The general features of the monsoon meteorology and dynamics are
reasonably reproduced by WRF-Chem. In the supplement (Fig. S1),
the WRF-Chem simulated average wind pattern at 850 hPa
and Outgoing Longwave Radiation (OLR) are shown for July 2008.
The typical monsoonal wind pattern bringing in the
moist air masses from oceanic regions is successfully captured by WRF-Chem.
Latitudinal extent of low OLR values between 70–100∘ E has also been qualitatively reproduced in agreement
with the OLR climatology over this region .
The biases in WRF OLR as compared to NOAA OLR data are similar to , who compared WRF OLR with reanalysis data.
Further details of general meteorology, wind patterns and OLR variations over the Indian region during the summer monsoon
can be found elsewhere
e.g..
Detailed evaluations of WRF simulated meteorology and evaluations of convection
parameterizations in WRF model during the summer monsoon over India have been published previously.
Model evaluation
In this section, WRF-Chem simulated ozone and carbon monoxide data over Chennai are evaluated against the CARIBIC observations, MOPITT retrievals of CO
profiles and the ground-based measurements.
Comparison with CARIBIC profiles
The hourly output of WRF-Chem simulations has been spatially and temporally
interpolated along the CARIBIC flight tracks. The observed and model simulated
profiles have been averaged into vertical bins of 50 hPa for the
comparison analysis. The comparison of O3 and
CO profiles from CARIBIC measurements with standard WRF-Chem simulations (Std) is shown in
Fig. . Here we
only show the profiles collected during the descent of the aircraft as
these have complete coverage until about 800 hPa, while
the measurements start from about 600 hPa upwards in the
ascending profiles. However for the analysis of model biases,
all the ascending and descending profiles have been averaged to calculate
the monthly profiles (Fig. ).
Comparison of ozone
and carbon monoxide profiles from WRF-Chem simulations (Std, red lines)
with the CARIBIC observations (blue lines) during June, July, August and
September 2008. Model output has been spatially and
temporally interpolated along the CARIBIC flight tracks.
Only data collected during the aircraft descent are shown here (see Sect.
for details).
Higher levels of ozone and carbon monoxide occur in the
lower troposphere (LT: 850–600 hPa) and Upper Troposphere
(UT: above 300 hPa), while lower levels in the Middle Troposphere
(MT: 600–400 hPa) cause a typical C-shape structure during
July. This feature is suggested to be associated with the monsoonal convective
uplifting of the lower tropospheric pollution and is captured by WRF-Chem.
Despite the qualitative agreement of the vertical distributions of O3 and CO, significant differences occur between
model and measurements, particularly in lower tropospheric CO. For
example, on 19 June the observational CO levels vary from
91.5±3.9 to 104.4±0.6 nmolmol-1 in the LT, whereas WRF-Chem simulated
CO levels are significantly lower (75.4±1.0 to
85.8±0.7 nmolmol-1). The average underestimation (Mean Bias)
of CO in the LT is found to be
12.6±4.4, 22.8±12.6 and 19.9±7.5 nmolmol-1 during June, July and August respectively,
as calculated from all the ascent and descent profiles averaged for a month
(Fig. ).
WRF-Chem simulated average CO shows very good agreement with CARIBIC measurements during
September in the LT (MB = -0.1±4.2 nmolmol-1).
Comparison of monthly average
ozone and carbon monoxide profiles from standard WRF-Chem simulations
(Std) with the CARIBIC observations during June, July, August and
September 2008. Numbers in brackets denote the number of observational
profiles in the respective month. Model output has been spatially and
temporally interpolated along the CARIBIC flight tracks. Comparison with another simulation
Std_INTEX is indicated in black.
The model underestimates a pollution event of strongly elevated ozone
observed on 15 July 2008 (146.4±12.8 nmolmol-1 at 810 hPa). In contrast to CO which is typically underestimated in LT,
the bias in model simulated O3 varies from an
overestimation by 4.3±1.8 during June to an
underestimation by 7.8±1.6 nmolmol-1 during August,
except during the strong pollution event (-71.5± 25.9 nmolmol-1).
