Impacts of 2006 Indonesian fires on tropical upper tropospheric carbon monoxide and ozone

Introduction Conclusions References


Abstract
We investigate the relative impacts of biomass burning emissions and dynamics on tropical upper tropospheric carbon monoxide (CO) and ozone (O 3 ) over western and central Indonesia during the August-November 2006 fires in equatorial Asia by using a global three-dimensional model of tropospheric chemistry (GEOS-Chem) and by comparing model results with Microwave Limb Sounder (MLS) observations of upper tropospheric CO and O 3 .GEOS-Chem CO and O 3 reproduce MLS observed enhancements from convective lifting of fire emissions.In the tropical upper troposphere (UT), fire effluents from equatorial Asia are primarily transported southwestward to the eastern tropical Indian Ocean, driven by the high-pressure systems along 10 • N-15 • N and 10 • S-15 • S latitudes, and northeastward to southeast Asia and beyond, driven by the western North Pacific subtropical high.A characteristic feature of these CO enhancements is that they lag behind biomass burning emissions (by 2-3 weeks) at the three pressure levels from 215 hPa to 100 hPa, resulting form the decreasing influence of deep convective lifting with altitude in the UT.We estimate the fire influences by contrasting one model simulation with year-specific and another with climatological biomass burning emissions.Biomass burning accounts for about 50-150 ppbv of CO and 5-20 ppbv of O 3 in the tropical UT below 100 hPa during October and November, with temporal variations driven by biomass burning and deep convection.We estimate the dynamic impacts by examining the difference between a model simulation for 2006 (El Ni ño) and another for 2005 (neutral).The dynamic impacts are far more complex and account for up to 100 ppb of CO and 30 ppb of O 3 in the tropical UT below 100 hPa.
The temporal variation of the dynamic impact on CO is driven by deep convection.The variation of the dynamic impact on O 3 not only depends on deep convection but also reflects the non-linearity of O 3 chemistry.

Introduction
Smoke and excess tropospheric ozone from biomass burning have long been observed over the tropics (Thompson et al., 2001).In equatorial Asia, droughts during El Ni ño events are typically followed by large fires (van der Werf et al., 2008a).Previous modeling studies have shown that dynamic processes related to El Ni ño events and the shift in the large-scale Walker circulation also contributed to the observed enhancements in tropospheric O 3 columns over the equatorial Western Pacific during Indonesian fire seasons (Sudo and Takahashi, 2001;Chandra et al., 2002Chandra et al., , 2004;;Doherty et al., 2006).The fire emissions and the perturbed dynamics together result in variations in tropospheric composition (Chandra et al., 2002;Ziemke and Chandra, 2003).Doherty et al. (2006) showed that tropospheric ozone column over equatorial Asia and west Pacific was modulated by the El Ni ño-Southern Oscillation (ENSO).On the other hand, aerosols produced by these fires had strong influence on tropical atmospheric dynamics (Ott et al., 2010).There was a possible positive feedback in which the anthropogenic burning in Indonesia enhanced drought stress during El Ni ño (Tosca et al., 2010).These large fires significantly alter tropospheric composition including aerosol loading and tropospheric ozone and CO (Duncan et al., 2003a).Duncan et al. (2007) used the Global Modeling Initiative (GMI) chemical transport model (CTM) to estimate that these fires increased CO by more than 40 % in the tropical tropopause layer and by more than 10 % in the lower stratosphere for several months.Their results also demonstrated that the increased presence of CO from the Indonesian fires could reduce OH levels thereby increasing the atmospheric lifetimes and troposphere-to-stratosphere transport of trace gases.Chandra et al. (2002) studied the effects of forest fires in the Indonesian region during the 1997 El Ni ño and found that about half of the increase in tropospheric column ozone was due to biomass burning and the other half was due to dynamical effects.Logan et al. (2008) (Chandra et al., 2009).

