Dec 20, 1999 - precursors reduction scenarios over the large domains undergoing .... Species Name ..... sunset, for an integration time affordable for a regional.
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 104, NO. D23, PAGES 30,351-30,371,DECEMBER 20, 1999
Studying ozone climatology with a regional climate
model
1. Model description and evaluation V. S. Bouchet, • R. Laprise,and E. Torlaschi D•partement des Sciencesde la Terre, Universit• du Quebec k Montr6al, Canada
J. C. McConnell Department of Earth and AtmosphericScience,York University, Toronto, Ontario, Canada
Abstract. On the basisof the CanadianRegionalClimate Model (CRCM) a new regional oxidant model has been developedto study ozone climatology in eastern Canada. In addition to the semi-Lagrangianadvectionand vertical diffusionschemes already present for tracers, a chemical module, dry deposition parameterization, and anthropogenicand on-line biogenicemissionswere added to the CRCM. The completemodel forms a singlesystemwhich integratesmeteorologicaland chemical variables simultaneously. Transport of 25 chemical speciesis evaluated on a 80 x 80 horizontal grid at 42.3 km resolutionand for the 24 unequallyspacedlevels. The chemical schemeincludes47 speciesand 114 reactionsused in the Acid Deposition and Oxidant Model (ADOM) gas-phase mechanism.Precalculatedphotolysisrates, correctedfor the model cloud cover through the variations of the simulated solar radiation penetration, are used in the model. This limited-area model is driven at its boundaries by objective reanalysesfor the meteorologicalfields and by climatologicalconcentrationsfor the chemicalcounterparts.A time step of 15 min common to all processesis currently used. A two-step validation procedure, which includesspecificcasesand climatologicalsimulations,was adopted. The first test consistsof a week-longsimulationfor the first weekof August 1988 when an intense ozoneepisodeaffectedmostof northeasternAmericaduring the first Eulerian Model Evaluation and Field Study (EMEFS) campaign. Resultsshowthat the CRCM ability to simulate this episodeis comparableto other existingmodelsusingoff-line approaches.The CRCM performancewas substantiallyimprovedby the addition of the biogenicemissionparameterization. Climatology-specificresults are presented
in the companionpaperby Bouchetet al. [thisissue]. 1.
Introduction
mationof the role of biogenicVOCs [Chameides et al., 1988] and, especially in eastern North America, of longWith increasingevidencefor harmful effectsof groundrange transport of ozone and precursors [NAS, 1991] as level ozone on human health and ecosystems,control
possiblecausesfor this lack of efficacy. programshave been initiated in many urban centers Three-dimensionalemission-based modelshave aparoundthe world,with variousdegreesof success [Napeared as a key research tool to investigate various tionalAcademyof Science(NAS), 1991].Thoughtto be precursors reduction scenarios over the large domains the most efficient control, limitations of anthropogenic undergoinglong-rangetransport and aid in the develvolatile organiccarbon (VOCs) emissionsappearedto managementstrategies.Regional be effective in the worst urban locations but failed to opmentof emissions models such as those of Carmichaelet al. [1986],the improveair quality in smallurban, suburban,and rural
surroundings.Further researchpointedto an underesti- Acid Depositionand OxidantModel (ADOM) [Vekatram et al., 1988],the RegionalAcid DepositionModel
(RADM) [Changet al., 1987],or the RegionalOxidant • Now at AtmosphericEnvironmentService,Environment Model(ROM) [Schere and Wayland,1989]describe the Canada, Downsview,Ontario, Canada. numerousinteractionsbetween chemical, meteorological, and biological processeswhich result in the forCopyright1999 by the AmericanGeophysicalUnion. Paper number 1999JD900805.
0148-0227/99/1999JD900805509.00
mation and accumulationof ozone. As a consequence of their complexity,modeling applicationshave often beenlimited to shortsimulationslastinga few daysto a
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30,352
BOUCHET ET AL.: MODELING OZONE CLIMATOLOGY, 1
week[Hedleyet al., 1997;Pudykiewicz et al., 1997],with
This paper and the companion paper by Boucher et
emissionsscenariosusually evaluated on the same cases
al. [thisissue]presentthe development, validation,and
[Roselleand Schere,1995;EnvironmentCanada(EC), applications of a regional oxidant model designedfor 1997].Whetherthe conclusions basedon theseepisodes long simulations.The recentdevelopmentof the Canawould remain valid for different meteorologicalperiods dian RegionalClimateModel (CRCM) hasprovidedan adequate framework for this purpose, and a chemical module was thereforeintroduced "on-line." A general descriptionof the completemodel is given in section2. itations. Bastrup-Birket al. [1997],for example,simu- Resultsfrom the evaluationof the CRCM for the highly lated ozoneexposureduring a 7-year period but had to studied, intense ozone episode which affected most of restrict their study to two dimensions. Results of a lim- northeasternAmerica during the first week of August ited2-daycomparison by RoselleandSchere [1995]hint, 1988 are reported in section 3. Sensitivity tests on the nevertheless,that the chemicalregimein severalregions influence of chemical boundary conditions and unceraffectedby long-rangetransport in northeasternUnited tainties in biogenicemissionsinventoriesare described Statescan changefrom VOC-limited to NOx-limited de- in section4, and section5 summerizesthe conclusions. pending on the meteorologicalconditions,which could Application and validation for five consecutivesJulys result in drastically different emissionreduction strate- are presentedby Boucheret al. [thisissue]. is an open question. In fact, until recently the influenceof meteorologicalvariability on the resultshas not receivedmuch coveragedue to model and computerlim-
gies.
Sincemeteorologyplays an essentialrole in air quality problems,a tighter couplingbetweenair quality and meteorologicalmodels has been recommendednot only for the third generationof oxidant modelsin order to minimize
inconsistencies
due to differences
in coordi-
nates and grid systemsand land-useor topographyinformation and resolution, but also in the methods used to represent their common processessuch as advection,
turbulent diffusion,convection,clouds,etc. [Peterset al., 1995; Dennis et al., 1996]. Applyingthe sameal-
2. Model Description The CRCM is a limited-areamodel resultingfrom the couplingof the completesubgrid-scaleparameterization packageof the CanadianGeneral CirculationModel sec-
ond generation(CGCM II) [McFarlaneet al., 1992] with the semi-implicit and semi-Lagrangianmodel of the Cooperative Centre for Researchin Mesometeorology. The model has beenusedfor severalapplications, and variousdetails of the descriptionof the CRCM are
gorithms to identical processesis a simple way to insure maximum consistency.It is more readily achieved givenby Caya et al. [1995, 1998], Caya and Laprise with
an "on-line"
model in which the treatment
of wa-
[1999],and Lapriseet al. [1997,1999].To simulateox-
ter vapor, a tracer in prognosticmeteorologicalmodels, idant chemistryusingthe CRCM, the Acid Deposition is extended
to chemical tracers.
Additional
benefits re-
sult from the availability of the meteorologicalfieldsat each advection time step of the chemicalfields, including smallerstoragerequirementsand the suppression of errorsintroducedby usingand/or interpolatinghourly
and OxidantModel(ADOM) [Venkatramet al., 1988] gas-phasemechanism,emission,and dry depositionparameterizationswereincorporated. The model includes 47 chemicalspecies(seedetailsin Table 1) of which25 are transported accordingto
windfieldsin off-linemodels[Pielkeandal., 1998].This becomesmore feasible as the chemistry takes a larger fraction of the computer time with the addition of yet more speciesand aerosolsize distribution. Ground-level ozone is also a pervasive problem in eastern Canada, affectingparticularly the Atlantic re-
Ot
j
(Ofi) J
'
(1)
where fi is the mixing ratio of speciesi at time t and the sum over j includesadvection,diffusion,dry deposition, emissions,and chemistry.Equation (1) is solved with an operator-splitting technique, with the contriWQC are typically associatedwith slowmoving anticy- bution of transport by large-scalemotions(advection) clonic systemsor within the warm sectorof a cyclonic calculatedfirst, followedby the evaluationof the contrisystems,both generatingweak south to southwesterly bution of small-scalemotions(diffusionand dry depoflowand warmtemperatures[Fuenteset al., 1994].Al- sition)and emissions in a singlestep,and finallyby the thoughthere are significantsourcesof O3 precursors in calculation of the tendency due to the chemicalreacthe WQC, owingto thesepredominantmeteorological tions themselves. The numerical treatment of this last conditionsover the summer,long-rangetransport from step is detailed in section2.3. For the calculationsprethe highlyindustrializedDetroit-Windsor-Sarnia trian- sented herein, a constant time step of 15 min is used. gle is estimatedto contributeto an overall50-60%to The current configurationconsistsof 80 x 80 points ozone concentrationsin the southernpart of the WQC on a polar-stereographic grid, with 42.3-km resolution [Yapet al., 1988].Air qualityin the WQC coulddepend at 60øN, centeredon (45øN, 80øW), and 24 unequally as much on emissionscontrols initiated in the upwind spacedvertical levels. The vertical terrain-following sourceregionsas on local ones. Gal-Chencoordinate[Gal-ChenandSummerville, 1975]
gionsand the Windsor-Quebec City corridor(WQC), a heavily populatedarea as well as one of crucialimportance for Canadian agriculture. O3 exceedences in the
BOUCHET ET AL.' MODELING OZONE CLIMATOLOGY, 1
30,353
Table 1. Glossaryof the Chemical SpeciesUsed in the Mechanism SpeciesName
SpeciesSymbol
Dry Depositeda
Emitted
Transported Species
Nitrogen dioxide
NO2
Nitric oxide Nitrous acid Nitric acid Ozone
NO HONO HNO3
03 H202 SO2 SO4
Hydrogen peroxide Sulfur dioxide Sulfate Carbon monoxide
Ethene
Higher alkenes Isoprene aromatics
Xylene and di- and tri-substituted aromatics Formaldehyde Aldehydes Ketones
Methyl glyoxal Dicarbonyls Peroxyacetyl nitrate Organic nitrate Organic peroxide
x
MEK MGLY DIAL PAN
ROOH
O CRG1 CRG2 Other Species C2H2 FRMA
Acetic acid
ACTA
Nitrogen trioxide Dinitrogen pentoxide
NOs N205
Pernitric acid
HNO4
Hydroxyl radical Hydroperoxy radical Alkyl nitrate organicperoxy radical Acetyl peroxy radical Phenoxy radical Generic peroxy radical Organic peroxy radical 1 Organic peroxy radical 2
OH HO2
RO2N MCO3 BZO RO2 RO2R R202
Watervaporb
H20
Methane c
CH4
Ethane d
C2H6
Backgroundnumber density e
M
aDry-depositedor emitted speciesare indicated by a cross. ½Heldconstant at 1.7 ppmv.
