EMEP Technical report 2/2006
Date: July 2006
METEOROLOGISK INSTITUTT
Norwegian Meteorological Institute
First results from the hemispheric EMEP
model and comparison with the global
Oslo CTM2 model
by
Jan E. Jonson1 , Peter Wind1 , Michael Gauss2 , Svetlana Tsyro1 ,
Amund Søvde2 , Heiko Klein1 , Ivar S.A Isaksen2 and Leonor
Tarrasón1
1
Norwegian Meteorological Institute, EMEP/MSC-W
2
Department of Geophysics, University of Oslo
EMEP MSC-W
Technical report 2/2006
ISSN 1504-6179 (print)
ISSN 1504-6206 (online)
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Preface and Acknowledgements
This report was prepared for presentation at the thirtieth session of the Steering
Body to EMEP (Co-operative Programme for Monitoring and Evaluation of the
Long Range Transmission of Air Pollutants in Europe). This is the first time that
results from the hemispheric version of the EMEP Unified model are presented. It
is the result of the EMEP model development in the past few years to allow for
a flexible choice of the model grid and domain. The model results are compared
here to measurements from several sources, including surface measurements from
the EMEP and the GAW (Global Atmospheric Watch) databases, vertical sounding
data from ozone sondes and remote sense data. In addition, the model results
have been compared with a state-of-art global scale model, namely the Oslo CTM2
model, developed at the University of Oslo, Norway. Further validation of the model
is still necessary and the co-operation with the University of Oslo is to continue in
particular as these models intend to contribute to the work initiated under the Task
Force of Hemispheric Air Pollution Transport.
This work has received support from the Research Council of Norway through
computer time granted at the Norwegian Metacenter for Computational Science
(NOTUR). In addition to EMEP funding, this work has been partly supported by
the European Union FP6 project IP-NEEDS and by the Norwegian Ministry of the
Environment.
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4
Contents
1 Introduction
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2 Model description and input data
2.1 The hemispheric model version: modifications
2.2 The Oslo CTM2 model . . . . . . . . . . . . .
2.3 Input data . . . . . . . . . . . . . . . . . . . .
2.3.1 The hemispheric model version . . . .
2.3.2 The Oslo CTM2 model . . . . . . . . .
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3 Model results in the northern hemisphere
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3.1 Surface ozone: EMEP and Oslo CTM2 model calculations . . . . . . 9
3.2 Preliminary SR calculations with the hemispheric EMEP model . . . 10
4 Validation with surface measurements
4.1 Ozone . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.1 European ozone data from the EMEP database
4.1.2 GAW data for ozone . . . . . . . . . . . . . . .
4.2 PM and other key species . . . . . . . . . . . . . . . .
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5 Validation with ozone sonde data
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6 Initial validation with remote sensing data
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6.1 NO2 data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
6.2 HCHO data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
7 Conclusions and recommendations on model performance
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6
1
Introduction
The development of a hemispheric version of the EMEP Unified model has come
about as a result of a recognition that pollution levels in Europe are effected also
by sources in other continents. In particular for ozone, but to some extent also
for other pollutants as particulate matter, the influence from sources outside the
EMEP domain is increasing, and sources of this increase are unclear (Jonson et al.,
2006).Satellite, aircraft, and ground-based observations as well as model studies have
recently shown that air pollution can be transported over long, even intercontinental
and hemispheric distances (e.g. Berntsen et al., 1999; Stohl and Trickl, 1999; Yienger
et al., 2000; Edwards et al., 2003; Jaffe et al., 2003; Huntrieser et al., 2005).
While the major transport mechanisms for intercontinental pollution exchange
are relatively well known, the impact of intercontinental transport on surface pollution concentrations is still rather uncertain. Further studies on the exchange
mechanisms from the free troposphere to the surface layer, on the evaluation of the
free tropospheric levels and the origin of ozone and PM, and on the analysis of long
term budgets would be necessary to allocate the contribution of intercontinental
transport to surface PM and ozone levels. Under the Convention on Long-range
Transport of Air Pollution (CLRTAP), the Task Force on Hemispheric Transport of
Air Pollution (TFHTAP) is currently establishing scientific work and co-operation
necessary to develop a fuller understanding of intercontinental pollution transport.
The EMEP Centres are to contribute to this work.
In order to better contribute to the work of the TFHTAP on ozone and particulate matter, EMEP/MSC-W has recently initiated a collaboration with the Department of Geophysics at the University of Oslo. The cooperation is intended to
provide better insight in atmospheric transport, identify differences in regional and
global model approaches and evaluate the consequences of the different approaches
for intercontinental pollution transport.
In this report, the first model results from the hemispheric version of the Unified
EMEP model are compared to measurements from different sources. The main
focus is on ozone and the hemispheric model results are compared with with ozone
values from the well established Oslo CTM2 global model. The model validation is
mainly based on measurement data from surface measurements from the EMEP and
the GAW (Global Atmospheric Watch) databases. As in Jonson et al. (2004) model
results have been compared to ozone sondes, here including also ozone sondes in Asia
and North America. In addition model results have been compared to measurements
outside Europe compiled under GAW (global Atmospheric watch). Model results for
NO2 and HCHO have also been compared to satellite data. Further model validation
7
will be carried out as the model is intended to contribute to the international model
intercomparisons presently organised under the TFHTAP.
2
Model description and input data
This study mainly presents model data calculated with the hemispheric version of
the EMEP unified model, but also results calculated with the Oslo CTM2 model.
Below follows brief model descriptions of both models and an overview of model
input needed to run the models.