The 2006 Indonesian fires
Climate strongly regulates fire emissions and deforestation in equatorial Asia (van der Werf et al., 2008a, b).Previous studies have shown that fire emissions in equatorial Asia show strong interannual variability and increase significantly during El Ni ño (Bowen et al., 2001;Heil and Goldammer, 2001;van der Werf et al., 2006).The extended dry season during El Ni ño periods enables more effective use of fires for land management purpose, which often leads to widespread fires (van der Werf et al., 2008b).Fires in Indonesia were intentionally set to clear out cropland and for industrial expansion during the dry season of El Ni ño.Some of these fires got out of control and led to extensive burning, for instance in 1997 (Duncan et al., 2003and references therein) and 2006(ver der Werf et al., 2008).During the 2006 moderate El Ni ño, large and widespread fires occurred in Indonesia, Malaysia, and northern Australia during the extended dry season (August through November) (van der Werf et al., 2008a, b).
Figure 1a shows the total CO emissions from August to November 2006 with largest emissions in southern Borneo, Sumatra, and northern Australia.The emission data are from the Global Fire Emissions Database (GFED v2) (van der Werf et al., 2006).
Much of our analysis focuses on western and central Indonesia (EQ-10 • S latitudes, 100-125 • E longitudes), referred to hereafter as the WCI domain (the blue rectangle in Fig. 1a).Figure 1b shows the monthly CO emissions for the WCI domain from emissions during the 2000 La Ni ña (van der Werf et al., 2008).The 2006 fires started in August and lasted through late November (Fig. 1c).Peak emissions of CO were seen in both early October and from late October to early November.There was a broad peak for much of August and early September.The CO emissions in October 2006 were several hundred times larger than the climatological values for this region.

MLS observations of upper tropospheric O and CO
The Microwave Limb Sounder (MLS) instrument (Waters et al., 2006) aboard the Aura spacecraft has been measuring atmospheric parameters since August 2004 (Schoeberl and Talabac, 2006).MLS uses microwave limb sounding to measure temperature and chemical constituents, including CO, water vapor, O 3 and cloud ice water content (IWC) in the UT (pressure ≤215 hPa) and stratosphere with a vertical resolution of ∼4.5 km and a horizontal resolution of ∼3 • along the orbit (Livesey et al., 2006).MLS chemical composition measurements in the UT are generally not degraded by the presence of clouds because the typical cloud particle sizes are much smaller than the wavelength of the radiation being observed.The CO, O 3 and cloud IWC observations used here are MLS retrieval version 3.3 (Livesey et al. 2011).The observations are averaged onto 2 • latitude ×5 • longitude grids for every five days.Our analysis focuses on the observations for pressure levels 100 hPa, 147 hPa, and 215 hPa.Previous (version 2) biases of MLS upper tropospheric CO at 215 hPa and partly at 146 hPa have been ameliorated in version 3.3 compared with previous versions (Livesey et al., 2011).
MLS cloud IWC was derived from the 240-GHz cloud-induced radiances at high tangent heights and is scientifically useful at 215-83 hPa (Wu et al. 2008).We include the IWC data in our analysis because it is a proxy for deep convection in the UT (Fu et al., 2006;Jiang et al., 2010;Jiang et al., 2011): larger IWC indicates stronger deep convection.In addition to MLS cloud IWC data, we also examined NOAA outgoing longwave radiation (OLR) interpolated from satellite observations (Liebmann and Smith, 1996).deep convection (Randel et al., 2006;Logan et al., 2008;Nassar et al., 2009).The OLR data are global, daily data with a horizontal resolution of 2.5 • ×2.5 • .We averaged the OLR data for every five days as we did for MLS data.The year 2005 was a neutral year from El Ni ño perspective.As in Chandra et al. (2007Chandra et al. ( , 2009) )  Figure 3 shows MLS CO concentrations (5-day averages) in the tropical UT at 215 hPa, 147 hPa, and 100 hPa for 2005 and 2006.Again, we included 2005 here for comparison because it was a neutral year and the fire emissions over the Indonesia domain were considerably smaller than those from 2006 (Fig. 1b).Strongly enhanced CO concentrations are clearly evident from August to November 2006 at all three pressure levels with maximum CO concentrations exceeding 150 ppb at 215 hPa and 147 hPa and 110 ppb at 100 hPa.At 147 hPa and 215 hPa, the year-over-year enhancements during October-November are more than 70 % from 2005 to 2006.The enhancements are widespread between 20 • S and 10 • N latitudes.Some noticeable time lags are seen in the CO enhancements among the pressure levels -the enhancements at 100 hPa lag those at 147 hPa and the latter lag behind those at 215 hPa.These time lags likely reflect the gradual upward propagation (via advection) of the convectively lofted surface biomass burning emissions (Liu et al., 2010).Correspondingly, the CO concentrations from the Tropospheric Emission Spectrometer (TES) retrievals also showed a very strong maximum over Indonesia and the Indian Ocean with peak concentrations exceeding 200 ppb in October and November in the lower troposphere (825-511 hPa) (Logan et al., 2008;Nassar et al., 2009).In addition, both very high CO concentrations Figures