dHeldconstantat 1.0 ppbv. eDerived from CRCM pressure.
x x x
x
RNOa
01D
bCalculatedin the meteorology code.
x x x x x x x x x x
Ground state oxygen atom Criegeeradical I Criegeeradical 2
acid
x x
ALKA ETHE ALKE ISOP TOLU CRES AROM HCHO ALD2
OxygensingletD
Formic
x
x x x
CsHs
Steady State Species
Ethyne
x x
CO
Propane Higher alkanes
Toluene and mono-substituted o-Cresol
x
x
x
30,354
BOUCHET ET AL.: MODELING OZONE CLIMATOLOGY, 1
allowsthe modelto accountfor the surfacetopography proximations made with the interpolation of upstream in the bottom levels;for this versionof the model there
values. The SL solutions, however, show far less false
are 10 levelsfor the bottom1.6 km (seeTable2) sothat ripples than correspondingsolutionsfrom many Eulethe dynamicsand chemistryin the planetaryboundary rian schemes. layer should be well represented. The horizontal and vertical resolutions,as well as the time step, are flexible model parameters and can be modified if needed.
SL schemescan be designedto be globally masscon-
servative[LapriseandPlante,1995],but the associated computational overhead does not seem worthwhile in a
limited area model wherethe masslossesor gains,consideringthe time an air masstypically spendsin the do2.1. •ransport main, are expected to be small. For the purposeof this Semi-Lagrangian(SL) transport schemeswere first study the CRCM is run with an unconstrainedcubic introduced in meteorologicalmodelsin the early 1990s interpolation, and no smoothingis applied to the point [Robertet al., 1985] and have sincebeen appliedto sourceemissions.Any spuriousnegativesproducedby tracer advectionin chemicaltransportmodels[Miiller the advection schemeare dropped, i.e., the concentraand Brasseur,1995;Pudykiewiczet al., 1997]. The SL tions are set to a minimum positive value. An average schemehas beenprovedto be very reliablefor modeling mass gain of 3% of NOx was observedfor the entire complex thermodynamic and dynamical processesand, simulation of the first week of August 1988 described thereafter. owing to its stability, allowsfor the use of longer time
steps[see,e.g., Robertet al., 1985]. The performanceof the SL transport schemeusedfor
our simulations wasstudiedby Pellerin et al. [1995]for the advection-condensationproblem. They show that this particular versionof the SL scheme,with unconstrainedcubicinterpolation, performswell when the initial distributionof the thermodynamicfieldsis not discontinuous,but it doesproducespuriousnoisein fields exhibiting sharp gradient zonesas a result of the ap-
2.2.
Subgrid-Scale Processes
With the exceptionof dry depositionand emissions parameterizationswhich are specificto the oxidant sim-
ulations,the CGCM II physicalparameterizationpack-
age [McFarlaneet al., 1992]is usedto represent the subgrid-scaleprocesses.It accountsfor vertical turbu-
lent fluxesof momentum,heat, and moisture;solarand terrestrial radiation; diagnosticallydetermined cloud amountsand water content;convection,condensation, and precipitation;variation of the surfacealbedo;surface energybudgetthroughthe force-restore method; Table 2. Levels of the Model in Pseudo-Sigma Coordinate,and the CorrespondingPressureand Height and a bucket-methodsoil moistureregime, as well as vegetationand soilcharacteristics.FollowingLapriseet for a Constant Temperature Profile with T = 220 K Level
Pseudo-Sigma
Pressure, kPa
Gal-Chen Height, m
al.'s [1999]recommendations, the thresholdof the fractional cloudcover,evaluatedfrom the prognosticmoisture and temperaturefieldsthrough relative humidity, has been adjusted to reflect the CRCM horizontal res-
i 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
0.082 0.118 0.163 0.216 0.273 0.334 0.397 0.459 0.518 0.571 0.619 0.659 0.699 0.739 0.779 0.819 0.854
7.9 11.5 16.1 22.4 29.8 37.4 44.8 51.8 58.1 63.5 68.3 72.1 75.9 79.5 83.1 86.6 89.5
16,105.94 13,762.11 11,681.66 9,868.70 8,360.57 7,061.88 5,949.12 5,014.63 4,235.91 3,608.59 3,088.81 2,685.56 2,306.09 1,947.74 1,608.28 1,285.82 1,016.34
18 19
0.884 0.909
92.0 94.0
794.00 614.41
20 21 22 23 24
0.934 0.957 0.974 0.984 0.996
96.1 97.9 99.2 100.0 100.9
439.70 283.04 169.65 103.87 25.81
olution.
The CRCM
solar radiation
scheme was also modi-
fied to allow the extractionof informationrequiredto calculatetwo important quantities,on-line, within the model. One quantity was the photosyntheticallyactive radiation flux necessary to evaluatebiogenicemissions,and the other wasinternal solarfluxesnecessary to evaluate the correctionfactors required to convert precalculatedclear-skyphotolysisrates to those occurring within cloudsusing the cloud information native to the model. These processesare describedin sections 2.2.5
and 2.3.3.
Parameterizationfor rain out/washouthasnot been included at this point. Many of the precursorsto Os formation are not affectedby this process.However,soluble moleculessuchas H202 and HNOa are depletedby precipitation and interfere with ozone formation by influencingOH-HO2 and NOx budgets,respectively,and a slight overestimationof O• concentrationfollowing precipitation can be expected. As most of the oxidant events occur during summer high-pressureevents, pre-
BOUCHET ET AL.: MODELING
cipitation should not be an important factor in the results. Nevertheless,the model does have a surrogate sensitivity to rain out events via the associated optically thick cloudy skies which can induce a reduction of the photochemical activity due to decreasesin the photolysis rates at the surface.
OZONE CLIMATOLOGY,
fusion coefficient
is used to simulate
their vertical
dif-
fusion, and when appropriate, the boundary conditions
at the surfaceare specifiedby an emissionflux and/or a dry depositionflux (see Table 1). As in the work by McFarlane et al. [1992],the planetaryboundary layer is consideredto be well-mixed during the daytime throughout its height, whoseextent is determinedfrom the calculated temperature profile. In this version of the CRCM, large-scaleconvection in the 'meteorologicalsectionof the model is simulated by a simpleconvectiveadjustment(CA) scheme.For certain domains and at the scale currently used, this coarse parameterization can lead to an overestimation of some convective events. In this version of the model
the chemical tracers have not been put through the CA scheme. However, chemical tracers should not be unduly affected by convectionfor summer conditions and so the effects of convection on the chemical tracers
were omitted becausethey should remain small for this
30,355
where Rst, Rmeso,Rdc, Rwc and Rgr are the stomatal, mesophyll, dry and wet cuticule, and ground resistances,respectively. The detailed Canadian Land-
Surface Scheme(CLASS), developedfor CGCM III [Verseghy et al., 1993],providesthe requiredvegetation parameters and surface roughness. The aerodynamic resistance
2.2.1. Vertical transport. Vertical fluxes of momentum, heat, and moisture due to turbulent diffusion are representedusing eddy diffusivity formulations in the free atmosphereand in terms of drag coefficients at the surface. For the chemical speciesthe heat dif-
1
is defined as the inverse of the bulk transfer
coefficient for heat Cs times the wind speed Vz at an altitude z correspondingto the height of the model level
the closestto the surface[Verseghyet al., 1993]. The different components of the surface resistance
(in equation(3)) are estimatedusingthe approachdescribedby Padro et al. [1991],with the exceptionof Rst. The stomatal resistanceof each depositedspecies is scaled on the water stomatal resistanceby the ratio
of the moleculardiffusivities(DH•.o/Di). The expression used for this latter
resistance
is similar
to the one
proposedby Jarvis[1976]and is detailedby Verseghy et al. [1993].It takesinto accountthe mostimportant environmental factors which may stressthe canopyand cause the stomata to close to prevent excessivetranspiration, namely, the incoming solar radiation, the air vapor pressuredeficit, and the canopytemperature. As the soil representationin the force-restoremethod only includesone soil layer, the dependenceof Rst upon the soil moisture suctionin the rooting zone had to be neglectedin this versionof the model.
