climate change scenarios macedonia - report

7/29/2019 Climate Change Scenarios Macedonia - Report

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CLIMA T E C H A N G E S C E N A R I O S

F O R M A C E D O N I A

REVIEWOFMETHODOLOGY AND RESULTS

DOC.DR.KLEMENBERGANT

NOVA

GORICA,

SLOVENIA,

SEPTEMBER

2006

U N I V E R S I T Y O F N O V A G O R I C A C E N T R E F O R A T M O S P H E R I C R E S E A R C H


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TABLEOF CONTENTS

TABLEOFCONTENTS ..................................................................................................................................... 3

INTRODUCTION ............................................................................................................................................... 4

HUMANIMPACT

ON

CLIMATE................................................................................................................... 6

ESTIMATINGCLIMATERESPONSEONCHANGESINATMOSPHERICCOMPOSITION ...... 10

CLIMATECHANGEPROJECTIONSFORMACEDONIA ..................................................................... 13

PATTERNSCALINGTODIFFERENTEMISSIONSCENARIOS ...................................................... ..... 17DIRECTOUTPUTOFGENERALCIRCULATIONMODELS .................................................. ............... 17EMPIRICALDOWNSCALING ................................................... ........................................................... ..... 25SoutheasternandcentralpartofMacedonia/SubMediterranean............................................................ 27SouthernandsouthwesternpartofMacedonia/Continental .................................................................... 28EasternpartofMacedonia/Continental ..................................................................................................... 28NorthwesternpartofMacedonia/Alpine .................................................................................................. 28

UNCERTAINTIESINREGIONALCLIMATECHANGEPROJECTIONS .......................................... 45

GENERALCONCLUSSIONS ........................................................................................................................ 47

REFERENCES .................................................................................................................................................... 48


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INTRODUCTION

Several economicbranches, like agriculture, construction, energetic, tourism, etc., stronglydepend on weather and climate. Knowing the present and foreseeing the future climateconditions enables anoptimaluse of natural resources taking into consideration not only

economicbutalsoenvironmentalfriendlysolutionsinanaspirationforabetterstandardofliving.

Thereare several climatic factorsgoverning climate conditionsof selected region (e.g.,Piexoto & Oort, 1991): received solar radiation, physical and chemical properties of theatmosphere, surfaceproperties, land/seadistribution,atmosphericandoceanic circulation,and relief. As all the factors exhibit temporal and/or spatial variability, the climaticconditionsarenotconstantintimeand/orinspace.Ifwefocusonspecificregionandtimespanofafewcenturies,atleastanimpactofreliefandland/seadistributioncanbetreatedasconstant. On the other hand, changes in solar activity, volcanic eruptions, land use,anthropogenicemissionsofgreenhousegassesandaerosols,etc.,causechanges inclimatic

factorssuchasreceivedsolarradiation,atmosphericandsurfaceproperties,atmosphericandoceanic circulation.Variabilityof climatic factors results in climatevariability and changeevenwithinarelativelyshorttimespan.Somecausesforclimatevariabilityarenatural,butalso humankind plays an important if not a crucial role in changing the climate. Theanthropogenic impact on climate variability is especially evident since thebeginning ofindustrialera(e.g.,Houghtonetal.,2001)mostlythroughtheemissionsofgreenhousegassesandaerosolsintheatmosphereandthroughtheintensivelanduse.Adirectanthropogenicimpactonatmosphericcompositionandsurfacepropertiescanresult inan indirect impacton other climatic factors, like atmospheric and ocean circulation, which additionallycontributetoclimaticchanges.Anevidentsignofachangingclimate,thatcouldbeatleastto

some extend related to thehumankind, is the increased frequencyof extreme events (likefloods, draughts, heat waves, etc.) in last few decades and persistent positive trend intemperaturetimeseriesinthepreviousandthebeginningofthiscentury,practicallyontheentireglobe.

The increasedawarenessofclimatechangeasaserious threat tohumankindbroughtaneed for knowledge on how the climate might change in the future. Estimates of futureclimate change shouldbe valuable information for national governments, and plans formitigationandadaptationonclimatechangeshouldbeincludedinlongtermplanninganddevelopmentstrategies.Themainproblemwhentryingtoestimatethefutureclimateisthechaoticnatureofclimatesystem(Lorenz,1967),whichdoesnotenablethepredictabilityof

climateyearsahead.However,a longtermsystematicchange inboundaryconditions (e.g.change inatmospheric composition)may influence the climate statistics,and the resultinglongterm climatic response to such change may stillbe estimated (Benestad, 2003). Theproblem of unpredictability remains in the assumptions on future change inboundaryconditions. Several assumptions on future socioeconomic development and consequentemissionsand concentrationsofgreenhousegassesand sulfateaerosols in theatmospherehavebeenproposedbyIntergovernmentalPanelonClimateChange(IPCC)(Nakienovi etal.,2000).Suchassumptions,whichpresentthebasisforestimatingpotentialanthropogenicimpactonfutureclimate,introduceuncertaintyattheverybeginningofanyfutureclimatechangestudy.Furtherassumptionsabouttheimpactofchangesinatmosphericcomposition

onglobal,regionaloreven localclimateenlarge thecumulativeuncertainty inquantitativeclimatechangeestimates.Asprojectionsofclimatechangeareoftenusedinimpactstudies


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(e.g., Buma & Dehn, 2000), additional uncertainty arises from the estimation of climatechange impact.Due to theoveralluncertainty,projectionsof futureclimatechangeand itsimpacts areusually related to the term scenario1andnot to the termprediction.Climatechangescenariosonnationalorregional levelarecommonlybasedonclimatesimulationswithGCMsandregionalorlocalprojectionsoftheirresultswithempiricaldownscaling(e.g.Benestad,2002).

Thegoalofthepresentstudyistoprovideplausibleestimatesofregionalfutureclimatechange for Macedonia, which could be used in impact studies and as a base for thepreparation of strategies for mitigation and adaptation to climate change. Additionally,uncertaintiesrelatedtosuchscenariosarediscussed.

Thepresentreportstartswiththeillustrativedescriptionofanthropogenicroleinclimatechange together with the description of future emission and concentration scenarios forgreenhouse gasses and sulfate aerosols that are considered in the estimation of climatechange on the region of Macedonia. This is followedby a short description of GeneralCirculationModels(GCMs),acommontoolfortheestimationofclimatesystemresponsetothechangesinatmosphericcomposition.Methodologicalpartofthereportincludesashortdescriptionofdataandmethodsused for thedevelopmentofclimatechangescenarios forMacedonia.EmphasizeisgiventotheempiricaldownscalingofGCMresultstoMacedonianregion. The results for regional climate changeprojections for Macedoniabasedon directGCMoutputareshowninthemainpartofthisreportbesidesempiricaldownscalingresultsforseveralregionsofMacedonia.AlltheresultsaresummarizedintablesthatcanbeusedasinformativeclimatechangescenariosforMacedoniafor21stcentury,separatelyfordifferentseasons of theyear. Expected changes arepresented with regards to the reference period19611990. The report concludes with a general description of uncertainties related to theregionalclimatechangescenarios.

1SCENARIO:Aplausibleandoftensimplifieddescriptionofhowthefuturemaydevelop,basedonacoherentandinternallyconsistentsetofassumptionsaboutdrivingforcesandkeyrelationships.Scenariosmaybederived

fromprojections,butareoftenbasedonadditionalinformationfromothersources,sometimescombinedwithanarrativestoryline(Houghtonetal.,2001).


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HUMAN IMPACTON CLIMATE

Theclimatehasalwaysperformedsomenaturalvariabilityindependentonhumanactivities.On the other hand, since early 1800s, the anthropogenic impact on climate has increased,mostlyduetotheemissionsofgreenhousegassesanddifferentaerosols.Relatedchangesin

atmospheric concentrations of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O),andsulfateaerosolsareshowninFigure1.

Figure 1: Observed changes in atmospheric concentrations of carbon dioxide, methane, nitrous oxide andsulphateaerosols(Houghtonetal.,2001).