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Full in the middle to UT (400-200 hPa) observed by the Atmospheric Chemistry Fourier Transform Spectrometer (ACE-FTS) (Rinsland et al., 2008) and high CO columns by the Measurement Of Pollution In The Troposphere (MOPITT) instrument (Yurganov et al., 2008) were also seen over the same broad region during the 2006 Indonesian fires.These observations clearly showed that the biomass burning emissions from the large fires of 2006 over Indonesia significantly enhanced the CO concentrations in the middle to UT over that region.The biomass burning emissions from northern Australia (Fig. 1a) likely also contributed to these enhancements.We will address the Australia fire contribution in subsequent sections.NO x -hydrocarbon chemistry coupled with aerosol chemistry (Bey et al., 2001).Gas phase chemical reaction rates and photolysis cross sections are taken from Sander et al. (2000).Photolysis frequencies are computed using the Fast-J algorithm (Wild et al., 2000).
Tracer advection is computed every 15 min with a flux-form semi-Lagrangian method (Lin and Rood, 1996).Tracer moist convection is computed using the GEOS convective, entrainment, and detrainment mass fluxes as described by Allen et al. (1996a, b).
The deep convection scheme of GEOS-4 is based on Zhang and McFarlane (1995), and the shallow convection treatment follows Hack (1994).GEOS-5 convection is parameterized using the relaxed Arakawa-Schubert scheme (Moorthi and Suarez, 1992).
222 Rn is commonly used as a tracer for diagnosing convection in chemical transport model (Jacob and Prather, 1990;Considine et al., 2005).Figure 5 compares the annual zonal mean distributions of 222 Rn for 2004 simulated by GEOS-Chem driven by GEOS-4 and GEOS-5, respectively.The tropical upper tropospheric 222 Rn concentrations are much higher in the model results from the simulation driven by GEOS-4 meteorological data than those from the simulation driven by GEOS-5 data.These differences indicate that the deep convection in the tropics, especially in the northern tropics, is significantly deeper in GEOS-4 than in GEOS-5 (Liu et al., 2010).GEOS-Chem simulations of the tropical upper tropospheric CO and O 3 will undoubtedly bear these differences, as discussed in subsequent sections.
The fossil fuel emissions are from the Emission Database for Global Atmospheric Research (EDGAR) inventory for NO x , CO, and SO 2 (Olivier et al., 2001) and from the Global Emission Inventory Activity (GEIA) for other chemical compounds (Benkovitz et al., 1996) with additional updates as described by Hudman et al. (2007).Asian anthropogenic emissions are updated with the estimates from Zhang et al. (2009).
Biofuel emissions are from Yevich and Logan (2003).The biogenic VOCs emissions are based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) inventory (Guenther et al., 2006) of flash rates (Hudman et al., 2007;Sauvage et al., 2007).Biomass burning emissions are from the Global Fire Emission Database version 2 (GFEDv2) that resolves the interannual variability of biomass burning emissions (van der Werf et al., 2006;Randerson et al., 2006).GFEDv2 was derived using satellite observations including active fire counts and burned areas in conjunction with a biogeochemical model.Carbon emissions were calculated as the product of burned area, fuel loads and combustion completeness.Burned area was derived using active fire and 500-m burned area datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS) as described by Giglio et al. (2006).The original GFEDv2 inventory has a spatial resolution of 1 • (latitude) ×1 • (longitude) and a monthly temporal resolution.The emissions were re-sampled to 2 • (latitude) ×2.5 • (longitude) grids for use in our GEOS-Chem simulations.Forest fires typically last from several days to weeks as seen in MODIS active fires (Giglio et al., 2003).Therefore, the monthly GFEDv2 emissions were re-sampled to an 8-day time step according to MODIS 8-day active fire counts (Chen et al., 2009).The 8-day GFEDv2 emissions were used for the model simulations presented here unless stated otherwise.Additionally, a climatological monthly mean biomass burning emission inventory from Duncan et al. (2003a) is also included in the model and were used in two simulations.
We conducted several model simulations for 2006 and 2005 driven by either GEOS-4 or GEOS-5 meteorological data.Either 8-day GFEDv2 or climatological biomass burning emissions were used in these simulations.Justifications for these simulations are provided where appropriate.The details for these experiments are summarized in Table 1.For direct comparison with MLS observations, we extracted model results at the time and location of the observations and applied the same 5-day averaging as we did for the observations (see Sect. 2).
Our standard simulation (experiment A) is driven by GEOS-4 meteorological data and with 8-day GFEDv2 emissions for 2006.Figure 6  are averages between 100 • E and 125 • E longitudes.GEOS-Chem CO reproduces the seasonal cycles seen in MLS data at all three pressure levels: broad enhancements in spring (March), relatively low concentrations in summer (June-July), and large extensive enhancements in October-November.In addition, model CO also captures the time lags in the October-November enhancements among the three pressure levels: the enhancements extend to well in December at 147 hPa and 100 hPa.Model CO concentrations are generally lower than MLS data at all three pressure levels with largest differences of more than 50 ppbv at 100 hPa during the peak fire season in October and November.Part of these discrepancies is due to the weak convection in the model hence insufficient convective lofting of surface biomass burning emissions to the tropical UT over equatorial Asia.Nassar et al. (2009) compared GEOS-4 OLR with NOAA interpolated OLR for October and November 2006 and concluded that GEOS-4 convection was too weak over equatorial Asia in Java, Borneo, and New Guinea.Additionally, part of the discrepancies is explained by the positive biases in MLS CO at these pressure levels despite significant bias reductions in MLS v3.3 data (Livesey et al., 2006(Livesey et al., , 2011)).Previous studies have shown that outflow of CO from East Asia were transported in the UT to tropical South and Southeast Asia (Liu et al., 2003;Li et al., 2005).The lower concentrations simulated by the model at the northern edge of the domain thus likely reflect in part the insufficient transport of CO from East (and Southeast) Asia in the model.North Pacific subtropical high, both in the observations and in the model, is also evident.We find similar CO outflow patterns at 147 hPa (not shown).
Figure 8 shows GEOS-Chem simulated and MLS observed O 3 at 215 hPa and 147 hPa for 2006.Values are averages over the 100-125 • E longitudes.At 215 hPa, the highest O 3 levels during October-December are seen over the southern tropics extending from the equator to 20 It is conceivable that biomass burning emissions in northern Australia during October and November 2006 (Fig. 1a) may contribute to the upper tropospheric CO over equatorial Asia.Luo et al. (2009) examined satellite observations of CO during December 11-19, 2006 from MLS and the Tropospheric Emission Spectrometer (TES) (Beer et al., 2006) downwind of the Australian fires.They found significant amount of northern Australia biomass burning emissions lifted to the middle and UT.To quantify the influence of northern Australia fire emissions on tropical upper tropospheric CO and O 3 , we conducted a GEOS-Chem sensitivity simulation where biomass burning emissions in Australia ( 110• -179 • E, 11 • -50 • S) were shut off.The differences with the standard simulation (experiment A) thus represent the impact of Australia biomass burning emissions for October and November 2006.The results show that northern Australia biomass burning has rather small influences on the tropical upper tropospheric CO (less than 10 ppbv or 6 % of the total CO) and O 3 (less than 4 ppbv or 4 % of the total O 3 ).Introduction

