DTIC ADA523108: Orography-Induced Gravity Wave Drag Parameterization in the Global WRF: Implementation and Sensitivity to Shortwave Radiation Schemes

1.7 MB·English

by  Defense Technical Information Center

HindawiPublishingCorporation
AdvancesinMeteorology
Volume2010,ArticleID959014,8pages
doi:10.1155/2010/959014
Research Article
Orography-Induced Gravity Wave Drag Parameterization in
the Global WRF: Implementation and Sensitivity to Shortwave
Radiation Schemes
HyeyumHaileyShin,1Song-YouHong,1JimyDudhia,2andYoung-JoonKim3
1DepartmentofAtmosphericSciencesandGlobalEnvironmentLaboratory,YonseiUniversity,Seoul120-749,RepublicofKorea
2MesoscaleandMicroscaleMeteorologyDivision,NationalCenterforAtmosphericResearch,Boulder,CO80305,USA
3MarineMeteorologyDivision,NavalResearchLaboratory,Monterey,CA93943,USA
CorrespondenceshouldbeaddressedtoSong-YouHong,[email protected]
Received24December2009;Accepted24March2010
AcademicEditor:Hann-MingHenryJuang
Copyright©2010HyeyumHaileyShinetal.ThisisanopenaccessarticledistributedundertheCreativeCommonsAttribution
License,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperly
cited.
This paper describes the implementation of the orographic gravity wave drag (GWDO) processes induced by subgrid-scale
orographyintheglobalversionoftheWeatherResearchandForecasting(WRF)model.Thesensitivityofthemodelsimulated
climatologytotherepresentationofshortwaveradiationandtheadditionoftheGWDOprocessesisinvestigatedusingtheKim-
ArakawaGWDOparameterizationandtheGoddard,RRTMG(RapidRadiativeTransferModelforGCMs),andDudhiashortwave
radiationschemes.Thissensitivitystudyisapartofeffortsofselectingthephysicspackagethatcanbeusefulinapplyingthe
WRFmodeltoglobalandseasonalconfiguration.TheclimatologyisrelativelywellsimulatedbytheglobalWRF;thezonalmean
zonal wind and temperature structures are reasonably represented with the Kim-Arakawa GWDO scheme using the Goddard
and RRTMG shortwave schemes. It is found that the impact of the shortwave radiation scheme on the modeled atmosphere
ispronouncedintheupperatmosphericcirculationsabovethetropopausemainlyduetotheozoneheating.Theschemethat
excludestheozoneprocesssuffersfromadistinctcoldbiasinthestratosphere.Moreover,giventheimproperthermodynamic
environmentconditionsbytheshortwavescheme,theroleoftheGWDOprocessisfoundtobelimited.
1.Introduction WiththeverificationoftheregionalWRFmodelperfor-
mance,NationalCenterforAtmosphericResearch(NCAR)
The Weather Research and Forecasting (WRF) model has researchers tested the ability of the WRF model to cover
been evaluated in terms of regional modeling for both the global domain. It is noticed that a global version of
research and operational applications since it was first WRF was first developed to study atmospheres on Mars
releasedin2000.ThecapabilityoftheregionalWRFmodel and other planets by Mark Richardson and colleagues at
isestablishedoverawidetemporalrange;fromshort-range CaliforniaInstituteofTechnology,andresearchersinNCAR
forecastssuch assimulations oflocalized heavy rainfalland Mesoscale and Microscale Meteorology (MMM) Division
snowfallwithinacoupleofdaysoverKorea(i.e.,[1,2]),36-h extended that version of the WRF-ARW model to forecast
realtimeforecastsintheUnitedStates[3],andsimulationsof weatheronEarth(NCARarticleson9November2007,avail-
typhoonandhurricanethataffectsynopticfieldsforseveral able in http://www.ncar.ucar.edu/index.php/ncar/articles/
days (i.e., [4, 5]), to regional climate simulations of such weather forecast goes global).TheregionalWRFmodelwas
as U.S. warm-season precipitation and East-Asia summer extended with a latitude-longitude grid system to cover
monsoon circulations (i.e., [6, 7]). These studies support the global domain, based on the Advanced Research WRF
the satisfactory performance of the WRF model in various (ARW)version3.0thatwasreleasedinApril2008.Theglobal
regionsovertheglobe. WRF shares the same dynamic core with the regional WRF
Report Documentation Page Form Approved
OMB No. 0704-0188
Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and
maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information,
including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington
VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it

does not display a currently valid OMB control number.
