Observed Vertical Distribution of Tropospheric Ozone. During the Asian Summertime Monsoon

Transcription

1 1 2 3 Observed Vertical Distribution of Tropospheric Ozone During the Asian Summertime Monsoon John Worden 1, Dylan B. A. Jones 2, Jane Liu 2, Kevin Bowman 1, Reinhard Beer 1, Jonathan Jiang 1, Valérie Thouret 3, Susan Kulawik 1, Jui-Lin F. Li 1, Sunita Verma 1, and Helen Worden Jet Propulsion Laboratory / California Institute of Technology Department of Physics University of Toronto, Toronto, ON, Canada Laboratoire d'aérologie, UMR 5560, CNRS, Université de Toulouse, 14 Avenue Edouard Belin, Toulouse, France National Center for Atmospheric Research 1

2 Abstract We present new satellite measurements of vertically resolved tropospheric ozone profiles from the Aura Tropospheric Emission Spectrometer (TES) and Microwave Limb Sounder (MLS) instruments over the region affected by deep convection and summertime upper tropospheric anticyclones associated with the Asian Monsoon. The TES observations show that ozone enhancements of up to 100 ppbv or more occur in the upper and middle troposphere between 300 hpa and 450 hpa. Lower ozone values of 70 ppb or less are generally observed by both TES and MLS at 215 hpa but MLS also shows relative ozone enhancements of 100 ppbv or more at the tropopause that TES cannot resolve due to limited sensitivity to ozone at the tropopause. Over India the enhanced tropospheric ozone layer is at approximately 300 hpa whereas this layer drops to approximately 450 hpa over the Middle East. Enhanced ozone values are observed in June and July, corresponding to the onset of the Asian summertime monsoon, and begin to dissipate in August. Over Central Asia and the Tibetan Plateau, we observe significantly enhanced ozone of 150 ppbv or more at pressures greater than 300 hpa; these high ozone amounts suggest a stratospheric source consistent with previous modeling and analysis of surface ozone on the Tibetan Plateau Introduction 2

3 The summertime Asian Monsoon significantly affects the climate over North Africa, the Middle East and Central Asia [Hoskins and Rodwell, 1995; Rodwell and Hoskins, 1996; 2001]. However, only recently have observations begun to provide understanding on how the Asian Monsoon affects the chemical composition of the troposphere. For example, space based observations from Measurements of Pollution in the Troposphere (MOPITT) [Kar, et al., 2004], the Microwave Limb Sounder (MLS) [Jiang, et al., 2007; Park, et al., 2007], the Atmospheric Composition Experiment (ACE) [Park, et al., 2008], and the Atmospheric Infrared Sounder (AIRS) [Randel and Park, 2006] have shown how deep convection associated with the Asian monsoon lofts boundary layer air with low ozone and high water as well as surface emissions such as CO from Asia into the upper troposphere and lower stratosphere [Fu, et al., 2006; Gettelman, et al., 2004]. These surface emissions and boundary layer air can then be trapped and transported in the upper tropospheric anti-cyclone that forms during the summer time in this region [Barret, et al., 2008; Dunkerton, 1995; Hoskins and Rodwell, 1995; Park, et al., 2008; Park, et al., 2007; Randel and Park, 2006, Kunhikrishnan et al., 2006]. Understanding the effects of the Asian summertime monsoon on the distribution of tropospheric ozone must also include the vertical and horizontal distribution of lightning produced NOx, and the subsequent photochemical production [Li, et al., 2001] as well as stratospheric / tropospheric exchange [Gettelman, et al., 2004] and long range transport of pollutants from Europe and Asia [Duncan, et al., 2008; Li, et al., 2001]. Based on modeling simulations using the GEOS-CHEM model, it was suggested by Li et 3

4 al. [2001] that enhanced summertime ozone (greater then 80 ppbv) should be observed in the middle troposphere over Africa the Middle East and Central Asia with peak values over the Middle East. This prominent feature in the GEOS-CHEM model was shown by Li et al. [2001] to be dynamically driven by the anticyclones which forms in response to the Asian Monsoon; the anti cyclone traps ozone and ozone-precursors that are transported from Asia and Europe. Observations using solar occultation as discussed in [Kar, et al., 2002] does suggest the existence of peak ozone amounts at 7 km over North East Africa and North West Saudi Arabia relative to the rest of the globe; however, observations of total tropospheric ozone from the Ozone Monitoring Instrument (OMI) and the Global Ozone Monitoring Instrument (GOME) show that tropospheric ozone columns are enhanced between the latitudes of 25 and 35 degrees and particularly over Northwest Saudi Arabia [Liu et al., 2006]. However ozone abundances as observed by GOME are not enhanced in the Eastern hemisphere relative to the Western hemisphere [Liu et al., 2006]. Both the model predictions as well as the satellite observations of total tropospheric ozone and upper tropospheric ozone, suggests that the vertical and horizontal distribution of ozone varies strongly in response to the dynamics of the Asian Monsoon and the horizontal and vertical distribution of ozone precursors in this region. Understanding the distribution of the middle and upper tropospheric ozone from these chemical and dynamical processes has both climate and air quality implications. For example, upper tropospheric ozone is a greenhouse gas that affects global outgoing longwave radiation [Worden, et al., 2008]. Furthermore, the collected ozone can act as a pollution reservoir if it is transported to the boundary layer [Fiore, et al., 2002]. 4