2.2.4. Anthropogenic emissions. The anthropogenic emissionsdatabase used in these scenariosis derived from the 1985 National Acid Precipitation As-
sessment Program(NAPAP) EmissionInventory[Environmental ProtectionAgency(EPA), 1989]. Area emisa more complexschemewithin the next meteorological sions (mobile, nonmobile,and minorpoint sources)are versionof the CRCM.) Becauseof the lack of largeprojected onto the polar-stereographicgrid and downscale convectiona slight overestimationof the surface study. (The CA schemehasrecentlybeenreplacedwith
O3 concentrationduring convectiveevents may occur, sinceneglectingconvectiontriggersthe boundarylayer regime, generatinglarger diurnal variationsand an in-
creasedO3 daily maximum[Flatly andHov, 1995]. 2.2.2. Horizontal diffusion.
FollowingChanget
scaled to the 42.3 km resolution
ered run.
used for the consid-
CO emissions have been added to this inven-
tory. Owing to its long lifetime, CO is a good tracer of anthropogenicemissions. Emissionsare scaled on NO area emissionsand assumedto be 10 times greater in moleculesper squaremeter (or 9.3 times greaterin mass). This is within the rangeof what is assumedby
al. [1987],contributionsto the transportof chemical otherauthors[Changet al., 1987].Major point sources
tracersfrom horizontal diffusion,typically I to 2 orders of magnitudesmallerthan transport throughadvection, are neglected.A weak horizontaldiffusionof water va-
are addedat stackheightinto the corresponding vertical level as plume rise calculationsare not included at this point of development.All the emissionsvary according por is appliedin the CRCM [seeCaya and Laprise, to the time of the day and the day of the week. 1•]. There has been some discussionthat anthropogenic VOC and NOx emissionsmay have been underesti2.2.3. Dry deposition. Spatially and temporally matedin the 1985NAPAP inventory[EC, 1997].Howvarying depositionvelocitiesv•,i are estimated,in the ever, in this paper we havenot attempted to validatethe lowest model level, from an aerodynamicresistancera emissioninventory. Rather, as we have comparedour and a species-dependent surfaceresistance r s,i accord- modelagainstother modelswhichhaveinvestigatedthe same event, we have chosento use the same emissions. ing to: Validation of the emissioninventory would require more = + (2) measurementsthan presently available to us. 1 1 1 1 1 2.2.5. Biogenic emissions. The base run uses the N APAP precalculated biogenic emissionsfor the
l's,i= Rst _{_ Rmes ø-{-•dc-{-•wc-{-•-•gr, (3)
30,356
BOUCHET ET AL.: MODELING OZONE CLIMATOLOGY, 1
first weekof August 1988,whichwerebasedon the Bio- alkanes,2 alkenes,2 aromatics,2 aldehydes,1 ketone, genic EmissionInventory System(BEIS 1) algorithm and I aromatic alcohol. The list of the speciesis given
[Pierceet al., 1990]and land useinformationavailable in Table 1. The quantumyieldof O(•D) wasupdated accordingto the latest recommendations by DeMote et at that time. During the developmentof this model it was clear that further consistencycould be achievedby al. [1997]. taking into account the simulated meteorologyto esti2.3.2. Chemical solver. The change in concenmate the biogenicemissions.Thus section4.2 presents tration due to chemicalreaction is given by the contithe resultsof the August 1-6 simulationperformedwith nuity equation on-line biogenic emissionsbased on the BEIS 2 algo-
rithm [Geronet al., 1994]. This algorithmis alsoused for the longer runs. The on-line blogeniccalculations use a detailed land use, including the full 127 categories provided by the EPA for the Regional Oxidant Model (ROM), coveringmostof our domainup to 47øN [Hansenet al., 1992; Guentheret al., 1994],and a less detailed land use (only 21 differentvegetationtypes) for the remainingpart [Pierceet al., 1990]. Both components are projected from their original grid with a resolutionof 1/6 ø latitude by 1/4 ø longitudeonto the polar-stereographicgrid. Vegetationtypes with similar canopystructuresare lumped together into six canopy types for the organicspeciesand four categoriesfor NO. For these reduced number of categoriesa normalized emission rate is then calculated for each grid square and each canopy type as an area-weightedaverage of the original land use categoriesand is usedas a direct input to the model. At each time step the normalized rates of isopreneand monoterpenesare correctedto reflect the attenuation of photosynthetically active radiation (PAR) throughthe canopyas well as the variations of the air temperature over the courseof the day
[Guentheret al., 1993]:the PAR is estimatedusingthe transmission
of the solar flux calculated
from the mete-
orologicalpart of the code. At the presenttime, the dry depositionand biogenicemissioncalculationsare based on two different land uses. This inconsistencywill be addressed in future
simulations.
Oci'• - Pi- Lici, Ot ] chem
(4)
where Pi and Lici are the photochemical production and loss of the speciesi and ci is its number density. Because Pi and Li both depend on the concentration of other chemical specieswhoselifetimes span many or-
dersof magnitude,the systemformedby equation(4) is stiff, and its integration, doneat each grid point and eachlevel, can be time consuming.The solveradopted here classifiesthe speciesin different groupsdepending on their lifetime, a processsomewhat similar to that
usedby other groups[e.g., Changet al., 1987; Gong
and Cho, 1993](seeTable 1). O(•D), atomicoxygen, the phenoxyradical,and the two Criegeeradicals are assumedto be in a photochemicalsteady state. A fully implicit and mass conservingbackward Euler finite differenceschemeis usedto time stepequation(4) [cf. Gongand Cho, 1993; $andilandsand McConnell, 1997].A Newton'smethodsolveris usedto solvefor 16 species,while the remaining24 longer-livedspeciesare solvedusinga iterated semi-implicitmethod. Sinceall 47 speciesare includedin the iteration loop, the final
solution,whichis solvedto a relativeaccuracy of 10-3
conserves mass. This approach forsolving equation (4i
is similar to that used by $andilands and McConnell
[1997]and yieldsgoodaccuracy, exceptat sunriseand 2.3.
Photochemistry
A gas-phasemechanism,capable of simulating oxidant chemistry at a regional scale, has been included
sunset,for an integrationtime affordablefor a regional oxidantmodel. Performancecomparisons with the Gear solverare documented by Plummet[1999].
to reproduce the mechanisms of ozone formation and 2.3.3. P hotolysis rates. Following the convenaccumulation in the troposphere. At this point of de- tional approach[Changet al., 1987; Milllet and Brasvelopment, heterogeneousreactionsare not considered. seur, 1995],the 16 photolysis rate constantsJi are upAs mentioned before, the chemical module is run on- dated at each time step by interpolating in altitude and line inside the CRCM, with a constant time step of 15 solarzenith angle from a look-up table. The Ji are premin, and for the lowest 22 levels. calculated using the radiative transfer model of Hen-
2.3.1. Gas-phase mechanism. The gas-phase dersonet al. [1987],whichtakesinto accountRayleigh mechanismis derivedfrom the Acid Depositionand Oxscattering, absorption by O2 and 03, and reflection at idant Model (ADOM II) mechanism,which itself was the ground and includes34 spectral intervals between 287 and 420 nm with correction factors to take into acobtained by condensingthe explicit mechanismof Lurmann et al. [1986]. An updateto includenew results count longer wavelengthswhen necessary.Each Ji is in organic chemistry led to a mechanismwith 114 reac- precalculated for clear skies, 10 different altitudes up tionsand 47 species[Pudykiewicz et al., 1997],of which to 12 km, 10 solar zenith angles,and differentoverhead 25 are advected. Organic compoundsare lumped into column ozone amounts and surface albedo. In the sim17 stable speciesand 5 radical intermediates with the ulations presentedin this paper the chosentotal ozone following speciationof the genericemitted species:2 amount is 300 DU, and a fixed surfacealbedo of 0.2 is
BOUCHET ET AL.' MODELING used for the J value calculations.
