mediterranean sea atmospheric surface function data deliverable nr. 4€¦ · perseus deliverable...

MediterraneanSeaatmosphericsurfacefunctiondata

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The research leading to these results has received funding from the EuropeanCommunity's Seventh Framework Programme ([FP7/2007-2013]) under grantagreement n° 287600 – project PERSEUS (Policy-oriented marine EnvironmentalResearchfortheSouthernEuropeanSeas)Thematerialsinthisdocumentreflectonlytheauthor’sviewsandthattheEuropeanCommunityisnot liableforanyusethatmaybemadeoftheinformationcontainedtherein.Thisdeliverableshouldbereferencedasfollows:T. Lovato andM. Vichi, 2012.Mediterranean Sea atmospheric surface function data.PERSEUSProject.ISBN978-960-9798-21-1Tocontacttheauthors:TomasLovato(tomas.lovato@cmcc.it)

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ProjectFulltitle Policy-oriented marine Environmental Research

intheSouthernEUropeanSeas

ProjectAcronym PERSEUS

GrantAgreementNo. 287600

Coordinator Dr.E.Papathanassiou

Projectstartdateandduration 1stJanuary2012,48months

Projectwebsite www.perseus-net.eu

DeliverableNr. D4.1 DeliverableDate 31/03/2012

WorkPackageNo 4

WorkPackageTitle Developing integrated tools for environmentalassessment

Responsible M.VichiAuthors&

InstitutesAcronymsT.LovatoandM.Vichi(CMCC)

Status: Final(F) !

Draft(D) Reviseddraft(RV)

Disseminationlevel: Public(PU) !

Restrictedtootherprogramparticipants(PP)

Restricted to a groupspecifiedby the consortium(RE)

Confidential, only formembersof the consortium(CO)

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CONTENTSExecutivesummary/Abstract...............................................................................................................5Scope..................................................................................................................................................................5ATMOSPHERICdatafortheMediterraneanbasin.........................................................................6Generalinformation....................................................................................................................................6Datasetorganization...................................................................................................................................6APPENDIX.....................................................................................................................................................10A.1Biascorrectionofatmosphericboundaryconditions...................................................10A.2Howtoapplythecorrectionfields........................................................................................11A.3Estimationofatmosphericbiases..........................................................................................12

References....................................................................................................................................................14

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EXECUTIVESUMMARY/ABSTRACTTheactivityprovidestheatmosphericforcingfunctions(surfacefluxesofmomentum,heat and mass) necessary to run Southern European Sea basin scale and regionalmodels over theMSFD time horizon (1980-2020), accounting for both natural andindirectanthropogenicpressures.TheatmosphericdatarelyontheoutputoftheCMCC-CMclimatemodelthatispartofthetotheClimateModelIntercomparisonProject5.IncoordinationwiththeotherpartnersofWP4,asetofatmosphericvariableswereextractedfromtheclimatemodeldatarepositorytocomplywiththespecificsurfaceboundaryconditionsneededforeachmodelingapplication.Theatmospheric forcingdata for thebasinand regional scalesareavailableon theCMCCFTPsitefordistributionwithintheprojectWPs..

SCOPEThedeliverable4.1setthestagefortheapplicationofSouthernEuropeanSeabasinscaleandregionalmodels,bydistributingtheatmosphericforcingfunctionsneededtoprovidesurfaceboundaryconditionsforthemodellingactivities.WithregardstotheoverallobjectiveoftheWP4,thedistributionoftheatmosphericforcing is crucial as it provides a hindcast on the recent past climate and thepredictionofnearfutureconditions.Thisinformationwillserveasabasistoforcethenumericalmodelsdealingwithboththereconstructionofland-basedfluxestowardthecostalareasandtheinvestigationof ecosystemdynamics in theMediterraneanandBlackSeas.Moreover, the forcingfunctionswillcontributetothedefinitionofthephysicalgroundsfortheupgradeofexistingmodelstowardsanEcosystemEndtoEnd.Ultimately,theatmosphericdatasetrepresentsanessentialelementinthedefinitionof the MSFD descriptors, in particular for the hydrogeographical conditions of themarineenvironment(D7).

