignalbyitsproximitytocrustthatisbothfreefrompresent-dayicesheetchangesandnearplaceswherethepasticesheetadvancesoverland.Wetermthislattercategory“GIA-merit”.ForevaluationofastationsvalueinmeasuringSMB-D,weusetwocriteria:thelocationofthemappedZOI

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(Figure11)andthelocationofthestationwithrespecttoannualaveragesofoutletglaciervelocity(seeFigure11,inset).Thirdly,astationmayalsobeshowntobeofvalueinhelpingtosortoutdifferencesinRSLvs.GNET-weightedGIAmodelsolutions(Figures2and3).Thelaterevaluationcategoryweterm“GIA-discrepancy”,andthescoringsystemisslightlydifferentthanthatforGIA-meritorSMB-D.Fortheformer,scoresareeither0or2,foreachstation,whilethelattertwocanscore0,1and3.Ascoreof3inthelattercasesmeansthatthestationlacksambiguityinitssensitivity,andtherefore,meritinevaluatingthesignaturesrelatedtoeitherGIAortoSMB-D.Table1.Scoresfor40oftheexistingGNETstations.A‘*’indicatesthatadditionalinformationmaybefoundinBevis

etal.[2012]orAdhikarietal.[2017].

Northwest GIA-merit SMB-D GIA-discrepancyHRGD 1 3 0KMOR 3 0 2KAGZ 3 0 2SCBY 3 3 2THU2 3 0 2DSKG 3 3 0

Northeast KMPJ 3 0 0NORD 3 1 0NRSK 3 0 0JBLG* 3 0 0LBIB 1 3 0DMHN 3 0 0GROK 1 3 0LEFN 1 3 0

EastCentral DANE 3 0 0HMBG 1 3 0MSVG 3 1 0DGJG 1 3 0SCOR 3 0 0VFDG 1 3 0KUAQ 3 3 2MIK2 3 0 2

SouthGreenland KSNB 3 1 0KELY 3 0 0KULU 3 1 0KBUG 3 1 2KAPI 3 0 2HJOR 3 0 2TIMM 3 0 2NNVN 3 1 0SENU 3 1 0NUUK* 3 0 2

WestCentralGreenland KULL 3 0 2UPVK 1 3 2

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RINK 1 3 0QEQE 3 0 0AASI* 3 0 0ILUL* 3 1 0SRMP* 1 3 2KAGA 1 3 0

ForinterpretingthescoresshowninTable1,itisadvisedthatatotaladdedscoreisinappropriatetoemployforevaluation.Forexample,Adhikarietal.[2017]showedthemeritsofthesensitivityoftheRINKstationtoSMB-Dwithveryhighfidelityduringextrememeltyears,whereas,stationHMBGwouldhaveidenticaltotalscore,eventhoughnodemonstrationofhorizontalcrustalmotionsensitivityhasyetbeenfullycarriedout.Also,itmightbetemptingtoaddthetwoGIArelatedscores,butsomedifferencescouldbeduetolateralheterogeneityinmantleviscosity,orsomeotherpartoftheicehistory,thatiscurrentlyunderdevelopment[GlennMilne,personalcommunication,July2017].Obviously,thistableismosthelpfuloncedecisionsaremadeastothepreferredapproachtothefutureofGNET:toisolateSMB-Dononehand,orGIAontheother.TheultimatedecisionregardingtherelativeweightingofthescoresinTable1shouldbeguidedbytheacceptanceofviablescienceprojectsselectedbytheNationalScienceFoundation.

4.2 AddingstationstotheexistingnetworkManydisciplineswouldbenefitfromtheadditionofstationstothenetwork,buttheadditionwouldbetargeted.TheGlacialIsostaticAdjustmentcommunityhaspointedoutahandfulofkeylocationswheretheadditionofonlyafewnewstationswouldhelpconstrainGIAestimates.TheDynamicMassBalance(iceflow)communitywouldalsosuggesttargeteddensificationofthenetwork,butdrivenbyspecificsciencegoalsandlikelytargetingspecifickeyoutletglaciers.Thetroposphericandionosphericcommunitieswouldalsobenefitfromadensernetworkalongthecoast.Tobenefitreflectometrystudiesofsealevel,newstationswouldneedtobeclosertotheoceanthanexistingstations,allowingmultipathreflectionsfromtheoceansurface.Anotherdesireexpressedbymultiplegroupswastohavestationsaddedontheinlandice.Boththereflectometrycommunity(forstudiesofaccumulationandfirndensification)andthetropospheric/ionosphericcommunityexpressedthisdesire.Suchstationswouldposeuniquechallenges,dependingonwheretheywereplacedontheicesurface.Inparticular,stabilitywouldbeasignificantproblem.Intheablationzone,icewouldmeltoutfromunderneathanchorsandmonuments,increasingthechallenge-thishasbeenhandledwithvaryingdegreesofsuccessbyshorter-termcampaigngroups,butmaintainingalong-termstationundersuchconditionswouldbedifficult.Intheaccumulationzonetheproblemissimpler,butnolessaproblemtobesolved-inparticulartheantennawouldneedtoberaisedperiodicallytokeepaheadoftheaccumulatingsnow,andonallpartsoftheicesheet,theiceisflowing,resultinginsignificantchangesinthepositionofastationoverthecourseofevenoneyear.Thesechallengesaresignificantbutarenotimpossibletoovercome.

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4.3 Detailedsitecharacterizationofexistingsites,additionalmeasurementsSeveralgroupsexpressedadesireforamoredetailedsitecharacterizationofexisting(andfuture)GNETsites.Thesitecharacterizationsrangedfromdetailedtopographicalsurveyingviaterrestriallidarorstructure-from-motionphotography,toadditionalatmosphericandgeophysicalmeasurements.Gravitymeasurementsexistatsomesites,butexpandedmeasurementsatotherGNETsitesisdesirable.Finally,agreaterunderstandingofthemeteorologicalconditionsatthesiteswasdesired.Thiscouldtaketheformofanythingfromafull-scaleweatherstation(unlikely)toamicro-meteorologicalstation,someofwhichcanplugdirectlyintotheGPSloggerpoweranddatastreams.

4.4 ExpandedskycoverageanddataaccessforexistingsitesThereareseveralimprovementsthatcanbemadetothenetworkwithouttheneedforadditionalstationsormeasurementsatexistingstations,butwhichwilladdvaluetothedataformultipleusers.ManyofthegroupsexpressedthatlimitingthedatacollectiontotheGPSconstellationwasaproblem,andwantedGLONASSandGALLILEOcoverageaswell,makingthenetworktrulyGNSSandnotonlyGPS.Manyapplicationsincludingspaceweather,geodesy,andothersneedaccesstodatainnear-real-timeforittobeuseful,sorapidaccesstodataisessential.Inadditiontofastaccesstothedata,manyapplicationswouldbenefitfromhigher-ratedatathanwhatiscurrentlyavailablethroughGNET.Finally,traditionalGPSusagerequiresthatthesignalpathbetweensatelliteandgroundstationbeasinglestraightline,andanyinterferencewiththisisaproblem.Forthisreason,itiscommontolimitdatacollectiontoonlysatellitesthatareaboveacertainangleinthesky,reducingtheriskofmultipathreflections.Foruserswhoutilizethemultipathreflectionsforadded-valuedataproducts,however,theselow-anglemeasurementsareessential.Thus,removingthemaskingforlow-angledataisdesirable.

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