The significantly higher levels of O3 (146.4±12.8 nmolmol-1) and
CO (136.4±12.2 nmolmol-1) as observed during July are from two
observational profiles on the same day (15 July), discussed
separately as an event of strong pollution.
For the complete profiles from Standard WRF-Chem
simulations (Std), the Root Mean Square Deviation (RMSD) values for
O3 are found to vary from 6.5 to 12.6 nmolmol-1,
except during a strong pollution event (RMSD = 48.1 nmolmol-1).
RMSD values for CO are in the range of 5.5 to 18.2 nmolmol-1.
Additional simulation Std_INTEX using a different emission inventory INTEX-B also shows similar results
(Figs. , S2), as seen with simulation Std using HTAP emissions.
The average vertical distribution of the water vapor mixing ratios
from WRF-Chem is compared with the
CARIBIC measurements in Fig. .
Generally, WRF-Chem simulated H2O is in very good agreement with the observations, i.e., within
the variability of 1 standard deviation. The observations are not available below 500 hPa in months other
than during July, when the model tends to overestimate H2O in the lower troposphere.
Comparison of monthly average
H2O gas (ppm) from standard WRF-Chem simulations
(Std) with the CARIBIC observations during June, July, August and
September 2008. Numbers in brackets denote the number of observational
profiles in the respective month. Model output has been spatially and
temporally interpolated along the CARIBIC flight tracks. Note the logarithmic scale on the x axis.
Comparison with ozonesonde climatology
WRF-chem simulated ozone profiles are compared with the monsoon-time climatology obtained from ozonesonde observations at Delhi, Pune and Thiruvananthapuram
(Fig. ), as described in Sect. .
WRF-Chem simulated ozone profiles in the lower and middle troposphere
are generally observed to be within the 1 standard deviation
variability of the observational climatology over the three stations.
However, in the upper troposphere, WRF-Chem overestimates
ozone mixing ratios over Delhi and Pune.
The mean biases of the WRF-Chem are estimated against average ozonesonde climatology in summer monsoon in the LT (850–650 hPa)
as calculated against CARIBIC observations in Sect. .
MB in the LT are found to be lower at Delhi (-2.2±3.8 nmolmol-1) and Pune (-1.2±3.6 nmolmol-1),
as compared to that over Thiruvananthapuram (-12.4±1.3 nmolmol-1). However, in the UT (e.g. at 150 hPa) ozone mixing ratios in WRF-Chem
simulations at Delhi (94.1±31.1 nmolmol-1) and Pune (69.4±23.5 nmolmol-1) are found
to be higher as compared to ozonesonde observations (61.1±34.0 and 31.3±17.5 nmolmol-1 respectively).
The overestimation in upper troposphere by WRF-Chem has been reported earlier with a slightly different model setup
(different convective parameterization ).
Comparison of average ozone mixing ratios during the summer monsoon (June–September) from Std and Std_INTEX WRF-Chem simulations
with the ozonesonde observational climatology during 2006–2009 period
over Delhi (DEL), Pune (PUN) and Thiruvananthapuram (TVM).
Comparison with MOPITT CO profiles
Figure shows the monthly average
CO profiles from simulation Std and the CO retrievals obtained from
MOPITT over Chennai. For consistency with the comparison with CARIBIC
observations (Sect. ), which are collected only
during nighttime, we restrict the comparison of WRF-Chem and MOPITT to
nighttime data, though we do not find large diel variability in free tropospheric CO in our simulations.
The averaging kernel and the a priori profiles of MOPITT data
have been applied on the monthly average CO profile from standard WRF-Chem simulation, denoted as Std(AK).
