Preparatory meteorological modeling and theoretical analysis for a neighborhood-scale cool roof demonstration

2018·1.4 MB·English

by  Dev Millstein

UrbanClimate24(2018)616–632
ContentslistsavailableatScienceDirect
Urban Climate
journalhomepage:http://www.elsevier.com/locate/uclim
Preparatory meteorological modeling and
theoretical analysis for a neighborhood-scale cool
roof demonstration
⁎
DevMillstein ,RonnenLevinson
HeatIslandGroup,LawrenceBerkeleyNationalLaboratory,Berkeley,CA94720,USA
a r t i c l e i n f o a b s t r a c t
Articlehistory: Replacingdarkconventionalroofswithmorereflective“cool”roofshas
Received3June2016 beenproposedasamethodtolowerurbanairtemperatures.Manyme-
Receivedinrevisedform15December2016 teorologicalstudieshavesimulatedpotentialcoolroofairtemperature
Accepted17February2017 reductions.However,economicandlogisticalchallengesmakeitdiffi-
culttoperformthelarge-scaledemonstrationsneededtoverifythese
Keywords: modelresults.Thisworkassesseswhetheraneighborhood-scalecool
Coolroofs roofdemonstrationcouldyieldanobservableairtemperaturechange.
Urbanheatisland
Weusebothanidealizedtheoreticalframeworkandameteorological
Urbanmeteorology
modeltoestimatetheairtemperaturereductionthatcouldbeinduced
Climatechangeadaptation
byincreasingroofalbedoover~1km2areaofacity.Boththeidealized
analysisandmodelindicatethatanairtemperaturereductioncould
bedetected,withthemodelindicatingareductionof0.5°Candtheide-
alizedanalysisindicatingalargerreductionof1.3°C.Follow-onmodel-
ing is recommended prior to design of a neighborhood-scale
demonstration.
©2017ElsevierInc.Allrightsreserved.
1.Introduction
”Cool”roofsreflectmoreofthesun'senergythandostandardroofs.Increasingthealbedo(solarreflec-
tance)ofaroofhasbeenshowntosaveenergyinaconditionedbuilding,andtolowertemperatureinanun-
conditionedbuilding(Gaoetal.,2014).Urbanclimatemodelsindicatethatreplacingalargeportionofacity's
standardroofswithcoolroofscouldreduceoutsideairtemperatureinthatcity(Rosenfeldetal.,1998;Millstein
andMenon,2011;Georgescuetal.,2014;Santamouris,2014;Salamancaetal.,2016).
⁎ Correspondingauthor.
E-mailaddress:[email protected](D.Millstein)
http://dx.doi.org/10.1016/j.uclim.2017.02.005
2212-0955©2017ElsevierInc.Allrightsreserved.
D.Millstein,R.Levinson/UrbanClimate24(2018)616–632 617
AspartoftheCERC-BEECoolRoofs&UrbanHeatIslandsproject,wehaveinvestigatedthepotentialofcool
roofstodecreasebuildingenergyuseinChina“directly”byreducingtheenvelope'ssolarheatgain(Gaoetal.,
2014).Coolroofsmayalsosaveenergy“indirectly”bydecreasingtheairtemperaturedifferenceacrossthe
buildingenvelope.Inmanycities,meteorologicalmodelshavebeenusedtoestimatethepotentialcoolingof
outdoorairfromthereplacementofallstandardroofs(e.g.,agedalbedo0.12)withcoolroofs(e.g.,agedalbedo
0.65).Forexample,meteorologicalmodelingshowedthataveragesummerdaytimetemperaturereductionsof
about1°CcouldbeachievedinGuangzhou,China(Caoetal.,2015).However,therehavebeennodemonstra-
tionsperformed,inGuangzhouorelsewhere,thatcouldverifythemodeledpredictionsofcool-roofinduced
city-wideairtemperaturechanges,hereafterreferredtoasthe“coolroofeffect”.Onepartialexceptionto
thisstatementistheanalysisofcoolingtrendsassociatedwiththeexpansionofhigh-albedogreenhousefarm-
inginaregioninsoutheasternSpain(Campraetal.,2008).However,follow-onmeteorologicalmodelingindi-
catedthatonlyaportionofthehistoricaltemperaturetrendswaslikelyassociatedwiththeexpansionofhigh-
albedogreenhousefarming;theremainderofthetrendwasunexplained(CampraandMillstein,2013).