Increasedatmosphericconcentrationsofgreenhousegassesresultinintensifiedabsorptionoflongwaveradiationcomingfromthesurfacetotheatmosphere. Consequently,thereisanincreaseinradiativeforcingofgreenhousegassescausingtheenhancedgreenhouseeffect.On

the other hand, aerosols have mostly cooling effect due to the direct impact on thetransmission of solar radiation through the atmosphere, and due to the indirect impactthroughtheirroleinthecloudformation. Estimatesofnaturalandanthropogenicforcingonglobal temperature,asan indicatorofglobal climate change, are shownonFigure2. It isevidentthattheincreaseinglobaltemperatureafter1970,asanobviousindexoftheglobalclimatechange,cannotbeexplainedwithouttakingintoaccounttheanthropogenicforcing.Thehumanroleinrecentclimatechange,viatheemissionsofgreenhousegasses,cannotbeneglected and is expected tobe even more pronounced in the future. To estimate theintensityofhumanimpactonfutureclimateknowledgeonfutureemissionsofgreenhousegassesandaerosolsisneeded.


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Figure2.Comparisonofobserved(redline)andmodeled(grayrange)variabilityofglobaltemperature.Changesin atmospheric concentrations ofgreenhousegasses and sulfate aerosols were considered in case ofmodeledvariabilitywith regards tothenatural (upper leftplot)andanthropogenic sources (upperrightplot), asalsowithregardstoboth(lowerplot)(Houghtonetal.,2001).

As the future is not predictable, but can only be foreseen with regard to presentknowledge, IPCC has developed several socioeconomic storylines that might beaccomplishedinthe21stcentury(Houghtonetal.,2001).Suchstorylinesrepresentthebasisfor emission scenarios reported in the Special Report on Emissions Scenarios (SRES)

(Nakienovi etal.,2000).TheA1storylineandscenariofamilydescribesafutureworldofvery rapid economic growth, global population that peaks in midcentury and declinesthereafter, and the rapid introduction of new and more efficient technologies. Majorunderlyingthemesareconvergenceamongregions,capacitybuildingandincreasedculturaland social interactions, with a substantial reduction in regional differences in per capitaincome. The A1 scenario family develops into three groups that describe alternativedirections of technological change in the energy system. The three A1 groups aredistinguishedby their technological emphasis: fossil intensive (A1FI), nonfossil energysources (A1T),orabalanceacrossallsources (A1B).TheA2 storylineandscenario familydescribes a very heterogeneous world. The underlying theme is self reliance and

preservationoflocalidentities.Fertilitypatternsacrossregionsconvergeveryslowly,whichresultsincontinuouslyincreasingpopulation.Economicdevelopmentisprimarilyregionallyoriented andper capita economicgrowthand technological changemore fragmentedandslower thanother storylines.TheB1 storylineand scenario familydescribes a convergentworldwiththesameglobalpopulation,thatpeaksinmidcenturyanddeclinesthereafter,asin the A1 storyline,but with rapid change in economic structures toward a service andinformationeconomy,withreductionsinmaterialintensityandtheintroductionofcleanandresourceefficient technologies.Theemphasis isonglobalsolutionstoeconomic,socialandenvironmental sustainability, including improved equity,but without additional climateinitiatives.TheB2storylineandscenariofamilydescribesaworldinwhichtheemphasisis

on local solutions to economic, socialand environmental sustainability. It isaworldwithcontinuously increasingglobalpopulation,atarate lower thanA2, intermediate levelsof


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economicdevelopment,andlessrapidandmorediversetechnologicalchangethanintheA1andB1storylines.Whilethescenarioisalsoorientedtowardsenvironmentalprotectionandsocialequity,itfocusesonlocalandregionallevels.QualitativedirectionsofSRESscenariosfordifferentindicatorsareshowninFigure3.

Figure3:QualitativedirectionsofSRESscenariosfordifferentindicatorsin21stcentury(Metzetal.,2001).

Figure4:Emissionandconcentrationscenariosforsomeofgreenhousegasses(CO2,CH4 inN2O)andsulfurdioxide/sulfateaerosolsin21stcentury(Houghtonetal.,2001).


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Emissionsofsomegreenhousegasses(CO2,CH4inN2O)andsulfurdioxide(SO2),expectedto followdifferent socioeconomicdevelopments,arepresented inFigure4. It canbe seenthatSRESscenarioscan lead toverydifferentconcentrationsofCO2andothergreenhousegasses.Noneofthestorylinesandrelatedemission/concentrationscenariosissupposedtobemore credible for the future than theothers.Because thewide rangeofpossible emissionscenarios together with related changes in the atmospheric concentrations of greenhousegasses and sulfate aerosols present crucial information in future climate simulations withGCMs, it introduces a large amount of uncertainty at the verybeginning of any futureclimatechangestudy.


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ESTIMATINGCLIMATE RESPONSEON CHANGESIN ATMOSPHERIC

COMPOSITION

The GCMs are one of the most important tools in the studies of climate variability andclimate change (Zorita&Storch,1999;Houghton eta..,2001),despite some skepticismon

theirreliability(e.g.,Schackleyetal.,1998;Idso,1998).These3Dnumericalmodelsarestateoftheartnumerical coupledmodels that includeadescriptionofmainphysical, chemicalandbiological processes in the atmosphere, ocean, polar ice and land surface as also theinteractionsamongthem(McGuffie&HandersonSellers,1997).

AcomparisonbetweenGCMsimulation resultsandobservationsofpastclimateshowgoodagreementinthedescriptionoflargescaleclimatephenomena(Houghtonetal.,2001).Areliabilityoftheirresultsismuchlowerinaregionalorevenalocalscale. Thefactthatthemodels do a crediblejob on the globalscale and fail on the regionalscale seems tobe acontradiction.However,theglobalclimateistoagreatextenttheresponsetothedifferentialsolarforcing,theearthrotation,andthelargescalestructureoftheearthssurface(land/sea

distribution,topography).Theregionalclimates,on theotherhand,aretheresponseoftheglobal climate to regional details (topography, vegetation, soil moisture, etc.) that are notcapturedwellinGCMs.ThespatialresolutionofGCMsprovidesaninadequatedescriptionofthestructureoftheEarthsurface.Theland/seadistributionisheavilysmearedoutandthemountainsappearasbroadflathills.Relatedtothemodelresolutionisalsoaproblemoftherepresentationof thesubgridscaleprocesses,suchascloud formation,rainfall, infiltration,evaporation,runoff,etc.ThesehavetobeparameterizedinGCMsandwithincreasingmodelresolution more andmoreprocesses canbe explicitly represented,butmanyof them stilloccur at too small scales tobe realistically modeled in the present and probably nextgeneration of climate models (Zorita & Storch, 1999).The horizontal resolution of GCMs,

whose results are currently available to the wide science community (e.g. see IPCC DataDistributionCentre athttp://ipccddc.cru.uea.ac.uk/) isusually 22ormore (Crane et al.,2002).The subgridprocessesnotwelldescribedby the GCMs are actually thosewith thegreatestecologicalorsocietalimpact,sincetheystronglyaffectthelocalclimateatthescalesof thehuman and ecological environment (Zorita& Storch, 1999). As the skilful scale ofGCMsisdefinedasatleast8gridpointdistances(e.g.Grotch&MacCracken,1991;Storchetal.,1993),thedirectuseofGCMresultsinimpactstudiesisverylimited.

Despite relatively low horizontal resolution, simulations with GCMs are stillcomputationally very demanding, especially when considering a large time span. That iswhyfutureclimatesimulationsarecommonlybasedonlyonfewrepresentativesofemission

scenariosandarescaledafterwardsalsototheotherscenariogroups.Inthelastassessmentreport (Houghton et al., 2001), IPCC has used the resultsof simulations withnineGCMsbased on SRES A2 and B2 marker scenarios, which were additionally scaled to the othermarker emission scenarios SRES A1T, A1Fl, A1B and B1 usingpattern scalingmethod(Mitchell, 2003). This method uses the estimates of global warming under different SRESscenarios, which were estimated with MAGICC2 model. The expected range of globaltemperature change under different emission scenarios for 21st century, using differentGCMs,isshowninFigure5.

2ThecurentversionofthemodeltogetherwiththesoftwarefordevelopingclimatechangeSCENGENsiavalable

freeathttp://www.cgd.ucar.edu/cas/wigley/magicc/.


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Figure5:TheglobalmeantemperatureprojectionsforthesixillustrativeSRESscenariosusingasimpleclimatemodeltunedtoanumberofcomplexmodelswitharangeofclimatesensitivities.ThedarkershadingrepresentstheenvelopeofthefullsetofthirtyfiveSRESscenariosusingtheaverageofthemodelresults(meanclimate

sensitivity is 2.8C).The lighter shading is the envelope based on all ninemodelprojections (with climatesensitivityintherange1.7to4.2C).Thebarsshow,foreachofthesixillustrativeSRESscenarios,therangeofsimplemodelresultsin2100forthesevenAOGCMmodeltunings(Houghtonetal.,2001).