Conclusions References
Tables Figures

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Full Figure 9 show MLS observed and model simulated CO at 100 hPa, 147 hPa, and 215 hPa and O 3 at 147 hPa and 215 hPa over the WCI domain from July to December 2006.Also shown are MLS cloud IWC at 215 hPa and GFEDv2 CO emissions.The maximum MLS CO concentrations are seen in late October with more than 300 ppbv at 215 hPa, 250 ppbv at 147 hPa, and 120 ppbv at 100 hPa.The second peaks are seen in early November at 215 hPa and 147 hPa.It is more than twice increase compared with the background CO concentrations (Fig. 9a).The MLS CO concentrations started to increase in the early October at 215 hPa and 147 hPa, about 2-3 weeks after the onset of the biomass burning.The cloud IWC increased at the same time as the enhancements of MLS CO.The increased convection might possibly contribute to the increase of CO concentrations after the large biomass burning.Both the MLS CO concentration and biomass burning emissions showed two peaks with the same time lag.The largest CO enhancement is therefore a combined effect of both relative stronger convection and large biomass burning emission from Indonesian fires.GEOS-Chem CO shows an extended maximum of CO concentrations (up to 300 ppbv) at 215 hPa from October to November, in broad agreement with the MLS observations (Fig. 9b).Model CO at 147 hPa shows elevated concentrations (∼150 ppbv) during the second half of October.The peak concentrations at 147 hPa are much lower in the model results than in the observations.Part of the difference is again attributable to the weak deep convection in GEOS-4 during October and November 2006.The observed November enhancements at 147 hPa are entirely absent in the model results.
The MLS O 3 concentrations also show similar double peaks at 147 hPa and, to a lesser extent, 215 hPa in October and November 2006, respectively (Fig. 9c).GEOS-Chem O 3 shows enhanced concentrations at both 215 hPa and 147 hPa in September and October 2006 (Fig. 9d).The simulated concentrations are much lower than the observations.Introduction

