Effects of Surface Heat and Moisture Exchange on ARW-WRF Warm-Season Precipitation

23 Pages·2011·9.22 MB·English

VOLUME26 WEATHER AND FORECASTING FEBRUARY2011
Effects of Surface Heat and Moisture Exchange on ARW-WRF Warm-Season
Precipitation Forecasts over the Central United States
S.B.TRIER,M.A.LEMONE,F.CHEN,ANDK.W.MANNING
NationalCenterforAtmosphericResearch,*Boulder,Colorado
(Manuscriptreceived25March2010,infinalform29July2010)
ABSTRACT
Theevolutionofthedaytimeplanetaryboundarylayer(PBL)anditsassociationwithwarm-seasonpre-
cipitationisstronglyimpactedbyland–atmosphereheatandmoistureexchange(hereaftersurfaceexchange).
However,substantialuncertaintyexistsintheparameterizationofthesurfaceexchangeinnumericalweather
prediction (NWP) models. In the current study, the authors examine 0–24-h convection-permitting fore-
casts with different surface exchange strengths for a 6-day period during the International HO Project
2
(IHOP_2002). Results indicate sensitivity in the timing of simulated afternoon convection initiation and
subsequentprecipitationamountstovariationsinsurfaceexchangestrength.Convectioninitiationinsimu-
lationswithweaksurfaceexchangewasdelayedby2–3hcomparedtosimulationswithstrongsurfaceex-
change,andarea-averagedtotalprecipitationamountswerelessbyuptoafactorof2.Overthewesternhigh
plains(1058–1008Wlongitude),wheredeepconvectionislocallygenerated,simulationsusingaformulation
forsurfaceexchangethatvariedwiththevegetationcategory(height)producedarea-averageddiurnalcycles
offorecastedprecipitationamountsinbetteragreementwithobservationsthansimulationsthatusedthe
currentAdvancedResearchWeatherResearchandForecastingModel(ARW-WRF)formulation.Parcel
theoryisusedtodiagnosemechanismsbywhichdifferencesinsurfaceexchangeinfluenceconvectioniniti-
ationinindividualcasestudies.Themorerapidinitiationinsimulationswithstrongsurfaceexchangeresults
fromamorerapidremovalofnegativebuoyancybeneaththeleveloffreeconvection,whicharisesprimarily
fromgreaterPBLwarming.
1. Introduction Recentsimulations(e.g.,Trieretal.2004;Holtetal.
2006)withnumericalweatherprediction(NWP)models
Land surface conditions including soil moisture and
havefoundsensitivitiesinconvectioninitiation(CI)and
green vegetation fraction can impact deep convective
quantitative precipitation forecasts (QPFs) related to
precipitation(e.g.,Pielke2001).Thisresultsfromtheir
theseeffectsofthelandsurface.However,amajorsource
effect on the daytime sensible and latent heat fluxes,
of uncertainty is the strength of the bulk aerodynamic
whichinfluenceslocalconditionalinstability(e.g.,Betts
coefficients for heat and moisture calculated in surface
and Ball 1995; James et al. 2009) and mesoscale circu-
layerparameterizationsofsuchmodels(e.g.,Chenetal.
lations arising from surface heterogeneity (e.g., Pielke
1997). In this study, we examine the role of the related
and Segal 1986; Lanicci et al. 1987; Segal and Arritt
surface exchange strength on convection initiation and
1992).
short-range(e.g.,0–24 h)QPFs.
Overalleffectsofland–atmospherecouplingonwarm-
*TheNationalCenterforAtmosphericResearchissponsored seasonprecipitation have also been widely explored in
bytheNationalScienceFoundation.Anyopinions,findings,con- atmospheric general circulation models. There, land–
clusions or recommendations expressed in this publication are
atmosphere coupling on seasonal time scales has been
thoseoftheauthorsanddonotnecessarilyreflecttheviewsofthe
establishedasanimportantfactordeterminingpredict-
NationalScienceFoundation.
abilityincertainregions(e.g.,Kosteretal.2004,2006).