1. REPORT DATE 3. DATES COVERED
2010 2. REPORT TYPE 00-00-2010 to 00-00-2010
4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER
Orography-Induced GravityWave Drag Parameterization in the Global
5b. GRANT NUMBER
WRF: Implementation and Sensitivity to Shortwave Radiation Schemes
5c. PROGRAM ELEMENT NUMBER
6. AUTHOR(S) 5d. PROJECT NUMBER
5e. TASK NUMBER
5f. WORK UNIT NUMBER
7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION
Department of Atmospheric Sciences and Global Environment REPORT NUMBER
Laboratory,Yonsei University, Seoul 120-749,Republic of Korea, ,
9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S)
11. SPONSOR/MONITOR’S REPORT
NUMBER(S)
12. DISTRIBUTION/AVAILABILITY STATEMENT
Approved for public release; distribution unlimited
13. SUPPLEMENTARY NOTES
14. ABSTRACT

15. SUBJECT TERMS
16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18. NUMBER 19a. NAME OF
ABSTRACT OF PAGES RESPONSIBLE PERSON
a. REPORT b. ABSTRACT c. THIS PAGE Same as 8
unclassified unclassified unclassified Report (SAR)
Standard Form 298 (Rev. 8-98)
Prescribed by ANSI Std Z39-18
2 AdvancesinMeteorology
except that a polar filter is applied in the global version 2.ExperimentalDesign
[8].Inaddition,thephysicsoptionsandbehaviorshouldbe
examinedseparatelyfromtheregionalconfigurationbecause 2.1. The Advanced Research WRF (ARW) Model. The
the intrinsic requirements for global circulation modeling, AdvancedResearchWRF(ARW;[14])isacommunitymodel
such as higher model top, and coarser resolution require designed for both research and forecasting, which is a fully
furthervalidation. compressiblenonhydrostaticmodelwiththeArakawa-Cgrid
The advancement of human knowledge continues to- system. The model performs reasonably well for detailed
getherwithincreasingcomputingresources;thecutting-edge numerical weather prediction (NWP) cases with real-data
numerical weather prediction (NWP) and climate models, initial and boundary conditions. The WRF model became
however, cannot resolve all relevant scales of atmospheric availablewiththeglobalcoveragestartingfromWRFversion
phenomena. Global numerical prediction models are typ- 3.0,whichwasreleasedinApril2008.Themodelusedinthis
ically run with horizontal resolutions that cannot capture studyisabetaversionoftheARWversion3.1withtheglobal
atmosphericprocessessmallerthanabout10–100km.Grav- domain. The global WRF utilizes the latitude-longitude
itywaveisanunresolvedprocessincoarseresolutionmodels, grid system and then a polar filter is used to filter out
playinganimportantroleintransportingmomentumfrom small-scale waves and avoid the singularity problem at the
sourceregionstoregionswheregravitywavesaredissipated poles.
or absorbed during their propagation, producing synoptic
scale body forces [9]. Palmer et al. [10] and McFarlane
2.2. Implementation of the KA GWDO Parameterization
[11]notedthatunresolvedmountaingravitywavedragwas
Scheme. The KA GWDO scheme [12] includes the lower-
one of the most critical causes of the systematic biases in
tropospheric enhancement of GWDO due to selective low-
seasonalsimulations—excessivesurfacewesterliesandatoo
level wave breaking mainly in downstream regions with
cold pole—and suggested a GWDO parameterization for
the aid of additional subgrid-scale orographic statistics:
large-scale models. Since then, this subgrid-scale process
the orographic asymmetry (OA) and orographic convexity
of gravity waves has been an essential physical process
(OC). The OA measures the asymmetry and location of
that should be parameterized in global models to represent
subgrid-scale orography relative to the model grid box
global circulations realistically. However, the global WRF,
anditdistinguishesbetweentheupstreamanddownstream
which is a spatial extension of the original regional WRF,
regions.TheOCmeasureshowconvexorsharpthesubgrid-
currently does not include any orography-induced gravity
scaleorography is by statistically relating the characteristics
wave drag (GWDO) parameterization. It is noted that the
ofthemountainwavestothesubgrid-scaleorography.
GWDO parameterization is not included in most regional
The KA GWDO parameterization is implemented in
models including the WRF since horizontal resolutions
the WRF model following Hong et al. [13]; in Hong et al.
of regional models are considered to be sufficiently high
[13] the reference level is determined as the larger value
to resolve gravity waves. Moreover, global models include between the PBL height and 2σh following Kim and Doyle
much of stratosphere, whereas the model top is lower (i.e., [15], where σh is the standard deviation of subgrid-scale
typically lower than 50hPa) for regional models. Thus,
terrain heights. Kim and Hong [16] demonstrated that this
most regional models do not typically include the GWDO
method in determining the reference level greatly improves
parameterization.
theclimatesimulationscomparedwiththepreviousmethod
The purpose of this study is to describe the imple-
thatemploysthePBLheightasthereferencelevelheight;we
mentation of the GWDO parameterization based on Kim
note that the new method generally elevates the reference
and Arakawa [12] (hereafter, KA GWDO) into the global
level height. The mechanism behind the improvement is
WRF model and evaluate the performance of the model in
explainedinKimandHong[16].