Thereasonthatnofieldtestshavebeenperformedistheneedtochangealargeportionofacity'sroofing
stocktoproduceatemperaturesignallargeenoughtoobserve—say,atleastafewtenthsofadegreeCelsius.A
smallexperimentencompassingafewbuildingscouldquantifybuildingcoolingenergysavingsthatresult
fromreducingroofsolarheatgain,butwouldnotvalidatethemeteorologicalmodelsthatshowreductions
tocity-wideoutsideairtemperatures.
Ontheotherhand,expenseandlogisticalchallengestendtomakeacity-widetestimpractical.Ademon-
strationwouldneedtobelargerthanafewbuildingsbutsmallerthanthescaleofthecity.Thispaperexplores
whetheraneighborhood-scale(~1km2)demonstrationofcoolroofscouldproduceameasurablereductionto
airtemperature.First,weperformanidealizedheattransferanalysisthatindicatesthatattypicalurbanwind
speeds,airmustflowoverabout1kmofmodifiedsurfacetoyieldameasurablechangeinnear-groundairtem-
perature.Next,weapplyameteorologicalmodeltosimulatetheimpactonairtemperatureofalteringroofal-
bedoacross0.77km2sectionsofanurbanarea.
Weemployahigh-resolutionregionalweatherandclimatemodel(WeatherResearchandForecasting,or
WRF)tosimulateambienttemperaturechangesfromdeploymentofcoolroofstoasmall(0.8km²)neighbor-
hoodofGuangzhou,China.Thesimulationusesasingle-layerurbancanopymodel;itdoesnotincludespecific
buildingcharacteristicsoramultilayerurbancanopymodel.Thiseffortsimplytestswhetherdeployingcool
roofstoanarea~1km2withinthegreaterurbanareaofGuangzhoucouldproducesignificanttemperature
changeswithinasimplemodelingframework.WhilewehavechosentosimulatethecityofGuangzhou,the
generalresults—meaningthechangeindaytimetemperatureperchangeinalbedo—arelikelyapplicableto
many,butnotall,urbanareas.Tosupportthisstatementwepointtotheroughsimilarityinmodeledtemper-
aturesensitivityacrossmanyU.S.cities(MillsteinandMenon,2011;Ban-Weissetal.,2015)aswellasGuang-
zhouChina(Caoetal.,2015).
Thistestisnecessaryasmodelingeffortstothisdatehavegenerallybeendesignedtoevaluatelarge-scale,
city-widecoolroofeffects,buthavenotbeendesignedtoestimatechangesfromneighborhood-scalemodifi-
cations.Thisexerciserepresentsthefirststepsofdevelopingaprogramtodemonstratetheabilityofreflective
surfacestocoolcities.Morecomplexmodeling(suchasworkbyTaleghanietal.,2016)shouldbepursuedto
increasethelikelihoodofthesuccessofanactualdemonstration.Specificsuggestionsforfollow-onmodeling
areincludedintheconcludingsectionofthispaper.
2.Simplifiedheattransferanalysis
Asairflowsfromahigher-albedoneighborhoodtoalower-albedoneighborhood,thestepchangeinsurface
albedoattheinterfacebetweenneighborhoodswillleadtoastepchangeinsurfacetemperature.Herewepres-
entasimpleanalyticalmodeltoestimatetheairtemperaturechangeinducedbyastepchangeinthetemper-
atureofthesurfaceoverwhichitflows.Weareparticularlyinterestedinthechangeinairtemperatureasa
functionofheightaboveground,andofdistancefromthepointofthestepchange.Thisallowsustoestimate
theairflowdistanceneededtoyieldanobservablechangeinairtemperatureat,say,2mabovegroundlevel.It
therebyinformsandcomplementsourmeteorologicalanalysis.
Thissimplifiedanalysisisprovidedonlytoestimatethecharacteristiclengththatairmusttraveloverasur-
faceforastepchangeinsurfacetemperaturetobedetectableataspecifiedheightabovethesurface.Itmodelsa
618 D.Millstein,R.Levinson/UrbanClimate24(2018)616–632
longflatplate,andneglectsvariationsintheelevationoftheurbansurface.Itisananalogtoairflowoveropen
ground.