Projectionsof changes inglobal temperature (Figure 5) andotherglobal climatevariablesgiveasusaroughinsightintoexpectedclimatechangeinfuture.Asthespatialpatternsofclimatechangearenotexpectedtobeuniformontheentireglobe,estimatesofsuchpatternswouldbeofmorevaluableinformationthanglobalaverages. TheGCMresultscanbeusedtoestimate thespatialpatternsofclimatechange ina largescale.Unfortunately, their lowhorizontal resolution limits the direct use of GCM results in impact studies (e.g. for

agriculture, forestry,energetic,waterresources, tourism),because the information inmuchmore detailed spatial scale is needed (Dubrovsky, 1997; Benestad, 2001; Houghton et al.,2001).ItwillprobablybedecadesbeforeGCMswillbeable toresolvescalessmallenoughformost climate change impact studies.That iswhy translationof theGCMsoutput intoreliableregionalandlocalscaleinformationremainsoneofthemostdifficultproblemsfacedbyclimatologist(Craneetal.,2002).Thechallengeishowtobridgethegapbetweenlargescale,wheretheinformationfromGCMsisavailable,andregionalorlocalscale,wheretheinformationforimpactstudiesisneeded.

Asbridging thisgap isamatterofdifferentspatialscales, letusdefine first thehorizontal

scalesusedintheinterpretationofGCMresults(Storchetal.,1993),asalsocommonlyusedinthisreport:

minimumscale: adistancebetweenneighboringgridpointsofGCM; skillfulscale: ascale,whereGCMresultscontainemployableinformation largescale: ascalelargerthanskillfulscale; regionalscale: ascalelowerthanskilfulscale; localscale: ascaleofasinglelocation; globalscale: ascaleoftheentireglobe.

Minimumscale corresponds to the horizontal resolution of GCMs and is for the models,whichresultsareavailableatIPCCDataDistributionCentre3,between2in5.Theskilful

3PubliclyavailableatwebpagesofIPCCDataDistributionCentrehttp://ipccddc.cru.uea.ac.uk/


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scaleofGCMsshouldcontainatleasteightgridpointdistances(Storchetal.,1993;Storch,1995;Benestad,2001).

Themain taskof thepresentstudy is tobridge thegapbetween largescale,wherewehave information of expected climate change and climate variability from GCMs, andregionalorlocalscale,coveringdifferentclimaticregionsofMacedonia,whereweneedtheinformation for vulnerability and assessment studies. For the information on present andfuturelargescaleclimatevariability,theresultsoffourGCMs3willbeusedtogetherwiththeNCEP/NCAR reanalysis (Kalnay et al., 1996; Kistler et al., 2001) data representing theobserved largescale climate variability (Table 1). The four GCMs are Australian coupledGCM CSIRO/Mk2 developed by the Commonwealth Scientific and Industrial ResearchOrganization(Godron&OFarrel,1997), theUKcoupledGCMUKMO/HadCM3developedbytheHadleyCentreofUnitedKingdomMeteorologicalOffice(Popeetal.,2;Gordonetal.,2000), the USA coupled GCM DOENCAR/PCM developed as a common project of theNational Center forAtmosphericResearch andDepartmentofEnergy (Washington et al.,2000),andtheGermancoupledGCMMPIDMI/ECHAM4OPYC3developedasacommonprojectoftheMaxPlanckInstitutfrMeteorologieandtheDeutschesKlimarechenzentrum(Roeckneretal.,1996;Stendelletal.,2000).

Table 1:General circulation models, the results ofwhichwere used in this study: model label, country ofdevelopment,periodforwhich the datawere used, the approximate horizontal resolution of data, and somereferencesforthemodelsand/orsimulations.

Model Country Period Resolution

NCEP/NCARreanalysis USA 19612005 1,91,94CSIRO/Mk2 model Australia 19612100 5,63,2UKMO/HadCM3model Unitedkingdom 19612099 3,82,5DOENCAR/PCMmodel USA 19612099 2,82,8

ECHAM4OPYC35model Germany 19612100 2,82,8

The entire area of Macedonia corresponds to the size of approximately one grid point,making it obvious that the GCMs can not explain the spatial variability of Macedonianclimate.ThereisanevidentneedformethodsforregionalprojectionsofGCMresultstothescale,where the regionaldetailsofMacedonianclimateare tobecaptured.Approaches totheregionalprojectionsofclimatechangeusedforestimatingclimatechangeinMacedoniatogetherwiththeirresults,aredescribedinthefollowingchapters.

4IncaseofsealevelpressuredatathehorizotalresolutionofNCEPNCARreanalysisis2.52.5.

5Theentirenameofthemodelincludesthelabelofdevelopmentcenters(MPIDMI/ECHAM4OPYC3).Dataformonthlyaveragesofmaximumandminimumdailytempertureswerenotavailableforthismodel.


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CLIMATE CHANGE PROJECTIONSFOR MACEDONIA

Because the topography and surface properties, as the most important factors for spatialclimatevariability in regionalscale,arestable in time, themaincause for regionalor localclimatechangesisthelargescaleclimatevariability.Ifthereisaclearrelationshipbetween

largescale and regional/localscale climate variability, it canbe used tobridge the gapbetween the GCM output and needed information in regional/local impacts studies(Benestadetal.,2002).DifferentapproachescanbetakentobridgethisgapandtodevelopregionalorlocalclimatechangescenariosbasedontheoutputofGCMs(Figure6).

Figure 6: Different approaches to creating highresolution weather datafrom thegeneral circulation modeloutput(Dubrovsky,1997).

With an exception of direct GCM output, all these methods can be characterized asdownscaling methods. There are two main approaches to downscaling. One is dynamical,wheretheregionalclimatemodels(RCMs)arenestedinGCMs(e.g.,Giorgi&Mearns,1999;Wangetal.,2004),ortheGCMswithvariablehorizontalresolutionareused(e.g.,Dequeetal.,1998).Theotherapproachisempirical(orstatistical)(e.g.,Wilby&Wigley,1997;Wilbyetal.,1998;Zorita& Storch,1999),where simplemathematical/statisticalmodelsareused todescribe therelationshipbetween thedynamicsof largescaleclimatevariables(predictors)

and regional/localscale climatevariables (predictands).Thesemodelsareusedafterwardsfor the projection of GCM results of future climate simulations to a regional/local level.Another approach to regional climate change scenarios, mostly used in vulnerability andimpact studies, is an approach of incremental scenarios. Different possible combinations ofchanges inaveragevaluesandvariabilityof localclimatevariablesof interestareadded totheobservedvalues(Carteretal.,1999).Initssimplestversion,incrementalscenarioscanbebasedonlyonroughexpertjudgmentonpotentialclimatechange,butontheotherhand,itcanbebasedondetailedanalysisofpastclimatevariability,futureclimatesimulationswithGCMs, and final expertjudgment. Among the mentioned approaches, the direct GCMoutputandempiricaldownscaling,both incombinationwithpatternscaling,willbeused

for climate change projections for Macedonia and are described in more details in thefollowingsections.


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For the investigation of relationshipbetween largescale climate variability and regionalvariabilityofMacedonianclimate,observationsfromfifteenmeteorologicalstations(Figure7, Table 2) are used together with the largescale reanalysis and GCM results (Table 1).Selected locations represent different climatic types and subtypes affecting the climate ofMacedonia,whichareacombinationofthreemajorclimatedriversthatmeetovertheregionof Macedonia: Mediterranean, Continental and Alpine. According to the climate typesproposedbyRistevski(Filipovskietal.1996;Ristevski,2006),definedmainlywithregardstoaltitude, and according to the typical annual cycle of mean daily air temperature andprecipitation amount (Figure 8) six geographical regions of Macedonia were treatedseparatelyinouranalysis:

1. southeasternpartwithsubMediterraneanclimate;2. centralpartwithcombinedsubMediterranean/continentalclimate;3. southernpartwithcontinentalclimate;4. southwesternpartwithcontinentalclimate;5. easternpartwithcontinentalclimate;6. northwesternpartwithprevailingmountain/Alpineclimate.

Figure7:ApproximatelocationsofselectedfifteenmeteorologicalstationsinMacedonia.