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ATMOSPHERICDATAFORTHEMEDITERRANEANBASIN

GeneralinformationThe reference Southern European Seas atmospheric forcing data for PERSEUSoriginatedfromtheEUprojectsCIRCEandCOMBINE,andtheyarepartoftheCMCCcontribution to the ClimateModel Intercomparison Project 5 (CMIP5, http://cmip-pcmdi.llnl.gov/cmip5). Data are available to partners for scientific use in theframeworkofthepresentprojectandcannotbedistributedtootherparties.The coupled climate model is CMCC-CM (http://www.cmcc.it/data-models/models/cmcc-cm), that implements the ECHAM5 atmospheric model on aGaussiangrid(T159)correspondingtoaresolutionofabout0.75°x0.75°(seedetailsinScoccimarroetal.,2011).The chosen future climate scenario is RCP8.5 (Reference Concentration Pathway,Meinshausenetal.,2011),thehighreferencescenariowithaprojectedincreaseoftheEarth radiative forcing of about 8.5Wm-2 at the end of this century (Fig. 1). It isimportant to note that all scenarios are somewhat equal in the target periodconsideredbyPERSEUS.ThePERSEUSforcingdatasetwasgeneratedfromtheoriginalGRIBarchivesbyusingtheCDOsoftware(www.mpimet.mpg.de/fileadmin/software/cdo)fortheextractionof specific information on a regular grid in the NetCDF format. Note that, all theoperations carried out to compose the final archives are recorded in the historyattributeofeachNetCDFfile.ThedataaredistributedtopartnersviaanFTPserversetupattheCMCCandaccessrequestshouldbeaddressedtoTomasLovato(tomas.lovato@cmcc.it).

DatasetorganizationTheatmosphericforcingdatafortheperiod1980-2020aredistributedintheoriginalspatialandtemporalresolution,whichensuresthemaximumflexibilityforthechoiceoftheoptimalinterpolationstrategyineachregionalapplication.

Dataarecontainedintotwosubfolders:

§ MED-HRT159,atmosphericdataovertheMediterraneanSea(seeFig.2),§ DRAIN-HRT159, meteorological fields for the Mediterranean drainage basin

(seeFig.3).

Bothfolderscontainmonthly filesoftheselectedvariables,whichareidentifiedbyareference number set in agreement with the ECMWF standard table 128(http://www.ecmwf.int/services/archive/d/parameters).Thetimehorizonwasfurthersplitintwoseparatedfolderstomaintainadistinctionbetween the data produced for the current (historical) and the future climatescenarios(RCP8.5).

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Table1containsthelistofalltheparametersdistributedfortheMediterraneanbasin,whileonlyasubsetofdata(surfacetemperature,totalandconvectiveprecipitation)wasmadeavailableforthecomputationofriverrunofftotheSES(D4.3),asspecifiedbythepartnersinvolvedinthisactivity.PleaseaddressanyfurtherquerytoTomasLovato(tomas.lovato@cmcc.it).

Table 1. Atmospheric forcing data available for the Mediterranean region.Parametersnotedwith*aretheonlyonesavailableinthedrainagebasinarchive.

ECMWFcode LongName Shortname Units

134 Surfacepressure Aps Pa

142* Largescaleprecipitation Aprl kg/m2s

143* Convectiveprecipitation Aprc kg/m2s

146 Sensibleheatflux ahfs W/m2

147 Latentheatflux ahfl W/m2

157 Relativehumidity rhumidity 0-1

164 Totalcloudcover aclcov 0-1

165 10mu-velocity u10 m/s

166 10mv-velocity v10 m/s

167 2mtemperature temp2 K

168 2mdewpointtemperature dew2 K

169* Surfacetemperature tsurf K

175 Surfacealbedo albedo (0-1)

176 NetsurfaceSWradiation srads W/m2

177 NetsurfaceLWradiation trads W/m2

182 Evaporation evap kg/m2s

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Figure1.GlobalAnthropogenicRadiativeForcingforthehighRCP8.5,themedium-

highRCP6,themedium-lowRCP4.5andthelowRCP3-PD.

Figure2.Airtemperatureatthesurface(°K)overtheMediterraneanSearegionin

January2000.

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Figure3.Airtemperatureatthesurface(°K)overtheMediterraneandrainagebasin

domainforJanuary2000.

