Comparison of Thunderstorm Simulations from WRF-NMM and WRF-ARW Models over East Indian ...

21 Pages·2014·9.1 MB·English

TheScientificWorldJournal
Volume2012,ArticleID951870,20pages The cientificWorldJOURNAL
doi:10.1100/2012/951870
Research Article
Comparison of Thunderstorm Simulations from WRF-NMM and
WRF-ARW Models over East Indian Region
A.J.Litta,1SumamMaryIdidcula,1U.C.Mohanty,2andS.KiranPrasad2
1DepartmentofComputerScience,CochinUniversityofScienceandTechnology,Cochin,Kerala682022,India
2CentreforAtmosphericSciences,IndianInstituteofTechnologyDelhi,HauzKhas,NewDelhi110016,India
CorrespondenceshouldbeaddressedtoA.J.Litta,[email protected]
Received30October2011;Accepted12December2011
AcademicEditor:FeiChen
Copyright©2012A.J.Littaetal. This is an open access article distributed under the Creative Commons Attribution License,
whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperlycited.
Thethunderstormsaretypicalmesoscalesystemsdominatedbyintenseconvection.Mesoscalemodelsareessentialfortheaccurate
predictionofsuchhigh-impactweatherevents.Inthepresentstudy,anattempthasbeenmadetocomparethesimulatedresultsof
threethunderstormeventsusingNMMandARWmodelcoreofWRFsystemandvalidatedthemodelresultswithobservations.
Bothmodelsperformedwellincapturingstabilityindiceswhichareindicatorsofsevereconvectiveactivity.Comparisonofmodel-
simulatedradarreflectivityimagerieswithobservationsrevealedthatNMMmodelhassimulatedwellthepropagationofthesquall
line,whilethesqualllinemovementwasslowinARW.Fromthemodel-simulatedspatialplotsofcloudtoptemperature,wecan
seethatNMMmodelhasbettercapturedthegenesis,intensification,andpropagationofthundersquallthanARWmodel.The
statisticalanalysisofrainfallindicatesthebetterperformanceofNMMthanARW.Comparisonofmodel-simulatedthunderstorm
affectedparameterswiththatoftheobservedshowedthatNMMhasperformedbetterthanARWincapturingthesharprisein
humidityanddropintemperature.ThissuggeststhatNMMmodelhasthepotentialtoprovideuniqueandvaluableinformation
forseverethunderstormforecastersovereastIndianregion.
1.Introduction facet. Because of its propensity to harm life and property,
this weather phenomenon has drawn the attention of the
Thunderstorm,resultingfromvigorousconvectiveactivity,is professionalmeteorologistsforthelastninedecades[3].
oneofthemostspectacularweatherphenomenaintheatmo- Awarm,moist,andsoutherlylowlevelflowfromtheBay
sphere. Northeastern part of Indian region (20◦N to 24◦N ofBengalandacool,dry,westerly,ornorthwesterlyupper-
latitude,85◦Eto93◦Elongitude)experiencesthunderstorms levelflowgiverisetoafavorablesynopticsettingforthefor-
at higher frequency during premonsoon months (March– mationofNor’westers.Further,Nor’westershaveamesoscale
May), when the atmosphere is highly unstable because of structure with a very rapid development. The surface ob-
high temperatures prevailing at lower levels. These storms servations and radiosonde data are usually being used for
predominantly come from the northwest and hence called forecasting Nor’westers. However, the timing and spacing
Nor’wester, locally named as “Kal-baishakhi” [1], though of these observations are often inadequate to diagnose the
theycancomefromotherdirectionsaswell.Theyareoften evolution of preconvective conditions of Nor’westers. The
associatedwithmoderate/severesquallsachievingaspeedin understanding and prediction of these weather events is a
therangeof130–150km/hr,whichmayevenreachtornadic challengetotheatmosphericscientists.STORMprogramme
violence causing considerable damage to property and loss focuses a comprehensive observational and modeling study
oflife.Suchsevereweathersystemsaffectthecropsandlives on genesis,evolution, andlifecycleof intense tropical con-
on the ground and aviation aloft [2]. Naturally, it has im- vective activities over east and northeast regions of India
mense economic and societal impact on human existence. duringpremonsoonperiodthroughmesonetworkofobser-
The associated large hailstones, high wind gust, and heavy vations and mesoscale analysis and prediction systems. As
rainfall have given the weather phenomenon a hazardous the Nor’westers also affect Bangladesh, Nepal, and Bhutan,