simulatinggeneralfeaturesoftheborealwinterclimatewith
For utilizing the KA GWDO in the WRF model, the
theKAGWDO.TheKAGWDOincludestheenhancedlow-
necessary input to the KA GWDO scheme (i.e., mean,
tropospheric gravity wave drag in addition to the upper-
variance, asymmetry, and convexity) is derived from a 30-
level wave breaking that is traditionally incorporated into
arcsecond resolution topography dataset [17] for global
GWDO schemes. The KA GWDO was earlier implemented
domains with 10min., 20min., 30min., 1deg., and 2deg.
into the National Centers for Environmental Prediction
resolutions. These orographic statistics are interpolated to
(NCEP) Global Spectral Model (GSM) successfully and its
the model grid points using one of the five-resolution
performance was later reported by Hong et al. [13]. The
datasetsintheWRFPreprocessingSystem(WPS);prepared
KAGWDOschemewentintooperationattheNCEPglobal
statistics of a comparable resolution to model grid size are
forecast system in 2000. Sensitivity of the simulated clima-
used.
tology to shortwave radiation schemes is also investigated
in order to re-evaluate present physics options in the WRF
model in global and seasonal configuration, which have 2.3.ExperimentalSetup. Seasonalsimulationsareconducted
been evaluated only in regional configuration. Section2 forthreeborealwintersinDecember,January,andFebruary
describes the experimental setup and implementation of (DJF) of 1996/1997, 1997/1998, and 1999/2000. For each
the KA GWDO parameterization, and results are discussed winter, five ensemble runs are conducted with different
in Section3. Concluding remarks are given in the final initializationtimesof00UTC1–5Novembertoaverageout
section. the unpredictable parts of the flow. Thus, one experiment
AdvancesinMeteorology 3
Table1:Asummaryofthephysicsoptionsusedinthenumericalexperiments.“—”denotesthesameoptionasthatintheGsw nGWD
experiment.
GWDO SW LW PBL LSM CPS MPS
Gsw nGWD None Goddard RRTMG YSUPBL NOAH Grell-Devenyi WSM3
Rsw nGWD None RRTMG — — — — —
Dsw nGWD None Dudhia — — — — —
Gsw GWD KAGWDO Goddard — — — — —
Rsw GWD KAGWDO RRTMG — — — — —
Dsw GWD KAGWDO Dudhia — — — — —
consistsof15runs.InitialconditionsareforcedbytheNCEP- clear distinction, the global WRF without the KA GWDO
Department of Energy (DOE) (NCEP-DOE) Reanalysis II implementationisdesignatedtheearlierversion.
(R2) data on the 2.5◦× 2.5◦ global grid. The National
OceanicandAtmosphericAdministration(NOAA)Optimal
Interpolation Sea Surface Temperature (OISST) is used 3.1. Wind and Temperature Structures. Figure1 compares
as the surface boundary conditions every 24 hours. The thethree-winterensembleaveragesofthezonal-meanzonal
horizontal resolution of 1.875◦× 1.875◦ is used, which is wind and temperature structures simulated with the God-
comparabletothe200kmresolutionalongtheequator.The dard (Figures 1(a) and 1(d)), RRTMG (Figures 1(b) and
38-layer Eta level system is used with the model top at 1(e))andDudhia(Figures1(c)and1(f))shortwaveparam-
10hPa. Intervals between the adjoining vertical levels are eterizations in the earlier version of the global WRF that
determined not to exceed 1km or to be comparable to includes no effect of the GWDO (denoted by Gsw nGWD,
1km. Rsw nGWD,andDsw nGWD,resp.).Thecontoursineach
The physics package includes the RRTMG scheme [18] figure represent the 3-year averaged fields from the 15
for longwave radiation, the Yonsei University Planetary ensemble members, and the color shades denote their
Boundary Layer (YSU PBL) [19] for vertical diffusion deviations from the reanalysis fields. As can be expected
process,theNoahlandsurfacemodel[20],theGrell-Devenyi and as the results show, the earlier version of the global
ensemble scheme [21] for cumulus parameterization, and WRF cannot reasonably represent the typical boreal winter
the WSM3 (WRF Single-Moment 3-class) scheme [22] climatology. The model clearly shows the systematic errors
for microphysics. In the YSU PBL, the vertical diffusion inthesimulatedclimatology—toocoldpoleandexcessively
coefficients in the stable boundary layer (SBL) conditions strongwesterliesoverthenorthernhemisphere(cf.Figure1),
are calculated as in the case of the unstable conditions; which is typical when GWDO is not included in general
the coefficients are parabolic functions of heights as in circulation models. There is no separation between the
the mixed layer, and the SBL top is determined by the troposphericsubtropicaljetandstratosphericpolarnightjet
bulkRichardsonnumber.KimandHong[16]demonstrated and also the polar night jet is overly strong due mainly to
that the interaction between the KA GWDO and YSU thelackofGWDO.Thethermodynamicstructureshowstoo
PBL processes is improved with the SBL parameterization strongmeridionaltemperaturegradientinbalancewiththe
mentioned above. For shortwave radiation, three different improper wind structure; the simulated temperature of the
shortwave schemes are used to observe the sensitivity of Arctic polar stratosphere is almost about 40K colder than
the simulated climate associated with the GWDO to the that of the reanalysis. Thus, it is obvious that the earlier
shortwave radiation processes in the modeled atmosphere: version of the global WRF has a systematic problem due
theGoddard[23],RRTMG,andDudhia[24]schemes.The toamissingcriticalprocess;thatis,orographicallyinduced
physics options used for the numerical experiments are gravity wave drag. Note that the three nGWD experiments
summarizedinTable1. are conducted in parallel with the three GWD experiments
(i.e.,Gsw GWD,Rsw GWD,andDsw GWD)tovalidatethe
implementationoftheKAGWDOintheglobalWRFmodel,
3.Results andthusthesensitivitytoshortwaveprocessschemesisnot
discussedforthesenGWDexperiments.