In future
simulations
OZONE CLIMATOLOGY,
1
30,357
rest of the domain(freezone),the CRCM variablesare
the fixed albedo will be replaced by the albedo values not affectedby the reanalyses, i.e., neitherdata assimgiven by the land use. ilation nor nudgingis applied. Clouds, which are calculated by the meteorological Boundaryconditionsfor mostof the transportedchem.
model,affectthe Ji [e.g.,Changet al, 1987;Madronich, ical speciesare set to constant,low background values 1987;KaminskiandMcConnell,1991]andsothe chem- up to •6 km and to a minimum valueof 10-10 molecules ical activity. Thus clear-sky photolysisrates are cor-
cm-a above•6 km. Thechosen mixingratiosarede-
rected on-line to account for the cloud cover calculated
tailedin Table3 andarebasedonground-level measureby the model as follows. In the heating sectionof the mentsat nonurbansitesin North America. Boundary CRCM, solar radiation is divided into two wavelength and initial conditions for ozoneconsistof a background regions,UV-visibleand near-IR [Cayaet al., 1995].In value of 35 ppbv used at all levels and over the enthis sectionthe diffusionof solar radiation through the atmosphereusing the flux form of the two-stream 5Eddington approximation is calculated with and without clouds, from which it is possibleto retrieve the direct and diffuse fluxes at all levels.
The calculation
of
the Ji, however, requires the evaluation of radiances which can readily be obtained if it assumedthat the radiance is isotropic in both the upward and downward hemispheres.Thus, if •rF0 is the incident solar flux, •0 is the solar zenith angle, and r is the optical depth at
tire domainexceptfor the southwest and south(over landonly)boundaries wherethe climatological valueof 50 ppbv is adopted[Fiore et al., 1998]. The chosen boundary condition for ozone above 3 km is lower than commonlyobservedvalues,especiallyin the the northern part of the domain. Its effect on the simulated ozone concentrationsis investigated in section 4.1. The CH4 mixing ratio is held constant at 1.7 ppmv, and the wa-
ter vapor concentrationis one of the CRCM prognostic variables. The remaining chemicalspecies,mostly rad-
a certainheight,a correctionfactorC(z) for the short- icals, are set to zero. For justification of the chosenmixing ratios we note that from June to August, seasonalaveragemixing ratios rangingfrom 0.04 ppbv [Bakwinet al., 1994]to 1.30 ppbv [Parrish et al., 1993]for NOx (0200 LT meC(z) (v3c+ v3c)+ (0.5dian), from 2.0 ppbv [$hepsonet al., 1991]to 4.4 ppbv [Martin et al., 1991]for HCHO (0200 LT mean), and from 117 ppbv to 215 ppbv [Parrish et al., 1991]for whereF •,• represent the upwardanddownward fluxes,
wavelengthchannel can be expressedas
(vc* +vc*) +
(0.5 - ,0) , (5)
respectively,at the height z, and the subscriptsC and
NC refer to the cloudand noncloud(clear-sky)cases,
CO have been reported in the literature. Ozonesonde
data for northernmidlatitudes[Tarasicket al., 1995]
show averagevaluesof 35 ppbv from the surfaceup to respectively. Becausecloud optical properties are rel700 mbar (•-3 km) but higher mixing ratios between atively insensitiveto near-UV and visible wavelengths
[Peterset al., 1995],a singlecorrection factorshouldbe reasonablefor all visiblewavelengths.At the UV end of the troposphericspectrum,,•300 nm, the singlescattering albedo within the atmosphereincreasesdue to 03
700 and 100 mbar (50-70 ppbv). The annual average
ozone mixing ratios at Wallops Island, Virginia, show the same vertical behavior with ,.•55 ppbv between850
absorption, and the correction factor is modified some-
what [cf. Kaminskiand McConnell,1991]. However, Table 3. Mixing Ratios Used as Boundary Conditions the wavelength resolution within the CRCM does not permit such a detailed correction at present. This de-
pendence of the correction factorsonwavelength [Chang et al., 1987]wasneglected.Typicalclear-skycorrection factorsfor COS--I•0= 23.7ø andrc = 4.2 are0.86,0.90, 1.35, and 1.28 at 0.24, 1.24, 1.50, and 5.20 km.
2.4. Meteorological and Chemical Initial and Boundary Conditions Boundary conditionsfor the meteorologicalparameters are taken
from the National
Centre
for Environ-
mental Prediction (NCEP) reanalysesfor the correspondingday. The objectivereanalyses(OA), available every 12 hours, are interpolated to provide boundary conditionsat every model time step. A transition zone of ten grid points is applied on the boundariesof the domain. Over this zone, the CRCM meteorologicalvari-
ables are blended with the OA, while throughout the
Between
Species NO NO2 CO HCHO ISOP SO2
the Surface and -•6 km
Concentration,ppbv 0.12 0.12 150 1.0 0.001 2.0
Calls
1.0
ALKA ETHE ALKE TOLU AROM
2.5 O.3 O.5 0.3 O.5
The boundary condition for Os is detailed in the text. Boundary conditionsfor PAN, HNOa, HONO, H202, ROOH, SO4, ALD2, MEK, MGLY, DIAL, RNOa and CRES are set to 10-xø molecules cm -•.
30,358
BOUCHET ET AL.: MODELING OZONE CLIMATOLOGY,
and 700 mbar and 65 ppbv between 500 and 300 mbar
(,,6-9 km) [Oltmanset al., 1998].
1
persistent upper ridge. During the first week of August the high-pressuresystemis located on the eastern
For initialization, the CRCM, with the chemistry module turned off, usesOA as initial conditionsfor the meteorologywith chemical fields identical to the ones describedfor the boundary conditionsfor the chemical tracers. The model is run for i month prior to the period of interest to allow the soil-atmospheresystem to equilibrate. In the last 6 days the chemistry module is
U.S.
seaboard
and extends
to the south of the Great
stationsscatteredover the domain (Figure 1). A detailed descriptionof the synopticconditionsfor the period of studyis givenby EC [1997]and only the main
but in the transition
features
data assimilation,nudging,or frequent reinitialization with the objective analyses fields. In our case the
Lakes. A frontal zone generallylies betweenthe west-
ern Great Lakes to central Quebec with occasionalintrusionsinto the WQC and the Marltimes. Light southwesterly winds, clear skies,and surfacetemperature in the mid-20s to low 30s persisted over most of the domain thorough the period. Only isolatedshowerswere activatedand "clean"anthropogenic emissions(1/10 of reported. On August 5, a low starts to developat the the NAPAP emissions) are turnedon for the first 4 days surfaceover Lake Superior and movesacrossthe Great followedby another 2 days with normal anthropogenic Lakesthe .followingday as the upper ridge finally weakemissions. The last output provides realistic meteoro- ens, bringing drier and cooler air from the northwest. logicaland chemicalinitial conditionsfor the simulation The wind and temperature fields as calculatedby the starting on August 1, 1988. model at the lowestmodel level and for August 2 and 6 are given by Figures 2a and 2b. The model reproduces relatively well the meteorologicalconditionsfor both 3. Model Evaluation days, although the near-surfacetemperatures,while in An evaluation of the model was performed for an in- general agreementwith the observations,seemslightly tense ozone episodewhich occurredbetween August 1 overestimated. As the model is forced at its boundaries and 6, of 1988. This event coincidedwith one of the with objective reanalyses,the major synoptic features Eulerian Model EvaluationField Study (EMEFS) cam- are expected to be present. Their specific locations, paigns[Hansenet al., 1990]and hasprovidednumerous however,as well as fields influencedby the smaller-scale modelswith a uniquedata set for testing [EC, 1997; surfaceprocesses,suchas air temperature or wind speed Pudykiewiczet al., 1997;Plummet, 1999]. For the se- closeto the surface, are completely determined by the lected week, hourly ozone data are available from •70 model in the free part of the domain, i.e., everywhere
will be summarized
here. The summer
of 1988
was characterized by hot, humid, and stagnant conditions due to a semipermanenthigh-pressurearea in the southern part of our domain associatedwith a very
zone.
Some models are constrainedto keep them as closeas possibleto the objective analysesby four-dimensional
CRCM is run for 5 weeks(4 weeksof warm-up and i week of simulation) without any other forcing than the boundary conditions,in a setup similar to the one usedfor the climatologicalruns, and is not reinitialized at the begining of the 6-day simulation, based on evi-
denceof Antheset al. [1989]that objectivemeasures of error showlittle growth beyond36 hours of simulation. Consideringour meteorologicalforcings,the CRCM reproducescorrectly the high- and low-pressuresystems at the surface,especiallythe high-pressuresystemsouth to southeastof the Great Lakes, which persiststhrough the entire episode. The sea level pressure1020 isobar seems,however, to penetrate too far in land, generating surfacepressuregradientsslightlydifferentthan observed. As a result, the wind circulation at the surface
* , ,.:.i•øn Yøntmø& .
differs at time from observations.