2 TheScientificWorldJournal
therefore,in2009thefieldexperimentwasextendedtocover quantitative verification of the results was performed with
these countries as well. A coordinated field experiment classical statistics parameters, namely, mean absolute error
named“SAARCSTORM”wasconductedjointlywiththe4 (MAE), root mean square error (RMSE), and correlation
countriesduring1–31May2009[4]. coefficient (CC). The temporal variations of temperature
Numerical modeling has made substantial advances in and relative humidity, which are useful for occurrence and
themodelingofconvectivecloudsandmesoscaleconvective intensity of the severe thunderstorms, are evaluated and
systems[5].ManymesoscalemodelslikeMM5,WRF-ARW validated the model results with observations. The model-
(advancedresearchWRF),WRF-NMM(nonhydrostaticme- simulatedradarreflectivityandcloudtoptemperaturewere
soscalemodel),ARPS(advancedregionalpredictionsystem) compared with the Kolkata DWR and Kalpana satellite
and RAMS (regional atmospheric modeling system) have imageries,toverifywhetherthemodelswereabletosimulate
been in operational use for forecasting thunderstorms at thegenesis,intensification,andpropagationofthesethunder
manyplacesintheworld.Abasiccharacteristicofthesemod- squalls. This study is presented in the following manner.
elsisthattheirgoverningequationsarenonhydrostaticsince Section2presentsthecasedescriptionofallthreecasestaken
the vertical and horizontal scales of convection are similar. up in the present study. Section3 presents the description
Suchmodelsarealsonecessaryforexplicitlyresolvinggravity of numerical model and configurations. The results and
wavestriggeredbyclouds.Presently,mesoscalemodelshav- discussionaredescribedinSection4andtheconclusionsin
ingaresolutionlessthan9kmarealsoavailableforthesim- Section5.
ulation and prediction of regional weather systems. These
models can be used for a variety of applications including 2.CaseDescription
simulationandpredictionofheavyrainfall,severethunder-
storms,andtropicalcyclones[6–8].Thunderstormforecast- Forthepresentstudy,threeseverethunderstormcasesduring
ing is one of the most difficult tasks in weather prediction, SAARCSTORMfieldexperiment2009havebeentaken,and
duetotheirrathersmallspatialandtemporalextension[9]. thedescriptionofeachcaseisasfollows.
The understanding of the dynamical/physical mech- Case 1 was a severe thunderstorm, which was reported
anisms of thunderstorms is essential for improving the on 03 May 2009 over Kolkata (Figure1) with a maximum
forecastofthesesystems.Oneofthewaystounderstandthe speed of 61.2kmph lasting for a few minutes. This intense
physics and dynamics of these severe thunderstorms is to convectiveeventproduced31.4mmrainfalloverKolkata.In
simulatethesesystemswiththehelpofmesoscalemodels.A the synoptic charts at 0000UTC, a low-pressure area was
numberofstudieshavebeencarriedout[10,11]tosimulate found at the surface over north Chattisgarh and adjoining
thunderstorms for studying various dynamical and physi- Jharkhand,andatroughfromthisextendingsouthwardup
cal processes occurring within them. Accurate simulation to interior Tamilnadu across Andhra Pradesh is found. At
requires knowledge about “where” and “when” storms will 1.5km above sea level (a.s.l), cyclonic circulation is seen
developandhowtheywillevolve.Thehigh-resolutionnon- over west Uttar Pradesh, and a trough from this extends
hydrostaticmesoscalemodelswithsophisticatedparameteri- southeastwards up to south peninsula across east Madhya
zationschemesfortheimportantphysicalprocesseswouldbe Pradesh and Andhra Pradesh. No significant trough in
averyusefultoolforreasonablyaccuratepredictionofthese midtroposphere. No subtropical westerly jet maxima were
severe thunderstorms [12]. However, mesoscale research seenovertheregion.Afewplacesrecordedmoderaterainfall
and forecasting in India could not keep pace with devel- overGangeticWestBengal(GWB)andisolatedrainfallover
opments of the post-1970 period, especially in respect of Orissa, Chattisgarh, and Bihar. Bankura recorded 24.9mm
mesoscaleobservationaltechniques(Dopplerweatherradar andSriniketan38.2mmofrainfall.