Averagemonthlyvaluesformean(Tavg),maximum(Tmax),andminimum(Tmin)dailyairtemperaturesasalsofortheaveragedailyamountofprecipitation(Prec)fortheperiod19612005 were provided for fifteen meteorological stationsby Hydrometeorological office ofMacedonia.Severalproblemswiththe localmeteorologicaldatahavebeendetectedwithintheperformedanalysis.Simplequalitytests(e.g.,Tavg>Tmin,Tavg


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climatevariability. Ifbiasedmodel,describingnotonly therealclimatesignalbutalso theartificialsignalcausedbyerroneousdata,isusedforfutureclimateprojection,theresultsofsuchprojectionarealsobiasedgarbagein,garbageouteffect.Thisisanimportantsourceofuncertaintyinregional/localclimatechangeprojectionthatwehavetobeawareof. Forthefutureworkonclimatechangeprojectionsusingobserveddataweproposeacomprehensivequalitycheckofthedatabeforeprovidingthemforadditionalanalysis!

Table2:Selectedmeteorologicalstationstogetherwiththeirgeographicaldata: longitude, latitudeandz altitude),prevailingclimateimpactsandgeographicalregion.

GeographicaldataMeteorologicalstation

[V] [S] z[m]

Prevailingclimateimpacts Geographical

region

Gevgelija 22.50 41.15 57 SubMediterranean South/EastNovDorjan 22.72 41.22 180 SubMediterranean South/EastVeles 21.77 41.72 175 SubMediterranean/Continental CentralStrumica 22.65 41.43 224 SubMediterranean/Continental CentralSkopjePetrovac 21.63 41.95 234 SubMediterranean/Continental Centraltip 22.18 42.02 326 SubMediterranean/Continental CentralBitola 21.33 41.05 586 Continental SouthPrilep 21.57 41.33 673 Continental SouthOhrid 20.80 41.12 760 Continental South/WestResen 21.02 41.08 881 Continental South/WestBerovo 22.85 41.72 824 Continental EastKrivaPalanka 22.33 42.20 691 Continental EastLazaropole 20.70 41.53 1332 Mountain/Continental North/WestPopovaapka 20.88 42.02 1750 SubAlpine North/WestSolunskaGlava 21.42 41.70 2540 Alpine North/West

Sometimes trends inobservedvaluesareused inextrapolationmodeasafirstestimateforclimatechangeinthefuture.Theproblemofusingobservedtrendsforfutureclimatechangeprojectionisinnonstationarityofthetrents.Selectionofthesubperiodforwhichthetrendiscalculatedcanstronglyinfluencetheestimatedtrendvaluesandsotheestimatedclimatechangeprojections.Alsochangesinstationlocationsorobservingprocedurescanintroduceartificial trendwhich isnot related to thechanges inclimateconditions.This is illustratedwith an example of average annual air temperature measured at Bitola (Figure 9), whereadditionalinformationaboutchangesinlocationandintroductionofmeteorologicalsheltersare used (Trajanovska et al., 2004). Additionally, the future trend in temperatures is notsupposedtobelinear.

Due to theproblemswith trendsasa sourceof future climate change information,we based our projections of future climate change in Macedonia on the results ofsimulations with selected GCMs. The observed local datawere used forgrouping the stations in to different climatic regions of Macedonia (Table 2, Figure 8) and fordevelopingempiricalmodelsforlocalclimatechangeprojections.


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Figure8:Annualcycleofairtemperatureandprecipitationamountdeviationsfromaverageannualvalues (infigure legends) observed in theperiod 19611990 at differentmeteorological stations inMacedonia,groupedaccordingtothesimilarityofannualcyclesandaverageannualvalues.


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Figure 9: Average annual air temperature in Bitola and its linear trends for different subperiods ofmeasurementswithconsequentprojectionsoffutureclimatechangeuptotheyear2025.Blackdashedverticallinespresent theyears when the station changed the location and red dashed line theyear in which themeteorologicalshelterswereintroduced.

PATTERNSCALINGTO DIFFERENTEMISSIONSCENARIOS

Asmentionedinthechapteronclimateresponsetothechangesinatmosphericcomposition,future climate simulationswithGCMs take intoaccountonly limitednumberof emissionscenario representatives, usually A2 and B2 SRES. Results of these simulations or their

projections to the regionalscale canbe further scaled to other emission scenarios usingpattern scaling method.Themethod,proposedbyMitchell (2003),wasalreadyused in thethirdassessmentreportofIPCC(Houghtonetal.,2001).

The core of the pattern scaling method is the assumption that there is a linearrelationshipbetweenregionalor localclimateand theamountofglobalwarning(Mitchell,2003).Inthismanner,wecanestimatetheregional/localresponseoftheclimatevariabletoselectedSRESscenario(ysel)byknowing theregional/localresponse to thereferenceSRESscenario (yref), and the global warming under the selected (Tsel) and reference SRESscenario(Tref).Inourcase,whenusingtheGCMresultsforSRESA2andB2scenarios,theestimatesfortheotherSRESscenarios(A1FI,A1T,A1B,inB1)atlocallevelwerecalculated

asysel/yref = Tsel/Tref. SRESA2 scenariowasusedasa reference for SRESA1 (FI,T,B)scenarios, and SRES B2 for SRES B1 scenario. This is in accordance to Mitchell (2003)recommendations, that pattern scaling shouldbe performed from a scenario with greaterincreasesinradiativeforcing.Allthedifferences()werecalculatedrelativetotheyear1990usingtheratiosTB1/TB2andTA1T,A1Fl,A1B/TA2(e.g.,Bergantetal.,2006).Theratiosarebasedontheresultsofsimulationoffutureglobalairtemperaturewithsimple,1DmodelMAGICC(Hulmeetal,2000).

DIRECTOUTPUTOF GENERALCIRCULATIONMODELS

Thesimplestapproachtotheregional/localclimatechangescenariosbasedonGCMresults

is thedirectuseofGCMoutput.Theresultsofselected fourGCMswere interpolated to thegeographic location 21.5E and 41.5N approximately to the middle of the country


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using simplebilinear method (Press et al., 2001). As the GCMs include only a roughdescriptionoftopographyandasthesizeofMacedoniaiscomparabletothesizeofonegridpoint in selected GCMs, the impact of agitated relief and opening to the Aegean Sea onspatialvariabilityofMacedonian climate isaveragedout inGCMs.As shown inpreviousanalysis(see thepreliminaryreport) it isnotreasonable to interpolate theGCMsoutput tosingle locationsofMacedonia,as the interpolatedvalues for temperatureandprecipitationchangesarepracticallythesameforalllocations.TheheterogeneityofMacedonianclimate,duetothedifferentzonalclimatic typesMediterranean,continental,andAlpine,crossingover theMacedonianregion, togetherwith thelocal impactofagitatedrelief,causeagreatspatialvariabilityofclimatethatcannotbecapturedwellwiththeGCMsimulations.

Despite the limitedabilityofGCMs todescribe regional climatevariability, suchas incaseofMacedonia, it isassumedwith thedirectGCMoutputapproach that the intensityofclimate change in regional/localscale will be the same as in largescale, where theinformationofGCMsisreliable(Zorita&Storch,1999).Inafirststepwedefineareferenceperiod,usually19611990(labeled1990),asforthisperiodtheavailableGCMsimulationsarebasedonobservedconcentrationsofgreenhousegassesandsulfateaerosols,andafter1990onemissionscenarios6. Inclimatechangeprojections for21stcenturyusing thedirectGCMoutputmethodweaddtotheobservedregional/localvaluesanestimateofanabsolute(e.g.,inCfortemperatures)orrelative(e.g.,in%forprecipitation)changeofclimatevariableinfuture.TheestimatesofchangesarebasedoninterpolatedGCMvalues.Suchanapproachistosomeextendplausiblefor theprojectionsofair temperature,as theGCMsdescribewellthelargescaletemperaturepatterns.Astheregionalmodificationoflargescaletemperaturepatternsismostlyrelatedtothealtitude(andimpactofthesea),thedependenceonaltitudeis indirectlyconsideredbyadding theexpectedchanges to theobservedaveragevalue forreferenceperiodandnotusingtheabsoluteGCMvalues.Thisapproachmostlyfailsincaseof precipitation, as the GCM results for this climate variable are less reliable than for air

temperatureeveninlargescale(Trigo&Palutikof,2001)aswellasthespatialvariabilityofprecipitationsimuchstrongerthanforairtemperature.Precipitationisgenerallyoneofthemost difficult climate variables to simulate, especially if convective precipitations areconsidered.