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Full The distribution of UT pollutants, such as O 3 and CO, can be influenced both by surface emission sources and by dynamical factors, such as convection and horizontal winds (e.g.Jiang et al., 2007).Chandra et al. (2007Chandra et al. ( , 2009) )  Experiments A1 and A share the same configuration except for the aforementioned different biomass burning emission inventories used.The differences between the results from these two simulations, presented in Fig. 10 for the WCI domain, thus show the impact of enhanced biomass burning emissions.We then conducted a simulation driven by GEOS-4 meteorological data for 2005 (experiment A2) with otherwise the same configuration as the standard simulation.The differences between these two experiment results, shown in Fig. 11 for the WCI domain, therefore reflect the differences in the dynamics between the 2006 El Ni ño and 2005, a neutral year from an El Ni ño perspective.We discuss these differences as shown in Figs. 10 and 11 in more detail later in this section.
It is conceivable that the deep convection parameterizations used in the GEOS reanalysis system and the GEOS-Chem model strongly influence the abovementioned impacts.To examine this sensitivity, we conducted three GEOS-Chem simulations driven by GEOS-5 meteorological data (experiments B, B1, and B2), which differs significantly from GEOS-4 data in the deep convection scheme used (Sect.4).Other than Introduction

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Full temporal variations of the deep convection in GEOS-4 and GEOS-5 (Fig. 12).At 147 hPa, the biomass burning emissions contribute about 40-70 ppbv to the CO enhancements during middle to late October 2006 (Fig. 10a).The biomass burning influences for October 2006 are comparable between the two model simulations.The differences are in November when results from the simulation driven by GEOS-4 meteorological data decrease sharply through November while results from the simulation driven by GEOS-5 meteorological data show another maxima of 40-60 ppb of CO.Again, these differences are because of the different temporal variations of deep convection during October and November 2006 in GEOS-4 and GEOS-5 (Fig. 12).The dynamic impacts at 147 hPa (Fig. 10b) are comparable to the corresponding impact at 147 hPa from the biomass burning emissions.The temporal variations of the biomass burning and the dynamic impacts track closely those at 215 hPa.
Deep convection rarely penetrates the tropical tropopause region (Alcala and Dessler, 2002;Gettelman et al., 2002).As such, both the biomass burning and the dynamic impacts are relatively small (about 15 ppb of CO) at 100 hPa.The biomass burning impacts show notable time lags among the three pressure levels while the dynamic impacts show no obvious time lags.The larger differences of biomass burning impacts between 215 hPa and 147 hPa in GEOS-4 (∼100 ppbv CO) than in GEOS-5 (∼60 ppbv CO) again reflects the different strengths of deep convection in the respective reanalysis data sets (Figs. 5,12).
Previous studies showed that during El Ni ño, both the biomass burning and the changes in meteorological conditions including low convective activity, sparse precipitation, dry air condition, and large-scale dynamical changes contributed to the observed enhancements in tropospheric ozone columns over equatorial Asia (Sudo and Takahashi, 2001;Chandra et al., 2002;Chandra et al., 2009).Our model results show significantly enhanced O 3 concentrations at both 215 hPa and 147 hPa because of the biomass burning emissions (Fig. 11a).For the same reason provided in previous sections, we do not include the model results at 100 hPa in the discussion here.The biomass burning emissions contribute about 5-20 ppbv (GEOS-4) and 10-15 ppbv Introduction