Figure 3 gives an example of typical midafternoon 03 dry depositionvelocitiesas calculatedby the model
duringthisepisode.Valuesof Vdof 0.4 cms-x overthe midwest,0.65 cm s-1 overforestedareas(with a maximumof 0.85 cm s-x), and 0.5 cm s-1 overnorthern forests are within the range of the observedreported
values[Ritter et al., 1994;Padro, 1996]. At the consideredscale(42.3 km), eachgrid cell is composedof Figure 1. Location of the measurementstationson the model's
domain.
at least two vegetationtypes. The correspondingdry depositionvelocity representsan averagevelocity and should be expected to differ from the values measured
BOUCHET ET AL.: MODELING OZONE CLIMATOLOGY, 1
30,359
(b)
Figure 2. Near-surface windspeed(m/s),winddirection andtemperature (øC)ascalculated by the modelat 2000UT for (a) August2 and(b) August6. at a specificlocation. Modeled dry depositionveloc- lowing, near-surfacemixing ratios, i.e., calculated at ities for peroxyacetylnitrate (PAN) rangefrom 0.015 the lowestmodellevel (,•26 m abovethe surface),are to 2.5 cm s-1 at night (average0.04 cm s-1), which usedas a surrogatefor ground-levelmixing ratios. The agreeswell with measurements reportedby Schrimpfet model correctlycapturesthe developmentof the episode al. [1996]and $hepsonet al. [1992].HNO3 dry depo- with the highestozonemixing ratios simulatedon Ausition velocity, however,is strongly underestimated,as gust 2 and 3 as generallyobserved.Late on August 3, the maximum value never exceeds0.5 cm s-1. Values
southwesterly windsof increased strengthbl0wdirectly
reportedin the literaturerangefrom2.5 to 3.2 cms-1 duringmidday[Meyerset al., 1998].
into the WQC from American border states,resultingin decliningbut still significantozonelevelsreachingmost
3.1.
of QuebecbetweenAugust4 and 6 (not shown),,•1000 km away from the closestAmerican precursorsources.
Spatial Patterns
Plate 1 presents the simulated near-surfaceozone For the entire episode, ozone mixing ratios exceed 60 mixing ratio at 2000 UT for August 1-4. In the fol- ppbv over a large part of the domain, which reflects the regionalextent of the event,with highervaluessimulated in distinctive plumes originating from the major sourceareas. The model presentsfeaturesand concentrations similar to the ones simulated by peer mod80 els (ADOM, ROM, and the ChemicalTransportModel
(CTM) described by Pudykiewicz et al. [1997])for this episode[EC, 1997],althoughit tendsto movethe plume from the eastern U.S. seaboard to more over water than 56
its CTM equivalent, inducing more transport of ozone toward the Canadian maritime provinces.If the CRCM capturesthe spatial pattern reasonablywell, peak valuesare generallyunderestimated.Althoughthis underestimation may be related to the horizontal resolution, a significantimprovementis not expectedto be reflected in the ozone field unless the resolution is increased to ,•5
ß. 0
km. Major changesare usually associatedwith a better representationof the meteorologicalforcings;at 42.3 km, the synopticscaleand someof the mesoscaleforc-
ingsare adequately represented, whilesmall-scale features, suchas thermal circulation,wouldrequirea draFigure 3. Calculatedozonedry depositionvelocity maticincreaseof the resolution[EC, 1997;Pudykiewicz et al., 1997]. (10-4 m s-•) for July31, 1988,at 1600UT.
30,360
BOUCHET ET AL.: MODELING OZONE CLIMATOLOGY, 1
95 90
I
85
t
t
t
80
t
75
t
,•. ,7-
70 65 60
55 5O
45 40
•%•
•, , , ,
35 30 25
o•
•1
20
•, ,
t
....
lo
'
(b)
(a) i
:8,
95 90
85
:3
8O 75 70
65
-' '
-'' ' '
' :
'
.//.
-
60
55 5O
45 40
35 ;
r,
..... '
'
30
25 20 15 lo
(d)
(c) Plate 1. Near-surfaceozonemixingratio (ppbv) and wind field as calculatedby the modelat 2000UT on (a) August1, (b) August2, (c) August3, and (d) August4.
movesthrough Dorset overnight. The increaseis temperedby dry depositionin the surfacelayer. By 0900 Because most of the available ozone data are surface UT, mixingratiosare backto their earlymorninglevel data, it is difficult to assessthe accuracyof the mod(Figure4a) as cleanerair has beenadvectedin. The eled vertical distribution of ozone. However, a comparCRCM capturesthe measuredincreaseat 0100UT but isonwith someEMEFS aircraft measurements [Macit disappearsby 0900 UT, whereasthe measurements donaldet aL, 1993]doespermitsomeverificationof the suggest that morepollutedair is still beingtransported model's behavior. The evolution of the vertical profiles to Dorset. Above I km, in the free troposphere,the at Dorset betweenAugust 4 and 5 are presentedin Figsimulated ozone mixing ratios are almost constant at ure 4. In the early morningon August4 (1300 UT), a sharpgradient in the first 100 m due to overnightdry 35 ppbv, reflectingthe initial conditions.However,the lowest values encountered in the measurements are in depositionin the surfacelayer is visible in both the airthat the craft and the simulated profiles as the PBL is starting the 50-60 ppbv range,whichstronglysuggests to develop. The simulated height of the P BL at 1300 initial conditionscould be improvedat theselevels. InUT coincidesquite well with the measurements.Later terestingly,ozonelevelsin the free troposphereare not Between1300 and 1700UT, there is an in the day, a relatively homogeneous PBL extendsfrom homogeneous. the surfaceup to 1000 m in the model, while the actual increaseof 20 ppbv, indicatingthat polluted air is transtop of the P BL is not very pronouncedin the observa- ported in. By 0100 UT, ozonemixing ratios are back to tions. Ozone mixing ratios in the first 1000 m increase •055 ppbv. Three hours later, there is another increase between 2100 and 0100 UT as a more polluted air mass up to 80 ppbv at 3 km followedby a generaldecrease 3.2.
Vertical
Distribution
BOUCHET ET AL.' MODELING
.(•.),A.u9.us.t ,4,.1.9.88,, .13.00 ,U.T ..
5000
OZONE CLIMATOLOGY,
30,361
ß .(b.),A.ucj.us.t ,4,.1.988 ,, .17.0.0 ,U.T . .
5OOO
4000
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,
,
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.
,
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,
,
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80
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, . .(c.),A.ug.us.t ,4,.1.988 ,, .2!0.0 ,U.T ..
5000
,
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o
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.,
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., ,
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i
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Ozonemixingratio (ppbv)
,
.
i
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.
.
,
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.
,
,
i
,
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Ozonemixingratio (ppbv)
ß .(e.),A.ucj.us.t ,5,.1.988 ,, .05.00 ,U.T..
5OOO
,
. .(f.),Au.g.us.t ,5,.1.988 / .090.0 ,UT. '
5ooo
,.
,.
4OOO
4oo0
3000
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2000
2000
lOOO
lOOO
o
i
o
i
,
i
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•
i
40
,
i
i
i
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i
,
,
i
80
i
,
o
,
lOO
Ozone mixing ratio (ppbv)
o
20
40
60
80
O0
Ozonemixingratio (ppbv)
Figure 4. Ozone vertical profilesat Dorset, Ontario (45.22øN-78.93øE),during the night of August 4. The simulatedprofilesare givenby the dotted line. above 2 km. Finally, by 0900 UT, a plume with a peak mixing ratio of 95 ppbv is being advectedin. The observedprofilesreflect the heterogeneitywithin the free troposphere, perhaps related to effects of convection, noneof which appearsto be capturedby the CRCM on
balanced, with numerousmonitors located in urban and suburban areas for public protection. Another important sourceof error in regionalmodelscomesfrom inaccuraciesin the transport of pollutants by advectionand turbulence, and large apparent errors in the ozonefield this timescale. can result from small displacementsof ozone plumes. Numerous uncertainties are carried forward when pro3.3. Daily Ozone Maximum and Minimum ceedingto such an evaluation and must be taken into The evaluation of regional models using point ob- considerationwhen drawing conclusionson the model servations is limited by several problems inherent to performance. the nature of the measurements as well as models deThe mixing ratio is a function of spacein the x, y, and sign. A model producesvolume-averaged concentra- z directionsas well as time. Thus no singlemeasureof tions for a grid box, and the information content is fur- accuracywill completely characterizethe model perforther constrainedby the chosenspatial and vertical reso- mance, and various statistics must be considered. Here, lutions. Most observations,on the contrary,are realized two of the standard parameters, the ozone daily maxat ground level and are influencedby local emissions imum and minimum, are compared with observations. and local meteorologyoccurringat a muchsmallerscale By only consideringextrema, errors on the simulated than the one typically resolved by three-dimensional time at which they occur are minimized. Scatter plots models. Furthermore,the spatial coverageof data is un- of simulated versusobserveddaily ozone maximum for
30,362
BOUCHET ET AL.' MODELING OZONE CLIMATOLOGY, 1
eachday of the event are presentedin Figure 5. The CRCM performancevariesover the episode:there is little correlationat the beginningand at the end of the simulation,while the agreement,reflectedby the slope of the regression line, is satisfactory on August3, 4, and 5. It appears,however,that valuesare systematically underestimatedat levelsabove60 ppbv. A comparison
perform significantlyworsefor the minima than for the maxima. Although nighttime chemistryis still crudely representeddue to numerousunknowns,nighttimeconcentrationsare more subject to subgridvariability than during the day when mixing is strong over the entire grid square. Such processesas drainageflow or nighttime jet can becomeimportant and influencedeposition with the other models cited in Table 4 shows that this and mixing of local emissionsin the nocturnal boundunderestimation is commonto all models,althoughit ary layer (NBL), makingspatialand verticalresolutions is the leastpronounced with ROM. The regression lines bigger issuesat night. for the ROM simulationexceed0.55 everyday except The CRCM correlation coefficients,for both daily the last one[EC, 1997]. maximum and minimum, are comparable to those of The correlationcoefficients for daily ozonemaximum other models. This measure might, however,be misand minimumobtainedby differentmodelsfor this par- leading as the correlation coefficientsfor ADOM are ticular case are summarized in Table 4. ADOM was run most satisfactorywhile the slopeof the regressionlines in its originalconfigurationat 127 km resolution,ROM never exceed 0.33. As observed with other models, wasrun at 18.5 km resolution,and the CTM wasrun at the variance of the simulated data is much lower than
40 km resolution[EC, 1997].It is clearthat all models for the observeddata with an averageof 218 ppb•'
200
200
O,(colc)= 32.43 + 0 30 O,(obs) ." ß
O,(celc)= 59.12 + 0.22 O,(obs).."