2.1.Heattransfertheory
Considerafreestreamofairwithuniformvelocityu∞[m/s]anduniformtemperatureTi[K]thatstrikesa
long,thin,andinfinitelywideplateathighertemperatureT [K].Wewanttogaugetheextenttowhichthe
0
airstreamiswarmedbytheplatebyevaluatingtheairtemperatureT(x,y)[K]asafunctionofdistancex[m]
traveledalongtheplateandheighty[m]abovetheplate(Fig.1).
2.1.1.Differentialequation
Intheframeofthefrontoftheairstream,theaircanbeapproximatedasasemi-infinitecolumnwithinitial
condition(IC)
Tðy;t¼0Þ¼T ð1Þ
i
andtwoboundaryconditions(BCs):convectiveheattransferattheplate
(cid:1) (cid:3)
∂T
−k ¼h½T −Tðy¼0;tÞ(cid:2); ð2Þ
e ∂y y¼0 0
andconstanttemperaturehighabovetheplate:
Tðy¼∞;tÞ¼T: ð3Þ
i
Heret=x/u∞[s]istheresidencetimeoftheaircolumnovertheplate,h[W/m2·K]istheconvectiveheat
transfercoefficientattheplate,andk [W/m·K],theair'seffectivethermalconductivity,isthesumofitsmo-
e
lecularthermalconductivitykanditseddythermalconductivityk .Inthemovingframe,theairtemperature
H
T(y,t)isgovernedbythe1-Dheatequation
(cid:4) (cid:5)
∂ ∂t ∂T
k ¼ρc ð4Þ
∂y e∂y p∂t
whereρ[kg/m3]andc [J/kg·K]arethedensityandgravimetricspecificheatofair.
p
Thispartialdifferentialequation(PDE)canbeexpressednondimensionallyas
(cid:4) (cid:5)
∂∂y^ k^e∂∂y^^t ¼∂∂T^^t ð5Þ
Fig.1.Sketchofairstreamtravelingoverflatplate,passingsurfacetemperaturediscontinuityatx=0.
D.Millstein,R.Levinson/UrbanClimate24(2018)616–632 619
wherey^≡y=y ,^t≡t=t ,T^≡ðT−TÞ=ðT −TÞ,and^k ≡k =karethedimensionlessheight,time,temperature,
0 0 i 0 i e e
andeffectivethermalconductivity;y [m]isacharacteristicheight;t ≡y2/α[s]isacharacteristictime;
0 0 0
andα≡k/ρc [m2/s]isthemolecularthermaldiffusivityofair.
p
2.1.2.Characteristicheight
ToapplyanysolutionofEq.(5),wemustestablishacharacteristicheight,y .FollowingKaysandCrawford
0
(1993),wedefineacharacteristicheight
y ¼ν=u ð6Þ
0 t
wherev[m2/s]isthekinematicviscosityofair,
pffiffiffiffiffiffiffiffiffiffi
ut¼u∞ cf=2 ð7Þ
isfrictionvelocity[m/s],andc isthedimensionlessfrictioncoefficient.LetdimensionlesslocalReynold's
f
number.
Rex¼xu∞=ν: ð8Þ
ApplyingtheSchultz-Grunowcorrelationforturbulentflow(106≤Re ≤109),
x
c =2¼0:185ðlog Re Þ−2:584: ð9Þ
f 10 x
Therefore,
ν
y ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi: ð10Þ
0
u∞ 0:185ðlog10RexÞ−2:584
2.1.3.Effectivethermalconductivity
Letε [m2/s]andε [m2/s]representtheeddydiffusivitiesforheatandmomentumtransfer,respectively.