In this study, the results are obtained from and discussed With the KA GWDO implemented, the global WRF is
basedonthecompositeof3-yearsimulations(i.e.,ensemble able to reproduce the general mean structures of both the
averages of the 15 simulations). The simulated zonal wind zonal-meanzonalwind(Figures2(a)–2(c))andtemperature
and temperature structures are evaluated in comparison (Figures2(d)–2(f))inthetroposphere.Allthreeexperiments
with the reanalysis (R2) data. The shortwave process in R2 simulatethesubtropicaljetinthenorthernhemispherewith
is based on Chou [25] and Chou and Lee [26], and the realistic intensity, which is comparable to 45ms−1 of the
GWDO scheme used in the R2 is described by Alpert et al. reanalysisdata,aswellastheoverallmeanwindstateofthe
[27].Inprecipitationanalysis,thedailyGlobalPrecipitation troposphere(Figures2(a)–2(c)).Thisreasonablerepresenta-
Climatology Project (GPCP) data with a 1◦× 1◦ spatial tion of the wind fields including the mid-latitude jet in the
resolution are used for the evaluation. Hereafter, to make a northerntroposphereisattributedtotheimplementationof
4 AdvancesinMeteorology
20
−5
20
ure(hPa)×1102 25 4550 ure(hPa)×1102 25 −5 4550 ure(hPa)×1102 35 −5 0
Press 186420 11230500 −5 3223405050 1150 Press 186420 11230500 3223405050 1150 Press 186420 11302500 25 0 32340550 211050
90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N
Latitude Latitude Latitude
(a) Gsw nGWD (b) Rsw nGWD (c) Dsw nGWD
240
170
230 210
a) 220 200 a) a) 180
P P P
h×102 h×102 220 210 h×102
ure( 1 210 ure( 1 ure( 1 190 200
Press 2 230 220 Press 2 230 220 Press 2 222300 210
240 240 240
4 250260 4 250260 4 226500
6 280 6 280 6
8 8 8
10 270 10 270 10
90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N
Latitude Latitude Latitude
−26 −18 −10 −2 2 10 18 26 −26 −18 −10 −2 2 10 18 26 −26 −18 −10 −2 2 10 18 26
(d) Gsw nGWD (e) Rsw nGWD (f) Dsw nGWD
Figure 1: Three-winter ensemble averages (contours) of the zonal-mean zonal wind (upper panels) and temperature (lower panels)
structures simulated from the (a), (d) Gsw nGWD, (b), (e) Rsw nGWD, and (c), (f) Dsw nGWD experiments with the earlier version
ofglobalWRFwithouttheKAGWDOimplementation.DifferencesfromtheNCEPreanalysis(R2)arecolorshaded.
