MC2-AQModel configuration and preliminary results for

ESCOMPTE experiment

Joanna Struzewska

Institute of Environmental Engineering Systems

Warsaw University of Technology, Poland

Jacek W. Kaminski

York University, Toronto, Canada

OUTLINE

MC2-AQ model description Model configuration for ESCOMPTE

experiment Model results - meteorological parameters Model results - chemical parameters Modelling issues Summary

MULTISCALE AIR QUALITYMODELLING SYSTEM GEM-AQ / MC2-AQ

Joint project between Institute of Environmental Engineering Systems

Warsaw University of Technology

York University, Toronto, Canada Department of Earth and Atmospheric ScienceMultiscale Air Quality Modelling Network (www.maqnet.ca)(sponsored by the Canadian Foundation for Climate and Atmospheric Sciences www.cfcas.org)

MC2 - Host Meteorological Model

model dynamics MC2 - „Mesoscale Compressible Community”

model (Robert et al., 1985; Tanguay et al., 1990; Benoit et al., 1997) Limited Area Model (LAM) Semi-implicit, semi-lagrangian discretization of the

Euler (compressible) equations. A non-hydrostatic approach

MC2 - Host Meteorological Model

Model physics Radiation : IR Garand (1983, Garand et Mailhot

1990); Solar: Fouquart-Bonnel (1980) Surface boundary layer : Force-restore method

(Deardorff 1978; Benoit et al. (1989) Turbulence and Vertical diffusion: Turbulent

Kinetic Energy (Benoit et al 1989) Horizontal diffusion : Second order (KH * 2) Orography treatment : Filtered over 3 grid

points, subgrid scale orography

MC2-AQ: Air Quality Module Gas phase chemistry (native to ADOM)

32 advected species 14 short-lived species

Aerosol chemistry and physics (CAM) Dry and wet removal

MC2-AQ: Air Quality Module Biogenic emissions (meteorology

dependent) Anthropogenic emissions

area emissions point source emissions

ESCOMPTE Modellin Exercise Modelling strategy Cascade mode (MC2-AQ - self nesting)

0.9 deg resolution simulation over Europe Objective analysis from CMC Chemical boundary conditions from global CTM

0.09 resolution simulation over Western Europe (centered over France)

0.009 resolution simulation over Southern France

ESCOMPTE Modelling Exercise Model domains

ESCOMPTE Modelling Exercise Model grid definition Lat-Lon projection

0.9 deg - 56 x 56 grid points 0.09 deg - 207 x 207 grid points 0.009 deg - 227 - 207 grid points

Gal-Chen vertical coordinate model top - 20 000 m 35 levels bottom layer thickness ~17 m, 25 levels below 5 km, 17 levels below 1500 m

ESCOMPTE Modelling Exercise Input data: emission 0.9 deg - EMEP emission inventory 0.09 deg - EMEP inventory combined with

processed escompte inventory 0.009 deg - ESCOMPTE emission inventory

convertion the detailed NMVOC inventory to mc2-aq VOC speciation

interpolation from UTM to latlon projection

ESCOMPTE Modelling Exercise NO surface emission - 1km

ESCOMPTE Modelling Exercise Modelled period - IOP 2A Time span: 20.06.2001 00 UTC - 24.06.2001 00 UTC

20.06.2001 00 UTC 24.06.2001 00 UTC

CMC Objective Analysis - every 6 hours

20.06.2001 12 UTC 24.06.2001 00 UTC

20.06.2001 18 UTC 23.06.2001 23 UTC

Time step = 300 s

Time step = 120 s

Time step = 20 s0.009 deg:

0.09 deg:

0.9 deg:

Boundary conditions from 0.9 deg run - every 1 hours

Boundary conditions from 0.09 deg run - every 1 hours

ESCOMPTE Modelling Exercise IOP-2A meteorological situation

ESCOMPTE Modelling Exercise IOP-2A ozone episode

ESCOMPTE Modelling Exercise

Model output Required meteorological parameters:

temperature (~5 m) sea level pressure U,V wind relative humidity [%]

Additional analysis (planned) BL height cloud cover surface heat and momentum fluxes

ESCOMPTE Modelling Exercise

Model output - 5 m temperature

T [oC]

10

15

20

25

30

35

18 28 38 48 58 68 78

ALTHEN

mc2-aq

T [oC]

10

15

20

25

30

35

40

18 28 38 48 58 68 78

BARBENTANE

mc2-aq

T [oC]

10

15

20

25

30

35

40

18 28 38 48 58 68 78

PUJAUT

mc2-aq

T [oC]

10

15

20

25

30

35

18 28 38 48 58 68 78

AVIGNON/INRA

mc2-aq

ESCOMPTE Modelling Exercise

Model output - sea level pressurePN [hPa]