Similar studies for 0–24-h forecasts are less common,
Correspondingauthoraddress:StanleyB.Trier,NationalCenter
which maybepartlyrelatedtotherelativelypoorpre-
for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307-
dictability of convective precipitation on these shorter
3000.
E-mail:[email protected] timescales(FritschandCarbone2004).
DOI:10.1175/2010WAF2222426.1
(cid:2)2011AmericanMeteorologicalSociety 3
4 WEATHER AND FORECASTING VOLUME26
It has been difficult to objectively demonstrate that developmentofdeepconvection.TheNoahlandsurface
high-resolution NWP models do a better job of pre- model (LSM; Ek et al. 2003) provides lower-boundary
dictingconvectiveprecipitationthanthecoarseroper- conditionsforthePBLschemeinARW-WRF,whichde-
ationalmodelsdo.However,comparativestudiesusing pend on the surface fluxes of heat H and moisture LE,
both enhanced convection-permitting grids with Dx # definedinthebulktransferformulas,
4 km and coarser resolutions that rely upon cumulus
parameterizations (Done et al. 2004; Kain et al. 2006; H5rc C U(T (cid:2)T(cid:2)gDz) and (1a)
p H s
Weismanetal.2008)havediscussedhowimprovements
intherealismofconvectioninitiationandthemodeof LE5rdLyCHU(qs(cid:2)q). (1b)
subsequentconvectionorganizationwithexplicitmodels
providesvalue-addedbenefitstoweatherforecasters.This In the above equations, rd and r are, respectively, the
motivates us to use a convection-permitting model to densityofdryandmoistair;cpisthespecificheatforair
study impacts of uncertainties in the surface exchange atconstantpressure;Lyisthelatentheatofvaporization;
onconvectioninitiationandsubsequentprecipitationin U,T,andqarethemeanwindspeed,temperature, and
short-rangeforecasts. specifichumidityatthefirstmodellevel,respectively;gDz
We examine multiple 0–24-h forecasts for a 6-day is an adiabatic correction to the temperature; Ts and qs
‘‘retrospective’’ period during the International H O arethetemperatureandspecifichumidityatthesurface
2
Project(IHOP_2002)fieldcampaign(Weckwerthetal. (whoselevelisthatoftheroughnesslengthforheatand
2004), where deep convection was particularly active moisturez0t);andCHisthebulkaerodynamiccoefficient
over the Great Plains of the United States (section 3). forheat(1a)andmoisture(1b).Toavoidsingularitiesin
Ourstudyispartofabroader,consolidatedeffortatthe convectivelyunstablesituations(›T/›z. g),weusethe
NationalCenterforAtmosphericResearch(NCAR)to Beljaars(1995)correction,asdescribedinJanjic(1996b)
improveshort-termexplicitprecipitationprediction(STEP); andreferencestherein.
throughexaminingdifferentcomponentsoftheAdvanced In(1a)and(1b),largerCHresultsinlargerfluxesfor
Research Weather Research and Forecasting Model thesameverticaldifferencesof(Ts2T)and(qs2q).
(ARW-WRF;Skamarocketal.2005)forthisretrospective In the surface layer parameterization, CH is approxi-
period. Past studies of warm-season precipitation have mated to be the same for heat and moisture and is
shownparticularsensitivitytolandsurfaceprocessesover estimated from the Monin–Obukhov similarity theory.