theGWDO.Associatedwiththeseimprovementsinthewind responsible for the typical thermodynamic structure of
fields,thecoldbiasofthethermodynamicstructuresisalso the stratosphere; an ozone-absorption coefficient profile is
reduced. In the troposphere, the simulated results are less specified in the Goddard scheme according to an observed
sensitive to the shortwave schemes than those in the upper climatology,andtheRRTMGschemeincludestropical/mid-
atmosphere. On the other hand, clear differences among latitude/polar and summer/winter ozone profiles. The sim-
the shortwave radiation parameterizations exist in upper ulated temperature-profile inversion near the tropical and
levels.Thesubtropicaljetandstratosphericpolarnightjetin southern-hemisphericpolartropopauseisshownwiththese
the northern hemisphere are reasonably separated with the two shortwave schemes due to the ozone heating effects
Goddard and RRTMG shortwave radiation processes while (Figures 2(d) and 2(e)). Because of this temperature inver-
the two jets are unrealistically bonded to each other with sion, there exists meridional temperature gradient in the
the Dudhia scheme; the westerly continuously decreases as middlestratosphereoverhighlatitudes,whichisresponsible
the height increases such that the magnitude of the wind for the presence of the northern polar night jet in the
is evidently underestimated at the location of the observed two experiments (i.e., Gsw GWD and Rsw GWD). In the
polar-night jet, which is entirely missing in the simulation Gsw nGWD and Rsw nGWD experiments, there is sig-
(cf.Figure2(c)).Moreover,inthesouthernhemisphere,the nificant cold bias related to the extremely overestimated
tropospheric westerly jet is erroneously extended into the temperature gradient in the lower stratospheric regions
stratosphereintheDsw GWDexperiment. associatedwiththeexcessivewesterliescausedbythemissing
This radical difference in simulating the wind structure drag, as shown previously, this cold bias is alleviated by its
in the middle atmosphere among the three experiments balance with the wind reduction due to the GWDO in the
(Gsw GWD, Rsw GWD, and Dsw GWD) is related to twoGWDexperiments.
the different thermodynamic structures that heavily rely Ontheotherhand,theDudhiaschemedoesnotconsider
on the shortwave heating processes. The Goddard and theozoneeffects[28]andthuscannotsimulatethetemper-
RRTMG shortwave schemes include ozone effects that are ature inversion; the strong cold bias is induced throughout
AdvancesinMeteorology 5
15
15 20
ure(hPa)×1102 2025 −10−5 3025 ure(hPa)×1102 20 −10−5 30 ure(hPa)×1102 −5 0 3025
Press 2 30 40 Press 2 30 Press 2 30 25 40
35 35 35
4 4 25 25 4
86 1520 2105 10 86 15 1250 10 86 1250 0 210510
10 10 5 10 10 5 10 10 5
90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N
Latitude Latitude Latitude
(a) GswGWD (b) RswGWD (c) DswGWD
210
230 170
200
a) 220 a) a)
P P P
h×102 h×102 220 210 h×102 180
( ( (
Pressure 21 221300 220 Pressure 21 220300 220 Pressure 21 122292300000 210
240 240 240
4 250260 4 250260 4 226500
6 280 6 280 6
8 8 8
10 270 10 270 10
90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N 90S 60S 30S EQ 30N 60N 90N
Latitude Latitude Latitude
−26 −18 −10 −2 2 10 18 26 −26 −18 −10 −2 2 10 18 26 −26 −18 −10 −2 2 10 18 26
(d) GswGWD (e) RswGWD (f) DswGWD
Figure2:AsinFigure1,butwiththenewversionofglobalWRFincludingtheKAGWDOparameterization.
thestratosphere(Figure2(f))(notethatthecoldbiasinthe In summary, shortwave radiation significantly impacts
Dsw nGWD experiment is due to the absence of both the the modeled atmosphere, especially on the upper atmo-
ozone heating and GWDO). Moreover, given the highly- spheric circulations above the tropopause mainly due to
unrealistic thermodynamic structure, the GWDO process the ozone heating. The heating scheme without the ozone
does not improve but continues to force the unrealistic process undergoes a distinct cold bias in the stratosphere,
system.Wenotethatsimilarresultswerepreviouslyreported which in turn results in improper wind fields balancing
by Kim et al. [29]. They demonstrated that the underesti- with the cold bias. Under the unreasonable environmental
mated ozone mixing ratio inducing an underestimation of conditions, the GWDO process continuously forces the
shortwave heating can result in significant bias in zonal- systemtowardanunrealisticstate.
mean temperature and wind structures; the impact of the
low ozone mixing ratio is the largest in the lower polar 3.2.TropicalPrecipitation. InFigure3,thesimulated3-year
stratosphere, which leads to the overly strong polar night mean daily precipitation is compared with the daily GPCP
jet in the northern hemisphere and unrealistically strong datawitha1◦×1◦spatialresolution.Thepatterncorrelation
extension of the tropospheric westerly jet into the strato- (PC),biases,andRootMeanSquareError(RMSE)between
sphere in the southern hemisphere. Consequently, when each simulation and GPCP data are presented at the top
the GWDO parameterization is given wrong information of each panel. The overall performance of the global
from other physical process, including GWDO does not WRF model in simulating the precipitation is acceptable
improve the simulated results even though the GWDO in the three GWD experiments regardless of the shortwave
process itself is a critical component in climate models. processes (e.g., Figures 3(e)–3(g)). As seen in Shimpo et al.