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Full  Full Discussion Paper | Discussion Paper | Discussion Paper | examined observations from the Tropospheric Emissions Spectrometer (TES) to study the influences of the 2004 and Discussion Paper | Discussion Paper | Discussion Paper | . Many previous studies of the Indonesian fires, including the ones in 2006, have focused largely on the lower and middle tropospheric CO, O 3 and aerosols and on tropospheric ozone columns.In this study, we analyze Microwave Limb Sounder (MLS) measurements of CO and O 3 to investigate the impact of the 2006 Indonesian fires on the tropical upper tropospheric CO and O 3 over equatorial Asia.Our approach is to apply a global three-dimensional chemical transport model to interpret the MLS observations.We intend to delineate the relative importance of the fire emissions and the dynamics in influencing the tropical UT CO and O 3 over equatorial Asia.We give a Discussion Paper | Discussion Paper | Discussion Paper | brief description of the 2006 Indonesian fires during August-November 2006 in Sect. 2. Section 3 presents MLS observations of upper tropospheric CO, O 3 and cloud ice water content (IWC).Model simulations of tropical UT CO and O 3 during the fires are discussed in Sect. 4. The relative impacts of biomass burning and dynamics on the UT CO and O 3 are examined in Sect. 5. A summary and conclusions are presented in Sect.6.
1997 to 2008.Large emissions occurred during the 1997, 2002, 2004, and 2006 El Ni ño.Emissions from Borneo during the 2006 were more than 30 times higher than Discussion Paper | Discussion Paper | Discussion Paper | OLR is a widely used proxy for deep convection with lower values indicating stronger Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Figure 4
shows the time-latitude cross-sections of MLS O 3 (5-day averages) at 215 hPa, 147 hPa, and 100 hPa for 2005 and 2006.Significant enhancements in O 3 are clearly seen at 147 hPa and to a lesser degree at 215 hPa in October and November 2006 relative to 2005.Ozone enhancements at 100 hPa due to the Indonesian fires, if any, are difficult to quantify because of the already high background O 3 concentrations near the tropical tropopause.The enhancements at 215 hPa are mainly confined to south of the equator with increases of 15-20 ppb during October and November 2006 relative to 2005.It is probable that these enhancements were influenced by the emissions from the 2006 Indonesian fires.We will address that in the following sections.4GEOS-Chem model description and simulationsGEOS-Chem is a global three-dimensional chemical transport model(Bey et al., 2001) driven by assimilated meteorological observations from the Goddard Earth Observing System (GEOS) of the NASA Global Modeling and Assimilation Office (GMAO).We use GEOS-Chem version 8-01-04 (http://acmg.seas.harvard.edu/geos/)driven by GEOS-4 and GEOS-5 meteorological fields with 6-h temporal resolution (3-h for surface variables and mixing depths), 2 • (latitude) × 2.5 • (longitude) horizontal resolution, and 30 (GEOS-4) or 47 vertical layers between the surface and 0.01 hPa.The GEOS-Chem model includes a detailed description of tropospheric O 3 Discussion Paper | Discussion Paper | Discussion Paper | . The lightning NO x emissions are parameterized based on cloud top height and regionally scaled to climatological satellite observations Introduction Discussion Paper | Discussion Paper | Discussion Paper | compares model simulated and MLS retrieved CO concentrations at 100 hPa, 147 hPa, and 215 hPa for 2006 over equatorial Asia and northern Australia between 20 • S and 20 • N. The values shown Introduction Discussion Paper | Discussion Paper | Discussion Paper |