the southern plains region on longer time scales (e.g., AnapproximateformofEq.(A4)inChenetal.(1997)
Koster et al. 2004). Thus, we anticipate the represen- isused,
tation of the surface exchange could impact shorter-
rangeforecastsinthisregionaswell. k2/R
Theorganizationofthepaperisasfollows.Insection2, CH5 (cid:6) (cid:2) z (cid:3) (cid:4)z(cid:5)(cid:7)(cid:6) (cid:2)z(cid:3) (cid:4)z(cid:5)(cid:7), (2)
ln (cid:2)C ln (cid:2)C
wereviewhowtheland–atmosphereexchangeishandled z m L z t L
0m 0t
in ARW-WRF. Section 3 provides an overview of our
6-day retrospective period and its contrasting precipi- wherek50.4isthevonKa´rma´nconstant,Ristheratio
tationeventsalongwithadescription of the model and of the exchange coefficients for momentum and heat
experimentdesign.Thesensitivityofthesimulatedsur- under neutral stability (assumed to be unity), and the
face fluxes, planetary boundary layer (PBL), and pre- functionsC andC arecorrectionsforthenear-surface
m t
cipitation to the strength of the parameterized surface atmosphericstabilityz/L,wherezisthegeometricheight,
exchange is examined and compared with observations ListheObukhovlength,andz andz are,respectively,
0m 0t
insection4.Weemphasizehowthestrengthofthesurface the roughness lengths for momentum and scalars (e.g.,
exchangecaninfluenceconvectioninitiationandprecip- heatandmoisture). Thez isdefinedas theheightat
0m
itationforecastsinselectedindividualcaseswithdifferent andbelowwhichthemeanwindspeedbecomeszeroand
synopticsituations,andexaminemechanismsbywhich is a function of the vegetation category with values of
thisoccurs,insection5. about 0.05–0.10 m for grasslands to about 1 m for for-
ested regions. The z , below which vertical transfer is
0t
throughmoleculardiffusionandabovewhichmixingby
2. Surfaceexchangeprocessesinthe
aircurrentsdominates,istypically,z butislesswell-
ARW-WRF–Noahmodel 0m
known(e.g.,Chenetal.1997;ChenandZhang2009).
The strength of the surface exchange is an impor- TheradiativeskintemperaturecalculatedintheLSM,
tantfactorinthedaytimegrowthandthermodynamic T5T,isusedasalower-boundarycondition(atz5z )
s 0t
destabilization of the PBL, which often leads to the for the surface layer parameterization in which C is
H
FEBRUARY2011 TRIER ET AL. 5
calculated.Here,z isdeterminedbytheZilitinkevich
0t
(1995)equation,
rffiuffiffiffiffiffizffiffiffiffiffiffiffi!
* 0m
z 5z exp (cid:2)kC , (3)
0t 0m zil n
as describedby Janjic (1996a). In(3), u is thefriction
*
velocity(i.e.,squarerootofthesurfacestress),n isthe
kinematicmolecularviscosityofair(;1.531025m2s21),
andC isanempiricalcoefficient.Inthecurrentversions
zil
of ARW-WRF, C is assigned a default value of 0.1
zil
basedonearliercomparisonsofmodelresultsandfield
data(Chenetal.1997).
Equation(3)relatesz andz ,whichareimportant
0t 0m
indeterminingC [Eq.(2)]and,throughEqs.(1a)and
H
(1b), the strength of the surface fluxes. From Eq. (3),
estimates of z are influenced by the appropriateness FIG.1.EffectofCzil(xaxis)onthecouplingstrengthrcpCHU
0t (yaxis)forsurfacefluxesalongtheIHOP_2002westernflighttrack
in choice of z0m, the accuracy of u* obtained from the of29May2002basedonofflineNoahLSMrunsforthetimethe
surfacelayerparameterization,andthespecificationof aircraftwasflying(;1700–2100UTC).Eachpointrepresentsarun
C .Sincesurfaceroughness(andwinddrag)isstrongly initializedusingtheNCARHRLDAS(Chenetal.2007)withdif-
zil
ferentsoilmoistureandgreenvegetationfractionvaluesasinput.
dependentonvegetationheight,z inNWPmodelsis
0m AdaptedfromLeMoneetal.(2008).