(DWR), wind profilers, mesonetwork), mesoscale analysis, Case 2 was a severe thunderstorm, which was reported
and mesoscale numerical weather prediction (NWP) [13]. on11May2009overKolkatawithsquallywindsoftheorder
In India, studies related to modeling of clouds are very of87kmph.Rainfallof33.3mmwasreportedoverKolkata.
scarce and in particular intense thunderstorm events [14]. The synoptic charts show a trough at sea level chart from
Simulation of severe thunderstorms with high-resolution east Uttar Pradesh to north Tamilnadu across east Madhya
mesoscalemodelsovereastIndianregionhasbeenattempted Pradesh and Andhra Pradesh. Cyclonic circulation in lower
bymanyIndianresearchersrecently[7,15–17]. levels is found over Bihar and neighborhood. Trough from
In the present study, an attempt has been made to this extends up to extreme south peninsula across Chattis-
comparethesimulatedresultsofthreethunderstormevents garh, Telangana, and Rayalaseema. Another cyclonic circu-
(03 May 2009, 11 May 2009, and 15 May 2009) during lation was existed over Arunachal Pradesh and adjoining
SAARC STORM field experiment 2009, using WRF-NMM AssamandMeghalaya.AtroughfromArunachalPradeshto
model developed by National Oceanic and Atmospheric northwest Bay of Bengal was found in middle troposphere.
Administration(NOAA)/NationalCentersforEnvironment Subtropicalwesterlyjetmaximawerefoundovertheregion.
Prediction(NCEP)andWRF-ARWmodelingsystemdevel- Light-to-moderate rain occurred at few places over Orissa
opedbyNationalCentreforAtmosphericResearch(NCAR). and GWB with Midnapore and Alipore reporting 17.8mm
ThecapacitiesoftheWRF-NMMandWRF-ARWmodelin and21.9mm,respectively.
retrievingprecipitationfieldsovereastIndianregionduring Case 3 was a severe thunderstorm, which was reported
threeseverethunderstormeventswereanalyzed,bycompar- on15May2009.AsquallpassedoverKolkataat1230UTC
ing the outputs of the models with ground observations. A on15May2009withamaximumspeedof68.4kmph.This
TheScientificWorldJournal 3
Figure1:ThegeographicallocationofKolkatainWestBengal(regionofstudy).
Table1:ARWandNMMmodelconfiguration. Table2:Thedifferentstabilityindicesandtheircriticalvaluesfor
severethunderstorm.
Model WRF-NMM WRF-ARW
Criticalvalues
Dynamics Nonhydrostatic Nonhydrostatic Stability
Description forsevere
Horizontalresolution 3km 3km indices
thunderstorm
Forecastlength 24hrs 24hrs
Liftedindex T −T <−3
Rotatedlatitudeand 500 parcel
Mapprojection longitude Mercator Kindex (T850 − T500)+Td850−(T700− >33
DT )
Horizontalgrid 700
system ArakawaE-grid ArakawaC-grid TotalTotals (T850 + Td850)−2(T500) >44
Terrainfollowing Showalter
Hybridsigmato sigmavertical index T500−T850 <−2
Verticalcoordinate pressurevertical
coordinate(38 12Td +20(TT−49)+2f +
coordinate(38levels) SWEATindex 850 850 >250
levels) f +125(s+0.2)
(cid:2) 500
Radiation GFDL/GFDL GFDL/GFDL CAPE (cid:2) zzfng(Tvparcel−Tvenv/Tvenv)dz >1500
Surfacelayer Janjicscheme Janjicscheme CIN ztop g(Tv −Tv /Tv )dz <50
Noahlandsurface Noahland zbottom parcel env env
Landsurface
scheme surfacemodel
Cumulus Grell-Devenyi Grell-Devenyi
Mellor-Yamada- West Uttar Pradesh and a trough from this extends up to
PBLparameterization Mellor-Yamada-Janjic
Janjic coastal Andhra Pradesh across Vidarbha with embedded
Ferrier(neweta) Ferrier(neweta) cyclonic circulation over Telangana. Trough in midtropo-
Microphysics
scheme scheme sphere is found from Arunachal Pradesh to north Bay of
Bengal. Subtropical westerly jet maxima were found over
theregion.AfewplacesofGWBrecordedmoderaterainfall
intense convective event produced 16.9mm rainfall over andisolatedrainfalloverOrissaandBihar.Bankurarecorded
Kolkata.Thesynopticchartsshowatroughatsealevelfrom 34.0mmandMidnapore51.6mmofrainfall[4].