Figure 7
Figure 7 shows the model simulated and MLS observed spatial distributions of monthly averaged CO concentrations at 215 hPa in October and November 2006.Also shown are streamlines from the NCEP/NCAR reanalysis data.Significant enhancements of CO concentrations are seen over equatorial Asia in both the model results and the observations.The spatial extents of the enhancements are larger in the observations than in the model results, especially in November.Sandwiched by the highpressure systems along 10 • N-15 • N and 10 • S-15 • S latitudes, the outflow of biomass burning CO in both months is mainly to the Eastern tropical Indian Ocean in both hemispheres.Northeastward outflow to Southeast Asia under the influence of the western Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 5 Impact of biomass burning and dynamics on upper tropospheric O 3 and CO Discussion Paper | Discussion Paper | Discussion Paper |the GEOS-5 meteorological data used, experiments B, B1, and B2 mirror experiments A, A1, and A2, respectively.We can then examine the impacts of the 2006 Indonesian biomass burning emissions and dynamics with experiments B, B1, and B2 exactly as we do with experiments A, A1, and A2.The results are also shown in Figs.10 and 11.At 215 hPa, the biomass burning emissions contribute about 60-120 ppbv (GEOS-5) to 80-180 ppbv (GEOS-4), depending on the meteorological data used to drive the model simulations, to the CO enhancements during much of October and November 2006 (Fig.10a).The CO enhancements show secondary peaks during early to middle September.The model results thus show a persistent biomass burning impact on the upper tropospheric CO concentrations during the 2006 Indonesian fire season.The stronger deep convection in GEOS-4 than in GEOS-5 largely explains the dependence of the model results on the meteorological data used.Figure12compares the convective precipitation and cloud top height, both proxies for deep convection, from GEOS-4 and from GEOS-5 during July-December 2006 averaged over the WCI domain.The convective precipitation is consistently larger and the cloud top is higher in GOES-4 than in GEOS-5 through much of the period.The temporal variation of convective precipitation is also markedly different between GEOS-4 and GEOS-5.The influences from dynamics are more complex.The corresponding influences at 215 hPa from dynamics (Fig.10b) amount to about 30-50 ppbv (GEOS-5) to 70-120 ppbv of the CO enhancements during much of October 2006.In comparison, the biomass burning influences at 215 hPa are not only larger but also more extensive throughout October and November 2006.Results from the simulation driven by GEOS-4 meteorological data show sharp decreases hence relatively small influence (less than 10 ppb CO) from dynamics during November 2006.In contrast, results from the simulation driven by GEOS-5 meteorological data show decreases of up to 40 ppb CO during late October and early November 2006 and CO enhancements of about 50 ppb during middle November 2006.Clearly both the magnitudes and the temporal variations of the biomass burning and the dynamic impacts differ between the two model simulations.These differences are mostly because of the differing strengths and Introduction Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |(GEOS-5) to the O 3 enhancements in the tropical UT during October and November 2006.The enhancements are larger by about 10 ppb at 215 hPa than those at 147 hPa in the model results driven by GEOS-4 meteorological data but comparable in the model results driven by GEOS-5 meteorological data.These differences reflect the different strengths of deep convection in GEOS-4 and GEOS-5 data.The dynamic impacts on O 3 are complex with O 3 enhancements up to 20-30 ppbv at both 215 hPa and 147 hPa (Fig.11b).The enhancements at 215 hPa and 147 hPa show similar temporal variations.The dynamic impacts on O 3 show large and frequent fluctuation, which reflects the non-linearity of both the dynamics and the O 3 chemistry.LightningNO x emissions strongly control tropical upper tropospheric O 3 production(Sauvage et al., 2007; and references therein).Logan et al. (2008) suggested that lightning NO x was a major contributing factor to the positive anomaly in the tropospheric column ozone observed over equatorial Asia by TES during December 2006.Nassar et al. (2009) in a modeling study using GEOS-Chem, showed that lightning NO x emissions contributed about 5-15 ppb to tropical tropospheric O 3 concentrations over equatorial Asia based on the differences in lightning NO x between 2005 and 2006 (2006 minus 2005), with the largest contribution in the UT.Lightning and the associated NO x emissions in the GEOS-Chem model version used here are related to deep convective cloud top height (Sect.4).Therefore, a large part of the dynamic impact on O 3 shown in Fig. 11b is due to the different lightning activities between 2005 and 2006 as predicted in the model.6 Summary and conclusions Observations from the Microwave Limb Sounder (MLS) showed significantly enhanced CO and O 3 levels were observed in the tropical upper troposphere over equatorial Asia during the 2006 Indonesian fires from August to November.We investigated the effect of these fire emissions and dynamics on the tropical upper tropospheric CO and O 3 by interpreting MLS observations using the GEOS-Chem model.The model Discussion Paper | Discussion Paper | Discussion Paper | captured the seasonal variations and special distributions of CO and O 3 in the tropical upper tropopshere over equatorial Asia.The biomass burning outflow as indicated by CO were primarily driven by tropical easterlies to the Indian Ocean and the western North Pacific subtropical high to the Southeast Asia.GEOS-Chem CO reproduced the distinct time lags between MLS observed CO enhancements at 215, 147, and 100 hPa, reflecting in part the decreasing influence of deep convective lifting with altitude in the tropical upper troposphere.In addition, a time lag of about two weeks between the surface fire emissions and the CO enhancements in the upper troposphere was seen both in the MLS observations and in the model results..These CO enhancements corresponded with increased cloud ice water content.The CO and O 3 enhancements in the tropical upper troposphere over equatorial Asia reflected the combined effect of large surface biomass burning emissions from the 2006 Indonesian fires and the dynamic effect during the 2006 El Ni ño.Biomass burning accounted for about 50-150 ppbv of CO and 5-20 ppbv of O 3 in the tropical upper troposphere below 100 hPa during October and November 2006, with temporal variations driven by biomass burning and deep convection.The dynamic impacts were complex and accounted for up to 100 ppb of CO and 30 ppb of O 3 in the tropical upper troposphere below 100 hPa.The temporal variation of the dynamic impact on CO was driven by deep convection.The variation of the dynamic impact on O 3 depended both on deep convection and the non-linearity of O 3 chemistry.Discussion Paper | Discussion Paper | Discussion Paper |