oftenspecifiedasafunctionofthevegetationcategory
alone. However, when this approach was adopted by
ChenandZhang(2009),C variationsofapproximately 3. ExperimentDesign
zil
two orders of magnitude (0.01 to 1.0) were needed to
a. The1200UTC10June–1200UTC16June2002
explainC variationsderivedusingEq.(1a)overava-
H IHOPretrospectiveperiod
riety of vegetation types (including multiple types of
grasslands,croplands,forests,andshrubland). The 6-day retrospective was an active precipitation
LeMone et al. (2008) compared observations of sur- periodhavingdiverseprecipitationsystemswithdiffer-
facefluxesatthreesitesalongaflighttrackinthewestern ent forcing mechanisms over the IHOP region shown
part of the IHOP region with results obtained from inFig.2a.Figure3indicatesmesoscaleconvectionthat
varyinginputs(soilmoisture,greenvegetationfraction, organizedalongquasi-stationarysurfaceboundariessuch
and C ) to the Noah LSM–WRF surface–PBL pa- as drylines and frontal zones (days 1–3) and a particu-
zil
rameterization run offline (uncoupled with the re- larly large rain event (day 6) associated with a rapidly
mainderofARW-WRF).Theyfoundthatthecoupling moving midtropospheric short wave and cold front at
strengthforfluxes, rc C U,wasverysensitiveto C , the end of the period. There was also a relatively pre-
p H zil
especiallyatlowvaluesofC (Fig.1).Theirresultsin cipitation free day (day 5) following a frontal passage
zil
Fig.1arefromanIHOPfair-weatherday,wheremea- in which the convection was orographically generated
surements of U, r, and c in Eq. (1a) were roughly (Fig.3)andlimitedtothewesternpartoftheIHOPre-
p
constant,sovariationsalongtheyaxisoccurprimarily gion (Fig. 2). Apart from days that had strong synoptic
fromchangesinC . forcing(days4and6),convectiontypicallyinitiateddur-
H
Theaboveresultsindicateconsiderableuncertainty ing the late afternoon with maximum domain-averaged
in the bulk aerodynamic coefficients for heat and precipitationamountsinthelateevening(Fig.3).
moisture that influence surface exchange strength.
b. Numericalmodel
These results further suggest that the sensitivity of
convective precipitation forecasts to possible ranges Our simulations utilize ARW-WRF (version 2) with
in surface exchange strength can be explored in a asingle8003750horizontaldomain(Fig.2)and3-km
particularly simple fashion by varying the empirical horizontalgridspacing.Thishorizontalresolutioncap-
parameterC inmodelsthatemployEq.(3)intheir tures the salient mesoscale aspects of convection with-
zil
surface layer parameterization. This has motivated outtheneedforcumulusparameterization.Thevertical
ourdesignofnumericalexperimentsdiscussedinthe gridcontains42levelsthatarestretchedtoprovideen-
followingsection. hancedresolutionwithinthePBL(whereDz,100 m)
6 WEATHER AND FORECASTING VOLUME26
FIG.2.(a)MapofUSGS24-categorylanduseoverthemodeldomainforsimulationsde-
scribedinsection3.Landusecategoriesthatdonotoccuroverthesimulationdomainare
markedwithanasteriskinthelegendatright.ThewhiteinnerrectangledenotestheIHOP
regionofinterestinthecurrentstudy.ThisistheregionforwhichareaaveragesinFig.3are
computed.(b)ValuesofC (seetext)forthesimulationswhereitisafunctionofthevege-
zil
tationtypesin(a)throughEq.(4).BothS2andS9arethelocationsofIHOPsurfaceflux
stationswherecorrespondingmodeloutputiscomparedinFig.5.
and ;1-km spacing at the model top near 50 hPa. All Other physical parameterizations include the Rapid
simulationsusetheThompsonetal.(2008)bulkmicro- RadiativeTransferModel(RRTM)longwave(Mlawer
physicalparameterization,whichpredictscloudwater, et al. 1997) and Dudhia (1989) shortwave radiation
cloudice,rain,snow,andgraupelhydrometeorspecies. schemes.
FEBRUARY2011 TRIER ET AL. 7
FIG.3.Timeseriesof Stage4precipitationobservationsduringthe 6-dayIHOP_2002
retrospectiveperiodareaaveragedovertheinnerrectangularregioninFig.2.Thedomi-
nantforcingsareannotatedforindicatedevents.Thedarkerannotationsandarrowsin-
dicatethespecificthreecasesexaminedinsection5.Localdaylighttime(LDT)overthis
regionisUTC–5to6h.