In contrast to the comparison with the in situ vertical profiles from CARIBIC,
the WRF-Chem simulated CO shows very good agreement with the
satellite data in the lower troposphere during June. The mean bias value between WRF-Chem and MOPITT is found to be
1.5±0.8 nmolmol-1 in the LT during June as compared to the WRF-Chem and CARIBIC
data comparison (-12.6±4.4 nmolmol-1).
Interestingly,
in comparison to the satellite data, WRF-Chem is found to overestimate CO in the LT by
21.4±2.8, 37.8±5.0, and 26.9±4.0 nmolmol-1 during July, August and September respectively. Middle
tropospheric CO is also significantly overestimated by WRF-Chem as compared to MOPITT during July–September. This
could be partially associated with the unscreened-out
cloud contamination in the satellite retrievals during the summer monsoon
season. The a priori CO data from the global chemistry transport model
could be another potential source of the discrepancy .
Comparison of monthly average
CO from WRF-Chem simulations (Std) with the MOPITT retrievals over
Chennai during the 4 months of the summer monsoon period of the year 2008.
The MOPITT averaging kernel and the a priori profile have been applied to the
WRF-Chem output, denoted by Std (AK). MOPITT a priori profile is also shown for comparison.
WRF-Chem profiles, after applying the satellite operator become very similar to the satellite a priori, especially in
the lower and middle troposphere. During this period, averaging kernels in the lower troposphere are found be smaller
(less than 0.1) as compared to the values reported for example during spring . This indicates
relatively lower sensitivity of MOPITT for lower tropospheric CO over this region during the summer monsoon.
The different results regarding the
WRF-Chem evaluation against the in situ measurements
and satellite data clearly
highlight the need of more in situ measurements of vertical profiles for
validation of chemistry-transport models as well as the satellite retrievals
over this region, particularly during the monsoon, when the sky is obscured by clouds. Such studies would be invaluable
for addressing the discrepancies due to limited overpassing time for MOPITT, retrieval errors due to sensor degradation,
not updated CO a priori, cloud-contamination, systematic errors as well as errors in model simulations.
Spatial distribution of monthly average
surface ozone and CO (nmolmol-1) from WRF-Chem simulations
(Std) during June, July, August and September
2008. The locations of two surface sites, Cape Rama (CR) and Gadanki (GAD), are also shown.
Comparison of WRF-Chem simulated
surface ozone and CO with the ground-based measurements at Gadanki
(79.2∘ E, 13.5∘ N; ) and Cape Rama
(73.8∘ E, 15.1∘ N). Open blue symbols for Gadanki show
observations from another study . Comparison with Std_INTEX simulation
is indicated in black.
Surface O3 and CO
In order to understand if the observed
discrepancies between WRF-Chem and CARIBIC observations are associated with
emissions and processes at the surface in India, we analyze the variations in
surface ozone and CO over this region. WRF-Chem (Std) simulated average
distributions of surface O3 and CO over the Indian region are shown
in Fig. for the 4 months of the summer monsoon in
2008. The distribution of O3 as well as CO shows large spatial
heterogeneity across the region in all 4 months.
Surface ozone levels are typically lower (<30 nmolmol-1) than aloft over most of the
domain. The ozone levels are found to be highest over the polluted
Indo-Gangetic Plain (IGP), in northeastern India, and also over the eastern coastal region (40–50 nmolmol-1).
Average
surface ozone levels over most of the Indian region are relatively low, mostly below
40 nmolmol-1, which is mainly due to the inflow of marine air masses and
suppressed photochemistry in cloudy and rainyconditions. The highest levels of
surface ozone are simulated over the northern part of the domain, where the influences
of marine air/monsoon are relatively smallest. While vertical trace gas distributions are affected by monsoon
convection, both CO and O3 are not soluble and not directly affected by precipitation scavenging.