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APPENDIXA.1BiascorrectionofatmosphericboundaryconditionsAs described in the Summary, the present deliverable focuses on the current andfuture atmospheric boundary conditions for further modeling activities in theframeworkofPERSEUSproject.The atmospheric fieldsmade available for themodeling activities within PERSEUSwere produced by the high-resolution coupled atmospheric and oceanic generalcirculation model CMCC-CM (Scoccimarro et al., 2011). In particular, the futureclimatevariabilityoftheCMCC-CMsimulationsaccountforbothRCP4.5andRCP8.5scenarios(detailsinMossetal.,2010).AnerroranalysisoftheCMCC-CMatmosphericdatawasperformedagainsttheERA-Interim reanalyses fields (Dee et al., 2011) to assess the presence of systematicerrors. In fact, a known limitation of the global atmospheric and oceanic generalcirculation models (AOGCM) is the occurrence of strong biases when focusing onspecific regional domains (see Berg et al., 2012; Cattiaux et al., 2013; Lafon et al.,2013).Theoverallcomparisonofthemonthlyclimatologiescomputedfortwodatasetoverthe period 1980-2010 indicates that remarkable differences affect the air and dewpoint temperature fields of the Southern European Seas area (see Fig. A.1). So, inorder to reduce thespatiotemporalbiasesof theair temperaturedata, a correctiontechnique was selected to adjust the CMCC-CM data or the atmospheric fieldsproduced by regional climatemodels,whichmake use of this dataset (e.g., COSMOCLM).The monthly bias correction of the temperature fields was achieved through thelinear scaling approach (see, e.g., Teutschbein and Seibert 2012). It consists insubtracting a corrective factor, calculated as the difference between simulated andobservedmonthlymeantemperature,tothemodeldata.Thecorrectedtemperaturevaluesareobtainedasfollows:

Tcorrm d( ) = Tsimm d( )− Tsim

m −Tobsm( )

(A.1)

where,fortheday d ofthemonthm , )(dT mcorr isthecorrectedvalue,Tsim

m (d) istheoriginallysimulateddailytemperature,

mobsT andTsim

marerespectivelytheobserved

andsimulatedmonthlymeantemperature,averagedoverareferenceperiod,forthemonth m . The procedure has to be performed on each grid node of the originalatmosphericfields.AdescriptionfortheestimatedbiasesisgiveninsectionA.3.

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a)

b)

Figure A.1. Time series of the difference between the CMCC-CM and ERA-Interim monthlyclimatologies over the Mediterranean Sea (a) and the Black Sea (b) for the period 1980-2010.Variables in the plot: SLP - sea level pressure (hPa); RH – relative humidity (%); TAIR – Airtemperatureat2m(°C);TDWP–DewPoint temperatureat2m(°C);WSPD–Windspeedmodule(m/s).PositivevaluesindicateanoverestimationoftheCMCC-CMdatawithrespecttoERA-InterimReanalyses.

A.2HowtoapplythecorrectionfieldsThemonthlycorrectionfieldsareprovidedinaseparatefile,astheyrepresentanaposteriorirevisionoftheoriginallydatamadeavailabletoallPERSEUSpartners.ItisstronglysuggestedtousetheavailablecorrectionfieldsthataredistributedinasingleNetCDF file via an FTP server set up at the CMCC. Access request should beaddressedtoTomasLovato(tomas.lovato@cmcc.it).Thefilecontainsa12monthsclimatologyofthebiasescomputedateachgridnodeofthe climate model for the reference period 1980-2010. In agreement with themethodology illustrated insectionA.1, thebiasrepresentsasystematicerrorof theclimatemodeland,thus,thecorrectionhastobeappliedtotheairtemperaturefieldsproducedbytheCMCC-CMmodelforbothcurrentclimateandscenariodata.Theavailablecorrectionfieldsarenamedaccordingtotheatmosphericvariabletheyapplies to,whichare identifiedby thenumberconventiondescribed in theECMWFGRIBAPItable(http://www.ecmwf.int/publications/manuals/d/gribapi/param/).

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Partnersshouldapplythecorrectionfieldbysubtractingthemonthlyairtemperaturebias from the fields of the respective month for all the user-selected years of theoriginal dataset. For example, a partner wants to correct the data of the airtemperature at 2m (var167) for the month of April 2015. This operation can beaccomplished by means of the following CDO commands(www.mpimet.mpg.de/fileadmin/software/cdo):cdo-monsub\

-selname,var167-selmon,mmData_yyyymm.nc\-setdate,yyyy-mm-01-selname,var167-selmon,mmbiasfile.nc\yyyymm_out.nc

where mm is the month (04 for April), yyyy the year (2015), -monsub is thesubtractionoperatorfromonthlyvalues,-selnameisusedtoselectaspecificvariable,-selmonallows to select a specificmonth as anumber, -setdate reset the time to aspecific value, Data_yyyymm.nc contains the 6-hourly simulated data, biasfile.nccontainsthecorrectionmonthlyfields,andout.nccontainsthecorrectedfieldsfortheuser-selectedvariable.Note that, the bias correction of the present deliverable addresses only to the airtemperature fields, while a methodology to correct also the 2m dew pointtemperatureisdescribedinsectionA.3.