2.1
The hemispheric model version: modifications
A generalised version of the EMEP model version rv2 4 has been used for the simulations. Compared to earlier versions of the EMEP model the model domain is
extended so that it can cover the entire Northern Hemisphere, but with a coarser
resolution. The model domain i chosen so that Each 2x2 grid cells from the regular
EMEP grid exactly form one grid cell in the hemispheric grid. The polar stereographic grid parameters are:
• Grid resolution: 100 km x 100 km
• Size: 242 x 242
• Coordinates of North Pole: xp=120.75, yp=120.75
• Reference longitude: fi=32◦ West
• Latitude of true resolution: 60◦ North
2.2
The Oslo CTM2 model
The Oslo CTM2 is a global 3-dimensional chemical transport model driven by
ECMWF meteorological data extending from the ground to 10 hPa in 40 vertical layers. The horizontal resolution can be varied, but is set to Gaussian T42 ( 2.8 ◦
x 2.8◦ ) for this study. Advection uses the Second Order Moment scheme of Prather
(1986), while convection is based on the Tiedtke (1989) mass flux scheme. Transport in the boundary layer is treated according to the Holtslag K-profile method
(Holtslag et al., 1990), and the calculation of dry deposition follows Wesely (1989).
Surface emissions are based on the EDGAR 3.2 data base (Olivier and Berdowski,
2001) and typical of the year 2000. Lightning emissions of NOx are parameterised
based on formulas by Price et al. (1997a) and Price et al. (1997b), distributing the
emissions according to convective activity in the model and choosing 5 Tg(N)/year
as total annual output. The model calculates the distribution of 58 chemical compounds through comprehensive modules for tropospheric chemistry (Berntsen and
Isaksen, 1997, Berntsen and Isaksen, 1999) and stratospheric chemistry (Stordal
et al., 1985, Isaksen et al., 1990). Photo-dissociation rates are calculated online by
the Fast-J module (Wild et al., 2000), taking into account changing ozone distributions and the scattering of sunlight by clouds.
8
2.3
2.3.1
Input data
The hemispheric model version
The hemispheric emission data was provided in November 2005 by IER / UniStuttgart, based on edgar 2000 and reprojected on the polar stereographic grid. For
the emissions of primary PM2.5 and PMco we used emission rates of 10 and 5%
of NOx emissions respectively. Within the EMEP area EMEP emissions are used.
Timefactors are used only for EMEP countries. For biogenic VOC from forests
emission factors were increased outside EMEP area to account for differences in tree
characteristics. Volcanic emissions of sulphur are included only within the EMEP
domain. No natural DMS emissions are included.
The meteorological input data correspond to the ECMWF ERA-40 data for year
2001. A comparison using the ERA-40 meteorological data and the more detailed
HIRLAM data has been presented in Forster et al. (2005). The most important finding was that due to the coarser resolution, the ERA-40 data tends to overestimate
wet depositions.
Inside the EMEP area EMEP landuse data have been used. Outside the EMEP
area landuse data from MM5 have been used.
2.3.2
The Oslo CTM2 model
Meteorological data for the Oslo CTM2 has been prepared by running the Integrated
Forecast System model (IFS) of ECMWF for the year 2001 at Gaussian T319 resolution. For the model run in this study the data have been truncated to Gaussian
T42 resolution.
Emissions are based on the EDGAR3.2 database.
Data for initialisation of the model was taken from a previous model run using
year 1999 and 2000 data. The model was thus effectively spun up for more than one
year.
3
Model results in the northern hemisphere
In this section model results for ozone from both the EMEP hemispheric model
and the Oslo CTM2 model are shown. In addition preliminary source receptor
calculations with the EMEP hemispheric model are presented.
3.1
Surface ozone: EMEP and Oslo CTM2 model calculations
In Figures 1 and 2 model calculated ozone for January and July are shown for
both models. Comparison with measurements are shown in section 4. As a result
of a finer resolution the EMEP hemispheric model has more details than the Oslo
CTM2 model. Both models have a winter minimum over Europe and North America
and summer maximum over parts of North America, East Asia and in and around
the Mediterranean. The are also some marked differences. The Oslo CTM2 has
higher winter ozone over sea areas close to polluted continents. Furthermore The
9
Oslo CTM model has a band of high ozone at middle latitudes across Asia, mostly
covering areas with low emissions of ozone precursors. It seems likely that the
differences in ozone are caused by advection. A major fraction of this region is at
high altitude and the high ozone levels in the Oslo CTM2 model could be caused
by free tropospheric air extending to the surface in combination with a low dry
deposition velocity. Unfortunately there are no ozone measurements available in
this region for 2001.
So far we have only been able to include data from the Oslo CTM2 model for 2
sites. Hohenpeissenberg and Mauna Loa, both GAW sites. The sites are selected as
they are also ozone sonde sites (or close to ozone sonde sites) from where hourly or
daily output was available from the Oslo CTM2 model. In Figure 3 measured ozone
and calculated ozone from both models are compared. Both sites are mountain sites
with Mauna Loa at 3397 m above sea level and Hohenpeissenberg at 985 meter above
sea level, and thus difficult to reproduce by the models. The measurements are well
reproduced by the Oslo CTM2 model, whereas the ozone levels are underestimated
by the EMEP hemispheric model. Ozone levels in the EMEP hemispheric model are
reduced to 2 meters height, whereas output from the Oslo CTM2 at approximately
8 meters, the midpoint of the lowest model layer. As these sites are well above the
model topography the comparison with measurements could probably be improved
by taking model data from a few model layers above the model surface. Similar
underestimation of ozone at mountain sites are seen for Izana at the Canary islands
and at Summit, Greenland for the EMEP hemispheric model (Figure 13).
3.2
Preliminary SR calculations with the hemispheric EMEP
model
Source receptor relationships on a hemispheric scale have been calculated with the
hemispheric version of the Unified model as part of the EU research project IP
NEEDS (http://www.isis-it.net/needs/). This is the first such set calculated with
the hemispheric version of the EMEP Unified model and the results should be considered with caution as they are very preliminary !
In Forster et al. (2005) the mechanisms for intercontinental transport at middle
latitudes are described. Between continents most of the transport takes place in the
free troposphere. Mechanisms lifting material from the boundary layer to the free
troposphere involves deep convection and warm conveyor belts. Such conveyor belts
are often formed over the ocean east of continents, at the entrance of storm tracks.
Major source areas in North America and in Asia are at the eastern seaboard, close
to the entrance of the North Atlantic and North Pacific storm tracks. Europe on
the other hand, is on the western side of the Eurasian continent and at a higher
latitude resulting in less convection. Thus advection out of Europe is mostly in the
boundary layer where the lifetime of air pollutants is lower and advection slower.