The PBL parameterization (Janjic 1990, 1994, 2001) offlinebutonthesame3-kmhorizontalgridastheARW-
usedinourprimarysimulations,referredtohereafteras WRFsimulationsforan18-monthspinupperiodpriorto
the Mellor–Yamada–Jancic (MYJ) PBL scheme, pre- eachforecast.Thislandsurfaceinitializationusesa vari-
dicts turbulent kinetic energy (TKE) and governs ver- ety of observed and analyzed conditions including the
ticalmixingbetweenmodellayers.LocalforcingofTKE following:1)theNationalWeatherService(NWS)Office
isprovided by shear production, buoyancyproduction, ofHydrologyStage4rainfalldataona4-kmnationalgrid
anddissipationterms.Horizontalmixingisdetermined (Fultonetal.1998);2)0.58hourlydownwardsolarradia-
usingaSmagorinskyfirst-orderclosurediscussedin4.1.3 tionderivedfromGeostationaryOperationalEnvironmen-
ofSkamarocketal.(2005). talSatellite-8and-9(GOES-8andGOES-9)asdescribed
The initial conditions for ARW-WRF are obtained byPinkeretal.(2002);3)near-surfaceatmospherictem-
fromtheNationalCentersforEnvironmentalPredic- perature, humidity, wind, downwardlongwave radiation,
tion (NCEP) Environmental Data Assimilation Sys- and surface pressure from 3-hourly EDAS analyses; 4)
tem (EDAS) analyses, which have a horizontal grid 1-kmhorizontalresolutionU.S.GeologicalSurvey(USGS)
spacingof;40 km.Lateralboundaryconditionswitha 24-categorylanduseand1-kmhorizontalresolutionstate
3-hfrequencyaregeneratedfromcorrespondingopera- soil geographic soil texture maps; and 5) 0.158 monthly
tionalEtaModelforthesametimes. satellite-derived green vegetation fraction based on 5-yr
This atmospheric model is coupled with the Noah averages(GutmanandIgnatov1997).
LSM(Eketal.2003).TheLSMhasasinglevegetation
c. Simulations
canopylayerandpredictsvolumetricsoilmoistureand
temperature in four soil layers. The depths of the soil Weanalyzesetsofsimulationsdesignedtoexaminethe
layersaresequentially0.1,0.3,0.6,and1.0 m.Theroot effect of the strength of the surface heat–moisture ex-
zoneiscontainedintheupper1 m(top-threelayers). change on daytime PBL evolution, convection initiation,
The initial land surface conditions are supplied by the and 0–24-h QPF over the IHOP region. A set of three
NCARhigh-resolutionlandsurfacedataassimilationsys- experiments(Table1)useconstantvaluesofC andspan
zil
tem (HRLDAS). HRLDAS (Chen et al. 2007) is run a range of values consistent with results from empirical
TABLE1.Listofnumericalsimulationsdiscussedinthepaper.
C ParameterValue PBLscheme Remarks
zil
Strongsurfaceexchange 0.01 MYJ All6days
Weaksurfaceexchange 1.0 MYJ All6days
WRFdefault 0.1 MYJ All6days
Variablesurfaceexchange FunctionofvegetationtypeaccordingtoEq.(4) MYJ All6days
Strongsurfaceexchange 0.01 YSU Day5only
Weaksurfaceexchange 1.0 YSU Day5only
8 WEATHER AND FORECASTING VOLUME26
studies (Chen et al. 1997; Chen and Zhang 2009). These
includesimulationswithC 50.01andC 51.0,which
zil zil
arerespectivelyreferredtoasthestrongsurfaceexchange
and weak surface exchange runs. Simulations with the
standardC valueusedinrecentversionsofARW-WRF
zil
of0.1arereferredtoastheWRFdefaultruns.Weanalyze
a fourth set of simulations where C varies across the
zil
domainasafunctionofmomentumroughnesslength,
C 510(cid:2)4.0z0m, (4)
zil
basedonempiricalrelationshipsbetweenvegetationtypes
andC discussedinChenandZhang(2009).Thesesim-
H
ulations are referred to as the variable surface exchange
runs(Table1).OvermostoftheIHOPregion,thevariable
C lies between the WRF default value of 0.1 and the
zil
weakexchangevalueof1.0(Fig.2b).Theserelativelylarge
C valuesareconsistentwiththerelativelysmallrough-
zil
ness lengths of the dominant grassland, cropland, and
shrublandvegetationtypes(Fig.2a).Inurbanareasandin
some forested regions near the edges of the IHOP sub-
domain(Fig.2a),includingtheOzarkMountainsandthe
easternedgeoftheRockyMountains,C valuesareap-
zil
proximately at or less than the strong exchange value of
0.01(Fig.2b).