5 In this paper we present three years of TES vertical profile observations of tropospheric ozone, taken during the summers of 2005, 2006 and 2007 that show the temporal, horizontal, and vertical distribution of tropospheric ozone over the region extending from North East Africa through Asia. The vertical distributions are compared with MLS observations of the upper troposphere for pressures below 200 hpa, and aircraft ozone measurements for pressures above 200 hpa from the Measurements of OZone and water vapour by in-service AIrbus aircraft (MOZAIC) program over Delhi, Teheran, and Dubai [Marenco, et al., 1998] ( Characterizing the spatial and temporal variability of this feature is a critical first step towards understanding how the dynamics controls this ozone and identifying the corresponding sources of ozone-precursors. A subsequent study by J. Liu et al. [2008] will conduct a detailed model analysis to better understand the transport and chemical processes responsible for observed ozone enhancements across North Africa, the Middle East. Verma et al; [In Preperation] will focus on the formation of ozone over South and East Asia Satellite Ozone observations Overview of TES instrument and sampling TES is an infrared, high resolution, Fourier Transform spectrometer covering the spectral range between 650 to 3050 cm -1 (3.3 to 15.4 µm) with an apodized spectral resolution of 0.1 cm -1 for the nadir viewing [Beer, et al., 2001]. Spectral radiances measured by TES are used to infer the atmospheric profiles through a non-linear optimal 5

6 estimation algorithm that minimizes the difference between these radiances and those calculated with the equation of radiative transfer subject to the constraint that the parameters are consistent with a statistical a priori description of the atmosphere [Bowman, et al., 2006; Rodgers, 2000]. TES provides a global view of tropospheric trace gas profiles including ozone, water vapor, and carbon monoxide along with atmospheric temperature, surface temperature and emissivity, and an estimate of effective cloud top pressure and an effective optical depth [Kulawik, et al., 2006; Worden, et al., 2004]. For cloud free conditions, the vertical resolution of TES ozone profile observations are typically 6 km in the tropics and mid-latitude summers [Jourdain, et al., 2007; Worden, et al., 2004]. TES observations have been validated against ozone-sondes and lidar measurements and it is generally found that upper tropospheric values are systematically biased high by about 15% after accounting for the TES vertical resolution and a priori constraint. This analysis uses TES data taken during the summers of 2005, 2006 and 2007, from both the nominal operation mode or global survey and from special observations using the Step-and-Stare mode [Beer, 2006]. The sampling for the global survey mode is one observation every 160 km with 16 orbits per global survey, over a time period of 12 hours. The step-and-stare mode spatial sampling is approximately 30 km but covering only part of an orbit over 60 degrees latitude MLS We also use monthly mean ozone observations from the Aura Microwave Limb Sounder (MLS) [Livesey, et al., 2008; Waters, et al., 2006] using Version 2 MLS 6

7 products. The MLS observes thermal microwave emission from the Earths limb in order to infer upper tropospheric and stratospheric profiles of ozone and many other stratospheric trace gasses. The precision from noise (or measurement error) for any give ozone measurement is at most 40 ppbv. For the monthly mean data shown in this paper we ignore the measurement error as it is about 4 ppbv or less through averaging of approximately 100 profiles or more Ozone Observations The Asian Monsoon forms in late spring and dissipates in the fall; therefore we focus our analysis for the June, July and August time period. We first examine TES monthly averaged observations of the upper troposphere followed by vertical ozone distributions as observed by TES and MLS TES Observed Monthly Mean Ozone In The Upper Troposphere Figure 1 shows TES ozone estimates for the summers of 2005, 2006, and 2007 for the pressure level at 464 hpa. Data for June 2005 are not shown as the TES instrument was not operating at that time. All data for which the TES master data quality is set to unity are used. Furthermore, only those data for which the degrees-of-freedom of signal (DOFS) for the upper troposphere between 300 and 600 hpa is 0.3 or larger are selected to ensure the estimate is sensitive to this part of the atmosphere. The grid used for Figure 1 is 6 degrees in both longitude and latitude. The figure is constructed by calculating the 7

8 average value of all ozone observations within the grid box. Because of the approximately 6 km vertical resolution the estimated ozone at 464 hpa is influenced by variations in the ozone abundance throughout the upper troposphere and into the the lower stratosphere. However, we use a single level to show the ozone distribution in the upper troposphere as opposed to averaging over many pressure levels because an averaged upper tropospheric quantity would have a latitude dependence due to tropopause variations. At the 464 hpa pressure level, mean ozone values greater then 90 ppbv are observed over north-east Africa, the Middle East, the Eastern Mediterranean, and over Central Asia north of the Tibetan plateau between 35 and 50 degrees latitude and approximately 75 degrees longitude. Although we should note that we have not corrected for the 5% 15% high bias that exists in the TES data in the middle troposphere when stating this value of 90 ppbv [Worden et al., 2006; Parrington et al., 2008]. High ozone values are also observed over East Asia but that is the subject for other analysis. This observed spatial variability is persistent from year-to-year with July typically showing the most enhanced values. In July 2005 the largest ozone values are observed over the Middle-East but not necessarily in July 2006 and July However, as discussed in the next section, many of the grid points shown in Figure 1 over the Middle-East had two or less overlapping observations; consequently, TES observations over the Middle-East during July of 2006 and 2007 are likely not be representative of the true ozone distribution during these time periods. In general, the number of observations in each grid point ranged from 3 to 30. 8