,.
.,
ß ß
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o. 150
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.... ..
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,
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Figure 5. Simulatedversusobserveddaily ozonemaximum(ppbv) for August1 to 6. regressionline equation is also shown.
The
BOUCHET
ET AL.: MODELING
OZONE CLIMATOLOGY,
1
30,363
Table 4. Correlation Coefficientsfor Maximum and Minimum Daily Os Values Daily Oa Minimum
Daily Os Maximum
Day August1 August2 August3 August4 August5 August6
ADOM
ROM
0.68 0.76 0.64 0.43 0.62 0.38
0.70 0.64 0.59 0.60 0.56 0.15
CTM a
CRCM
ADOM
ROM
CTM •
CRCM
0.55 0.52 0.64 0.67 0.76 0.33
0.36 0.22 0.26 0.46 0.51 0.50
0.15 0.20 -0.06 0.34 0.38 0.40
0.00 0.13 0.15 0.40 0.41 0.36
0.34 0.21 0.36 0.32 0.21 -0.03
0.50 0.69 0.63 0.58 0.58 0.44
ADOM, ROM, and CTM wererun for the sameOs episodeaspart of EC [1997]. aCTM refersto the modeldescribed by Pudykiewicz et al. [1997]for the EC [1997]simulations.
versus539 ppb2 for the daily ozonemaximum,which variation being strongly underestimated for the first 3 can be attributed in part to the fact that models produced smootherspatially averagedconcentrations.On the basis of the above statistics, it appears that the CRCM ability to simulate this episode is similar to the ability of the other models. Over the 6-day simulation, the CRCM resultsalso comparefavorably for severalstatistical performancemeasuresusedby other authors: the determinationcoefficient(squareof the
days. The correlation coefficientin this casemeasures the model'sability to simulatethe changesin mixing ratio, which means that the ozonediurnal cycle accounts for a significantfraction of its value. For a better overviewof the accuracyof the data set, the mean value, standard deviation, root-mean-square error, mean error, and bias scoreare reported in Table 5. As expectedfrom the comparisonof the daily extrema,
correlationcoefficient)for the periodis 0.33, and r 2
the calculated
mean
value
and standard
deviation
of
exceeding0.30 are consideredas indicatorsof a reason- hourly data are generallysmallerthan the observedones able correlation between simulated and observed values with discrepencies (in absolutevalues)rangingfrom 1.6 by Roselieand $chere[1995];the averagenormalized to 33% (0.7 to 14 ppbv) and from 9 to 56% (1.1 to 16 bias[Ccalc - Cobs]/Cobs andtheaverage normalized ab- ppbv), respectively.On a differentset of stationsbut solutebias ICcalc- Cobs I/Cobsof the daily ozonemax- for the sameepisodePudykiewiczet al., [1997]report imum, paired in space and time, are 9% and 22.5%, differences (absolutevaluesas well) rangingfrom 1.3 to respectively,i.e., lower than their respectivethresholds 43% (0.6 to 17 ppbv) for the meanvalueand from 0.2 of 10-15% and 30-35% as recommendedby the EPA to 29% (0.05 to 6.7 ppbv) for the standarddeviation. The rms error looks at the data set from a different an[1991]. gle with a few large errors weighted more than many 3.4. Hourly Ozone small ones. Although low rms errors often correspond The results of a statistical analysisperformed on all to rather good correlationcoefficients,there is no direct hourly data are presentedin this section. The sites il- correlation between the two measures,rather it outlines lustrated here were chosento covera large part of the some discrepenciesthat the correlation coefficientdoes modelingdomain(seeFigure1) aswell as a widerange not capture(seeWest Point or Argonne,for example). of correlation coefficients. Plots of ozone data series The mean error reflectsthe systematiclow biasthat has for a subsetof these stationsare depictedin Figure 6. been mentioned through all this analysisand appears The diurnal cycle is always adequatelyreproduced. Its to be quite variable between stations. The bias score amplitude, however, is generally too small, which cor- is definedas B sc = F/R, where F is the numberof roborates previous conclusionson daily extrema. The simulatedvalueshigher than or equalto a set threshold different urban, rural, or background regimes at the (60 ppbv) and R is the numberfor the measurements shownlocationsare correctly captured except at West higher than or equal to the threshold[Antheset al., Point, New York. The overall CRCM performance is 1989]. With the exceptionof Mendauminand West quite variable between the 72 monitoring sites, as illus- Point, the low bias scoresillustrate the CRCM problem trated by the distribution of the correlationcoefficients of reproducinghigh mixing ratios at the station locafor each station in Figure 7. tions and/or for an adequateperiodof time. The bias The correlation coefficientis commonlyused as an scoreat West Point rapidly decreaseswith an increasing indicator of model performance.More than 60% of the threshold as well. sites have a correlation coefficientabove 0.60, which is As mentioned at the beginning of this section, the quite satisfactory. However, as noted earlier, this mea- model evaluationcan only be performedthrough pointsureneedsto be usedwith caution when appliedto time to-point comparisonswhich artificially increasesthe imseries. West Point, for example, exhibits a correlation portance of spatial errors. Although the aboveanalysis coefficientof 0.66 inspite of the amplitude of the diurnal showsthat the model tends to underestimatehigh mix-
30,364
BOUCHET ET AL.' MODELING OZONE CLIMATOLOGY,
150
._
o
Mendoumin
! 45.0- 82.2)
100
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Alliston
1
( 44.2- 79.8)
.... Oo'c 1
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August 1988
150
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4
5
6
August 1988
( 44.4- 65.2) .
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01
6
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August 1988
Figure 6. Simulatedand observedhourlyozonedata series(ppbv) for selectedstations. ing ratios, the near-surfaceozonefield exhibhitsmixing parameterizationssuchas surfaceprocessparameteriza-
ratios as high as 150 ppbv (seePlate lc). The dis- tions. The spatial resolutioncan introduceerrorswhich crepanciescould be explained by inaccuraciesin the may introduce inaccuraciesinto the transported field meteorologicalfields generatedby the physicalsubgrid but more importantly limits the physical phenomena that can be resolvedby the model. For example, West Point measurementstation is located in a valley north Correlotion coefficients distribution of New York city. Although the valley is apparent in the model topography,the larger-scalecirculationdominates in the CRCM, whereas the valley is most likely influencedby the local wind circulation in this corridor. Finally, errors in the emissionestimates can propagate in the generationof ozoneprecursorsand can be a large 2O
sourceof error, as illustrated in section 4.2.
4. Model Sensitivity The CRCM sensitivityto changesof someinput parametershas been investigatedin order to estimatethe range of uncertainty in simulated ozonemixing ratios 0.0 0.2 0.4 0.6 0.8 1.0 due to these input uncertainties. This analysisfocuses Figure I. Distribution of the correlation coefficients on changesto the chemicalspeciesboundary conditions on hourly data. and biogenicemissions.