Itshouldbenoted,however,thatevenintheconstant
C runs, C varies spatially, primarily through its de-
zil H
pendence on z (2), which is a function of vegetation
0m
category. These interdomain variations of C for the
H
constantC runsarestillmuchlessthanthosethatoc-
zil
cur in simulations in which C is allowed to vary ac-
zil
cordingto(4).Eachofthefoursetsofsimulationswith
different specifications of C (and thus C ) comprise
zil H
24-hforecastsinitializedat1200UTCforeachofthesix
individualdaysoftheretrospectiveperiod(section3a).
To explore possible sensitivities to forecast length and
initialization time, 12–36-h forecasts initialized at
0000 UTC werecomparedtotheir 0–24-hcounterparts
(i.e.,samevalidtimes)initializedat1200UTC.
Theeffectsofsurfaceexchangestrengthontheevolu-
tionofthedaytimePBLandsubsequentprecipitationcan
beinfluencedbythechoiceofmodelPBLparameteriza-
tion.Weexplorethissensitivitybyperformingsimulations
thatusetheYonseiUniversity(YSU)PBLschemebutare

1900 UTC (1300–1400 LDT) 14 Jun 2002 for the simulation in
which C is based on vegetation type (section 3c). The IHOP
zil
surfacefluxstationsS2andS9forwhichsimulatedandobserved
fluxesarepresentedinFig.5areannotatedasinFig.2.TheWand
FIG. 4. (a) Volumetric soil moisture in the top 0.1-m layer, E partitioned rectangles denote subdomains for area averages
(b) surfacesensibleheat flux,and (c) surfacelatentheat flux at
presentedinsubsequentfiguresanddiscussedinthetext.
FEBRUARY2011 TRIER ET AL. 9
FIG.5.(a)–(d)ComparisonsofobservedandsimulatedsurfacefluxesatIHOPsurfacefluxstationlocationsS2and
S9(locationsshowninFigs.2and4)forthedaytimeandeveningportionofday5(1300UTC14Junto0400UTC
15Jun)oftheSTEPIHOP_2002retrospectiveperiod.Themodellandusecategories(Fig.2a)forstations2and9are
grassland/cropmosaicandgrassland,respectively.LDTisUTC25h.
otherwise identical to the strong (C 5 0.01) and weak from predominately sensible H to latent LE fluxes from
zil
(C 51.0) coupling runs described above (Table 1). In westtoeastacrosstheIHOPregion(cf.Figs.4band4c).