Wet scavenging of O3 precursors and prevailing cloudy-rainy meteorological conditions, however, could suppress
the ozone production, particularly near the surface. CO mixing ratios vary from about
50 to 300 nmolmol-1, except over the IGP where a high CO
belt (400 nmolmol-1 and more) accumulates throughout the monsoon season. Towards the end of the
monsoon period in September, ozone and CO levels show most pronounced
enhancements over the IGP and also a tendency of pollution
buildup in the surrounding regions.
The WRF-Chem simulated spatial distributions of surface ozone and CO are
found to be consistent with previous studies over the Indian region mostly
based on satellite observations
, simulations with a global
chemistry transport model and a previous study evaluating WRF-Chem simulations over the
Indian region . WRF-Chem simulations were found to significantly overestimate surface O3
and underestimate CO at an urban site in the Indo-Gangetic Plain towards the onset of monsoon, while the model
was in better agreement during May .
Figure shows a comparison of surface ozone
and CO variations from WRF-Chem with ground-based observations.
Unfortunately simultaneous measurements of ozone and CO are
sparse over this region and therefore observations of ozone are utilized from
Gadanki (79.2∘ E, 13.5∘ N) , a rural site in southern India
and observations of
CO are used from the coastal site Cape Rama (73.8∘ E
15.1∘ N; ). O3 and CO
model results from the Std simulation
are found to be within the 1σ standard deviation of the
measurements at Gadanki and Cape Rama.
Comparison of monthly average horizontal distribution of CO in the upper troposphere
(116 to 211 hPa) over India from the Std simulation (top panel) and 1.5×_EM simulation (bottom panel)
during June, July, August and
September 2008.
Monthly average
vertical profile of CO over Chennai during June from
Std and 1.5×_EM simulations. The
resulting enhancement in CO is also indicated in percentages along the right axis.
The significant underestimation
of CO by WRF-Chem in the free troposphere
(Sect. ) as compared to CARIBIC measurements is
not evident at the surface. It is suggested that the discrepancies between WRF-Chem and CARIBIC
observations are likely not caused directly by surface emissions and chemistry
and may be associated with the influence of large-scale air mass transports. We
further investigate this by conducting a sensitivity simulation with
50 % higher CO emissions (Sect. )
over the Indian region. The possible role of transport is investigated by
backward air trajectory analysis and conducting a sensitivity run with
25 % higher influx of CO from the domain boundary based on
trajectories (Sect. ).
Sensitivity to regional emissions
A sensitivity simulation 1.5×_EM has been conducted
by enhancing the CO emissions over the entire south Asian domain
(Fig. ) by 50 %, keeping all other inputs
fixed as for the Standard WRF-Chem simulations (Std,
Table ).
Previous studies e.g. have shown that monsoonal convection
plays a key role in uplifting the boundary layer emissions
/ pollution into the Upper Troposphere and Lower Stratosphere (ULTS)
altitudes. To investigate this effect, we compare the monthly
average horizontal distribution of CO from Std and 1.5×_EM
simulations for upper tropospheric altitudes (average for 116–211 hPa; Fig. ).
The spatial distribution of CO in the upper troposphere shows highest levels in the northern and
central Indian regions in both of the simulations. The effects of the monsoonal circulation are clearly
visible through convectively uplifted CO from regional emissions, in particular from the
Indo-Gangetic Plain (IGP) towards the west. The sensitivity simulation shows significant influence
on the upper tropospheric CO distribution and increases the westward export of pollution.
For example, over the north-central Indian region the CO mixing ratios are found to be higher
by about 20 % in 1.5×_EM simulation as compared to Std simulation.
The comparison of monthly average CO
over Chennai between the standard simulation and
1.5×_EM is shown in
Fig. . The percentage enhancement in the CO
mixing ratios due to the increased emissions is also shown. The maximum impact
(33 %) of the increased anthropogenic emissions on CO mixing
ratios is observed near the surface. The direct impact of emission enhancement is
found to be significantly lower (5 % and less) from 850 hPa
and above, where WRF-Chem was found to most strongly underestimate the CO
levels.