Estimated changes inmean,maximumandminimumdailyair temperatureaswellasdailyprecipitationamountinMacedoniaindifferentseasons,basedondirectGCMoutput,arepresented inFigure10.Theprojectionsarebasedon interpolatedvalues from selectedfour GCMs, which results arebased on SRES A2 and B2 emission scenarios and scaledadditionally to the other four marker emission scenarios, SRES A1T, A1Fl, A1B, and B1.ChangesaveragedacrossthefourGCMsarecalculatedforallthescenarios(labeledasA1T,A1Fl,A1B,A2,B1,andB2) aswell as their averagevalueacross the scenarios (labeled asmean). Additionally the range across all marker SRES scenariosbut averaged across theGCMs(labeledasrange:mean)aswellasrangeacrossallGCMsandSRESscenarios(labeledas range: allGCMs)arepresented in figures.Changes forperiods19962025 (labeled2025),20212050 (labeled 2050), 19462075 (labeled 2075) and 20712100 (labeled 2100) in

6ThisistrueforGCMsimulationsperformedforthethirdIPCCassessmentreport TOR(Houghtonetal.,2001),andwhichwereused inour study.Newer resultsofGCM simulationsmade recently available at IPCCdatadistributioncentrearebasedonobservedconcentrationsofgreenhousegassesandsulfateaerosolsup to2000.Duetothelimitedtimeforanalyses,thenewerGCMresultsperformedfortheupcomingfourthIPCCassessment

reportAR4werenotusedinpresentstudy.


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comparison to 19611990 (referenceperiod labeled1990) arealsopresented inTable3.Asnone of the SRES emission scenarios is supposed tobe more probable as the others, thevaluesinTablesarepresentedasthemeanvaluesacrossallsixmarkerscenarios(mean),aswell as their range across scenariosusing averages across theGCMs (low/high) and rangeacross thesixscenariosandthefourGCMs(minimum/maximum).Inthefollowing text, themeanvalueisusedtogetherwiththeexpectedrange,whereforthelatertherangebetweenlowandhighvalue ismeant.The expected range isprovided in text inbrackets following theaveragevalueofthechange.

The highest increase in the temperature on the level of entire country is expected insummer togetherwith themost intensivedecrease inprecipitation.Anexpected increase inmeandailyair temperature for summerperiod is2.5C (2.2C to2.9C) in2050and5.4C(3.7Cto7.6C)in2100incomparisonto1990.Themaximumdailytemperatureisexpectedtoincreasemorethanminimumdailytemperature,3.0C(2.6Cto3.4C)vs.2.1C(1.9Cto2.4C)in2050and6.2C(4.3Cto8.7C)vs.3.5C(2.5Cto4.9C)in2100.Thisindicatesanincrease indaily temperature range insummer.Thestrong increase inmaximumdailyairtemperature and consequently also in mean daily air temperature is probably related toexpectedstrongdecrease inprecipitation,which is supposed tobe 17% (16% to 18%) in2050and 37%(21%to 53%)in2100.

Inautumnthemeandailyairtemperatureisexpectedtoincreaseforabout1.7C(1.5Cto2.0C)in2050and4.2C(2.8Cto6.0C)in2100.Anexpectedincreaseofmaximumdailyairtemperature, 1.9C (1.7C to 2.2C) in 2050 and 3.7C (2.6C to 5.3C) in 2100, as well asminimumdailyair temperature1.7C(1.5C to2.0C) in2050and3.5C(2.5C to4.9C) in2100,arenotverydifferenttotheincreaseinmeandailyair temperaturewhichindicatesasmaller increase in daily temperature range in autumn in comparison to summer period.Precipitationinautumnisexpectedtodecreaseforabout 4%(2%to 7%)in2050and 13%(5%to 23%)in2100.

Anexpectedincreaseinmeandailyairtemperatureinwinteris1.7C(1.4Cto1.9C)in2050and3.0C(2.2Cto4.2C)in2100.Expectedchangesinmaximumdailyairtemperatureandminimumdailyairtemperature,1.4C(1.2Cto1.8C)vs.1.4C(1.2Cto1.6C)in2050and2.7C(1.7Cto4.0C)vs.3.2C(2.4Cto4.6C)in2100,indicateasmalldecreaseindailyair temperature range inwinter.Practicallyno change inprecipitation is expected for thewinterperiodin21stcenturyincomparisonto1990.

Inspringthemeandailyairtemperatureisexpectedtoincreaseforabout1.5C(1.3Cto1.8C)in2050and3.2C(2.2Cto4.6C)in2100.Anexpectedincreaseofmaximumdailyairtemperature, 1.4C (1.3C to 1.7C) in 2050 and 3.3C (2.2C to 4.7C) in 2100, as well asminimumdailyairtemperature,1.4C(1.2Cto1.6C)in2050and3.1C(2.2Cto4.3C)in

2100, ispractically the sameas increase inmeandailyair temperaturewhich indicatesnoevidentchangeindailytemperaturerange.Precipitationinspringisexpectedtodecreasefor6% (2% to 10%) in2050and 13% (5% to 22%) in2100,which isalmost thesameas inautumn.

Althoughsomeprojectedchanges forMacedoniamightseemverydramatic,especiallyprecipitation and temperature changes for summer period, the projected values are incorrespondencewiththeresultsobtainedbyMAGICC/SCENGEN7softwareusingthesamemodelsandallsixmarkerscenarios(testedbutnotshown).Itisaquestionifsuchprojections

7MAGICCSCENGENsoftwareisfreelyavailableatwebpages

http://www.cgd.ucar.edu/cas/wigley/magicc/installation.html


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are realistic or not,but they arebased on the direct GCM output. This means that if theresults of GCMs in a largescale are realistic also their direct interpolations to locationrepresentingMacedonianregionshouldberealistic.Astrongerincreaseofairtemperatureinsummerincomparisontootherperiodsoftheyearcouldberelatedtotheexpecteddecreaseinprecipitationasprecipitationhasacoolingeffectonneargroundtemperatureconditionsinsummermonths.Notonlytheaveragetemperatureshouldincreaseincaseofdecreaseinprecipitation, but also the temperature range would enlarge if there would be lessprecipitation and more sunny days. This also explains the stronger increase of maximumtemperature in summer in comparison to the increase of minimum temperature. We alsohave tobeaware, thatprovidingprecipitation change inpercentage,which is common inclimatechangestudies,alsohassomecaveats.Thechangesforsummerperiodmightseemmore dramatic in comparison to autumn and spring also due to the fact that there is aminimum of precipitation in Macedonia in summer months. Consequently, the sameabsolutechangepresentedasabsolutevalueforsummerandautumncanresult inamuchdifferentrelativevaluepresentedin%.

ResultsofdirectGCMoutputpresented in this study are also in correspondencewith the

resultsof aPRUDENCEproject forMacedonia (PRUDENCE,2004).The resultsof thisprojectindicatethataglobaltemperaturechangefor1Ccorrespondtothe1.4C(s.d.80.3C)ofchangeinMacedoniaonannuallevel,1.3C(s.d.0.3C)inwinter,1.2C(s.d.0.3C)inspring,1.9C(s.d.0.4C) in summer,and1.4C (s.d.0.3C) inautumn.The response inprecipitation in caseofaglobaltemperaturechangefor1CisforMacedonia 4.6%(s.d.2.8%)ofchangeinMacedoniaonannuallevel, 1.1%(s.d.3.5%)inwinter, 4.0%(s.d.3.8%)inspring, 11.8%(s.d.7.7%)insummer,and 4.1%(s.d.3.0%)inautumn.Consideringthattheglobaltemperatureissupposedtochangefor3.6C(1.4Cto5.8C)tilltheendof21stcenturywegetsimilarvaluesforthechangesastheonepresentedinourstudy.

Ourestimatesfortemperatureandprecipitationchangein21stcenturyaremoredramaticas

estimates based on IS92a and IS92d emission scenarios used in previous study (UNDPMacedonia,2003).Thedirectionofexpectedchanges(e.g.,strongestincreaseinairtemperatureinsummer, precipitation decrease in summer, etc.) is anyway the same, but the intensity isdifferent.ThedifferenceisprobablyrelatedtothefactthatIS92emissionscenarios,proposedbyIPCCin1995,weremoreoptimisticthatSRESscenariosproposedin2001.ThiscanbeseenalsoinglobaltemperaturechangeprojectionsbasedonIS92emissionscenarioswhichwere lowerthanthosebasedonSRESscenarios(Houghtonetal.,2001).