H M
Theair'seddythermalconductivity
(cid:1) (cid:3)
ε
k ≡ρc ε ¼ρc M ð11Þ
H p H p Pr
t
wherethedimensionlessturbulentPrandtlnumberPr≡ε /ε .Inthefullyturbulentregion,
t M H
ε
M¼κy^ ð12Þ
ν
whereκisthedimensionlessvonKármánmixing-lengthconstant(KaysandCrawford,1993).Substituting
thedimensionlessPrandtlnumberPr≡v/αintoEqs.(11)and(12)yields
(cid:1) (cid:3)
kH¼ Pr κy^: ð13Þ
k Pr
t
Therefore
^k ¼ke¼kþkH¼1þby^ ð14Þ
e k k
whereconstant
(cid:1) (cid:3)
Pr
b≡ κ: ð15Þ
Pr
t
620 D.Millstein,R.Levinson/UrbanClimate24(2018)616–632
2.1.4.Convectiveheattransfercoefficient
Thelocalforcedconvectiveheattransfercoefficientoveraflatplateis
h ¼kNu =x ð16Þ
x x
wherekisthethermalconductivityofairandNu isthelocalNusseltnumber.Assumethereisnounheated
x
startinglength.Iftheflowovertheplateislaminar(Re b500,000),
x
Nu ¼0:332Re 1=2Pr1=3: ð17Þ
x x
Iftheflowovertheplateisturbulent(Re N500,000),then
x
Nu ¼0:0296Re 4=5Pr1=3 ð18Þ
x x
(White,1988).Notethatatafree-streamairspeedof2m/s,aninitiallylaminarflowwillbecometurbulent
(i.e.,Re N500,000)within4m.
x
2.1.5.Finalsystem
ThefinaldimensionlessPDEis
" #
∂∂y^ ð1þby^Þ∂∂Ty^^ ¼∂∂T^^t ð19Þ
withdimensionlessIC
(cid:7) (cid:8)
T^ y^;^t¼0 ¼0 ð20Þ
andtwodimensionlessBCs:
!
− ∂T^ ¼Bi h1−T^(cid:7)y^¼0;^t(cid:8)i ð21Þ
∂y^ x
and
T^ðy^¼∞Þ¼0: ð22Þ
ThelocalBiotnumber,Bix=hxy0/k,isevaluatedwiththetransformationx=u∞t.Notethatk,ratherthanke,
appearsinBi becausek =kattheplate.
x e
2.2.Heattransfercalculations
Usingthetransformationsy^¼y=y and^t¼ðxÞ=t ,thedimensionlesstemperatureprofileT^ðx;yÞwascalcu-
latedatheightsupto100mforairflow0ingatfreeu-∞stre0amspeedsof1,2,and4m/soveraplateoflength1,000m.
Eqs.(19)through(22)weresolvednumericallywithMathematica11.0.1.0functionNDSolve,usingthe
methodoflines(reductionofthePDEtoacoupledsetofordinarydifferentialequationsintime).Thecharac-
teristicheighty wasevaluatedhalfwayalongthelengthoftheplate(x=500m),andtheconstanttempera-
0
tureboundaryconditionspecifiedinEq.(22)wasenforcedatthetopofthemodeleddomain(y=100m).The
maximumintervalindimensionlessheighty^wassettolimitto0.01mthemaximumintervalindimensional
heighty.FollowingKaysandCrawford(1993),themixing-lengthconstantκwassetto0.41,andtheturbulent
PrandtlnumberPr wassetto0.85.Themolecularpropertiesofairwereevaluatedat300Kand1atm.
t
2.3.Heattransferresults
Atawindspeedof2m,thedimensionlessairtemperatureT^ðx;yÞ2mabovetheplateisabout10−7at
10m,0.025at100m,and0.207at1,000malongtheplate(Fig.2).Dimensionlessairtemperatureversus
D.Millstein,R.Levinson/UrbanClimate24(2018)616–632 621
dimensionalheight(upto100m)anddimensionaldistance(upto1,000m)istabulatedinAppendixC
(Supplementarydata).
Toapplythisoutcome,consideranairstreamthathasflowedforaverylongdistanceovera“cool”ground
surfacewithhighalbedo(ρ =0.90)beforestrikingawarmerplateofloweralbedo(ρ =0.60).Notetheal-
i 0
bedochangehere(0.30)issimilartotheaveragegridcellalbedochangefoundinthemeteorologicalmodeling
section(0.28),butofoppositesign;themagnitudeofairtemperaturechangeisindependentofthesignofthe
surfacetemperaturechange.WeassumethatonatypicalsummerdayinGuangzhou,thepeaksolarirradiance
isabout800W/m2.Assumethatthesmallsolarheatgainofthecoolgroundsurface(about80W/m2)isfully
dissipatedviathermalradiativeexchangewiththesky.Thegroundsurfacewillbeatambientnear-groundair
temperature(say,T =310K),andtheaircolumnstrikingtheleadingedgeoftheplatecanbeassigneduni-
i
forminitialtemperatureT(x=0,y)=T.