east Madhya Pradesh to south coastal Tamilnadu across Thecommonfeatureinthesynopticsituationinallthe
Telangana and another trough to northeast Bay of Bengal cases was a trough, or a low pressure area was observed
across Orissa. Cyclonic circulation seen in lower levels over at the surface extending from Uttar Pradesh/Chattisgarh to
4 TheScientificWorldJournal
Table3:ComparisonofNMM-andARW-model-simulatedstabilityindiceswithFNLanalysisforthreethunderstormeventsduringSAARC
STORMfieldexperiment2009.
Stability Critical Thunder 0000UTC 1200UTC
indices level stormcases FNL NMM ARW FNL NMM ARW
3May 2035 2947 3338 3412 3361 3583
11May 2959 3685 3455 2248 3932 3963
CAPE >1500
15May 2395 3033 3100 656 2993 3554
MEAN 2463 3221.7 3297.7 2105.3 3428.7 3700
3May −5 −7 −8 −7 −7 −8
11May −9 −10 −9 −6 −10 −11
LI <−3
15May −8 −9 −8 −2 −6 −8
MEAN −7.3 −8.7 −8.3 −5 −7.7 −9
3May 48 50 49 47 49 50
11May 52 51 51 52 56 58
TT >44
15May 51 50 50 46 43 47
MEAN 50.3 50.3 50 48.3 49.3 51.9
3May 20 29 30 42 29 26
11May 28 28 27 44 39 36
KI >33
15May 35 33 34 37 29 28
MEAN 27.7 30 30.3 41 32.3 30
Table4:Comparisonofmodeledprecipitationofthreethunderstormcaseswithraingaugeobservations.
Date Station LAT LONG IMD ARW NMM
DumDum 22.39 88.27 31.4 6.56 23.26
Bankura 23.13 87.04 24.9 12.62 14.73
Basirhat 22.4 88.53 21.2 12.14 14.12
3-May-09 Sriniketan 23.39 87.42 38.2 35.24 26.06
Balasore 21.3 86.56 43.3 11.8 31.04
Jamshedpur 22.44 86.12 35.8 32 15.49
MEAN 32.47 18.39 20.78
DumDum 22.39 88.27 33.3 12.48 23.10
Bankura 23.22 87.07 22 3.44 15.13
Canning 22.25 88.67 26.4 12.87 21.00
11-May-09 Basirhat 22.4 88.53 48.4 18.74 24.75
Digha 21.83 87.8 24.4 0 10.08
Kharagpur 22.2 87.19 16.8 19.31 11.99
MEAN 28.55 11.14 17.68
DumDum 22.39 88.27 16.9 35.30 17.19
Bankura 23.13 87.04 34 20.40 24.69
Krishnagar 23.24 88.31 19.6 17.17 18.72
15-May-09 Digha 21.5 87.48 21 18.4 18.39
Midnapore 22.25 87.19 51.6 17.7 26.54
Haldia 22.04 88.04 33.2 21.2 30.39
MEAN 29.38 21.69 22.65
Table5:Statisticalanalysisofmodeledprecipitationforthreethunderstormcases.
Statisticalanalysis Descript(cid:4)ion NMM ARW
(cid:3)
Correlationcoefficient(CC) cc= (fi− f)(cid:4)(oi−o)/(cid:3)(fi− f)2(oi−o)2 0.565 0.121
Rootmeansquareerror(RMSE) RMSE= (1/N) N (f −o)2 13.785 18.464
(cid:3)i=1 i i
Meanabsoluteerror(MAE) MAE=(1/N) N |f −o| 10.905 15.379
i=1 i i
TheScientificWorldJournal 5
110 110
%)100 %)100
dity ( 8900 dity ( 8900
mi 70 mi 70
hu 60 hu 60
Relative 345000 Relative 345000
20 20
Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z
00 02 04 06 08 10 12 14 16 18 20 22 00 02 04 06 08 10 12 14 16 18 20 22
Time (UTC) Time (UTC)
OBS OBS
ARW ARW
NMM NMM
(a) (b)
110
%) 100
y ( 90
dit 80
mi 70
u
h
e 60
v
ati 50
el
R 40
30
Z Z Z Z Z Z Z Z Z Z Z Z
0 2 4 6 8 0 2 4 6 8 0 2
0 0 0 0 0 1 1 1 1 1 2 2
Time (UTC)
OBS
ARW
NMM
(c)
Figure 2: Inter comparison of NMM and ARW model simulated and observed diurnal variation of surface relative humidity (%) over
Kolkataon(a)03May2009(b)11May2011(c)15May2011.