As this is the first report where results from the hemispheric version of the EMEP
Unified model are presented, the calculated source receptor relationships should be
regarded as preliminary sets only. The calculated relationships are presented in a
tabulated form and as figures. Because of the preliminary nature of the calculations
only a limited set of species/parameters are shown.
In the source receptor calculations four separate regions have been considered:
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Figure 1: Surface ozone (see text) in ppb calculated with the Oslo CTM2 (top)
and the EMEP model (bottom). Left hand panels January, right hand panels July.
Notice differences in scale for the Oslo CTM2 model.
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North America
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Figure 2: Surface ozone (see text) in ppb calculated with the Oslo CTM2 (top)
and the EMEP model (bottom). Left hand panels January, right hand panels July.
For the EMEP model the Asian scale is the same as for North America. Notice
differences in scale for the Oslo CTM2 model.
12
Hohenpeissenberg
Maona Loa
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Figure 3: Modelled versus Observed Daily Max Ozone (ppb) at Hohenpeissenberg
(left) and Mauna Loa (right). Black, measurements, green Oslo CTM2 and red
EMEP hemispheric.
Europe (excluding Russia), the Middle East, the Far East and North America. The
regions are depicted in Figure 4.
In addition to the base case calculation, including the full effect of all sources
and regions, separate calculations are made for each of the above-mentioned regions
and for the following species (or set of species) reduced by 15%: SO2 , NOx and
PM2.5 and PMco, NMVOC and CO, NH3 .
Figure 5, top shows annually averaged ozone. High ozone levels are seen over the
main source areas over East Asia, North America and Europe excluding Russia).
The effects of 15% reductions in NOx (and primary particle) emissions from the
Far East, the Middle East, North America and Europe are also shown in Figure 5.
In addition source receptor relationships with 15% reductions in both NOx and
NMVOC + CO emissions are given in Table 1. In general reductions in NOx emissions have a larger effect than emissions in NMVOC + CO. An exception is Europe,
where NOx reductions results in a slight increase in ozone, caused by in increase in
titration, mainly in the winter months. The largest calculated reductions in ozone,
both locally and also in extension of the area affected, are achieved by emission
reductions over North America, and in particular over the Far East. The location
of these source regions are more favourable for lifting into the free troposphere as
described above. As a result of this lifting and the long lifetime of ozone in the free
troposphere (of the order of one month), emissions from these two regions are seen
(Figure 5) to affect large parts of the Northern Hemisphere. Reductions in NOx and
NMVOC + CO emissions are least effective over Europe, and changes are mainly
confined to the European region. But reductions also have small effects regionally.
To a large extent this can be explained by the northerly position of this continent
with less sunlight to drive the chemistry. Emissions from Europe largely remain in
the boundary layer where the lifetime of ozone is much shorter and the advection
much slower.
The calculated effects on ozone from emission reductions on an intercontinental
13
350
Figure 4: The continents as defines in the source receptor calculations. Blue = Europe, pink = Middle East, orange = Far east and green = North America
WEU
NA
FE
ME
15% VOC
WEU NA
0.408 0.056
0.100 0.183
0.047 0.056
0.013 0.010
reduction
15%NOx
FE
ME WEU NA
0.048 0.082 -0.063 0.016
0.039 0.054 0.142 0.627
0.257 0.049 0.040 0.068
0.025 0.204 0.021 0.014
reduction
FE
ME
0.017 0.038
0.059 0.064
0.650 0.047
0.058 0.697
Table 1: Average changes in O3 mixing ratio (ppb) resulting from a 15 % reduction
of VOC or NOx. left column: receptor region; upper row: emitter region
scale appears to be smaller than shown in previous studies (ie. (Derwent et al., 2004,
Li et al., 2002). With sources separately for individual continents completely shut
off Li et al. (2002) calculated a contribution of 2-3 ppb ozone from North American
sources and From Asia about 1 ppb for the summer months. Derwent et al. (2004)
calculated the annual contributions from 50% reductions in NOx emissions in North
America to a number of European sites to be in the 0.8 - 1.9 ppb range and from
Asia in the 0.5 0.7 ppb range. Linearly scaling our results from 15 to 50% reductions
we get a 0.5 ppb contribution from North America and a 0.2 ppb contribution from
Asia. Furthermore Derwent et al. (2004) report a 0.9 - 4.3 ppb contribution from
14
European sources, whereas our results indicates a slightly negative contribution from
European sources. Differences in results could be caused by differences in model
resolution and in nonlinearities in the chemistry going from 15 to 50% reductions
in NOx emissions. Differences could also be affected by lack of convection in our
hemispheric model.
Calculated PM2.5 concentrations are shown in Figure 6 top. High PM2.5 concentrations are seen over the polluted continents, and in particular so over East Asia.
The lifetime of PM2.5 is of the order of a few days only. The effects of 15% emission
reductions of NOx and primary particles are also shown in Figure 6. As expected
the calculated effect of these emission reductions are small outside the source regions
considered. Adding the effects of emission reductions of sulphur and ammonia (not
shown) does not alter these conclusions, as confirmed by calculated source receptor
relationships for SIA (Secondary Inorganic Aerosols)in Table 2. Both Anthropogenic
and natural emissions can however affect other continents during specific events.
WEU
NA
FE
ME
15% NOx
WEU NA
0.215 0.000
0.009 0.086
0.003 0.001
0.003 0.000
reduction
FE
ME
0.002 0.006
0.002 0.004
0.171 0.004
0.006 0.120
WEU
NA
FE
ME
15% SOx
WEU NA
0.286 0.000
-0.001 0.147
0.002 0.000
0.008 0.000
reduction
FE
ME
0.004 0.035
0.000 0.000
0.379 0.015
0.018 0.352
15%NH3
WEU NA
0.193 0.000
0.000 0.049
0.000 0.000
0.001 0.000
reduction
FE
ME
0.000 0.001
0.000 0.00
0.108 0.001
0.000 0.06
Table 2: Average changes in air concentration of SIA (µg/m3 ) resulting from 15
% reductions in NOx emissions (upper left), NH3 emissions (upper right) and SOx
emissions (bottom). left columns: receptor region; upper row: emitter region
Table 3 shows the effects of 15% reductions in SOx, NOx and NH3 emissions
on the depositions of oxidised Sulphur, oxidised nitrogen and reduced nitrogen. As
for SIA (and PM2.5) effects outside the source continents are relatively small, but
relatively larger than for SIA (and PM2.5). The reason for this is that for wet deposition in-cloud scavenging is far more effective than sub-cloud scavenging. Thus wet
deposition of pollutants from other continents involves (local) lifting and subsequent
advection in the free troposphere. Wet deposition (mainly in-cloud scavenging) over
the receptor continent does not require subsidence to the boundary layer.