Hence a significant increase (50 %) in the regional anthropogenic
emissions over India led to only minor enhancements in the model CO
levels as compared to the observed underestimation in the lower free
troposphere. Furthermore, the WRF-Chem simulated surface CO is in good agreement with ground-based observations over this
region. Therefore, it is concluded that the observed underestimation of
CO by WRF-Chem in the free troposphere is not primarily associated with local and regional
anthropogenic emissions. The next possibility of transport of CO into
the domain as controlled by the chemical boundary conditions in WRF-Chem is
investigated in the next subsection.
Influence of transport
We
investigate the role of transport over Chennai utilizing the 10-day backward
trajectories simulated using the HYSPLIT model in conjunction with
a sensitivity simulation with the MOZART/GEOS5 boundary condition. Air mass
trajectories color-coded according to the starting altitude over Chennai for
all the CARIBIC observation days are shown in Fig. .
Synoptic wind patterns appear to be very different in the lower troposphere
(2–4 km) compared to higher altitudes (8–12 km). Lower
tropospheric air over Chennai has been dominantly influenced by westerly air
masses, while the upper tropospheric air masses primarily originated from the
east during June–August. The wind patterns change significantly towards the
end of the monsoon period (September), when the trajectories are influenced by
different continental regions of South Asia.
To investigate the transport and influences from local and regional pollution,
we calculated the residence time of the air masses and mean pressure along the
trajectory over the southern Indian region
(74.9 to 81.7∘ E and 9.9 to 17.1∘ N) for all the backward air
trajectories at 2 and 4 km altitude above Chennai
(Fig. ). Residence time is derived by counting number of hours in the air trajectory within the specified
south Indian region and converting it into days. For all days the residence time in South India was about a day, except
for 15 July 2008 when the residence time was more than 3 days.
Strong pollution event on 15 July 2008
We begin by examining a pollution event observed on 15 July 2008 over Chennai to investigate its origin. Ozone and carbon monoxide levels were observed to be
very high during the month of July but are substantially underestimated by
WRF-Chem (Figs. and ). Since there were only two observational
profiles during July and both
on the same day (15 July 2008), this observation is suggested to be more
representative of a pollution event rather than the monthly average conditions
over this region. During this event, O3 (146.4±12.8 nmolmol-1) and CO
(136.4±12.2 nmolmol-1) mixing ratios are found to be very high in the
lower troposphere (∼805 hPa), indicating that these concentrations are
associated with the transport of polluted air with ample time for photochemical ozone build up,
while significant influence of
transport of ozone-rich air
from the stratosphere is unlikely.
It is found that the residence time
of this air mass is more than 3 days over southern India during this
event, much longer than during CARIBIC flight times in other months. Moreover, the air masses are found to be
influenced by boundary layer pollution as indicated by significantly higher
mean pressure along the trajectory (915±43 hPa). To investigate the underprediction of the event in the
model, we analyzed the wind fields over Chennai from radiosonde measurements. The model is found to generally reproduce
the variations in wind speed over Chennai at different altitude levels (e.g., in the range of 4–10 m s-1 at 980 hPa; Figs. S3, S4). However, the model does not capture the occurrences of low-wind speed (1–3 m s-1) and overestimates
systematically the wind speed during the July period. Therefore the air parcels could not possibly collect enough pollutants
from the boundary layer leading to the underprediction of the strong pollution event in model. Additionally,
no indication of underestimation of emissions is found as the model performance did not improve in reproducing the
event when emissions were increased by 50 %.
HYSPLIT simulated 10 days backward air
trajectories at 2, 4, 6, 8, 10 and 12 km a.s.l. over Chennai
for the CARIBIC measurement days. Different colors of trajectories correspond
to different starting altitude over Chennai for the trajectory
simulations.
Long-range transport
Long-range transport of pollution in regional models is controlled by the chemical boundary conditions,
generally provided from a global model. Previous studies investigated the impact and
uncertainties in long-range transport in regional model simulations. In WRF-Chem
simulations in this study the long-range transport is controlled by the time varying chemical boundary
conditions from a global model MOZART/GEOS5 simulations.
