SWOT-GPMExploringthecomplementaritiesinaltimetryandrainfallmeasurementfrom

satellite,intropicalbasins.

PIs:MarielleGosset(IRD,GET,France)andDanielVila(INPE,CPTEC,Brazil)

coIs:AdrienParis,RodrigoPaïva,StephaneCalmant,SylvainBiancamaria,RomuloOliveira

1.Introduction&ObjectivesThe project falls into the general objective of combining satellite missions in order tooptimizetheinterestofeachmission.ThespecificobjectiveistouseRainfallestimationfromsatellite (GPMconstellation/Megha-Tropiquesmission) tobetterunderstandandpredict the river discharge variability as it will observed by SWOT. The topic isimportanttoimproveSWOTapplicationsin2ways:

i) With the combination of Geostationary Meteorological satellites and theGPMconstellation,rainfallinformationisgatheredwithveryhighspatialandtemporal resolution (hour / few kilometers) compared to the expectedsampling of the SWOTmission. This small scale information on rainfall –togetherwith hydrologicalmodeling –would be usefull to document andpotentiallypredictdischargevariabilitybetweenSWOToverpassesandhelpdevelopingvalueadded,highresolutionSWOTdischargeproducts

ii) ApromisinguseofSWOTdataisthroughhydrologicalmodels;forinstancethroughdataassimilationofSWOTderivedwaterheightsorSWOTderiveddischargeinhydrologicalmodels;Parisetal.havealsoderivedamethodtogenerate a SWOT discharge ‘first guess’ product using model/observationtrained height/discharge relationship. For both type of applications,understanding the uncertainties in the model based discharge andquantitativeinformationonthehydrologicalmodelerrorstructureiscrucial.Oneimportantsourceoferrorinhydrologicalsimulationsisthepropagationoftheerrorsfromtheforcingfields–likerainfall.

Thefirstcontributionofthisproposal-inlinkwithotherSWOTproposal-isinassessingsatellite rainfall product performances and uncertainties over several Tropical basins,understanding their scale dependence, analyzing the error structure (i.e. space-timecorrelation)and studyingtheirpropagationthroughhydrologicalmodels, fordischargesimulationinvarioushydro-meteorologicalcontext.TheprojectwillbenefitfromtheexperienceofCPTECinthedomainofrainfallestimationandvalidation,andrainfallerrorpropagationinBrazil(Falketal.2015aandb),andoftheFrenchMegha-Tropiques teamoverAfrica(Casseetal,2015,Rocaetal,2015).ThedatafromtheCHUVAcampaigns(CloudprocessesoftHemainprecipitationsystemsinBrazil:AcontribUtiontocloudresolvingmodelingandtotheGPM)andfromthefutureSOS (SistemadeObservaçaoeprevisaode tempoSevero) projectprovide radarbasedrainfallestimatesundermanyrainfallregimesinBrazil.InAfrica,highresolutiongaugenetworkandsomeradardatahasbeencollectedthroughtheMTGVeffort.ThisreferencedatasetsarequiteuniqueintheTropics.

2.ApproachTheworkwillbebasedon:-satelliterainfallproducts(andtheirassociatederrormodelwhenavailable)-highqualitygroundbasedobservationsindedicatedGVsites(AfricaandBrazil)-aHydrologicalmodel(MGB)setupinseveralbasinsofinterest.-Dischargedatafrominsituobservations(scarceandwhenavailable).-Altimetrydata fromobservations (current satellites)or simulations (toemulateSWOTdata,usingSWOTsimulatorinpre-launchperiod).Ensemblerainfieldsaccountingforuncertainties,developedinthepresentproposal,willfeed into the MGB model which has been already set up in several Brazilian basins,including the Amazon ( Paiva et al. 2013) and in 2major rivers in Africa : Congo andNiger.Modeloutputandthediscrepancieswithobservationwillbeanalyzed.Sensitivitystudieswillbecarriedouttoassesstheimpactofvarioustypeofuncertainties(fromtheforcing ; from the model ; from the altimetry data and specially its sampling ) in thepredicteddischarge.3.AnalysisandanticipatedresultsThe work will be focusing on a selection of Tropical basins that will be used asdemonstratorsof the interestof combiningsatellitealtimetry, satellite rainfallproductsandmodeltounderstand–andpredict-thedischarge.Wewillintendtounderstandandqualifybetterthespace-timescalesofprocesseswhichcanberesolvedgiventhevarioussourcesofuncertainties.3.1)Combiningaltimetryandrainfallestimationforfloodprediction.TheFigure1and2belowillustratessomeoftheexpectedoutputswiththeexampleoftheNigerRiver, inNiamey, anareaprone toheavy floodingdue to the combinationof twoeffects : slowrise theriver (detectablewithaltimetry)and fast responsedue tonearbyheavyrainfallevents(detectablewithsatelliterainfallanalysis).

