mc2-aq model configuration and preliminary results for escompte experiment
DESCRIPTION
MC2-AQ Model 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 - PowerPoint PPT PresentationTRANSCRIPT
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