zil
contrasttotheMYJPBLscheme,theYSUscheme(Noh Though representativeness issues can complicate model
etal.2003;Hongetal.2006)allowsnonlocalverticalmix- comparisons with individual observation sites, the selec-
ing.ComparisonsaremadewiththeMYJsimulationsfor tionofstationswithsimilarobservedandmodellanduse
day5(1200UTC14June–1200UTC15June).Onthisday, types (grasslands) and cloudless conditions may mitigate
afternoon cloudiness was less widespread than on other suchdifficultiestosomedegree.Amodelcomparisonwith
days, which affords a cleaner comparison of surface ex- stationS2(Fig.5a)suggestsapositivebiasinthestrength
changeeffectsontheafternoonPBLandsubsequentpre- of simulated H in the western IHOP region, with values
cipitation.ThegenerallackofcloudsovertheIHOPregion fromtheweaksurfaceexchangerunmostcloselymatching
onthisdayisreflectedinthewidespreadstrongearlyaf- observations. In contrast, the observed LE lies in the
ternoonsurfacefluxes(Figs.4band4c). middleoftherangeofsimulatedLEatboththewestern
andeasternedgesoftheregion(Figs.5band5d).Here,the
variablesurfaceexchangerunagreesremarkablywellwith
4. Sensitivitytosurfaceexchangestrength the observations at each of these stations, which span a
andcomparisonwithobservations widerangeofsoilwetnessinthesimulations(Fig.4a).
The much greater total surface flux H 1 LE in the
a. ComparisonofsimulatedsurfacefluxesandPBL
strong surface exchange run than in the weak surface
withlocalIHOPmeasurements
exchangerun(Fig.5)impliessubstantialdifferencesin
ThesimulatedandobservedfluxesatselectedIHOP thesurfaceenergybudget,R 5H1LE1G,where
net
surfacefluxstationsonday5(Fig.5)representthetransition R is the net radiation gain (including incoming and
net
10 WEATHER AND FORECASTING VOLUME26
FIG.6.Simulatedandobserved(a)potentialtemperatureand(b)watervapormixingratiointheearlyafternoon
(1930UTC)ofday5(14June)attheHomesteadsoundingsite,whichisapproximatelycollocatedwiththeIHOP
surfacefluxstationS2,whoselocationisdepictedinFigs.2and4.Simulatedandobserved(c)surfacesensibleheat
fluxand(d)surfacelatentheatfluxatstationS2forthedaytimesurfaceheatingcyclethatapproximatelyprecedesthe
verticalsoundingsin(a)and(b).LDTisUTC25h.
reflectedshortwave and outgoing longwave), and G is relativelysmoothlybetweenthoseofthesimulationsus-
the flux into the ground. For example, at S2 midday ingourextremes,particularlyforpotentialtemperature
H 1 LE is ;300 W m22 greater in the strong surface (not shown). Although the weak surface exchange run
exchange run than in the weak surface exchange run (C 51.0withMYJPBL)producesfluxesthatclosely
zil
(Figs. 5a and 5b), with ;150 W m22 less G, which matchtheobservations(Fig.6c),theassociatedPBLis
contributestoalowerskintemperature(DT ;220 K) ;500 m too shallow and ;3 K too cool (Fig. 6a),
s
andsmalleroutgoinglongwaveradiationthatincreases whereas the strong surface exchange run (C 5 0.01
zil
R by ;150 W m22. Together, the differences in G with MYJ PBL) has a PBL depth and potential tem-
net
andR approximatelybalancethoseinH1LE. perature similar to the observations (Fig. 6a) despite
net
Thewesternmoststation(S2inFig.4)approximately much stronger than observed H (Fig. 6c). These com-
coincides with the IHOP Homestead sounding site parisons suggest that the vertical mixing in the MYJ
(Weckwerth et al. 2004) and thereby allows us to ex- PBLschememaynotbeaggressiveenoughatthispar-
aminetheimpactoflocalsurfacefluxesontheafternoon ticularlocation.
clearconvectiveboundarylayerandevaluatehowwell A simulation with strong surface exchange and the
this interaction is simulated at this location. More YSUPBLscheme(C 50.01withYSUPBL)produces
zil
comprehensive studies of the observed PBL evolution a warmer and deeper PBL than with MYJ (Fig. 6a)
on this day are found in Couvreux et al. (2009) and despiteslightlysmallerH(Fig.6c).Here,thetoowarm
Bennettetal.(2010). andtoodeepYSUPBLismoreconsistentwiththetoo
Figure6presentsobservationsandthesimulatedPBL large simulated H (Figs. 6a and 6c) than is the better
structure at our extremes of surface exchange strength representedPBLusingMYJ.Althoughthedifferences
(C 50.01andC 51.0)forday5.ThePBLthermal inpotentialtemperatureamongrunswithdifferentPBL
zil zil
and moisture structures for the other simulations vary schemes can be significant, these differences are much
FEBRUARY2011 TRIER ET AL. 11
FIG.7.ComparisonofgriddedRUCanalyseswithsimulationsofPBLquantitiesfor6-dayaveragesof0–24-h
forecasts initialized at 1200 UTC and area-averaged over the (a),(c),(e) western and (b),(d),(f) eastern sub-
domainsdepictedinFig.4.TheverticallinesindicateapproximateaveragenoonandmidnightLDToverthe
differentaveragingareas.
