1. First use of satellite AOD data for EMEP model validation for PM
Title
First use of satellite AOD data for EMEP model validation for PM
Svetlana Tsyro
TFMM 9-th meeting, Bordeaux, April 2008

2. Aerosol components and size distribution in the EMEP model
Natural
SIA
PPM X
Water O
coarse
2.5 < D < 10 µm
accumulation
0.1 < D < 2.5 µm
Aitken
0.02 < D < 0.1µm
nucleation
D < 0.02 µm
Sea salt
Dust
OC* EC
NH4
NO3
SO4 N
Size fractions
PM2.5
PM10
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3. Implementation of AOD in the aerosol model – observation operator:
1. Mass-based AOD
Mass specific cross-sections (m2/g) for 0.55 µm
(Tegen et al., 1997; Seinfeld & Pandis, 1997; Kinne et al., 2005)
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
0.4
0.9 9
5.0
8.5
Eext wet
Sea salt
Min. dust EC OC
NH4
NO3
SO4
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4. 2. Size-distribution-based AOD
Qext - extinction efficiency, calculated using Mie-scattering theory for spherical and internally mixed particles
Effective complex refractive index
is the sum of volume weighted complex refractive indices of all aerosol components, including aerosol water
meff = Σ (vi∙ni) + i Σ( vi∙ki)
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Lookup tables for Qext at 0.55 µm
as function of radius and complex refractive index (n+i∙k)
for monodisperse and log-normal distribution
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5. Data from MODIS on polar-orbiting NASA satellites AQUA & TERRA
Hierarchical Data Format (HDF) - as one granule per file.
Each granule consists of (203x135)10-km boxes along the satellite track.
Used the MODIS product “Optical_Depth_Land_And_Ocean”, which contains data for AOD at 0.55 μm.
relies on primary retrieved data only
has most stringent quality control
is a joint product, covering both land and ocean.
hourly and daily averages aggregated in the 50 x 50 km2 EMEP grid
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

6. Selected for comparison periods:
July-August and November-December in 2003
March-April and July-August in 2004
Model calculated AOD have been averaged:
for hours with sunlight and
cloud cover less than 50%
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

7. Modelled annual mean AOD, 2004
Mie-LogNor
Mass-based
Mie-MONO
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

8. Daily mean AOD MODIS 1 August 2003 1 April 2004 1 December 2003 Mie
LogNor
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Mass- based
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9. Model vs. MODIS AOD for entire EMEP area
0.36
-62
Mar-Apr
0.30
-32
Nov-Dec
-71
Jul-Aug
0.49
-69
Mass-based
0.11
-77
0.07
-58
0.17
-82
0.31
-79
Mie-mono
-51
-17
0.26
-54
0.35
-52
Mie-lognor
2004
2003 R
Bias (%)
AOD
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

10. Model vs. MODIS AOD for some regions
0.0
-59
0.35
0.32
-33
0.28
-53
Southern N. Atlantic
0.23
-26
-51
-18
0.05
-24
Mediterranean Sea
0.44
-71
0.37
-65 -
0.21
southern Norway
0.18
-56
0.24
-64
0.29
-14*)
0.67
central Russia
0.41
-29
0.17 8
0.66
-37
SE Europe
0.48
-54
0.30
-28 33
0.61
-44
Central Europe
0.53
-47
0.45
-23
0.87
23*)
0.65
-39 UK
0.50
-41
0.54
Benelux R
Bias (%)
Area
July-Aug 2004
March-April 2004
Nov-Dec 2003
July-Aug 2003
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Greater underestimation in summer
Correlation is worse for sea/ocean areas
Meteorologisk Institutt met.no

11. Daily timeseries for July-August 2003
Southern Europe
Greece, Albania and Macedonia
European part of Russia
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

12. Daily time-series of modelled and MODIS AOD EMEP stations for July-August 2003:
Birkenes (NO)
Aspvreten (SE)
Langenbrügge (DE)
Cabo de Creus for
July-August November-December March-April 2004
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

13. Daily time-series for EMEP sites (July-Aug. 2004)
measured and calculated PM2.5, modelled AOD and MODIS AOD (x25)
modelled and MODIS AOD
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

14. AOD vs. PM2.5: EMEP sites, summer months
Rather mixed correlations between measured PM2.5 and MODIS AOD are found for 18 considered stations.
In general, the correlation between measured PM2.5 and AOD: better for sites in Southern Europe (mostly between and 0.7)
lower in Central and Northern Europe (between 0.2 and 0.5)
Higher correlations between modelled and MODIS AOD than between calculated and measured PM2.5 for many sites, especially for summer 2003.
For instance, AOD and PM2.5 correlations are
Chaumont (CH)
Ispra (IT)
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

15. are associated with both
Uncertainties
are associated with both
Model calculations and MODIS data
COMPARABILITY…..
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

16. Sensitivity test diameters of primary emitted particles were decreased
Aitken particles from 0.04 μm to 0.03 μm
accumulation particles from 0.4 μm to 0.3 μm.
Relative changes in the annual mean
Accum. diameter
AOD
Accum. number
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
% Aitken
35 – 75% accum
5 - 15% Aitken
10 – 17% accum
5 - 20% land
1 – 5% ocean
The effect of increased aerosol number is overridden by the effect of decreased scattering cross-section
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17. Summary 1
Observation operator for AOD (at 0.55 µm) has been developed in the EMEP aerosol model
Several assumptions were tested:
mass based, Mie-monodisperse
Mie- lognormal BEST!
More tests: sensitivity studies (complex reflective indices, extinction efficiency dependence on the aerosol size distribution and mixture type)
Case studies (anthropogenic pollution episodes, Saharan dust, forest fires)
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

18. Summary 2
On average, model calculated AOD is lower compared to MODIS data for all seasons:
by 51 to 55 % for summer and spring
by about 11% for late autumn-winter months.
The spatial correlation between them is rather poor for all seasons:
somewhat better for summer months July and August (0.35 in 2003 and 0.26 in 2004).
The temporal correlation for locations (areas, EMEP sites) is actually fairly good ( ), even better than for PM2.5 for some sites
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no

19. Final remark
Using new types of measurements, other than EMEP monitoring data, for model validation is very instructive and exciting (and a bit scary)
… like EMEP intensive measurements, satellite total column data, LIDAR vertical profiles…..
Fine and coarse particles are distinguished in order to account for the different dry and wet removal rates.
Meteorologisk Institutt met.no