i
Underlow(0to2m/s),medium(2to6m/s),andhigh(6to10m/s)windconditions,ASTMStandard
E1980-11:StandardPracticeforCalculatingSolarReflectanceIndexofHorizontalandLow-SlopedOpaqueSur-
faces(ASTM,2011)assignstoahorizontalsurfaceaconvectiveheattransfercoefficientof5,12,or30W/m²·K,
respectively.Whensolarirradianceis800W/m2andconductionthroughthesurfaceiszero,thesteady-state
surfacetemperaturebalanceexpressedinEq.(1)ofASTME1980predictsthatasurfacewithsolarreflectance
0.60andthermalemittance0.90willbe20.3,12.9,or6.6Kwarmerthananotherwiseidenticalsurfacewith
solarreflectance0.30(Levinson,2016).Ofcourse,someheatwillbeconductedintothesurface,diminishing
temperaturechangesinducedbysolarheatgain.Hence,weassumethatatthewindspeedof2m/susedto
computethedimensionlessairtemperatureshowninFig.2,theplateisabout10Kwarmerthanthelong
coolgroundsurface.1
Iftheplateis10Kwarmerthanthegroundsurface(T −T=10K),theairtemperatureriseT(x,y)−T ata
0 i i
heightof2mwillbeabout10−7×10K=0.00Kat10m,0.025×10K=0.25Kat100m,and0.207×10K=
2.1Kat1,000malongtheplate.Forcomparisontothemodelingresultspresentedinthenextsection,welookat
adistanceof440malongtheplate.Thisishalfthewidthofthealteredneighborhood,representingtheaverage
temperaturechangeratherthanthetemperaturechangeatthedownwindedgeofthealteredneighborhood.At
440malongand2mabovetheplate,theairtemperaturerisewillbeabout0.131×10K=1.3K.Iftheplateis
10Kcoolerthantheground,1.3Kwillbetheairtemperaturereductionat440malongand2mabovetheplate.
3.Modelingmethodology
Tomeasuretheeffectofdeployingcoolroofsinacity,onewouldneedtomeasuretheoutdoorairtemper-
atureat2mabovegroundlevel(AGL)inatleasttwoneighborhoodsofacitybeforeandaftercoolroofshave
beendeployedinoneoftheneighborhoods.Withoutanyalbedochangewewouldexpectthetemperaturedif-
ferencebetweentheneighborhoodstobeconsistentduringthebeforeandafterperiods,especiallyifthetwo
periodsoccurredinthesameyearandseason.However,ifwealterthealbedoofoneneighborhood(neighbor-
hoodA)andnottheother(neighborhoodB),wewouldobserveacoolroofeffectonairtemperatureifthetem-
peraturedifference(A–B) wassignificantlygreaterthanthetemperaturedifference(A–B) ,
period1 period2
assumingperiod2occursafterthedeploymentofcoolroofs.Wefollowedthisapproachtosimulateaneigh-
borhood-scalecoolroofdemonstration.Thisisdifferentfrompastmeteorologicalmodelingeffortsdesigned
toassesstheeffectsofcoolroofdeploymentonoutdoorairtemperature.Thelattercompareamodifiedrun
toacontrolrun,bothtypicallyperformedoverthesametimeperiod.
3.1.Modelingsetup
Themeteorologicalsimulations,includingallsourcesofinputdataandphysicalparameterizations,were
basedonthemodelingsetupdescribedbyCaoetal.(2015).WRFversion3.6wasused.Notethatrecentre-
leasestoWRFhavecontainedupdatestotheurbancanopymodelwhichcouldleadtosomedifferencesin
theresultsiftheanalysiswasrerunwiththeupdatedcode.Thenewreleasesincludeupdatesrelatedtohy-
drologicalprocesseswithintheurbancanopymodel,includingspecificationofurbanirrigationandanthropo-
geniclatentheatoptions(Yangetal.,2015),evaporationoverimpervioussurfaces,andbugfixes.Wehaveno
1 Thevariationofbuildingenvelopesurfacetemperaturewithalbedoand/orwindspeedisfurtherdiscussedbyCostanzoetal.(2014),
PradoandFerreira(2005),andMirsadeghietal.(2013).