Similarprojectionswereadditionallyperformedalsoforscalarwindspeed(Windinm/s)andincident solar radiation (Srad in W/m2). Estimated changesbased on direct GCM output arepresented in Figure 11. Results for selected time spans (2025, 2050, 2075, and 2100) are alsopresentedinTable4.Forbothvariablesrelativeexpectedchangesareverysmall,practicallynotexceeding10%ineitherdirectionwhenconsideringthemeanrange.Aminorincreaseinincidentsolarradiationisexpectedinallseasons,thehighestinsummer.Themostextremeprojectionforthesummershowsan increaseupto25%tilltheendof21stcentury,but it isrelatedtoasingleGCM and so not very probable. The general small increase in incident solar radiation in allseasons and the strongest in summer is in correspondence to projected precipitation changes,withthehighestdecreaseinsummer.Lessprecipitationprobablymeansmorecleardaysandsomore incidentsolarradiationreceivedat theground.Practicallynochange isexpected inwindspeedoverMacedoniawhenconsideringdirectGCMoutputforthefourGCMs.

8Standarddeviation


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Figure10:Expectedchange inminimum,meanandmaximumdailyair temperature,anddailyprecipitationamountinMacedoniaindifferentseasonsin21stcenturyincomparisonto19611990.ResultsfromfourGCMs

(CSIRO/Mk2,HadCM3,ECHAM4OPYC3,andNCARPCM)interpolatedtogeographiclocation21.5Eand41.5NandscaledtosixSRESemissionscenarios(A1T,A1Fl,A1B,A2,B1,andB2)arepresented.


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Figure11:Expectedchangeinincidentsolarradiation(right)andscalarwindspeed(left)inMacedoniaindifferentseasonsin21stcenturyincomparisonto19611990.ResultsfromfourGCMs(CSIRO/Mk2,HadCM3,ECHAM4OPYC3,andNCARPCM)interpolatedtogeographiclocation21.5Eand41.5NandscaledtosixSRESemissionscenarios(A1T,A1Fl,A1B,A2,B1,andB2)arepresented.


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Table4:Projectedchangesofincidentsolarradiation(%)andscalarwindspeed(%)forMacedoniabasedondirectGCMoutpuand41.5N. Valuesarepresented separatelyfordifferent seasonsandarebasedonprojectionsof resultsfromfourGCMs (CNCARPCM)scaledtosixemissionscenarios(SRESA1T,A1Fl,A1B,A2,B1,andB2).Mean:averageacrossdifferentemissionminimum/maximumacrossdifferentscenariosaveragedacrossdifferentGCMs,Maximum/Minimum:minimum/maximumacGCMs.

INCIDENT SOLAR RADIATION [%]

DJF MAM JJA SON 2025 2050 2075 2100 2025 2050 2075 2100 2025 2050 2075 2100 2025 2050 2075

Minimum -3 -3 -1 -2 0 0 2 2 0 1 2 3 0 -1 2

Low 0 0 1 1 1 2 4 4 2 3 6 6 1 1 5 Mean 1 1 2 2 2 3 5 6 3 4 7 8 2 3 6 High 2 2 2 3 3 4 6 9 4 6 8 11 3 5 7

Maximum 4 7 9 9 6 8 12 17 9 14 23 25 5 9 12

SCALAR WIND SPEED [%]

DJF MAM JJA SON

2025 2050 2075 2100 2025 2050 2075 2100 2025 2050 2075 2100 2025 2050 2075

Minimum -1 0 -2 -2 -2 -2 -3 -7 -5 -5 -3 -4 -7 -20 -7 Low 2 1 1 0 0 3 2 3 -2 0 2 2 -1 -6 -2 Mean 3 2 1 0 2 4 2 3 0 1 2 2 -1 -4 -1

High 3 3 3 1 5 5 3 4 3 2 2 3 0 0 -1 Maximum 8 6 6 2 11 18 9 18 5 5 9 10 2 2 4


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Intherealworld,spatialvariabilityofprecipitationaswellasairtemperatureaswellaswind speedand incidentsolar radiation isvery strong,especially in regionswithagitatedrelief,suchasMacedonia.That iswhywecannotexpect that thechangepatternsof thesevariableswillbeuniformacross the entireMacedonian region, asdifferent factors impactclimate conditions in different Macedonian subregions. Heterogeneous climate ofMacedonia does not favor the direct GCM output approach for the use in climate changescenariodevelopmentforMacedonia.

Additional problemwith the useof directGCM output approach is that extreme events(droughts, intensiveprecipitations, heatwaves, etc.) are often limited to the scale smallerthantheminimumscaleofGCMs,astheyaremostlytriggeredbytheregionalmodificationoflargescale(synoptic)weathersituation.Forexample,draughtisacombinationoflackofprecipitation,whichdependsonsynopticweathersituationandregionaltopography,andasoil water capacity, which is a local property. When using the GCM results directly, weaverage out all the extremes that could happen in the subgridscale, which practicallycontainstheentireMacedonianregion.AnothergeneralandmajorlimitationforthestudiesofclimatechangeimpactonextremeeventswithavailableobservationsandGCMresultsisthetemporalresolutionof thedata.Forthestudyofextremeeventsatleastdailytemporalscaleisneeded,butinthepresentstudythemonthlytimescalewasused,asonlymonthlyaveragesofselected largescaleand localclimatevariableswereavailable.Inmonthly timescale,thestudiesofchangesinvariabilityofclimatevariablesareverylimited,andthefocusismostlyonchangesinaverageconditions.

Due to the mentioned facts, the direct GCM output method provide us only a roughdescription of expected climate change in 21st century in Macedonia, mostly about thechangesofaverage conditionson the levelofentire country.On theotherhand, thedirectGCMoutputapproachcanpresentabenchmarkformoredetailedandcomplicatedmethodsthat could suffer some other problems, like extrapolation with empirical models used for

regionalprojectionoffutureclimatechangeinempiricaldownscaling.

EMPIRICALDOWNSCALING

Empiricaldownscaling(e.g.,Wilby&Wigley,1997;Wilbyetal.,1998;Zorita&Storch,1999)hasbeenwidelyusedtobridgethegapbetweenthelargescale(resultsofGCMs)andlocalscale (inputdataneeded in impact studies).Thebasic ideabehind empiricaldownscaling(Figure 12) is to use simple mathematical models to describe the observed relationshipsbetween the largescale climate variable (predictor) and the localscale climate or climatedependent variable (predictand). These models are then used to project GCM results forfutureclimatetoaregionaloralocallevel.Amajorassumptionismade,thattheresponseof

localclimatetolargescaleclimatevariabilityisdescribedwellbyempiricalmodelandthatthe description willbe valid also in changed climate conditions. The entire method ofempirical downscaling isbased on this assumption (Giorgi & Mearns, 1991; Storch et al.,1993; Schubert, 1998), which isby no means guaranteed (Zorita in Storch, 1999). If theempiricalmodelsarebasedon longdatasetsofobservations that includedifferentweathersituation, some of them probably more frequent in the future, such an approach isacceptable.Theassumptionisvalidonlyintherangeofpresentclimatevariability,whichisnotnecessarilythecaseinprojectionsofclimatechange,especiallyforthesecondhalfofthe21st century, as the temperature is expected to exceed these limits. In such cases theinterpretation of projection need more caution and crossvalidation with some other

methods,likedirectGCMoutputisnecessary.


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Severalreviewsofempiricaldownscalingareavailableinliterature(Hewitson&Crane,1996;Wilby&Wigley,1997;Zorita&Storch,1997;Rummukainen,1997;Weichert&Brger,1998;Zorita&Storch,1999;Craneetal.,2002).

Figure12:Schematicviewonempiricaldownscaling(Heyen,2002).

In our caseEmpiricalOrthogonal FunctionsAnalysis (e.g., Preisendorfer, 1988; Storch &Zwiers,1999)wasused toextract important featuresfrom largedatasetsofdifferent largescaleclimatevariables.ThesefeatureswererelatedtothelocalclimatevariablesusingPartialLeastSquaresRegression(e.g.,Bro,1998;Helland,2001;Martens,2001).Developedempiricalmodels were used for local climate change projections (see Bergant et al, 2005, 2006 fordetaileddescriptionofmethodology).Themodelsweredeveloped separately for the fourseasons (winterDJF, springMAM, summerJJA,andautumnSON).Theobserved

valuesofminimum(Tmin),maximum(Tmax)andmeandailyair temperature(Tavg),anddaily precipitation amount (Prec) at selected fifteen locations were used in modeldevelopment together with largescale NCEP/NCAR reanalysis data (Kalnay et al., 1996;Kistleretal.,2001)forthesameclimatevariables.ThemodelswereappliedonthelargescaleanomaliesofpredictorsfromthefourGCMsoutput.