15
15% SOx reduction
NA
FE
ME
177
13165 14612
1302099
467
209
2013 2953963
2851
223
79923 254943
WEU
NA
FE
ME
WEU
640233
1864
1467
18767
WEU
NA
FE
ME
15% NH3 reduction
WEU
NA
FE
ME
498601
47
4149 3407
418 748947
126
58
438
1061 2632784 3251
6098
57
29102 84431
15% NOx reduction
WEU
NA
FE
ME
377291
1807
9906
6510
10513 680302
7595
2479
2234
6198 976230
2577
5419
889 29350 126037
Table 3: Changes in wet and dry deposition of Oxidised Sulphur (tons as S) due to
a 15% reduction of SOx emissions (upper left), Oxidised Nitrogen (tons of N) due to
a 15% reduction in NOx emissions (upper right) and Reduced Nitrogen (tons as N)
due to a 15% reducttion in NH3 emissions (bottom). Left column: receptor region;
upper row: emitter region
16
Figure 5: Top, annually averaged surface ozone (ppb). Middle left, middle right,
bottom left and bottom right shows the effects of a 15% reduction in the NOx
(and PM) emissions from the Far East, Middle East, North America and Europe
respectively.
17
Figure 6: Top, annually averaged surface PM2.5 (mugm−3 ). Middle left, middle
right, bottom left and bottom right shows the effects of a 15% reduction in the NOx
and PM emissions from the Far East, Middle East, North America and Europe
respectively.
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4
Validation with surface measurements
In this section model output from the EMEP hemispheric model are compared to
surface measurements of several species from the the EMEP database, covering Europe only, and from GAW (global Atmospheric watch) for ozone only. Measurement
data from other databases, as the EANET data (Acid Deposition Monitoring Network in East Asia), are available and will be included in comparisons with model
data at a later stage. The comparison should then also be expanded to include more
output from the Oslo CTM2 model.
4.1
4.1.1
Ozone
European ozone data from the EMEP database
The analysis of the European ozone data from the EMEP database builds on previously reported work as presented in Simpson et al. (2005), Jonson et al. (2004) for
the regional version of the EMEP Unified model. A general conclusion is that the
performance of the hemispheric model version is comparable to results from the the
regional model as presented in the previous reports, but with a somewhat poorer
day to day correlation. The slightly poorer correlation can be attributed to a coarser
horizontal model resolution in this model version.
Nordic Sites
Figure 7 presents time-series plots of modelled versus observed daily maximum
ozone concentrations for a number of Nordic sites for the year 2001. In general,
the model reproduces the observed concentrations rather well at these Nordic sites.
At the site Tustervatn (NO15), which is located at around 66◦ N, ozone is usually
predicted very well by the regional EMEP model, but with the hemispheric version
ozone is underpredicted, in particular in winter and spring. It seems to be a general
feature that ozone is underpredicted at high latitude. This is also seen for ozone
sondes as discussed in section 5 and for the the Canadian sites north of about 50◦ N
as seen in section 4.1.2. Possible reasons for the underprediction of ozone at high
latitudes will be discussed in section 7.
Eastern European Sites
Figure 8 present time-series plots of modelled versus observed daily maximum
ozone concentrations for a number of Eastern European sites for the year 2001.
The model is able to reproduce the time-series for most of these sites rather well
and comparable to previous results from the regional model version (but again with
poorer correlations). Performance is poor for the site Rucava in spring. However,
the very low spring measurement and the lack of measurement data in summer may
indicate an instrument problem.
Central and North-West European Sites
Figure 9 presents time-series plots of modelled versus observed daily maximum
ozone concentrations for a number of central and North-West European sites for
the year 2001. The correlations are generally good. The seasonal cycles at sites
often measuring background air as the British sites, and in particular Mace Head
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Figure 7: Modelled versus Observed Daily Max Ozone (ppb), Nordic Sites for 2001
20
Figure 8: Modelled versus Observed Daily Max Ozone (ppb), Eastern European
sites, Nordic Sites 2001
21
are well reproduced, strongly indicating that the seasonal cycle of boundary layer
background ozone is well reproduced by the model. The site Angra do Heroismo
at the Azores (Figure 13) is upwind from Mace Head, in the middle of the North
Atlantic. Ozone levels and seasonal cycles are very similar at these two sites.
Measured seasonal cycle and ozone levels at the polluted continental sites are
also well reproduced by the model.
Mediterranean Sites and Portugal
Considering the size of the Mediterranean area there are few measurements in
this region. The regional model version underpredicts ozone levels in this region,
and in particular so for sites within the Mediterranean basin as Giordan lighthouse
(Malta) and Finkalia (Crete). As seen in Figure 10, this underprediction is not seen
in the hemispheric version of the model. Considering the complicated terrain and
meteorological conditions in and around the Mediterranean basin, it is surprising
that the model performance is better (to a large extent also with regard to daily
correlations), taking into account the coarser grid resolution in the hemispheric
model version.
4.1.2
GAW data for ozone
At http://gaw.kishou.go.jp/wdcgg.html, World Data Centre for Greenhouse Gases
(WDCGG), measurements of greenhouse gasses , including ozone, are available from
a number of countries/regions (many of the EMEP sites are also available from
this site). The data are organised according to regions, and this organisation is
reflected in the station names. The first letter in the station names (as used in the
figure below) corresponds to the first letter in the site name. Next, the first digit
corresponds to the GAW region (relevant regions are region 1 Africa, region 2 Asia,
region 4 North America, region 5 South Asia and Oceania and region 6 Europe).
the two last digits corresponds to the latitude. As an example e444 is Egbert in
region 4 at 44◦ N.