Fig. 7 .
Fig. 7. MLS observed (top panels) and GEOS-Chem simulated (bottom panels) CO concentrations at 215 hPa in October (left panels) and November (right panels) 2006.Also shown are streamlines from NCEP reanalysis data.

Fig. 10 .
Fig. 10.Simulated upper tropospheric CO concentrations at 100 hPa, 147 hPa, and 215 hPa determined as the differences between two GEOS-Chem simulations: (a) both for 2006, but one with GFEDv2 biomass burning emissions for 2006 and the other with climatological biomass burning emissions and (b) one for 2006 and the other for 2005 and both with 8-day GFEDv2 biomass burning emissions for 2006.Results from GEOS-Chem simulations driven by GEOS-4 and GEOS-5 meteorological data are both shown.Values are averages over the Indonesia domain (see Fig. 1).

Fig. 11 .Fig. 12 .
Fig. 11 Chandra et al. (2009)on tropical tropospheric profiles of CO, O 3 and water vapor.Their results showed that 511 hPa CO and O 3 mixing ratios were on average 80 ppbv and 15-30 ppbv larger in October and November of 2006 than in the corresponding months of 2005 over the Indonesian region.In the region of highest CO (200 ppb), the contribution of the fires to enhanced O 3 was 45 % in October, 75 % in early November, and 10 % in December.Dynamical changes increase O 3 over a larger region than fire emissions which mainly increase O 3 at 10 • N-10 • S in October and November.Ziemke et al. (2009)used satellite observations and the GMI model to estimate that fire emissions led to increases of tropospheric ozone mixing ratios in the Indonesian region by 15-25 % during the 2006 Indonesian fires.Chandra et al. (2009)used the GMI model to separate the dynamical impact of the 2006 El Ni ño from changes in fire emissions.They found that emissions and dynamical changes contributed almost equally to observed ozone increases over Indonesia in October and November, though changes because of emissions were centered in the Indonesian region while dynamical changes were over the Indian and western Pacific Oceans.The global burden of CO increased by 8-12 % from October through December as a result of the 2006 fires • S in both the observations and the model results.The observed high O 3 concentrations in May are less obvious in the model results.These high O 3 concentrations in May appear to be a recurring feature and are related to lightning NO x emissions (Zhang et al., Lightning impact on tropical upper tropospheric ozone over tropical southern Indian Ocean, manuscript in preparation).The observations show high O 3 concentrations at 147 hPa during late October-November while the model results show correspondingly considerably lower values.The 100 hPa pressure level is either at or close to the tropical tropopause where the already high O 3 concentrations make it challenging to detect O 3 enhancements, if any, due to convectively lifted biomass burning emissions.
Duncan et al. (2003a)biomass burning and meteorological changes contributed almost equally to the observed increases in tropospheric column O 3 over Indonesia during the dry seasons of the 1997 and the 2006 El Ni ño.We investigate here the relative influence of the 2006 Indonesian biomass burning and dynamics on the tropical upper tropospheric CO and O 3 over equatorial Asia.For this purpose we conducted two GEOS-Chem sensitivity simulations as summarized in Table1.We first conducted a model simulation driven by GEOS-4 meteorological data for 2006 (experiment A1) where a monthly mean climatological biomass burning emissions fromDuncan et al. (2003a)were used in lieu of the 8-day GFEDv2 inventory for 2006 as used in experiment A, the standard simulation.

Table 1 .
Description of model experiments.