The Dudhia shortwave scheme shows good performance, [30],thedistributionofglobalprecipitationfromtheglobal
that is, without large systematic bias, in regional weather WRF is comparable, even though the integration period
prediction models since the model top is usually lower differs from one to another. The model produces tropical
than 50hPa in the regional model application, so that rainfall distributions quite reasonably, compared with the
the simulated results do not suffer from the absent ozone observationsshowingthedoublerainbeltsalongthedouble
effects. intertropical convergence zone (ITCZ) and precipitation
6 AdvancesinMeteorology
60N
40N
20N
EQ
20S
40S
60S
0 60E 120E 180 120W 60W 0
(a) GPCPprecipition(mmday−1)
PC (cid:2)0.713,bias (cid:2)0.373,RMSE (cid:2)2.086 PC (cid:2)0.704,bias (cid:2)0.374,RMSE (cid:2)2.102
60N 60N
40N 40N
20N 20N
EQ EQ
20S 20S
40S 40S
60S 60S
0 60E 120E 180 120W 60W 0 0 60E 120E 180 120W 60W 0
(b) GswnGWDprecipition(mmday−1) (e) GswGWDprecipition(mmday−1)
PC (cid:2)0.705,bias (cid:2)0.519,RMSE (cid:2)2.206 PC (cid:2)0.7,bias (cid:2)0.521,RMSE (cid:2)2.25
60N 60N
40N 40N
20N 20N
EQ EQ
20S 20S
40S 40S
60S 60S
0 60E 120E 180 120W 60W 0 0 60E 120E 180 120W 60W 0
(c) RswnGWDprecipition(mmday−1) (f) RswGWDprecipition(mmday−1)
PC (cid:2)0.65,bias (cid:2)0.719,RMSE (cid:2)2.467 PC (cid:2)0.663,bias (cid:2)0.714,RMSE (cid:2)2.423
60N 60N
40N 40N
20N 20N
EQ EQ
20S 20S
40S 40S
60S 60S
0 60E 120E 180 120W 60W 0 0 60E 120E 180 120W 60W 0
3 6 9 12 15 20 25 30 35 3 6 9 12 15 20 25 30 35
(d) DswnGWDprecipition(mmday−1) (g) DswGWDprecipition(mmday−1)
Figure3:Comparisonof3-yearaveraged dailyprecipitation(mmday−1)obtained from(a)observations,(b),(c),(d)theexperiments
withouttheKAGWDOschemeandwiththreedifferentshortwaveradiationprocesses,and(e),(f),(g)theexperimentsincludingtheKA
GWDOschemeandwiththreedifferentshortwaveradiationprocesses.
maximum regions over South America and South Africa. distribution,norimprovesthedistributionoftheprecipita-
However,themodelgenerallytendstooverestimatethelocal tion. With the Goddard and RRTMG shortwave processes
rainfall maximum values over tropical regions (e.g., central the statistics are slightly worse in the GWD experiments
SouthAmerica,thenorthwesternoceanofMadagascar,near while the GWD experiment shows slightly better statistics
Sumatra, and western equatorial Pacific near the maritime with the Dudhia shortwave. The simulated hydroclimate
continent), while it underestimates the rainfall around shows the best results—although not significant—with the
middle latitudes. Compared with the nGWD experiments, Goddard shortwave scheme in this study both with and
theinclusionoftheGWDOneithersignificantlychangesthe withoutGWDO.
AdvancesinMeteorology 7
Zonalmeanprecipitation(DJF) GWDO (KA GWDO) parameterization and the Goddard,
10
RRTMG,andDudhiashortwaveradiationschemes.
With the KA GWDO parameterization implemented,
9
the climatology from the global WRF is relatively well
simulated in the troposphere; the zonal-mean zonal wind
8
and temperature structures are realistically represented. In
7 the stratosphere, however, the performance of the model
)
−1 widely varies according to the representations of shortwave
y
da 6 processes mainly due to the ozone heating. The scheme
m
m that excludes the ozone process induces a distinct cold
n( 5 bias in the stratosphere, and modeled wind fields balance
o
ati with the unreasonable thermodynamic fields. The already
pit 4 unrealisticsystemduetothedeficiencyintheheatingscheme
ci
Pre 3 iscontinuouslyimpelledbytheGWDOprocess.Thisresult
supports the notion that the success of a particular physics
parameterization scheme in atmospheric models depends
2
notonlyontheaccuracyoftheparticularschemeitselfbut
1 alsoonthesuccessofotherphysicalprocesses[16].Inview
oftheprecipitation,theglobalWRFalsowellrepresentsthe
0 overall patterns of the tropical precipitation but the model
60S 40S 20S EQ 20N 40N 60N tends to overestimate (underestimate) the precipitation at
Latitude thetropical(mid-latitude)regions.Itisfoundthatthesimu-
GPCP GswGWD latedmeridionalprecipitationdistributionsdifferaccording
GswnGWD RswGWD to the shortwave schemes depending on the presence of
RswnGWD DswGWD ozoneeffects.
DswnGWD TheKAGWDOisimplementedintheWRFmodelbased
Figure4:Thezonal-meanofthe3-yearmeandailyprecipitation on this study and became available starting from the WRF
(mm day−1) obtained from the three nGWD (dotted lines) and version3.1,whichwasreleasedinApril2009.
three GWD (solid lines) experiments with the Goddard (green
lines), RRTMG (blue lines), and Dudhia (red lines) shortwave
radiationschemes,respectively.