North American sites (GAW region 4)
Calculated and measured ozone levels from this region are shown in Figure 11.
Only measurements from Canada and Alaska are available for 2001 in the database.
The model performance is good for the southernmost sites, but model results deteriorate further north with substantial underpredictions in particular in late winter and
spring north of about 50◦ N, as seen for the sites Esther and Barrow. The same type
of underpredictions was also seen at high latitude sites in Europe (section 4.1.1, and
may be linked to the underprediction in the free troposphere also seen in section 5
for the ozone sondes.
Asian sites (GAW region 2)
Calculated and measured ozone in GAW region 2 are listed in Figure 12. Only
measurements from Japan are available. The model performance is good with the
exception of Tsukuba with substantial overpredictions, in particular in summer.
This site is relatively close to Tokyo. The emission outside the EMEP model area
are from the Edgar database with a horizontal resolution of 1×1 degree resolution,
22
Figure 9: Modelled versus Observed Daily Max Ozone (ppb), Central and Northwestern sites, 2001
23
Figure 10: Modelled versus Observed Daily Max Ozone (ppb), Mediterranean and
one Portuguese sites, 2001
24
Figure 11: Modelled versus Observed Daily mean Ozone (ppb), North American
sites. Sites listed from top left to bottom right are: Egbert (e444), Kejimkujik
(k444), Algoma (a447), Saturna (s448), Experimental Lakes Area (e449), Bratts
Lake (b450), Esther (e451) and Barrow (b471)
25
Figure 12: Modelled versus Observed Daily mean Ozone (ppb), East Asian sites.
Sites listed from top left to bottom right are: Minamitorishima (m224), Yonagunijima (y224), Tsukuba (t236) and Ryori (r239)
and this may lead to a bias in the emissions. At the two southernmost sites the model
is able to reproduce the marked changes in ozone levels following the seasonal change
in circulation patterns here.
Atlantic sites
These GAW sites belong to different GAW regions. Both Izana at the Canary
Islands (GAW region 1, Africa) and Summit at Greenland (GAW region 6) are
mountain sites at 2367 and 3238 m ASL respectively. Measurements at mountain
sites are a tough task to reproduce for all models. In addition Summit is at high
latitude (72◦ N and it is shown for the North American sites and elsewhere (Sections
4.1.1 and 5) that the model performance is poor at high latitudes. Finally Angra do
Heroismo is in the Azores. This site is often in the westerlies, upwind from European
Atlantic coastal sites as Mace Head.
26
Figure 13: Modelled versus Observed Daily mean Ozone (ppb), Atlantic sites. Sites
listed from top left to bottom right are: Izana (i128), Angra do Heroismo (a638)
and Summit, Greenland (s672)
27
4.2
PM and other key species
In this section model calculated concentrations of gaseous species NO2 and SO2
and individual aerosol components sulphate, nitrate, ammonium and sodium are
compared to measurements. Also modelled concentrations of the sum of secondary
inorganic aerosols (SIA), PM10 and PM2.5 are presented. As an example, model
calculated hemispheric distribution of concentrations of PM10 and PM2.5 , as well as
primary PPM, SIA and sea salt are shown in Figure 14.
As for ozone this study builds on comparisons carried out in previous EMEP
reports (Fagerli, 2005, Fagerli, 2004). These species are all relatively shortlived.
Concentrations are therefore to a large extent controlled by regional sources, and
the intercontinental contribution is relatively small compares to ozone.
In Figures 15 to 19 model results from the hemispheric model version are compared to EMEP measurements. It is reassuring that the model performance for the
hemispheric model version is largely comparable to the regional version as reported
in previous reports as cited above. With an even coarser grid resolution than the
regional model version (100×100km−2 versus 50×50km−2 ) the variability within the
grid cell domain should be large. As a result model performance for individual
sites is often somewhat poorer than results obtained with the regional model version. However, there are also sites/species where the hemispheric model predicts
the temporal variation of air concentrations better than the regional model.
The model shows a good ability to represent the regional gradients of all individual aerosol components (SO2 , NO3 , NH4 and SIA). As expected, the mean annual
concentrations of all aerosol components and PM10 and PM2.5 calculated with the
hemispheric model are somewhat lower compared to the regional EMEP model due
to the coarse grid resolution. Another reason for the lower air concentrations of
pollutants calculated with the hemispheric model is probably a more efficient wet
removal of species (see below). In particular, calculated sea salt concentrations from
the hemispheric model are considerably lower as most sea salt aerosols to a larger
extent get wet deposited over the sea areas, before they arrive at the (mainly coastal)
measurement sites. Further, it is interesting to note that there is a better temporal
correlations of hemispheric model calculated concentrations of PM10 and PM2.5 with
observations at most of the EMEP sites compared to the regional model. The most
plausible reason for that is the smoothing effect of the coarser spatial resolution of
the hemispheric model which allows a more robust representation of the regional
transport.
As shown in Forster et al. (2005) precipitation in the ERA40 data are of the
order of 20 - 35% lower than in the HIRLAM data, potentially resulting in less wet
deposition (Figure 19 top left). As a result of the coarser resolution in the ERA40
meteorology, precipitation affects a larger area and this more than compensates for
the underestimation of precipitation. Thus wet deposition, often underestimated
in the regional model (Fagerli, 2005, Fagerli et al., 2004), compares very well with
measurements as seen in Figure 19 for sulphate, oxidised nitrogen and reduced
nitrogen.