I
BOUCHET ET AL.' MODELING
OZONE CLIMATOLOGY,
1
30,365
Table 5. Statisticson Hourly Time Seriesfor SelectedStationsfor August 1-6, 1988 Station
Mendaumin Merlin Alliston
r
•obs, ppbv
•calc, ppbv
•obs, ppbv
•calc, ppbv
rms error, ppbv
mean error, ppbv
Bsc
0.82 0.48 0.55
52.75 58.49 48.69
49.47 50.95 46.21
28.39 23.84 28.37
21.84 13.42 12.44
16.67 22.31 24.05
- 3.28 - 7.54 - 2.48
0.87 0.54 0.39
Montmorency
0.65
25.41
33.79
11.43
10.33
12.40
8.37
N/A
Kejimkujik Emporium
0.51 0.66
42.99 43.85
39.02 37.78
17.85 20.49
8.11 13.18
15.55 16.50
- 3.97 - 6.07
0.05 0.27
Argonne NL
0.79
53.91
39.96
20.64
15.48
18.92
-13.95
0.31
West Point
0.66
41.82
41.15
44.41
21.94
34.14
- 0.66
Ann Arbor Arendtsville
0.64 0.42
45.23 54.18
42.80 41.60
15.55 30.93
11.81 16.46
12.27 30.90
- 2.42 -12.58
0.88 0.18 0.21
Ft. Wayne Big Moose
0.78 0.77
46.30 47.51
43.97 43.66
24.64 17.19
14.79 12.57
16.20 11.67
- 2.33 - 3.85
0.46 0.44
r, the correlation coefficient;•, the mean value; a, the standard deviation; rms error, the root-mean-square
error;meanerror=•-](Xobs-Xcalc)/number of observations; andBsc,the biasscoreasdefined in thetext. profilesare in much better agreementwith the aircraft As noted in section 2.4, ozone initial and bound- observationsabove 3 km, and there is also a slight increasein mixing ratios below I km. However, as only ary conditionsin the upper levels (above 3 km) are boundary conditionswere modified, pocketsof air with lower than indicated by ozonesondedata. A simulation ozone mixing ratios of 35 ppbv have been trapped lofor the first week of August with boundary conditions above 3 km increasedto 60 ppbv was run to evaluate cally in places where little mixing has occurredin the free troposphere,and this is reflectedin the vertical proits effect on ozonemixing ratios. Figures8 and 9 illusfiles by the area of lower mixing ratios at the top of the trate the changesobservedin ozonevertical profilesand P BL between 1.5 and 2 km. near-surfaceconcentrations,respectively. The vertical As depictedby Figure 9, although differencesup to 7 ppbv are observedat ground level, they are limited to regionswith strong vertical mixing and downdrafts .(a),August 4, 1988, 1300 UT 5OOO as behind the cold front in the northern part of the 4000 domain. In this example, areas sensitiveto the modifi4.1.
Boundary
E '•
3ooo
•
2000
._
Conditions
1 ooo o o
20
40
60
80
lOO
Ozone mixing rotio (ppbv)
.(b) August5, 1988, 0100 UT ,
5000
.
4000 '•
3000
•
2000
._
lOOO o o
2O
4O
6O
8O
O0
Ozone mixing rotio (ppbv)
Figure 8. Verticalprofilesobtainedfor (a) August4 at 1300UT and (b) August5 at 0100UT with a modified boundaryconditionfor ozonein the upper levels(see text for details). The solidline indicatesthe observed Figure 9. Differences(ppbv) betweennear-surface profile, the dashedline indicatesthe profile simulated ozone mixing ratios at 2000 UT on August 4 for a with the old boundary conditions,and the dotted line changein ozoneupperlevelsboundaryconditions.(See indicatesthe new profile. text for details.)
30,366
BOUCHET ET AL.: MODELING OZONE CLIMATOLOGY,
cation alsocorrespondto rural locationswith little photochemicalactivity. Initial and boundary conditionsfor ozone in the upper levels will need to be corrected in future simulations and will be particularly important when effectsof large-scaleconvectionon chemicaltracers are introduced.
1
tion basedon the BiogenicEmissionInventorySystem version2.0 (BEIS2) [Geronet al., 1994]hasbeenimplemented in the CRCM. Revised emissionfluxes for NO,
isoprene,and monoterpenes and a light and temperature dependencyfor the organicsconstitutethe major improvementsof the BEIS2 parameterization.
Results for an increase from 50 to 70 ppbv in the ozoneboundary conditionsfor levelsbelow 2 km in the southwestcorner of the domain are illustrated in Figure 10. For the first week of August, effectsare mostly
Plate 2 showsthe ratio of the new isopreneemissions fluxes to the NAPAP ones at 1600 UT on August 2.
limited
largerat midday.Someof the major modifications are
to the locations close to the modified boundaries
The new isoprenefluxesare 2 to 100 times larger,with the majority of the pointsshowingfluxes5 to 30 times
and do not spread to any great extent to the rest of the domain. Although the impact of uncertaintyin the southwestarea is expected to vary with meteorology, this test suggeststhat the domain of simulationis large enoughto include most of the major emissionssources
located in Canada, in the part that is coveredby the BEIS2 land use. It is suspectedthat the CRCM surfacetemperaturesare largerthan the onesassumedby the NAPAP inventory,which may enhancethe differencesdue to the temperature dependenceof isoprene
which influence ozone formation
emissions.
in eastern North Amer-
ica and to limit the effectsof uncertain boundary conditions.
Finally, N Ox boundary conditionswere varied within the range of observedvalues and increasedto I ppbv from 0.24 ppbv. In the center of the domain, where emissionsof anthropogenicNO• are strong,changesin ozone mixing ratios at ground level do not exceed3 ppbv, which confirmsthe previousremark regardingthe grid size. Major impacts are limited to the rural areas
The new NO emissions fluxes are on aver-
age3 ordersof magnitudelargerthanthe NAPAP 1985 ones.Although,locally,NO soilfluxescan be 2 orders of magnitudesmallerthan NO anthropogenicfluxesat midday, they are comparablewhen averagedover the domain.
The August 1-6, 1988, simulation was redonewith the new biogenicemissions.The new ozonefields are presented in Plates 3a and 3b, and the new statistics in Tables 6 and 7. This CRCM simulation yields mixclose to the boundaries. ing ratios that are much higher than previously,showing an episodemore intense and less localizedto the 4.2. Biogenic Emissions major emissionsplumes. However,this is not reflected Over the last few years, much researchhas been de- in the new daily Os maximum and minimum correvoted to producingbetter estimatesof biogenicemis- lation coefficients, which are similar to the previous sionswhich may constitutea significantfraction of the ones. On the other hand, the slopesof the regression sourceof VOCs in rural and urbanareas[Chameideset lines have improved considerablydue to a much betal., 1988]. As noted in section2.2.5, a parameteriza- ter agreementfor most mixing ratios, as illustrated by Figure 11. On the percentile plots, daily ozonemaxima are ranked into groupsof equal number, and the mean value of each group is plotted against the correspondingobservedmeanvalue,minimizingthe effectsof temporaland spatialpairing. For the basecase(Figure
11a), mostpercentiles are underestimated by 20%,and this percentageworsensfor the highestpercentiles.The lower percentiles,on the other hand, are overestimated by approximatelythe same amount. With on-line biogenic emissions(Figure 11b) the range of mixing ratios calculatedby the model are now comparableto the observedone, with mixing ratios above 150 ppbv still slightly underestimated. The comparisonof the two percentileplots suggests that uncertaintiesin the emissionsinventory can contribute in an important manner to the general underestimationwhich appearsin the base run.
Although the rangeof valuessimulatedby the model is in better agreementwith the observedrange, statistics of hourly time seriesdo not showthe samelevel of improvement. The rms errors are slightly higher than Figure 10. Differences(ppbv) betweennear-surface ozone mixing ratios at 2000 UT on August 4 for a in the base case, while the mean errors and the bias
The uncerchangein ozonesouthwestboundaryconditions.(See score now reflect a small overestimation. tainty associatedwith biogenic emissionestimates as text for details.)
BOUCHETET AL.' MODELINGOZONECLIMATOLOGY,1
30,367
1183 5O0 100 90
70
L
60 5O 40
20 15 10
5 2
0
Plate 2. Ratioof newto oldisoprene emission fluxes at 1600UT onAugust2.
95 9O 85 8O
75 70
/;5
"•'
k
(;5
60 55
45
55 5O
1•
45
4O
4O
35
25
20
2O
15
10
15
k,
10
lo
(a)
(b)
Plate 3. Near-surface ozonemixingratio(ppbv)at 1600UT for (a) August2 and(b) August3
for the simulationwith on-linebiogenicemissions.