Acknowledgments
This paper was supported by the Basic Science Research
ProgramthroughtheNationalResearchFoundationofKorea
Figure4showsthezonalmeanofthe3-yearmeandaily (NRF) funded by the Ministry of Education, Science and
precipitation from 60◦S to 60◦N. The model is successful Technology (2010-0000840), and by the Korean Founda-
in representing meridional distributions of the zonal-mean tion for International Cooperation Science & Technology
precipitation, but tends to overestimate the precipitation (KICOS) 21 through a grant provided by the Korean Min-
over the tropics, regardless of the shortwave scheme. Near istryofScience&Technology(MOST).
theequator,thesimulateddailyprecipitationpatternsfrom
theexperimentswiththeshortwaveschemesincludingozone
effects (i.e., the Goddard and RRTMG) are similar to each References
other while the experiment with the Dudhia scheme shows
somewhatdifferentbehaviors,bothwithandwithouttheKA [1] S.-Y.HongandJ.-W.Lee,“AssessmentoftheWRFmodelin
GWDO.Inotherwords,theexperimentswiththeGoddard reproducing a flash-flood heavy rainfall event over Korea,”
and RRTMG schemes commonly produce less rainfall than AtmosphericResearch,vol.93,no.4,pp.818–831,2009.
theexperimentwiththeDudhiaschemesothattheamounts [2] K.-S. Lim and S.-Y. Hong, “Numerical simulation of heavy
are closer to observations than that with the Dudhia snowfall over the Ho-Nam province of Korea in December
2005,”JournaloftheKoreanMeteorologicalSociety,vol.43,no.
scheme.
2,pp.161–173,2007.
[3] M.L.Weisman,C.Davis,W.Wang,K.W.Manning,andJ.B.
Klemp,“Experienceswith0-36-hexplicitconvectiveforecasts
4.ConcludingRemarks
withtheWRF-ARWmodel,”WeatherandForecasting,vol.23,
no.3,pp.407–437,2008.
Theorographicgravity-wavedrag(GWDO)processinduced
[4] G. Jianfeng, Q. Xiao, Y.-H. Kuo, D. M. Barker, X. Jishan,
by subgrid scale orography is implemented in the global
and M. Xiaoxing, “Assimilation and simulation of typhoon
versionofWeatherResearchandForecasting(WRF)model.
Rusa(2002)usingtheWRFsystem,”AdvancesinAtmospheric
Thesensitivityofthesimulatedclimatologytotherepresen- Sciences,vol.22,no.3,pp.415–427,2005.
tationofshortwaveradiationwiththeGWDOprocessinthe [5] X. Li and Z. Pu, “Sensitivity of numerical simulation of
modeledatmosphereisinvestigatedusingtheKim-Arakawa earlyrapidintensificationofHurricaneEmily(2005)tocloud
8 AdvancesinMeteorology
microphysical and planetary boundary layer parameteriza- [22] S.-Y.Hong,J.Dudhia,andS.-H.Chen,“Arevisedapproachto
tions,” Monthly Weather Review, vol. 136, no. 12, pp. 4819– ice microphysical processes for the bulk parameterization of
4838,2008. cloudsandprecipitation,”MonthlyWeatherReview,vol.132,
[6] M. S. Bukovsky and D. J. Karoly, “Precipitation simulations no.1,pp.103–120,2004.
using WRF as a nested regional climate model,” Journal of [23] M.-D.ChouandM.J.Suarez,“Asolarradiationparameter-
AppliedMeteorologyandClimatology,vol.48,no.10,pp.2152– ization for atmospheric studies,” Technical Report Series on
2159,2009. GlobalModelingandDataAssimilation104606,1999.
[7] S.-R.Ham,S.-J.Park,C.-H.Bang,B.-J.Jung,andS.-Y.Hong, [24] J. Dudhia, “Numerical study of convection observed during
“IntercomparisonoftheEast-Asiansummermonsoonon11- the winter monsoon experiment using a mesoscale two-
18 July 2004, simulated by WRF, MM5, and RSM models,” dimensionalmodel,”JournaloftheAtmosphericSciences,vol.
Atmosphere,vol.15,no.2,pp.91–99,2005. 46,no.20,pp.3077–3107,1989.
[8] W.-C.Skamarock,“GlobalWRFdevelopment,”inProceedings [25] M.-D. Chou, “A solar radiation model for use in climate
of the 9th WRF User’s Workshop, Boulder, Colo, USA, June studies,”JournaloftheAtmosphericSciences,vol.49,no.9,pp.
2008. 762–772,1992.