A.3EstimationofatmosphericbiasesThe error analysis of the CMCC-CM atmospheric data over the Southern EuropeanSeas (Fig. A.1) showed remarkable differences with the ERA-Interim monthlyclimatologiesfortheperiod1980-2010.InthecaseoftheMediterraneanSea,theairtemperature data simulated with the CMCC-CM are remarkably underestimatedthroughouttheyear,withamaximumbiasof-3.5°CinJuly.Similarly,thedewpointtemperatureoftheairpresentsamaximumdifferenceof-3.7°CinAugust.Theothervariableshaveinsteadarelativelyuniformbias,withtheexceptionoftheSLPthatischaracterizedby larger errors in the springperiod.Nevertheless, themagnitude ofthe SLP bias is very small when compared with the mean values of the sea levelatmosphericpressureoverthedomain,whichisofabout1015hPa.Thepresentactivityfocusesonthetwotemperaturevariables,astheyarethemainatmosphericdriversinthestudyofclimatevariabilityscenarios.On the one hand, the estimation of the air temperature at 2m bias was computedimmediately as the difference between the CMCC-CM and ERA-Interim monthlyclimatologies.Ontheotherhand,thecomputationofthedewpointtemperaturebiascannot be achieved directly as in previous case, but it was reconstructed. As thedifferences in the relative humidity were not relevant (see Fig. A.1), the relativehumidity climatological field was used in combination with the unbiased airtemperaturetocalculateacorrecteddewpointtemperaturebymeansoftheMagnusformula(Lawrence,2005).

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InFig.A.2aredepictedtheestimatedbiasesfortheairtemperatureat2mforJanuaryand August, meant to be representative of the error distribution over theMediterraneanSea.

Figure A.2. Mean monthly biases of air temperature at 2 m between the ERA-InterimandCMCC-CMfor January(top)andAugust(bottom) in theperiod1980-2010.PositivevaluesindicateanoverestimationoftheCMCC-CMdatawithrespecttoERA-InterimReanalyses.

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ReferencesBerg,P.,Feldmann,H.,Panitz,H.-J.,2012:Biascorrectionofhighresolutionregionalclimatemodeldata.JournalofHydrology448-449,80-92.Cattiaux,J.,Douville,H.,Peings,Y.,2013:EuropeantemperaturesinCMIP5:originsofpresent-daybiasesandfutureuncertainties.ClimateDynamics,doi:10.1007/s00382-013-1731-y.Dee,D. P.,Uppala, S.M., Simmons,A. J., Berrisforda, P., Polia, P., Kobayashi, S., et al.2011: The ERA-Interim reanalysis: configuration and performance of the dataassimilationsystem.Quarterly Journalof theRoyalMeteorologicalSociety137,553-597.Lafon, T., Dadson, S., Buys, G., Prudhomme, C., 2013: Bias correction of dailyprecipitation simulated by a regional climate model: a comparison of methods,InternationalJournalofClimatology,33(6),1367-1381.Lawrence,M.G,2005:TheRelationshipbetweenRelativeHumidityandtheDewpointTemperature in Moist Air. A Simple Conversion and Applications. Bulletin of theAmericanMeteorologicalSociety86,225-233.Meinshausen,M.,S.J.Smith,K.V.Calvin,J.S.Daniel,M.L.T.Kainuma,J.-F.Lamarque,K.Matsumoto,S.A.Montzka,S.C.B.Raper,K.Riahi,A.M.Thomson,G. J.M.Veldersand D. van Vuuren (2011). "The RCP Greenhouse Gas Concentrations and theirExtension from 1765 to 2300." Climatic Change (Special Issue), DOI:10.1007/s10584-011-0156-zMoss,R.H.,Edmonds,J.A.,Hibbard,K.A.,Manning,M.R.,Rose,S.K.,etal.2010:Thenextgeneration of scenarios for climate change research and assessment. Nature 463,747-756.Scoccimarro,E.,S.Gualdi,A.Bellucci,A.Sanna,P.GiuseppeFogli,E.Manzini,M.Vichi,P.Oddo,andA.Navarra(2011),Effectsoftropicalcyclonesonoceanheattransportinahigh-resolution coupled general circulationmodel, J. Climate, 24(16), 4368–4384,10.1175/2011JCLI4104.1.