TamilnadualongAndhraPradesh,withcycloniccirculations 3.NumericalModel
at1.5kma.s.loverUttarPradesh/Bihar.Atroughinthemid
tropospherewasfoundincases2and3(11,May,2009and NMMandARWmodelingsystemswereusedinthisstudyto
15,May,2009)whichwasabsentinthefirstcase.Intheupper performcloud-resolvingsimulationofthunderstormevents
levels the westerly jet maxima was providing good amount thatoccurredovereastIndianregionduringthefieldexper-
divergence in Cases 2 and 3, but was not found in case 1. imentofSAARCSTORMprogramme2009. Severalstudies
Moisture incursion was found in the lower levels in all the relatedtothesimulationofseverethunderstormeventsusing
three cases with moist southerly/southwesterly winds from NMM model have been performed worldwide [12, 18, 19].
Bay of Bengal sweeping the domain. In view of the above Researches related to comparison of impacts of ARW and
environmentalsettings,itcanbefurtherseenthatalthough NMM mesoscale dynamic cores over the US have been
there was enough moisture incursion in the first case, the performed [20–22]. This study is the first attempt in India
convective system developed on the day was comparatively to compare ARW and NMM models in the same WRF
weak which displayed weak echoes. This can be attributed frameworkforthesimulationofthunderstormevents.
to nonsupportive synoptic situation in the mid and high NMMrunsareinitializedthroughthesamebasicmech-
levels,whereasintheothertwocasesthesynopticsituation anism as the ARW runs: the WRF preprocessing system
wasfavorablebothinthelowerandhigherlevelsproducing (WPS) reads GRIB data from an initializing model and
strongerechoesaswerewitnessedinDWRimages(Figures4, interpolates it onto the target WRF domain grid. However,
7,and10).Thedirectionofmovementofthesqualllinesgen- thefunctionalityoftheWPShadtobeexpandedtohandle
erated over the western part of the domain over Jharkhand thehorizontalstaggering,mapprojection,andverticalcoor-
was southwesterly, and the ones initiated over northwest dinate used by the NMM, as each is distinct from its ARW
Bangladeshweresoutherly.Thisfeatureofmovementofthe counterpart. The NMM is a fully compressible, nonhydro-
squall lines was similar in all the three cases. So the cases staticmesoscalemodelwithahydrostaticoption.Themodel
basically differ in convection getting initiated under weaker usesaterrainfollowinghybridsigma-pressureverticalcoor-
andstrongersynopticsituation. dinate. NMM model surfaces are terrain-following sigma
6 TheScientificWorldJournal
42 42
39 39
C) 36 C) 36
◦mperature ( 22334703 ◦mperature ( 22334703
Te 21 Te 21
18 18
15 15
Z00 Z02 Z04 Z06 Z08 Z10 Z12 Z14 Z16 Z18 Z20 Z22 Z00 Z02 Z04 Z06 Z08 Z10 Z12 Z14 Z61 Z18 Z20 Z22
Time (UTC) Time (UTC)
OBS OBS
ARW ARW
NMM NMM
(a) (b)
38
36
C) 34
◦e ( 32
ur 30
at 28
er
p 26
m
Te 24
22
20
Z Z Z Z Z Z Z Z Z Z Z Z
0 2 4 6 8 0 2 4 6 8 0 2
0 0 0 0 0 1 1 1 1 1 2 2
Time (UTC)
OBS
ARW
NMM
(c)
Figure3:Inter,comparisonofNMM-andARW-model-simulatedandobserveddiurnalvariationofsurfacetemperature(◦C)overKolkata
on(a)03,May,2009(b)11,May,2011and(c)15,May,2011.