28
ug/m3
ug/m3
30
20
15
10
5
1
30
20
15
10
5
1
PM10 Year: 2001
PM2.5 Year: 2001
ug/m3
ug/m3
10
5
3
2
1
30
20
15
10
5
1
Primary PM10 Year: 2001
SIA Year: 2001
ug/m3
20
15
10
5
1
Sea Salt Year: 2001
Figure 14: Surface concentrations of PM10 (top left) and PM2.5 (top right), PPM10
(middle left, notice different legend) and SIA (middle left), and Na+ (bottom). All
concentrations in µgm−3
29
Figure 15: Top: Scatter plots of measured versus modelled NO2 (left) and nitrate
(right). Timeseries to the left measured and modelled NO2 . Timeseries to the right
measured and modelled nitrate. All concentrations in µgm−3 as N
30
Figure 16: Top: Scatter plots of measured versus modelled SO2 (left) and SO4
(right). Timeseries to the left measured and modelled SO2 . Timeseries to the right
measured and modelled SO4 . All concentrations in µgm−3 as S
31
Figure 17: Top: Scatter plots of measured versus modelled PM10 (left) and PM2.5
(right). Timeseries to the left measured and modelled PM10 . Timeseries to the right
measured and modelled PM2.5 . All concentrations in µgm−3
32
Figure 18: Top: Scatter plots of measured versus modelled SIA (left) and Na+
(right). Timeseries to the left measured and modelled SIA. Timeseries to the right
measured and modelled Na+ . All concentrations in µgm−3
33
Figure 19: Top: Scatter plots of measured versus modelled precipitation in mm
(top left) and wet deposition of sulphate in mgm−2 as S (top right), wet deposition
of oxidised nitrogen in mgm−2 as N (bottom left) and wet deposition of reduced
nitrogen in mgm−2 as N (bottom right).
34
5
Validation with ozone sonde data
In this section model model results from both the Oslo CTM2 global model and
the EMEP hemispheric model are compared to ozone sondes. We also intended
to use MOZAIC data (http://aeropc35.aero.obs-mip.fr:8080/magnoliaPublic/data),
but unfortunately the database is located inside a firewall and are therefor inaccessible for EMEP.
The main incentive for the ozone soundings are to monitor ozone in the stratosphere, and most of the sonde measurements are made in winter/spring in order
to study ozone depletion here. The measurements are also very useful in studying
ozone throughout the free troposphere. In Figures 20 - 24 average ozone soundings
for individual months and sites are compared to model calculated ozone averaged
over the same locations and approximately the same times (mostly within 1 hour)
as the measurements.
In the free troposphere the chemical lifetime of ozone is of the order of weeks to
1-2 months. The advection from one hemisphere to another is of the order of at least
several months, whereas advection from the stratosphere to the troposphere is of the
order of several months. Thus calculated ozone in the EMEP hemispheric model is
mostly determined by chemistry and advection within the model domain with the
the exception of the first 1 - 2 months (January - February) when ozone levels to
a large extent are determined by the initial concentrations. The Oslo CTM2 has
a global coverage, and extends to much higher altitudes, and initial concentrations
are from previous model runs for 1999 and 2000 as described in section 2.3.
In the Figures 20 - 23 model results from both models are compared to measurements for the four seasons represented by monthly averages for January, April,
July and October (for a few sites no measurements are shown or other months are
shown due to lack of measurements). In Figure 24 a few extra sites are shown for
the EMEP model.
In winter (January) both models are able to reproduce the ozone soundings
very well at most sites. As this is the first month in the model calculation for
the EMEP model, this is a good indication that initial ozone concentrations are
representative. The Oslo CTM2 model was spun up one year with year 2000 data,
thus it’s no surprise the initial Jan2001 data are good. In the spring and summer
months ozone levels are often underestimated by the EMEP model in the middle and
upper free troposphere, and in particular so for the high latitude sites (Figure 21.
The underestimation is absent or much smaller for the southernmost sites as Hilo
on Havaii (Figure 24) and Taipei at Taiwan (Figure 22. For the same sites/season
there is no clear under (or over) estimation in the model results from the Oslo
CTM2 model. In the autumn months (represented by October in Figures 20 - 24)
the measured ozone profiles are again well reproduced by both models. Furthermore
model performance for December (not shown) is similar to that of January suggesting
that there is no drift or buildup of ozone over the one year integration time.
35
Uccle January 2001
100
200
Uccle July 2001
100
11 Sond
EMEP
CTM2
200
300
400
400
500
600
700
500
600
700
800
500
600
700
800
600
700
800
900
900
900
900
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
100
200
100
13 Sond
EMEP
CTM2
200
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Hohenpeissenberg July 2001 Hohenpeissenberg October 2001
100
10 Sond
EMEP
CTM2
200
100
9 Sond
EMEP
CTM2
200
300
400
400
600
700
500
600
700
Pressure (hPa)
300
400
Pressure (hPa)
300
400
Pressure (hPa)
300
500
500
600
700
600
700
800
800
800
900
900
900
900
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
DeBilt January 2001
100
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
DeBilt April 2001
100
3 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
DeBilt July 2001
100
4 Sond
EMEP
CTM2
200
DeBilt October 2001
100
4 Sond
EMEP
CTM2
200
300
400
400
400
400
600
700
500
600
700
Pressure (hPa)
300
Pressure (hPa)
300
Pressure (hPa)
300
500
500
600
700
600
700
800
800
800
900
900
900
900
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Lerwick January 2001
100
200
200
300
400
400
Pressure (hPa)
300
600
700
800
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Lerwick April 2001
100
14 Sond
EMEP
CTM2
500
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
4 Sond
EMEP
CTM2
500
800
1000
10 Sond
EMEP
CTM2
500
800
1000
13 Sond
EMEP
CTM2
500
1000
Hohenpeissenberg January 2001 Hohenpeissenberg April 2001
Pressure (hPa)
Pressure (hPa)
300
400
Pressure (hPa)
300
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Pressure (hPa)
200
400
800
Pressure (hPa)
Uccle October 2001
100
12 Sond
EMEP
CTM2
300
Pressure (hPa)
Pressure (hPa)
200
Uccle April 2001
100
13 Sond
EMEP
CTM2
8 Sond
EMEP
CTM2
500
600
700
800
900
900
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Figure 20: Model calculated ozone, and ozone sonde measurements for European
sites, averaged for all available sonde measurements in the individual months shown.