30,368
BOUCHET ET AL.' MODELING OZONE CLIMATOLOGY, 1
Table 6. Correlation Coefficients, Slope, and Intercept of the RegressionLine for Maximum and Minimum Daily O3 Values for the Simulation With On-Line BiogenicEmissions
A first evaluation of the CRCM was performed for the August 1-6, 1988, ozoneepisode,which constitutes a benchmarkfor the testing of oxidant modelsin the Canadian community. This event, which affectedmost of easternNorth America for 6 consecutivedays,is rear(max) r(min) Intercept Slope sonably well reproducedby the CRCM. A sequenceof spatial plots of surfaceozone mixing ratios illustrates August I 0.52 0.24 37.46 0.43 the realistic responseof the CRCM to the changein August 2 0.52 0.25 46.88 0.33 August 3 0.64 0.41 24.52 0.64 meteorologicalconditionsand showssome evidenceof August 4 0.62 0.43 25.50 0.67 long-rangetransport occurringin the WQC duringthis August 5 0.76 0.37 13.57 0.87 period. August 6 0.26 0.00 43.42 0.40 Although point-to-point comparisonsof daily ozone maximum and hourly time series were less favorable, showinga large scatter in the data, they were comparagivenby BEIS2 variesgreatlywith compound,loca- ble to thoseobtained by peer modelson the sameozone tion, and season. A minimum of 50% for summer iso- episode.Amongthe simplemeasuresof accuracywhich preneemissions hasbeensuggested (A. B. Guentheret were used in this analysis,it was noted that correlation al., Natural emissions of non-methane organicvolatil coefficientsoften give an incompleteidea of the data set compounds, carbonmonoxide, and oxidesof nitrogen accuracy. The root-mean-squareerror, the mean error, fromNorth America,submittedto Atmospheric Envi- and the slopeof the bestfit regressionline betweensimulated and observeddaily ozone maximum were found ronment,1998). to provide useful additional information. The CRCM performanceis considerablyimproved 5. Summary and Conclusions when the new biogenicemissionparameterizationis im-
The originalversionof the CRCM wasdeveloped in orderto performlongsimulations suitablefor developing climate statisticsof meteorological variables.How-
200
ever, it has become clear that it could be used to de-
velopclimatologies for chemicalspeciessuchas ozone. To do this, the ADOM gas-phasechemicalmechanism anddry depositionandemission parameterizations were imbededinto the CanadianRegionalClimateModel, taking advantageof its existingsemi-Langragian and
Q. 150
>, 100
..'
..o
ß
._
..''
semi-implicit advectionschemeand physicalsubgrid-
d
scaleparameterizations.Currently,the modelis run with a constant15-mintime stepon an 80 x 80 points grid,at 42.3km, andprovides meteorological andchem-
..,'•00 O0
50 ß
0
0
50
ical fields on the 25 levels within 1600 min of CPU for
1O0
150
20O
Ohs. 0_,daily max. (ppbv)
8 daysof simulationon a Origin 200 workstation. 2OO
Table 7. The rms Error, Mean Error and BiasScorefor
HourlyTime SeriesObtainedWith On-LineBiogenic
Emissions.
Station Mendaumin Merlin Alliston
Montmorency
•
rms Error,
Mean Error,
ppb
ppb
Bsc .•>,100
22.61 23.82 24.79
14.01 6.53 9.30
1.50 1.31 1.26
16.91
12.55
N/A
4.10 2.49 3.74
150
Kejimkujik Emporium Argonne NL
16.72 16.29 15.96
0.95 1.15 0.95
West Point
34.93
11.01
1.12
Ann Arbor Arendtsville Ft. Wayne Big Moose
16.13 28.47 17.17 14.15
8.65 -2.67 9.09 5.61
1.86 0.87 1.22 2.11
_• 50 0
, 0
,
ß ,
, 50
,
,
•
i 1 O0
i
,
, 150
200
Ohs. 0_,daily max. (ppbv)
(b)
Figure 11. Percentileplotsof daily O3 maximumcomparing simulatedpercentliesto observedpercentilesfor
the entireepisode for (a) thebasesimulation and(b) the simulationwith on-line biogenicemissions.The solid line representsa perfectcorrespondence, whilethe dotted lines mark the +20% lines.
BOUCHET
ET AL.: MODELING
plemented, although the CRCM slightly overestimates ground-levelozone mixing ratios. It is thus very sensitive to uncertainties
in emission inventories.
Further
tests needto be performedto assessits sensitivityto anthropogenicemissionsas emissionsfrom motor vehicles
are alsobelievedto be underestimated [EC, 1997]. Owingto the availabilityof measurements, the model
OZONE CLIMATOLOGY,
1
30,369
ing cumulativeozoneexposuresin Europe during a 7-year period. J. Geophys.Res., 102, 23,917-23,935, 1997. Bouchet V. S., R. Laprise, E. Torlaschi, J. C. McConnell, and D. A. Plummer, Studying ozone climatology with a regionalclimate model, 2, Climatology,J. Geophys.Res., this issue.
Carmichael, G. R., L. K. Peters, and T. Kitada, A second-
generationmodelfor regional-scale transport/chemistry/deposition, Atmos. Environ., 20, 173-188, 1986. evaluation had to be restricted to the single species, Caya, D., and R. Laprise, A semi-Lagrangiansemi-implicit ozone, and mostly at ground level. This is a strong regionalclimate model: The CanadianRCM, Mon. Wealimitation on the assesmentof the oxidant chemistry ther Rev., 127, 341-362, 1999. simulated by the model. Ozone is one of the lesssen- Caya, D., R. Laprise, M. Gigu•re, G. Bergeron,J.-P. Blanchet, B. J. Stocks, G. J. Boer, and N. A. McFarlane, Desitive by-productsof the reactionsbetween NOx and scription of the Canadian RCM, Water Air Soil Pollut., VOCs, and correctmixing ratios can be obtainedfrom
the wrongprecursors ratios [Sillman,1995]. Consideringthe limitations inherent to this kind of
82, 477-482, 1995.
Caya, A., R. Laprise, and P. Zwack, On the effect of using processsplitting for implementingphysicalforcings in a semi-implicitsemi-Lagrangianmodel, Mon. Weather
evaluation, it appears that the CRCM is able to corRev., 126, 1707-1713, 1998. rectly simulate gas-phaseoxidant chemistry. This is, however,restrictedto a singleepisodeand doesnot con- Chameides,W. L., R. W. Lindsay,J. Richardson,and C. S. Kiang, The role of biogenichydrocarbonsin urban phostitute a guaranteethat the model will perform as well tochemicalsmog: Atlanta as a casestudy, Science,2•1, for other meteorologicalconditions. In the best cases, 1473-1475, 1988. models are tested on different ozone episodes but for Chang,J. S., R. A. Brost, I. S. A. Isaksen,S. Madronich,P.
roughlythe samekind of meteorological conditions.As illustrated here, the model's performance is quite variable over the episodewith occcasionalpoor agreement
especiallyat the end of the 6 days. Is it only a coincidence
or can one see there an indication
that
the
actual models could have somedifficulties in simulating
Middleton, W. R. Stockwell, and C. J. Walcek, A threedimensional Eulerian acid deposition model: Physical conceptsand formulation, J. Geophys.Res., 92, 14,68114,700, 1987. DeMore, W. B., S. P. Sander, D. M. Golden, R. F. Hampson, M. J. Kurylo, C. J. Howard, A. R. Ravishankara, C. E. Kolb, and M. J. Molina, Chemical kinetics and photochemical data for use in stratosphericmodeling, in Evaluation 12, Rep. 97-0•, 151-152, Jet PropulsionLab., Pasadena, Calif., 1997. Dennis, R. L., D. W. Byun, J. H. Novak, K. J. Galluppi, C. J. Coats, and M. A. Vouk, The next generation of
regimesof low ozonein the main sourcesareas?What impact could this have on the analysis of emissionreduction scenarios?These issuesare particularly critical for establishingemissionsmanagementstrategies. The companionpaper tries to answer some of these quesintegratedair quality modeling:EPA's model-3, Atmos. Environ., 30, 1925-1938, 1996. tions through an evaluation of the model for 5 consecEnvironmental Protection Agency (EPA), The 1985 NAutive months of July.
Acknowledgments. This researchhas beensupported by grantsfrom the CanadianNatural Scienceand Engineering ResearchCouncil (NSERC), the CanadianInstitute for Climate Studies(CICS), and EnvironmentCanadathrough the Canadian RegionalClimate Model project. The authors would like to thank the Cooperative Centre for Researchin Mesometeorology(CCRM), the Canadian Centre for Climate Modellingand Analysisin Victoria, D. Verseghyfrom
Environment Canada,andJ.-P.Blancher fromUQ•M for providing parts of the code and for their assistancein the development of the model; R. Leaitch from Environment Canada for providing the aircraft data; and D. Plummer from York University for useful discussionsthroughout the course of this work.
J.C. McConnell
would also like to thank
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ARQB/ARQI, 4905 Dufferin St., Downsview, Ontario, Canada M3H 5T4. (Veronique. Bouchet•ec.gc.ca) R. Laprise and E. Torlaschi, D•partement des Sciences de la Terre, Universit• du Quebec k Montreal, Montreal,
Quebec, Canada H3C 3P8. laschi.enrico•uqam.ca)
(laprise.rene•uqam.ca;tor-
J.C. McConnell, Department of Earth and Atmospheric Science, York University, Toronto, Ontario, Canada M3J
1P3. (jack•nimbus.yorku.ca)
(ReceivedDecember18, 1998; revisedJune 24, 1999; acceptedJuly 28, 1999.)