[9] Y.-J.Kim,S.D.Eckermann,andH.-Y.Chun,“Anoverviewof [26] M.-D.ChouandK.-T.Lee,“Parameterizationsfortheabsorp-
thepast,presentandfutureofgravity-wavedragparametriza- tionofsolarradiationbywatervaporandozone,”Journalof
tion for numerical climate and weather prediction models,” theAtmosphericSciences,vol.53,no.8,pp.1203–1208,1996.
Atmosphere-Ocean,vol.41,no.1,pp.65–98,2003. [27] J. C. Alpert, M. Kanamitsu, P. M. Caplan, J. G. Sela, G. H.
[10] T.N.Palmer,G.J.Shutts,andR.Swinbank,“Alleviationofa White,andE.Kalnay,“Mountaininducedgravitywavedrag
systematicwesterlybiasingeneralcirculationandnumerical parameterizationintheNMCmedium-rangeforecastmodel,”
weather prediction models through an orographic gravity in Proceedings of the 8th Conference on Numerical Weather
wave drag parameterization,” Quarterly Journal of the Royal Prediction, pp. 726–733, American Meteorological Society,
MeteorologicalSociety,vol.112,no.474,pp.1001–1039,1986. Baltimore,Md,USA,1988.
[11] N.A.McFarlane,“Theeffectoforographicallyexcitedgravity [28] R. J. Zamora, S. Solomon, E. G. Dutton, et al., “Comparing
wavedragonthegeneralcirculationofthelowerstratosphere MM5radiativefluxeswithobservationsgatheredduringthe
andtroposphere,”JournaloftheAtmosphericSciences,vol.44, 1995and1999Nashvillesouthernoxidantsstudies,”Journalof
no.14,pp.1775–1800,1987. GeophysicalResearch,vol.108,no.D2,4050,2003.
[12] Y.-J. Kim and A. Arakawa, “Improvement of orographic [29] Y.-J. Kim, J. D. Farrara, and C. R. Mechoso, “Sensitivity of
gravitywaveparameterizationusingamesoscalegravitywave AGCMsimulationstomodificationsintheozonedistribution
model,”JournaloftheAtmosphericSciences,vol.52,no.11,pp. andrefinementsinselectedphysicalparameterizations,”Jour-
1875–1902,1995. nal of the Meteorological Society of Japan, vol. 76, no. 5, pp.
[13] S.-Y. Hong, J. Choi, E.-C. Chang, H. Park, and Y.-J. Kim, 695–709,1998.
“Lower-tropospheric enhancement of gravity wave drag in [30] A. Shimpo, M. Kanamitsu, S. F. Iacobellis, and S.-Y. Hong,
a global spectral atmospheric forecast model,” Weather and “Comparisonoffourcloudschemesinsimulatingtheseasonal
Forecasting,vol.23,no.3,pp.523–531,2008. mean field forced by the observed sea surface temperature,”
[14] W. C. Skamarock, J.-B. Klemp, J. Dudhia, et al., “A descrip- MonthlyWeatherReview,vol.136,no.7,pp.2557–2575,2008.
tion of the advanced research WRF version 3,” Tech. Rep.
NCAR/TN-475+STR,2008.
[15] Y.-J.KimandJ.D.Doyle,“Extensionofanorographic-drag
parametrizationschemetoincorporateorographicanisotropy
andflowblocking,”QuarterlyJournaloftheRoyalMeteorolog-
icalSociety,vol.131,no.609,pp.1893–1921,2005.
[16] Y.-J.KimandS.-Y.Hong,“Interactionbetweentheorography-
inducedgravitywavedragandboundarylayerprocessesina
globalatmosphericmodel,”GeophysicalResearchLetters,vol.
36,ArticleIDL12809,2009.
[17] S.-Y.Hong,“Newglobalorographydatasets,”OfficeNote424,
NCEP,CampSprings,Md,USA,1999.
[18] E.J.Mlawer,S.J.Taubman,P.D.Brown,M.J.Iacono,andS.A.
Clough,“Radiativetransferforinhomogeneousatmospheres:
RRTM, a validated correlated-k model for the longwave,”
Journal of Geophysical Research, vol. 102, no. 14, pp. 16663–
16682,1997.
[19] S.-Y.Hong,Y.Noh,andJ.Dudhia,“Anewverticaldiffusion
packagewithanexplicittreatmentofentrainmentprocesses,”
MonthlyWeatherReview,vol.134,no.9,pp.2318–2341,2006.
[20] F.ChenandJ.Dudhia,“Couplingandadvancedlandsurface-
hydrology model with the Penn State-NCAR MM5 model-
ing system. Part I: model implementation and sensitivity,”
MonthlyWeatherReview,vol.129,no.4,pp.569–585,2001.
[21] G. A. Grell and D. De´ve´nyi, “A generalized approach to
parameterizing convection combining ensemble and data
assimilationtechniques,”GeophysicalResearchLetters,vol.29,
no.14,1693,2002.