36
Alert January 2001
100
200
400
500
600
700
500
600
700
800
Pressure (hPa)
300
400
Pressure (hPa)
300
400
500
600
700
800
600
700
800
900
900
900
900
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Ny Alesund January 2001
200
11 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Ny Alesund April 2001
100
200
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Ny Alesund July 2001
100
7 Sond
EMEP
CTM2
200
Ny Alesund October 2001
100
5 Sond
EMEP
CTM2
200
300
400
400
600
700
500
600
700
Pressure (hPa)
300
400
Pressure (hPa)
300
400
Pressure (hPa)
300
500
500
600
700
600
700
800
800
800
900
900
900
900
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Eureka January 2001
100
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Eureka April 2001
100
10 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Eureka July 2001
100
1 Sond
EMEP
CTM2
200
Eureka October 2001
100
2 Sond
EMEP
CTM2
200
300
400
400
400
400
600
700
500
600
700
Pressure (hPa)
300
Pressure (hPa)
300
Pressure (hPa)
300
500
500
600
700
600
700
800
800
800
900
900
900
900
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Resolute January 2001
100
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Resolute April 2001
100
6 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Resolute July 2001
100
3 Sond
EMEP
CTM2
200
Resolute October 2001
100
3 Sond
EMEP
CTM2
200
300
400
400
600
700
800
500
600
700
800
Pressure (hPa)
300
400
Pressure (hPa)
300
400
Pressure (hPa)
300
500
500
600
700
800
600
700
800
900
900
900
900
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
1 Sond
EMEP
CTM2
500
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
3 Sond
EMEP
CTM2
500
800
1000
5 Sond
EMEP
CTM2
500
800
1000
3 Sond
EMEP
CTM2
500
1000
100
Pressure (hPa)
200
300
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Pressure (hPa)
200
Alert October 2001
100
3 Sond
EMEP
CTM2
400
800
Pressure (hPa)
Alert July 2001
100
4 Sond
EMEP
CTM2
300
Pressure (hPa)
Pressure (hPa)
200
Alert April 2001
100
4 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Figure 21: Model calculated ozone, and ozone sonde measurements at polar sites,
averaged for all available sonde measurements in the individual months shown.
37
Taipei January 2001
100
200
300
400
400
500
600
700
500
600
700
800
600
700
800
900
900
900
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Sapporo January 2001
200
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Sapporo April 2001
100
3 Sond
EMEP
CTM2
200
4 Sond
EMEP
CTM2
500
1000
100
Sapporo July 2001
100
4 Sond
EMEP
CTM2
200
Sapporo October 2001
100
3 Sond
EMEP
CTM2
200
300
300
400
400
400
500
600
700
500
600
700
Pressure (hPa)
300
400
Pressure (hPa)
300
Pressure (hPa)
500
600
700
600
700
800
800
800
900
900
900
900
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Tateno January 2001
100
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Tateno April 2001
100
7 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Tateno July 2001
100
8 Sond
EMEP
CTM2
200
Tateno October 2001
100
4 Sond
EMEP
CTM2
200
300
400
400
400
400
600
700
500
600
700
Pressure (hPa)
300
Pressure (hPa)
300
Pressure (hPa)
300
500
500
600
700
600
700
800
800
800
900
900
900
900
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Kagoshima January 2001
100
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Kagoshima April 2001
100
5 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Kagoshima July 2001
100
3 Sond
EMEP
CTM2
200
Kagoshima October 2001
100
4 Sond
EMEP
CTM2
200
300
300
400
400
400
600
700
800
500
600
700
800
Pressure (hPa)
300
400
Pressure (hPa)
300
500
500
600
700
800
600
700
800
900
900
900
900
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
4 Sond
EMEP
CTM2
500
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
5 Sond
EMEP
CTM2
500
800
1000
5 Sond
EMEP
CTM2
500
800
Pressure (hPa)
Pressure (hPa)
Pressure (hPa)
300
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Pressure (hPa)
200
400
800
Pressure (hPa)
Taipei July 2001
100
3 Sond
EMEP
CTM2
300
Pressure (hPa)
Pressure (hPa)
200
Taipei April 2001
100
3 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Figure 22: Model calculated ozone, and ozone sonde measurements in East Asia,
averaged for all available sonde measurements in the individual months shown.
38
Huntsville January 2001
100
200
400
500
600
700
500
600
700
800
Pressure (hPa)
300
400
Pressure (hPa)
300
400
500
600
700
800
600
700
800
900
900
900
900
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Trinidad Head January 2001
200
200
300
400
400
Pressure (hPa)
300
500
600
700
700
800
900
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Edmonton January 2001
200
5 Sond
EMEP
CTM2
600
900
100
0 20 40 60 80 100
Ozone mixing ratio (ppb)
500
800
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Trinidad Head April 2001
100
2 Sond
EMEP
CTM2
Edmonton April 2001
100
3 Sond
EMEP
CTM2
200
Edmonton July 2001
100
3 Sond
EMEP
CTM2
200
Edmonton October 2001
100
2 Sond
EMEP
CTM2
200
300
400
400
400
400
500
600
700
500
600
700
Pressure (hPa)
300
Pressure (hPa)
300
Pressure (hPa)
300
500
600
700
600
700
800
800
800
900
900
900
900
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Goosebay January 2001
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
200
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Goosebay April 2001
100
4 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Goosebay July 2001
100
3 Sond
EMEP
CTM2
200
Goosebay October 2001
100
2 Sond
EMEP
CTM2
200
300
400
400
600
700
800
500
600
700
800
Pressure (hPa)
300
400
Pressure (hPa)
300
400
Pressure (hPa)
300
500
500
600
700
800
600
700
800
900
900
900
900
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
3 Sond
EMEP
CTM2
500
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
3 Sond
EMEP
CTM2
500
800
100
2 Sond
EMEP
CTM2
500
1000
100
Pressure (hPa)
200
300
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Pressure (hPa)
200
Huntsville October 2001
100
3 Sond
EMEP
CTM2
400
800
Pressure (hPa)
Huntsville July 2001
100
4 Sond
EMEP
CTM2
300
Pressure (hPa)
Pressure (hPa)
200
Huntsville April 2001
100
4 Sond
EMEP
CTM2
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Figure 23: Model calculated ozone, and ozone sonde measurements in North America, averaged for all available sonde measurements in the individual months shown.
39
Hilo January 2001
400
400
Pressure (hPa)
300
500
600
700
7 Sond.
Mod.
500
600
700
800
800
900
900
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Yakutsk January 2001
Yakutsk April 2001
9 Sond.
Mod.