smallerthanthosebetweenrunsforwhichC isequalto PBL of all four simulations (Fig. 6b). This deeper and
zil
0.01 and 1.0 (Fig. 6a). This is not the case for the PBL driersimulateddaytimePBLusingtheYSUversusMYJ
moisture, where the choice of PBL scheme makes PBL scheme is consistent with results over the western
alargerdifferencethanforpotentialtemperature,par- highplainsfrompreviousstudies(Weismanetal.2008).
ticularlywhenthesurfaceexchangeisstrong(Fig.6b).
b. RegionalcomparisonofPBLvariables
Acting alone, the larger LE associated with stronger
surfaceexchange(Fig.6d)promotesgreaterPBLmois- Figure7presentsacomparisonofPBLvariablesinthe
ture.However,becauseoftheverydryconditionsabove primaryMYJsimulationswiththeRapidUpdateCycle
thePBLatthislocation(Fig.6b),particularlydeepver- (RUC)model(Benjaminetal.2004)analysesforthefull
ticalmixingoccurswithstrongsurfaceexchangeforthe diurnal cycle averaged over the 6-day retrospective pe-
moreaggressiveYSUPBLscheme,leadingtothedriest riodwithinthebroaderIHOPsubdomainregionsshown
12 WEATHER AND FORECASTING VOLUME26
FIG.8.ComparisonsofStage4precipitationobservationswith
simulated area-averaged hourly precipitation rates over the (a)
westernand(b)easternsubdomainsdepictedinFig.4for6-day
averagesof0–24-hforecastsinitializedat1200UTC.Thevertical
linesindicateapproximateaveragenoonandmidnightLDTover
thedifferentaveragingregions.
in Fig. 4. Here, we select RUC analyses as a proxy for
observations since they both assimilate more observa-
tionsatasynoptictimesthandothecorrespondingEDAS
analyses used to initialize the ARW-WRF simulations
(section 3b), and they are considered more independent
from these simulations. The mean diurnal cycles of po-
tential temperature and water vapor mixing ratio (Figs.
7a–d) are interpolated from the simulation and RUC
analysesgridsto100 mAGL.Thisheightisaboveday- FIG.9.ComparisonsofStage4precipitationobservationswith
timesuperadiabaticsurfacelayerssothatconditionsare simulatedarea-averagedhourlyprecipitationratesovertheentire
morerepresentativeofthePBL. IHOPregiondepictedbythesolidrectanglesinFig.4for6-day
averagesof(a)0–24-hforecastsinitializedat1200UTCand(b)12–
Overthewesternsubdomain(Fig.4),themagnitude
36-hforecastsinitializedat0000UTCbutvalidforthesametimes
of the diurnal cycle of potential temperature (Fig. 7a)
asthosein(a).(c)Equitablethreatscoresforsimulated3-hpre-
andwatervapor(Fig.7c)intheWRFdefaultandstrong cipitation amounts calculated over the same IHOP region and
surfaceexchangesimulationscomparebestwiththoseof averagedforthesix0–24-h(12–36-h)forecastsinitializedat1200
theRUCanalyses.Themuchweakerdiurnalcycleinthe (0000)UTC.Theverticallinesindicateapproximateaveragenoon
andmidnightLDTovertheIHOPregion.
weaksurfaceexchangeruns(Figs.7aand7c)isconsistent