6
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6
1
6
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6
3
2
Fig.2.Variationwithdimensionaldistancealongplate(x)anddimensionalheightaboveplate(y)ofthedimensionlesstemperatureT^ðx;yÞofairflowingat2m/sovera1kmlongflatplate.Atleft,general
contours;atright,valuesatheightsof1,2,and5m.
D.Millstein,R.Levinson/UrbanClimate24(2018)616–632 623
reasontothinktheprimaryconclusionswederivefromourmodelingwouldchangeifrerunwiththenewer
code.Themodelingdomain(showninFig.3)containedfivenestsandwascenteredonthegreaterurbanarea
ofGuangzhou.Theoutermostdomainwascenteredat23.17°Nand113.33°E,withhorizontaldimensionsof
2,520×2,520kmandgridcelldimensionsof36×36km.Thefournesteddomainshadgridcellswithhori-
zontalresolutionsof12,4,1.3,and0.44kmrespectively.
3.2.Modelingscenariodesign
Inthefifth,mostdeeplynesteddomain(resolutionof0.44km)wechoseaneighborhood,hereaftercalled
“COOL”,inwhichtomodelthereplacementofstandardroofswithcoolroofs(Fig.3).Itisimportanttonotethat
innowaywasthisparticularneighborhoodeverconsideredforaspecificfieldstudy;thislocationisjustnear
thecenterofthegreaterGuangzhouurbanarea,andhasrelativelyflatandhomogeneousurbanterrain.COOLis
specifiedasatwo-by-twoblockofgridcellswithacombinedwidthof0.88kmandcombinedareaof0.77km2.
“CONTROL”representsunalteredareasofthecityandiscomprisedofthreenon-contiguousgridcellsthatsim-
ulatetheplacementofthreeindependenttemperaturemonitors.Alltemperaturecomparisonsdescribedinthe
resultssectionweremadebetweentheaveragetemperaturesacrossthefourgridcellsinCOOLversusthe
averagetemperatureacrossthethreegridcellsinCONTROL.Werepeatedthissameexperimentaldesign
fourtimes,keepingthesametimeframeanddomaindefinitionbutchoosingdifferentCONTROLandCOOL
areas.Wechosefournon-contiguouscellsnumbered1to4.Inthefirsttrial,wespecifiedCOOLasatwo-by-
twoblockofcellsinwhichtheupperleftcornerofthisblockiscell1.Theremainingcells2,3,and4are
CONTROL.Inthenexttrial,theCOOLblockwasmovedsoitsupperleftcornerisatcell2andcells1,3,and4
wereCONTROL.Thisprocesswasrepeatedatotaloffourtimes,sothattheupperleftcornerofCOOLcould
belocated,inturn,atcell1,2,3,or4.Thus,eachlocationhighlightedinFig.3wassimulatedseparatelyasa
COOLareaandasaCONTROLarea.WerefertoeachscenariobytherelativelocationoftheCOOLarea.Forex-
ample,Fig.3showsthe“upper-leftcorner”scenario.
Wesimulated20daysinJune2005,and20daysinJuly2005.TheJunesimulationrepresentedtheperiod
priortoanycoolroofdeployment,andtheJulyperiodrepresentedtheperiodpostdeployment,inwhichthe
fourcellswerealteredtosimulatetheCOOLneighborhood.TheJuneandJulysimulationswerenotruncontin-
uously;instead,aseriesoffivemodelrunswasmadeforeachmonth,JuneandJuly.Eachruncoveredfivedays,
overlappingthesubsequentrunbyaday.Thispermittedthefirstdayofeachmodelruntoberemovedasspin-
uptime.Intotal20dayspermonth,the6ththroughthe25thofJuneandJuly,wereavailabletobeanalyzed.We
choose5-daymodelrunstohavesimulationssimilarinlengthtotheepisodesmodeledbyCaoetal.(2015).
NotethatCaoetal.(2015)includedacomparisonofmodeledandobservedtemperatures.Werepeatedthe
JulymodelrunsfourtimestosimulatethelocationoftheCOOLneighborhoodineachcorner.Thetime-inde-
pendentparameters(e.g.,theland-usetypesandtheorographiccharacterization)fortheJulyrunwerekept
exactlythesameastheJunerun.TheexceptiontothisistheroofalbedoinCOOL,whichwasincreasedto
0.65from0.12.Thisraisedthegrid-cellaveragesurfacealbedoinCOOLto0.39,up0.28fromtheCONTROL
grid-cellaverageof0.11.