200
Yakutsk June 2001
2 Sond.
Mod.
200
Yakutsk October 2001
2 Sond.
Mod.
200
300
300
400
400
400
400
500
600
700
500
600
700
Pressure (hPa)
300
Pressure (hPa)
300
Pressure (hPa)
500
600
700
1 Sond.
Mod.
500
600
700
800
800
800
800
900
900
900
900
1000
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Ankara January 2001
Ankara April 2001
Ankara July 2001
Ankara October 2001
200
2 Sond.
Mod.
200
2 Sond.
Mod.
200
1 Sond.
Mod.
200
300
300
300
400
400
400
400
500
600
700
800
500
600
700
800
500
600
700
800
Pressure (hPa)
300
Pressure (hPa)
Pressure (hPa)
200
300
200
Pressure (hPa)
4 Sond.
Mod.
Pressure (hPa)
Pressure (hPa)
200
Hilo April 2001
500
600
700
800
900
900
900
900
1000
1000
1000
1000
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
0 20 40 60 80 100
Ozone mixing ratio (ppb)
1 Sond.
Mod.
0 20 40 60 80 100
Ozone mixing ratio (ppb)
Figure 24: Model calculated ozone, and ozone sonde measurements averaged for all
available sonde measurements in the individual months shown.
40
6
Initial validation with remote sensing data
In this section model output is compared to remote sensing data retrieved from
GOME (Global Ozone Monitoring Experiment) aboard the second European Remote Sensing satellite ERS2. The main target of the instrument is observation of
ozone fields, but the data can also be used to retrieve column of other species as NO2
and HCHO. A description of the GOME instrument can be found at the GOME
homepage http://www-iup.physik.uni-bremen.de/gome/, and only a brief overview
is given here. This satellite was launched in April 1995. GOME is observing the atmosphere in nadir sounding having four spectral channels. The satellite moves in a
retrograde, sun-synchronous near polar orbit at a height of about 795 km. The local
crossing time at the equator is 10:30 am. The nadir viewing consists of four ground
pixel types (east, nadir, west, Backscan). The maximum scan width is 960km. Each
pixel is spanning an area of maximum 40km along the track and 320km across the
track. Global coverage is reached within three days (after 43 orbits).
There is a relatively high uncertainty in the retrieved columns of about 35 60% over larger columns over continental areas (Boersma et al., 2004). Over clean
areas measurements have little meaning due to large uncertainties. The uncertainty
is dominated by errors in the estimates of the tropospheric air mass factor. Such
errors are caused by uncertainties in cloud fractions, surface albedo and the assumed
profile shape (Boersma et al., 2004).
6.1
NO2 data
Compared to the satellite measurements the location of the major source regions for
NOx in the northern hemisphere are well reproduced by the model. (Figure 25, top)
shown as NO2 columns for July. Model calculated NO2 columns are lower than the
measurements, but this is within the uncertainty range of the satellite measurements
as given above. Focusing on Europe (Figure 25, bottom) the source region around
the English channel can be seen for both model and measurements. NO2 columns
over Spain and Northern Italy are less pronounced in the model data.
6.2
HCHO data
Formaldehyde (HCHO) is a major intermediate gas in the oxidation of methane
and many other hydrocarbons. Its major sinks are photolysis and the reaction with
OH. Because of the short lifetime of many hydrocarbons and of HCHO itself, the
presence of this species is an indicator for emissions of hydrocarbons from forests,
biomass burning, traffic and industrial sources. In figure 26 the tropospheric columns
from GOME and from the model are compared for July. Major source regions in
Africa, North America and Asia are seen in both the measured and model calculated
columns. The high columns indicated by the model over Japan and in particular in
the Middle East is not seen in the measurements.
41
Figure 25: Tropospheric NO2 column for July 2001 (units: 1018 molecules cm−2 .
Columns below 1×1018 are not shown due to large uncertainties in the measurements
for low columns. Panels to the left shows measurements from the GOME satellite
and right panels model calculated columns. The bottom two panels are based on
the same data focusing on Europe.
42
Figure 26: Tropospheric HCHO column for July 2001 (units: 1018 molecules cm−2 .
Columns below 1×1018 are not shown due to large uncertainties in the measurements
for low columns. Panels to the left shows measurements from the GOME satellite
and right panels model calculated columns. The bottom two panels are based on
the same data focusing on Europe.
43
7
Conclusions and recommendations on model performance
In this section we try to sum up where the hemispheric model is working well, and
more importantly where the model performance is poorer and model improvements
should be sought.
Over Europe, the hemispheric model performance is comparable to the regional
model version, but the daily correlation with the measurements is often lower. This
should be attributed to the coarser resolution in the hemispheric model version.
Model performance in other regions are in general also good, although somewhat
poorer than for the EMEP area. A likely reason for this is that input data in general
have a higher quality and a better spatial resolution over Europe than for the rest
of the model domain.
For ozone the seasonal cycles at Atlantic coastal sides as Mace Head are well
reproduced by the model. Measurements at Angra do Heroismo at the Azores are
very similar to the measurements at Mace Head, supporting the assumption made
in the Mace Head adjustment used in the regional model (Simpson et al., 2003) that
the clean sector at Mace Head is representative of inflow from a large part of the
North Atlantic.
In the spring and summer months ozone is often underpredicted in the free troposphere. The poor performance of the EMEP hemispheric model at high latitudes,
where ozone levels are underpredicted in the late winter/spring and summer months
is probably linked to problems in describing the free troposphere. Several possible
reasons for the lack of performance in the free troposphere and at high latitudes need
to be investigated further. One reason may be too low influx from the stratosphere.
This could be caused partly by too low values being ascribed at the upper boundary or by inadequate description of the exchange processes. Another reason may
be lack of lifting of ozone and/or ozone precursors by convection or by boreal fires
where the heat generates buoyancy lifting pollutants into the free troposphere. This
underprediction is not seen in the Oslo CTM2 model, where convention is explicitly
included. Further co-operation with the University of Oslo is envisaged in order to
elucidate the reasons for the present model performance and to determine to what
extent the two different model can learn from each other.
44
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