1005

1007

1009

1011

1013

1015

1017

1019

19 29 39 49 59 69 79 89

AIX LES MILLES

mc2-aq

PN [hPa]

1005

1007

1009

1011

1013

1015

1017

1019

19 29 39 49 59 69 79 89

AVIGNON

mc2-aq

PN [hPa]

1005

1007

1009

1011

1013

1015

1017

1019

19 29 39 49 59 69 79 89

NIMES-COURBESSAC

mc2-aq

PN [hPa]

1005

1007

1009

1011

1013

1015

1017

1019

19 29 39 49 59 69 79 89

ISTRES

mc2-aq

ESCOMPTE Modelling Exercise

Model output - chemistry Required chemical parameters:

O3, NO, NO2,CO (delivered)

RCHO, H2O2, ROOH, OH, HO2, RO2, HNO3, NOy (3D output)

SO2 (surface measurements)

Additional analysisconcentration of MC2-AQ hydrocarbon species vs. detailed emission inventory

ESCOMPTE Modelling Exercise

Model output - O3Ozone (ppbv)

0

10

20

30

40

50

60

70

80

90

18 28 38 48 58 68 78 88

ROUSSET

1 km mc2-aq

Ozone (ppbv)

0

10

20

30

40

50

60

70

80

90

18 28 38 48 58 68 78 88

CADARACHE/DURANCE

1 km mc2-aq

Ozone (ppbv)

-20

0

20

40

60

80

100

120

140

160

18 28 38 48 58 68 78 88

Marignane Ville

mc2-aq - 1km

Ozone (ppbv)

-10

0

10

20

30

40

50

60

70

80

90

18 28 38 48 58 68 78 88

ARLES

mc2-aq - 1km

ESCOMPTE Modelling Exercise

Model output - NO2NO2 (ppbv)

0

10

20

30

40

50

60

18 28 38 48 58 68 78 88

Vitrolles

mc2-aq

NO2 (ppbv)

0

10

20

30

40

50

60

70

18 28 38 48 58 68 78 88

Marignane Ville

mc2-aq

NO2 (ppbv)

0

10

20

30

40

50

60

18 28 38 48 58 68 78 88

ARLES

mc2-aq

NO2 (ppbv)

0

10

20

30

40

50

60

18 28 38 48 58 68 78 88

ST MARTIN CRAU

mc2-aq

ESCOMPTE Modelling Exercise

Model output - COCO (ppbv)

0

200

400

600

800

1000

1200

1400

1600

1800

2000

18 28 38 48 58 68 78 88

MARSEILLE PRADO

mc2-aq

CO (ppbv)

0

200

400

600

800

1000

1200

1400

1600

1800

2000

18 28 38 48 58 68 78 88

AIX ROY RENE

mc2-aq

CO (ppbv)

0

500

1000

1500

2000

2500

3000

18 28 38 48 58 68 78 88

MARSEILLE PARADIS

mc2-aq

CO (ppbv)

0

500

1000

1500

2000

2500

3000

18 28 38 48 58 68 78 88

MARSEILLE PLOMBIERES

mc2-aq

Modelling issues Underestimation of the temperature in the

lowest model layer (is „force-restore” parameterisation proper for high resolution runs?)

Surface ozone underestimation (due to temperature underestimation ?)

Problems with reproducing of the diurnal cycle of ozone and temperature for stations located on the cost

Modelling issues Costal stations: Toulon, Marseille

T [oC]

10

15

20

25

30

35

18 28 38 48 58 68 78

TOULON

mc2-aq

Ozone (ppbv)

0

10

20

30

40

50

60

70

80

90

18 28 38 48 58 68 78 88

TOULON ARSENAL

1 km mc2-aq

Ozone (ppbv)

0

10

20

30

40

50

60

70

80

90

18 28 38 48 58 68 78 88

MARSEILLE 5 AVENUES

1 km mc2-aq

T [oC]

10

15

20

25

30

35

18 28 38 48 58 68 78

MARSEILLE

mc2-aq

Toulon

Marseille

Modelling issues Questionalble initial conditions for initial run (global

CTM) Low quality of boundary conditions from 10km run

(results from 10 km simulation not satisfactory) 1 km resolution model run is computationally

expensive, and difficult to set up physical processes parameterisations

Modelling issues Is model performance influenced by:

low quality of initial and boundary conditions model configuration (e.g. surface energy

balance parameterisation) lack of chemical data assimilation ?

Planned improvements New model run (3 km resolution) with more

detailed surface scheme applied Model results analysis against surface

measurements: Temperature Wind speed ad wind direction Humidity Ozone, NOx and lumped VOC concentration

Model results analysis against vertical soundings