surfacesneartheground,purelyisobaricaboveaprescribed for horizontal advection, and Crank-Nicholson scheme for
pressure value (typically about 420hPa), and relax from verticaladvection.Thesametimestepisusedforallterms.
terrainfollowingtoisobaricovertheinterveningdepth.Fur- Thedynamicsconserveanumberoffirst-andsecond-order
ther details of the vertical coordinate can be found in [23], quantitiesincludingenergyandenstrophy[25],whileARW
whileARWmodel’sverticalcoordinateisaterrain-following modeluseshigher-ordernumerics.ThisincludestheRunge-
hydrostaticpressurecoordinate. Kutta 2nd- and 3rd-order time integration schemes and
Another key difference between the NMM and ARW 2nd-to6th-orderadvectionschemesinbothhorizontaland
relevant to model initialization is the use of a rotated verticaldirections.Itusesatime-splitsmallstepforacoustic
latitude-longitude grid in the NMM. The simplicity of a andgravity-wavemodes.Thedynamicsconservesscalarvar-
latitude-longitude grid is made applicable over the entire iables. Both models support a variety of capabilities, which
globebyrotatingtheearth’slatitude-longitudegridsuchthat include real-data simulations, full physics options, nonhy-
the equator and prime meridian intersect at the center of drostatic and hydrostatic (runtime option), one-way static
theNMM’scomputationalgrid.Thisrotationminimizesthe nesting,andapplicationsrangingfrommeterstothousands
convergenceofmeridians,keepingthetruehorizontalscale ofkilometers.
relativelyuniformoverthedomain.Thegridstaggeringused Inthepresentstudy,bothARWandNMMmodelswere
in NMM model is the Arakawa E-grid, where both wind integratedforaperiodof24hoursstartingfrom0000UTC
components are collocated on the same grid point offset of each day and ending at 0000UTC of the following day.
fromtheassociatedmasspoint.RationaleforselectinganE- Boundary and initial conditions for both models are from
gridoverthemorewidelyusedArakawaCgridisdiscussed the high-resolution global final (FNL) analyses data set of
elsewhere [24]. ARW model grid staggering is the Arakawa NCEPwith1.00×1.00 lat/longrids.Bothmodelsthushave
C-grid. a common starting point and avoid a potential source of
NMM model uses a forward-backward scheme for hor- difference. A single domain was configured with 3km hor-
izontally propagating fast waves, implicit scheme for ver- izontal spatial resolution, which is reasonable in capturing
tically propagating sound waves, Adams-Bashforth scheme the mesoscale cloud clusters. The domain covers 84.5◦E to
TheScientificWorldJournal 7
(a) 1000UTC (b) 1100UTC
0 7 3 8 7 3 6 7 3 4 7 3 2 7 3 0 7 3 8 7 3 6 7 3 4 7 3 2 7 3
2 2. 5. 2 0. 3. 3 8. 1. 4 6. 9. 5 4. 7. 2 2. 5. 2 0. 3. 3 8. 1. 4 6. 9. 5 4. 7.
2 2 3 3 3 4 4 4 5 5 2 2 3 3 3 4 4 4 5 5
(dBZ) (dBZ)
(c) 1200UTC (d) 1300UTC
Figure4:KolkataDopplerweatherradar(DWR)compositeradarreflectivity(dBZ)imageriesfrom1000to1300UTCon03,May,2009.
92.5◦E and 19.5◦N to 27.5◦N, and the grids are centered at various fields not directly computed by the models, and
88.5◦E, 23.5◦N. Both NMM and ARW domains are config- generates a GRIB file on the model’s native projection (ro-
ured with vertical structure of 38 unequally spaced sigma tatedlatitudelongitudefortheNMMandmercatorforthe
(nondimensionalpressure)levels.Inthisstudy,wechosethe ARW). NCEP’s “product generator” horizontally interpo-
same physics options for both the ARW and NMM sim- lates the data from each model onto a common grid used
ulations. Both models used Geophysical Fluid Dynamics for visualization and verification. The hourly observations
Laboratory(GFDL)forradiation[26],Mellor-Yamada-Janjic ofAWSdata,DWRimageriesoverKolkata,Kalpanasatellite
(MYJ) scheme [27] for planetary boundary layer, Ferrier imageries and rain gauge observations collected during the
scheme [28] for microphysics, Janjic similarity scheme for SAARC STORM field experiment 2009 are used in this
surfacelayer[29],Noahlandsurfaceschemeforlandsurface presentstudyformodelvalidation.