3.3.Modelingresultsanddiscussion
FollowingCaoetal.(2015),weexpecttoseethelargestsignalofthecoolroofeffectduringtheday.This
resultisapparentinFigs.4a,A1,A2,andA3.Specifically,weseethatwhileJunedaytimepeaktemperaturesin
COOLoftenequalorexceedthoseinCONTROL,nearlyallJulydaytimepeaktemperaturesinCOOLarelower
thanthoseinCONTROL.Thiscoolroofeffectisalsoevidentwhencomparingmapsofaveragetemperaturesat
2pmlocalstandardtime(LST)forJuneandJuly(Fig.5).
Thecoolroofeffectbecomesevenclearerwhenweexaminetheaveragediurnalcycleoftemperaturedif-
ferencesbetweenCOOLandCONTROL.Figs.6andB1showthatthestrongestcoolroofsignaloccursduring
middaywithpeaktemperaturedifferences(COOL–CONTROL)reachingabout-0.8°C.Wenotethecooling
seeninFig.4looksremarkablysimilartotheshapeandmagnitudeofcoolingshowninFig.4aofCaoetal.
(2015).ThissimilarityoccursdespitethefactthatCaoetal.(2015)modeledcoolingacrossthegreaterGuang-
zhouurbanareaandcomparedscenariosofthesametimeframe,butwithdifferentalbedos.
Finally, we measure the statistical significance of these findings by comparing the average daytime
(10:00AMto4:00PMLST)temperaturedifference(COOL-CONTROL).Wecalculated25daytimetemperature
624 D.Millstein,R.Levinson/UrbanClimate24(2018)616–632
A
B
Fig.3.(A)ThefivenestsofthemodeldomaincenteredonGuangzhou,China.(B)GoogleEarthimageofthefifthmodeldomain,including
theCOOLandCONTROLareasfortheupperleftcornerscenario.
D.Millstein,R.Levinson/UrbanClimate24(2018)616–632 625
A
B
Fig.4.COOLandCONTROLhourlyoutdoorairtemperaturesat2mAGLin(A)Juneand(B)July.
differencesforeachmonth,findingaverageandstandarddeviationvaluesof0.1±0.35°CinJuneand-0.5±
0.39°CinJulyfortheupper-leftcornerscenario.Asexpected,becauseCOOLandCONTROLsharethesameroof
albedoinJunebuthavedifferentroofalbedosinJuly,theairtemperaturedifferencebetweenCOOLand
CONTROLissignificantatthe95%levelonlyforJuly.WefoundsimilarresultsforallthreeoftheotherCOOL
scenarios(Table1).
Thetemperaturereductionfoundintheidealizedheattransferanalysis(1.3°C)islargerthanthat
modeledhere(0.5±0.39°C),butofthesameorderofmagnitude.
Whilethecoolroofeffectfoundheresuggeststhatthisexperimentaldesignwouldprovideausefulfield
testoftheabilityofcoolroofstoinduceurbanairtemperaturechange,theoverallmodelingresultsalsoillus-
tratepotentialchallengestoanyfuturefieldexperiment.Forexample,althoughitdidnotobscureresultsinthis
case,thespatialpatternofrelativetemperatureswasnotconstantbetweentimeperiods(Fig.5),raisingthe
possibilitythatothertimeperiodsorlocationsmaynotleadtosuchaclearcoolroofeffect.Anotherpotential
concernisthatbecauseonlyfourgridcellswereusedinthismodelingefforttorepresentCOOL,intra-cellpro-
cessesmightswampordegradethesignalfoundhere.
OuranalysisusedWRF's"2-meter"outputtoobtainanaverageairtemperatureacrosseachgridcell.The
2-metertemperaturecombinesthetemperaturesabovebothstreetsandroofswhileathermometerwould
measuretemperatureeitherinanurbancanyonoraboveabuildingroof.Thus,torecreatetheexperiment
simulatedhere,airtemperaturewouldneedtobemeasuredinboththeurbancanyonandoverrooftops.