Somepreprocessingofthedataisneededbeforetheycanbeusedinempiricaldownscaling.Local observations from selected meteorological stations in Macedonia were tested formissingandsuspiciousdata.SuchdatawerereplacedbyvaluesinterpolatedwithEmpiricalOrthogonalFunctionAnalysis for incompletedata (seeBergantetal.,2005 for thedetaileddescription of methodology). Reanalysis data and GCM results were interpolated to a

commongridof2.52.5byasimplebilinearinterpolationmethod(Pressetal.,2001).Thisstep isneeded tounify the formatof inputdata forempiricalmodels.As thepredictor


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domain influences thequalityof empiricalmodels (Benestad, 2002a,b),differentpredictordomains were evaluated, keeping in mind the skillful scale of GCMs (Grotch and MacCracken, 1991; von Storch et al., 1993). For themean,maximum andminimum daily airtemperatureapredictordomainextending from12.5E to30.0E and from 35.0N to50.0Nwasselectedasmostsuitable,andforprecipitationextendingfrom15.0Eto27.5Eandfrom37.5Nto47.5N.Averageannualcycleforthereferenceperiod19611990wasremovedfromallmonthlyvaluesoflocalandlargescaleclimatevariablesandremaininganomalieswereusedforthedevelopmentofempiricalmodels.

As the localresponseon largescaleclimatevariabilityacross theMacedonianregion isdifferentindifferentpartsofthecountry,whichcanbeseenalsofromdifferentannualcyclesofprecipitationandtemperature(Figure8),wecanalsoexpectthatclimatechangewillaffecttheseregions inadifferentway.For thatreason,weperformedempiricaldownscaling forseveral locations in Macedonia that represent different climatic subregions of Macedonia(Table2).SummaryofresultsoftheprojectionsforthesubregionsarepresentedinTables5to12,togetherwithgraphicalpresentationofresultsforonerepresentativestationforeachsubregion in Figures 13 to 20. If we make some general comparisonbetween empiricaldownscaling results and direct GCM output, we can see that the local projections showstronger increase in air temperature in winter and spring period in comparison to directGCM output for Macedonia. Additionally, local projections show less drastic decrease inprecipitation in summer period. Projections of change inmean daily air temperature anddailyamountofprecipitation forotherseasonsarecomparableforbothmethods.Also thechangesindailytemperaturerange,withregardstotheprojectionsofchangesinmaximumandminimumdailyairtemperatureareconsistentforbothmethods.Anevidentdecreaseindailyairtemperaturerangecanbeseenforwinterperiod,astheaveragemaximumdailyairtemperature is expected to increase less than average minimum daily air temperature.

Reversed situation is expected for summer period,but only a slight increase in dailytemperature range for spring and autumn seasons. Let us consider local projections fordifferentsubregionsofMacedoniainmoredetails.

SOUTHEASTERNANDCENTRALPARTOFMACEDONIA/SUBMEDITERRANEANIfwecompareclimatechangeprojectionsfortheregionofthesoutheasternMacedoniawithprevailing subMediterranean climate impact (representedby Gevgelija and Nov Dorjan)and for the centralMacedoniaundera combinationof continentaland subMediterranianclimateimpacts(representedbyVeles,SkopjePetrovec,Strumicaandtip),alessintensive

temperaturechangeisevidentforthefirstoneinwinterandmoreintensiveinsummerandautumn.Changesofair temperature inspringarecomparable inbothsubregions. Inbothsubregions thehighest increaseofair temperature is expected in summer.Thedifferencebetween winter and summer increase in air temperature is especially evident for southeasternregion.Withanexceptionofwinter,amoreintensiveincreaseinmaximumthaninminimumtemperatureisexpected(especiallyinsummer),whichwillbereflectedinalargeraveragedailytemperaturerangeintheseseasons.Theexpectedchangesinprecipitationaresimilar forboth subregions. Practically no change in precipitation is expected in winterseasonandadecrease inprecipitation inallother seasons.Moredetailed results for thesetworegionsarepresentedinTables5and6andFigures13and14.


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SOUTHERNANDSOUTHWESTERNPARTOFMACEDONIA/CONTINENTALBoth,southern (representedbyBitolaandPrilep)andsoutheastern (representedbyOhridand Resen) parts of Macedonia are under the prevailing continental climate impactsaccording to theclassificationproposedbyRistevski(2006).Theclimatechangeprojectionsfor these tworegionsarequitedifferentalthoughnotveryremote toeachother.Incaseof

southernregionrepresentedbyBitolaandPrileptheprojectionsofprecipitationchangearevery similar to the regions with prevailing or partial subMediterranean climate impacts.Almostnochangeofprecipitation isexpected inwinteranddecrease inotherseasons, thestrongest insummer.Alsoaslightlystrongersignal in temperaturechange isexpected forthisregionincomparisontoregionswithsubMediterraneanclimateimpacts.Thedifferenceis especially evident in projections for winter period. On the contrary, projections oftemperaturechangesforthesouthwesternregionrepresentedbyOhridandResenaremuchlowerthanforregionrepresentedbyBitolaandPrilep.Additionallyevenaslightincreaseofprecipitation isexpectedforwinter,butanevidentdecrease inotherseasons.Thedifferentresponse of these two regions on large scale climate variability couldbe related to the

proximityof largewaterbodies (lakePrespaand lakeOhrid) in caseofResenandOhridstations.Ontheotherhandweneedtobeawarethatourprojectionsarebasedonempiricalmodels that couldbebiasedby an artificial signal invoked in the data used for modelcalibration.Forexample,therearesomewellknownproblemswiththedataincaseofBitolastation (see Trajanovska et al., 2004) that mightbias the projection models. Details onprojectionsofchangesofselectedlocalclimatevariablesforstationsBitolaandPrilep,aswellasOhridandResencanbefoundinTables7and8andFigures15and16.

EASTERNPARTOFMACEDONIA/CONTINENTALForrepresentativesofeasternpartofMacedoniawithprevailingcontinentalclimateimpacts,

stationsBerovoandKrivaPalankawereused.Theannualpatternofexpected temperaturechange in this region is similar to the pattern for continental region in southern part ofMacedonia,but the intensity of the change is slightly lower. A comparison to Bitola andPrilepalsoa slight increaseofprecipitation isexpected inwinter,butdecrease inalotherseasons,mostintensiveinrelativesenseinsummer.Insummeraswellasinautumn,alsoanincrease in daily air temperature range is expected. Details on projections of changes ofselectedlocalclimatevariablesforstationsBerovoandKrivaPalankacanbefoundinTable9andFigure17.

NORTHWESTERNPARTOFMACEDONIA/ALPINE

Forallthreeclimatesubtypesunderthemountainousinfluence(mountain/continental,subAlpine,Alpine)thatcanbefoundinnorthweasternpartofMacedoniaandarerepresentedby stations Lazaropole, Popova apka and Solunska Glava, the projections of airtemperaturechangeandprecipitationareverysimilar.Anincreaseofprecipitationforafewpercent till theendof21stcentury isexpected inwinterandamore intensedecrease inallother seasons. The expected air temperature change is the strongest in this region of thecountry.Thehighestincreaseinairtemperatureisexpectedinsummer,butthedifferencesbetween seasons is not large. More detailed results for these two climatic regions arepresentedinTables10,11and12andFigures18,19and20.


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Figure13:Expectedchange inminimum,meanandmaximumdailyair temperature,anddailyprecipitationamountatlocationSkopjePetrovecindifferentseasonsin21stcenturyincomparisonto19611990.Empirical

downscalingresultsfromfourGCMs(CSIRO/Mk2,HadCM3,ECHAM4OPYC3,andNCARPCM)scaledtosixSRESemissionscenarios(A1T,A1Fl,A1B,A2,B1,andB2)arepresented.


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Figure14:Expectedchange inminimum,meanandmaximumdailyair temperature,anddailyprecipitationamount at location Gevgelija in different seasons in 21st century in comparison to 19611990. Empirical



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Figure15:Expectedchange inminimum,meanandmaximumdailyair temperature,anddailyprecipitationamount at location Bitola in different seasons in 21st century in comparison to 19611990. Empirical



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Figure16:Expectedchange inminimum,meanandmaximumdailyair temperature,anddailyprecipitationamount at location Ohrid in different seasons in 21st century in comparison to 19611990. Empirical



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Figure 17: Expected change in minimum, mean and maximum daily air temperature, and dailyprecipitationamountatlocationBerovoindifferentseasonsin21stcenturyincomparisonto19611990.Empiricaldownscalingresultsfromfour GCMs (CSIRO/Mk2, HadCM3, ECHAM4OPYC3, and NCARPCM) scaled to six SRES

emissionscenarios(A1T,A1Fl,A1B,A2,B1,andB2)arepresented.