[30], and Grell-Devenyi cloud ensemble scheme [31] for
cumulus parameterization. All the above schemes are well 4.ResultsandDiscussion
testedforNMMandARWmodels.Table1showsthemodel
configurationofthepresentstudy. Anumberofmeteorologicalconditionsarerequiredforcon-
Outputfromeachmodelispostprocessedtobringthem vectiontostart.Theseconditionsareinstability,asufficiently
back to a common format that enables direct comparison. deephumidlayerinthelowerandmiddletroposphere,and
TheNCEPWRFpostprocessor(WPP)verticallyinterpolates an updraft, which are needed to initiate convection, since
output from each model onto isobaric surfaces, diagnoses theupdraftsrelatedtoprocessesonasynopticscalearetoo
8 TheScientificWorldJournal
27N 27N
26N 26N
25N 25N
24N 24N
23N 23N
22N 22N
21N 21N
20N 20N
85E 86E 87E 88E 89E 90E 91E 92E 85E 86E 87E 88E 89E 90E 91E 92E
(a) 1000UTC (b) 1100UTC
27N 27N
26N 26N
25N 25N
24N 24N
23N 23N
22N 22N
21N 21N
20N 20N
85E 86E 87E 88E 89E 90E 91E 92E 85E 86E 87E 88E 89E 90E 91E 92E
0 5 10 15 20 24 27 30 33 36 0 5 10 15 20 24 27 30 33 36
(c) 1200UTC (d) 1300UTC
Figure5:NMM-simulatedcompositeradarreflectivity(dBZ)picturesfrom1000to1300UTCon03,May,2009.
slowtolifttheairtotheleveloffreeconvection(LFC).The weather events. The indices are having critical values and
formationofthunderstormsisaninteractionbetweenthese abovethesecriticalvalues,wecansaythatthereispossibility
conditions on different scales. Convective systems depend ofthesevereconvection.Studiesontheefficiencyofdifferent
primarily on large-scale processes that develop an adequate stability indices for the thunderstorm prediction have been
thermodynamicstructure,whereasprocessesonamesoscale made by several authors [34–36]. Advection of warm air in
actbasicallyatthebeginningoftheconvectivephenomenon the lower levels and cold air in the upper levels (generally
[32, 33]. In this paper, we are analyzing some of the severe associated with deep troughsin upper tropospheric wester-
thunderstorm-affectedparametersbycomparingNMMand lies) increases the conditional instability in the atmosphere
ARW model for three severe thunderstorm cases over east andfavoroutbreakofseverethunderstorms[37,38].
Indianregion. The introduction of an index by Showalter [39] rep-
resents a watershed moment, beyond which we have seen
4.1.AnalysisofStabilityIndices. Stabilityindiceshavebeena a steady proliferation of indices, which are lifted index,
cornerstone in the forecasting of convection for many dec- SWEAT, K index, total totals index, CAPE, and so forth.
ades and often are used in the research literature as well. Many of these indices are keyed to mandatory pressure
These indices are very helpful in predicting the severe levels, with Showalter’s prototype, for example, being tied
TheScientificWorldJournal 9
27N 27N
26N 26N
25N 25N
24N 24N
23N 23N
22N 22N
21N 21N
20N 20N
85E 86E 87E 88E 89E 90E 91E 92E 85E 86E 87E 88E 89E 90E 91E 92E
(a) 1000UTC (b) 1100UTC
27N 27N
26N 26N
25N 25N
24N 24N
23N 23N
22N 22N
21N 21N
20N 20N
85E 86E 87E 88E 89E 90E 91E 92E 85E 86E 87E 88E 89E 90E 91E 92E
0 5 10 15 20 24 27 30 33 36 0 5 10 15 20 24 27 30 33 36
(c) 1200UTC (d) 1300UTC
Figure6:ARW-model-simulatedcompositeradarreflectivity(dBZ)from1000to1300UTCon03,May,2009.