We assess
the contribution of long-range transport of CO in the lower troposphere
over Chennai by conducting a sensitivity simulation with increased CO at
the domain boundary. Backward air trajectories suggest that CO is
significantly underestimated in the lower troposphere in westerly air masses
(Figs. and ).
Therefore, we increase the CO mixing ratios by 25% in the MOZART/GEOS5 data,
over a region (7.5∘ N < lat <16.5∘ N) on the western boundary as
shown in Fig. , chosen suitably based on the backward
trajectories (Fig. ).
Residence time of air masses over the
southern Indian region on all CARIBIC measurement days calculated from the
back-trajectories at 2 and 4 km above Chennai. The mean
pressure along the trajectory over southern India is also shown.
Figure shows a comparison of average CO
profiles from CARIBIC measurements, WRF Chem standard simulations (Std) and the
sensitivity simulation with increased CO at the western boundary
(1.25×_BDY). In contrast to the sensitivity run
with increased emissions (1.5×_EM), here we
find significant improvement in the WRF-Chem simulated CO in the free
troposphere. For example during June, WRF-Chem simulated CO mixing
ratios from 1.25×_BDY simulation
(95.8±4.3 nmolmol-1) are comparable to the observations
(96.6±9.1 nmolmol-1) at ∼800 hPa. The improvements are also
significant in other months in the lower free troposphere.
In contrast to the June–August period, the air
masses over Chennai show influences of higher emissions on the free troposphere. This could be associated with the transport from the continental Indian
region as shown by backward trajectories (Fig. ). The enhancements due to higher CO in the boundary conditions are
significantly less during September as compared to June–August.
We suggest that since air masses over Chennai during September are more influenced by the regional emissions, the influence of uncertainty in
boundary conditions is not evident here. Further it is noted that such dominance of regional impacts on CO vertical distributions during
September is captured better by WRF-Chem, as compared to the global model simulation (Fig. S5).
Spatial distribution of CO at
810 hPa from MOZART GEOS5 boundary condition data on a typical day (18 June 2008 at 18:00 GMT).
The WRF-Chem simulation domain is shown as the dotted box.
The CO mixing ratios over part of the western boundary, shown by
the thick solid box, have been increased by 25 % in the simulation
1.25×_BDY.
This study suggests that anticyclonic advection plays a very important role
which could transport polluted air masses from outside the region (domain) during
the summer monsoon. This complements conventional thinking that convected regional
emissions dominate the tropospheric composition during the monsoon season and
points to a potentially significant external source of pollution to the monsoon
anticyclone. We show that this transport is generally very fast, i.e., the
residence time of air masses is 1–2 days over southern India, except during the strong
pollution event (Sect. ). This rapid transport
could advect CO-rich air masses from more strongly polluted upwind regions. As indicated
by the backward air trajectories and a sensitivity run, CO-rich air
masses could originate in central Africa and the Persian Gulf region.
During the summer monsoon, CO mixing ratios have been found to be
highest over central Africa associated with biomass burning emissions
and references therein.
A recent study utilizing the trajectory-mapping technique and aircraft observations also indicated elevated CO
mixing ratios over the western boundary of our model domain.
We suggest that improvements in the global fire emissions input to the global models and data assimilation would be helpful in better
constraining the effects of long-range transport during the monsoon. Regional emissions from continental India are shown
to significantly influence the free troposphere over southern India towards the end of the monsoon (September).
Sensitivity analysis of WRF-Chem
simulated CO profiles to the chemical boundary conditions. Standard
CO profiles are compared with the simulation driven by 25 %
higher CO at the western boundary of the
domain as shown in Fig. . Results from
50 % higher CO emissions over the whole domain
(1.5×_EM) are also shown for comparison. Numbers
in brackets denote the number of observational
profiles in the respective month.