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Figure18:Expectedchange inminimum,meanandmaximumdailyair temperature,anddailyprecipitationamount at location Lazaropole in different seasons in 21st century in comparison to 19611990. Empirical



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Figure 19: Expected change in minimum, mean and maximum daily air temperature, and dailyprecipitationamount at location Popova apka in different seasons in 21st century in comparison to 19611990. Empirical



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Figure20:Expectedchange inminimum,meanandmaximumdailyair temperature,anddailyprecipitationamountatlocationSolunskaGlavaindifferentseasonsin21stcenturyincomparisonto19611990.Empirical



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UNCERTAINTIESIN REGIONALCLIMATE CHANGE PROJECTIONS

Weneed tobeaware, thatany future climate change studyonaglobal, regional,or locallevel isandwillbeattributed tosomeuncertainty.Thebasicsourcesofuncertainty,whichcannotbeavoidedfromtheverybeginningofclimatechangescenariodevelopment,arethe

assumptionsaboutfuturesocioeconomicdevelopmentandrelatedemissionsofgreenhousegasses and sulfur dioxide. Such scenarios are used in simulations of future climate withGCMs.DifferentGCMsrespondslightlydifferent to identicalconcentrationsofgreenhousegasses and sulfate aerosols, which introduces additionaluncertainty to the simulationsoffutureclimate.Suchclimatemodelshortcomingsareanothersourceofuncertaintyandaremainly related to a crude description of unresolved processes using statisticalparameterization schemes (Benestad, 2002). To consider this uncertainty, at least to somelevel,theresultsofdifferentGCMswereusedinourstudy.Arangeofresultsacrossallfourselected GCMs and six SRES marker emission scenarios is presented as a measure ofuncertainty inGCMsandemissionsscenarios infiguresof localclimatechangeprojections

fordifferentlocationsinMacedonia.GCMsareabletosimulatereliablythemostimportantfeaturesoftheglobalclimateonalargescale(ZoritaandStorch,1999),butfailonaregionalorevenalocalscale,mostlyduetothelowhorizontalresolutionandlimiteddescriptionofsubgridprocesses(GrotchandMacCracken,1991).Asdifferentapproachescanbeused tobridgethegapbetweenlargescaleandscaleofanimpactstudy,theselectionofthemethodcan also introduce some uncertainty, especially if projection models are used in theextrapolationmode.Inourcaseonlyonedownscalingmethodwasused,sotheuncertaintyrelatedtoselectionofmethodwasnotevaluated.BothparameterizationsschemesinRCMsandempiricalmodelsarebasedontherangeofobservedvalues,whichcouldbeexceededinthe future.Theobservationdatasetscommonlycontainerrors,as foundalso in thecaseof

local meteorological data available for our study. Such errors can bias the developedprojectionmodelsandrelatedprojectionsoffutureclimatechange,especiallyasthemodelsareoftenused inan extrapolationmodel.This canbe evident also in someprojectionsoftemperaturechangeforMacedonia,wherewegetattheendofthecenturyhigherincreaseinmeanair temperature thanboth inminimumand inmaximum temperature,which isnotrealisticinasenseofthechangeofaveragedailyairtemperaturerange.Thisproblemcanberelatetotwofacts:i)incaseofminimumandmaximumtemperatureprojectionsonlythreeGCMswereused,but incaseofmean temperatureadditionalforthGCMwasused; ii) theinputdatawerebiasedwhichintroducedanerrorinfinalprojectionduetotheextrapolation.This is why, good quality observations of present climate and procedures for quality

checking of the data arebasic needs for any future climate change study. The results ofregional/local projections are commonly used further in impact models, which introduceadditional uncertainty to the final results. And at the end an expertopinion on results isneeded,whichisoftennotderivedsimplefromtheobtainedresults.

Due to the mentioned sources of uncertainties we have to keep in mind that theprojections of future climate are not exact predictionsbut indices in which direction theclimatechangemightdevelop.Oneof thequestionswithregards to theuncertainty is theaccuracythatshouldbeusedwhenreportingsuchuncertainprojectionsorusingtheminimpactstudies.As therangeofuncertainty forfutureprojectionsusuallyarisewitha timedistancefrompresentaswellaswiththemagnitudeofprojectedchange,itisnotreasonable

to consider projections with a constant accuracy over the entire period of 21st century. Areasonable approach wouldbe for example to use air temperature projections with an


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accuracyof0.1Cfortheperiod2025,0.2Cfortheperiod2050,0.3fortheperiod2075and0.5fortheperiod2100.Incaseofprecipitationprojections,whichareevenmoreuncertainthanairtemperatureprojections,higheraccuracythan5%fortheentireperiodof21stcenturyisnotreasonable.

Different assumptions and limited descriptions of real processes within the entireprocedureofdevelopingtheregionalclimatechangescenarioscontributetotheuncertaintyinfinalresults.Someoftheseuncertaintieswillprobablybereducedinthefuturebygainingnewknowledgeonclimatesystemresponsetothechangesintheatmosphericcomposition,and about response of climate dependent processes and activities to climate variability.BetterdescriptionofmodelphysicsandbetterhorizontalresolutionofGCMswillreducetheimportance of downscaling approaches and the uncertainties related to that, and willprobably also reduce the intermodel differences. More reliable estimates of the climatesystemsresponsetothechangedboundaryconditions(concentrationsofgreenhousegassesanddifferentaerosols)willbeavailableevenonaregionalorlocallevel.Differentlaboratoryandfieldexperimentswilldeepentheknowledgeaboutresponseandadaptationcapabilityofdifferentorganismsor entire ecosystems to the changed environmental conditions. Butstillatleasttheproblemofreasonableestimationofclimateboundaryconditionschangeinthe future will always remain as abasic source of the uncertainty in any climate changeimpactstudy.

Figure21:Increasinguncertaintyintheprocessofclimatechangescenariosdevelopmentbyfocusingfromthegeneralassumptionsaboutsocioeconomicdevelopmentinfuturetotheregionalimpactsofconsecutiveclimatechange(Bergant&KajfeBogataj,2005;Bergantetal.,2006).


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GENERAL CONCLUSSIONS

Abasic problem found during the analysis is that the quality of climatological data forselectedmeteorologicalstationsintheregionofMacedoniaisnotalwayshigh.Somesimpletestswereperformedtodetecterroneousdataandiftheprobleminthedatawasrelatedto

an obvious typing error (like missing negative sign) it was correctedbefore its use inanalysis.Otherwisethesuspiciousdatawereinterpolatedtogetherwiththemissingdataonthebaseofobservations from the other meteorological stations.As theprojection modelsdependonlocalclimatologicaldata,thequalityofthesemodelsandrelatedclimatechangeprojectionsdependstronglyonthequalityofinputdataduetothegarbagein,garbageouteffect.

The direct GCM output projected to Macedonia show more intensive increase in airtemperature in summer season than in winter season. The expected change in airtemperaturein21stcenturyismuchhigherthatexpectedglobaltemperaturechange,buttheresults of our study are consistent with other available studies that include Macedonian

region.Almostno change inprecipitation is expected forwinter season ingeneralon theareaofMacedonia,butquiteastrongdecreaseinsummerprecipitation.Adailytemperaturerangeissupposedtodecreaseinwinterandincreaseinsummer.

The local projections of climate change indicate that different climatic regions ofMacedonia will respond slightly different on largescale climate changes. The continentalclimate region in southwestern part of Macedonia, close to the Ohrid and Prespa lakes,seems to have the weakest response to largescale climate change in a sense of absolutetemperature and precipitation changes, and the northwestern part under the prevailingmountain/Alpineclimateimpactthestrongestresponse.Inmentionedregionsthedifferencebetweenastrongincreaseintemperatureinsummerseasonandweakerinwinterseasonis

notthatevidentasinsubMediterraneanclimateregion.Although such localprojectionsof climate changepresent a step forward towards the

neededknowledgeabouthowdifferentsubregionsofMacedoniamightresponseto largescaleclimatechange,weneedtobewareofalltheuncertaintiesrelatedtotheresultsbeforeusingtheminimpactstudies.

Due to the availabilityofonlymonthly averagesof localand large scale climatedata,only theexpectedchangesofaverageclimateconditions inMacedoniawereestimated.Noreasonableestimateonchangesofvariabilitycouldbemadeusingavailabledata.


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