exclusivelyto850and500hPa.Convectiveavailablepotential to −3. This is because air rising in these situations is much
energy (CAPE) is perhaps the index least dependent on warmerthanitssurroundingsandcanacceleraterapidlyand
mandatory pressure levels, since it involves integration createtallandviolentthunderstorms.
between levels of some physical significance (the LFC and The K index (KI) is a combination of the vertical totals
the LNB). CAPE represents the amount of buoyant energy (VT) and lower tropospheric moisture characteristics. The
available to accelerate a parcel vertically, and a CAPE value VT is the temperature difference between 850 and 500hPa,
greaterthan1500Jkg−1 issuggestedbyRasmussenandWil- while the moisture parameters are the 850hPa dew point
helmson [40] as being necessary for super cells to form. and700hPadewpointdepression.TheKIhasproveduseful
Liftedindex(LI)measuresthedifferencebetweenaparcel’s in indicating the probability of severe thunderstorms. As
temperaturescomparedwiththeenvironmentaltemperature the KI increases, so does the probability of having a severe
at 500hPa, after the parcel has been lifted from the lifting thunderstorm [41]. Miller [42] introduced the total totals
condensationlevel[41].TheLIisprovedusefulforindicat- index(TTI)foridentifyingareasofpotentialthunderstorm
ingthelikelihoodofseverethunderstorms.Thechancesofa development. It accounts for both static stability and the
severethunderstormarebestwhentheLIislessthanorequal presence of 850hPa moisture. A TTI of greater than 44
10 TheScientificWorldJournal
(a) 1000UTC (b) 1100UTC
0 7 3 8 7 3 6 7 3 4 7 3 2 7 3 0 7 3 8 7 3 6 7 3 4 7 3 2 7 3
2 2. 5. 2 0. 3. 3 8. 1. 4 6. 9. 5 4. 7. 2 2. 5. 2 0. 3. 3 8. 1. 4 6. 9. 5 4. 7.
2 2 3 3 3 4 4 4 5 5 2 2 3 3 3 4 4 4 5 5
(dBZ) (dBZ)
(c) 1200UTC (d) 1300UTC
Figure7:KolkataDWRcompositeradarreflectivity(dBZ)imageriesfrom1000to1300UTCon11,May,2009.
indicates favorable conditions for development of severe the validation of model-simulated stability indices. Table3
thunderstorms[41].Thequestionishoweffectivetheseare shows the intercomparison of FNL-analyzed and model-
whenemployedasthunderstormpredictors,thatis,usedfor simulated stability indices over Kolkata at 0000UTC and
“thundery”or“nonthundery”forecastsaccordingtoacer- 1200UTC. The NMM- and ARW-model-simulated CAPE
tainthresholdvalue.Usuallyconvectiveindicesareemployed valuesarehighandgreaterthanthecriticallevelat0000UTC
to alert the meteorologist on thunderstorm occurrence or and1200UTCofthesethreethunderstormevents,whichis
nonoccurrence. Often a certain threshold value is defined afavorableconditionforseverethunderstorms.Themodel-
above(below)whichthepossibilityofthunderstormsiscon- simulated CAPE values of 03, May, 2009 at 1200UTC are
sidered.Table2showsthedifferentstabilityindicesandtheir closetotheFNL-analyzedvalues(Table3).Itisalsoseenthat
critical values for severe thunderstorms. It should be noted except on 15, May, 2009, where the FNL value of CAPE is
that some of these indices are best suited for forecasting less than that of the model-simulated values, on all other
duringcertainconditions.Forexample,theKIisoptimalfor daystheFNLanalyzedandsimulatedCAPEvaluesaregreater
predictingairmassthunderstorms[40]. than 2000J/kg. On 15, May, 2009, the NMM- and ARW-
Inthepresentstudy,anattemptismadetoexaminedif- model-simulatedCAPEvalueswere2993J/kgand3554J/kg
ferentstabilityindicesobtainedfromNMMandARWmodel whicharefargreaterthantheFNL-analyzedCAPEvalueof
in three thunderstorm days during SAARC STORM field 656J/kg. The mean of simulated CAPE values at 1200UTC
experiment 2009 at 0000UTC and 1200UTC over Kolkata is found to be much larger than the FNL-analyzed values
(22.52◦N, 88.37◦E). FNL-analyzed data has been used for indicating that the models tend to simulate large CAPE