Figure1 :TheNiger rivernearNiamey (red star) showing themainriverand the3 rightbanktributaries,upstreamofNiamey,thatareresponsibleforheavyfloodingearlyduringtherainyseason(July-september)beforethemainfloodpeakarrival(nov-december).Theseearly season floods –also called red floods- have been increasing drastically in the lastdecade(Casseetal.,2015,aandb).

Left : superimpositionof currentoperationalaltimetry tracks.Right : the future samplingwithSWOTII – detecting predicting the slow rise of the Niger river ahead of Niamey thanks tospatialaltimetry

Thebluelineillustratesaprediction(5daysahead)ofthedischargeinNiameyduetothepropagationofthemainpeakupstreamNiamey.II- Fast response of the Niger in Niamey to the heavy rainfall system propagatingthroughthearea.a)Daily rainfallmaps (fromTAPEERproduct) that triggered2peaksof the so called‘redflood’inNiameythatreachedafirsthistoricalrecordinAugust2012.

b) Zoom on the discharge simulated observed (black) or simulated (red) inNiameyduringthefloodperiod.ThefloodlevelinNiameyisdefinedbylocalauthoritiesatthe1700m3/slevel.

Figure 2 : Towards a prediction of Niger river flood in Niamey by combiningmonitoringof theupstreamdischargeby satellitealtimetryandsimulating thelocalrunoffduetoheavystormsnearNiamey.

3.2)Combiningaltimetryandrainfallestimation–consistencystudies.Checkingtheconsistencybetweenindependentsatellitemeasurementsofthewatercyclecanbeusedasanindirectvalidationmethod.Acorollaryoutcomeofthepresentworkistoexplorehowaltimetrymeasurementcanhelpassessingthebiasesinrainfallproductsandtheirstabilityintime,inregionswherenoraingaugesareavailable.ApreliminaryillustrationispresentedbelowovertheCongoriverregion.Parisetal.havedevelopedamethodtoderiveafirstguessdischargefromaltimetrydataanywherealonga river : themethod isbasedonderivingheight-discharge relationshipfrommeasured height and simulated discharge. The robustness of the derived height-discharge relationship is impacted by the quality of the rainfield used for forcing.Preliminarycomparisonsareshownabovewhen2differentforcingareusedtoderivetherelationship in the Congo river area. The left panel shows the results obtained usingTMPA3B32(v7–gaugeadjustedversion)andtherightpanelisfortheMegha-TropiquesmissionTAPEERproduct(Rocaetal.,2016)AltimetryHeight–DischargerelationshipsderivedfromMGBinCongo(Ubangui)for2differentsatelliterainfallproductsasforcinga/TMPA3B42b/TAPEER

Figure 3 : checking inter-annual consistency between the satelliteobservedheight(x)and thesatelliterainfallbasedsimulateddischarge(y) over theUbangui sub-basinoftheCongo.2a)forcingoftheMGBmodelbasedonTMPA3B42v7(gaugeadjusted)2b)forcingbasedonTAPEERproduct.Citedreferences:

FalckA.,MaggioniV.,TomasellaJ.,VilaD.andDinizF.,2015a:PropagationofSatellitePrecipitationUncertaintiesthroughaDistributedHydrologicModel:ACase

StudyintheTocantins-AraguaiaBasininBrazil.JournalofHydrology.10.1016/j.jhydrol.2015.05.042

FalckA.,Vila.D.TomassellaJ.andMaggioniV.,2015b,AvaliaçãodeumModelo

EstocásticodeErroMultidimensionalAplicadoaEstimativasdePrecipitaçãoporSatélite,RevistaBrasileiradeMeteorologia,RBMET-2014-0042

RocaR,BrogniezH,ChambonP,ChometteO,ClochéS,GossetME,MahfoufJ-F,RaberantoPandViltardN(2015)TheMegha-Tropiquesmission:areviewafterthreeyearsinorbit.Front.EarthSci.3:17.doi:10.3389/feart.2015.00017

Casse,C.,M.Gosset,C.Peugeot,V.Pedinotti,A.Boone,B.A.Tanimoun,B.Decharme,2015;PotentialofsatelliterainfallproductstopredictNigerRiverfloodeventsinNiamey;AtmosphericResearch,doi:10.1016/j.atmosres.2015.01.010.

Casse,C.andM.Gosset,2015:AnalysisofhydrologicalchangesandfloodincreaseinNiameybasedonthePERSIANN-CDRsatelliterainfallestimateandhydrologicalsimulationsoverthe1983–2013period.Proc.IAHS,92,1–7,2015proc-iahs.net/92/1/2015/OpenAccessdoi:10.5194/piahs-92-1-2015

Paiva,R.C.D.,W.Collischonn,M.-P.Bonnet,L.G.G.deGoncalves,S.Calmant,A.Getirana,andJ.SantosdaSilva(2013b),Assimilatinginsituandradaraltimetrydataintoalarge-scalehydrologic-hydrodynamicmodelforstreamflowforecastintheAmazon,Hydrol.EarthSyst.Sci.,17,2929–2946,doi:10.5194/hess-17-2929-2013.