9 The spatial distribution of ozone in Figure1 show differences from the total tropospheric ozone amounts from the GOME instrument as shown in [Liu, et al., 2006] in that the largest ozone values in the upper troposphere are shown in the Eastern Hemisphere as opposed to similar total tropospheric ozone amounts in both hemispheres. However, [Liu, et al., 2006] does show peak total tropospheric ozone columns over the Eastern Mediterranean and Northwestern Saudi Arabia which is somewhat consistent with these TES distributions. Differences between the two ozone measurements are likely due to differences in the sensitivity of the instruments to tropospheric ozone, sampling, and the retrieval approach as well as the vertical distribution of ozone as discussed in Sections 3.3 and Sensitivity And Errors Of TES Ozone Estimates The sensitivity of the TES ozone estimates to the true ozone distribution depends primarily on atmospheric temperature, clouds, and trace gas amounts. As these quantities are strongly influenced by the summertime Asian monsoon it is necessary to determine how their variability impact the TES retrievals in this region. In this section we examine the errors, sensitivity, and retrieval bias of the TES ozone retrievals to show that the observed spatial distribution of ozone is statistically significant. For brevity we limit the error characterization to the ozone values of July 2006 as we do not find a significant difference in the error characterization from month to month and season to season. The error on the mean values shown in Figure 1 can in principle be theoretically calculated by averaging over the expected random errors for the distribution of retrievals 9

10 in each grid box. However, this approach assumes that the statistics of the atmosphere in the region of interest are well known, which may not be a good assumption for the Asian monsoon region given the scarcity of ozone profile observations in this region. We can empirically calculate the error on the mean by dividing the root-mean-square (RMS) of the mean within each grid point by the square-root of the number of observations in each grid [Worden, et al., 2007b]. As seen in Figure 2a (top panel), the error on the mean for July 2006 is typically 5 ppbv or less for the regions with the largest ozone values, but can be higher over parts of Central Asia due to the larger variance over this region. The topography in this region can also make atmospheric retrievals more challenging, which limits the number of available ozone profile estimates within some of the grid boxes, thereby increasing the error of the mean. In particular the error on the mean is large over parts of Saudi Arabia due to limited (one to two) observations per grid box for the July 2006 (and also July 2007, not shown). Consequently, the TES retrievals over this part of Saudi Arabia may not provide a representative description of the spatial distribution of ozone in this region. The TES estimates for ozone, or other trace gasses, are dependent on the sensitivity of the estimate to the true distribution of ozone as well as the a priori constraint used for the ozone retrieval; this dependency is represented by the following equation: ˆx = x a + A(x! x a ) (0.1) where ˆx, in this case, is the logarithm of the TES ozone profile estimate. The a priori constraint is given by x a. The log of the true ozone distribution is given by x and the sensitivity of the estimate to this ozone is given by the averaging kernel matrix, A =!ˆx!x. 10

11 The TES ozone estimate, a priori constraint and averaging kernel matrix, as well as the various error covariances, are provided with all TES observations. The averaging kernel is a function of the sensitivity of the TES measured radiance to the distribution of ozone, the noise in the radiance, and the constraint matrix used to regularize the retrieval. For ozone, the constraints and constraint matrices are computed using the MOZART global chemistry model as input [Worden, et al., 2004] and are gridded onto a 60 degree longitude by 10 degree latitude bins. As seen in Equation (0.1), TES estimates are biased towards an a priori constraint. The bias in TES estimates from the a priori constraint is given by the difference between the true distribution of the logarithm of ozone and the TES estimate of this true distribution: ˆx! x = (I! A)(x a! x), (0.2) A useful metric for the sensitivity of the estimate to the true distribution is the degrees-offreedom for signal (DOFS) which is the sum of the diagonal elements of the averaging kernel matrix; recall that a diagonal element of the averaging kernel matrix describes the sensitivity of the ozone estimate for the corresponding pressure level to the true distribution of ozone at that pressure level. In order to determine if the ozone estimates shown in Figure 1 are sensitive to the true distribution we examine the average DOFS for the altitude region between hpa as shown in Figure 2b (middle panel). For the geographical and altitude region of interest there is, on average, 0.65 DOFS. Consequently, while the estimate is sensitive to the true distribution of ozone in this 11

12 region, it is useful to determine the extent to which the retrieval bias might contribute to the spatial variability in the ozone retrievals. An approach for estimating an upper bound on the retrieval bias is to replace the true-state ozone (x) on the right side of Equation (0.2), with some value that is unlikely, although not unphysical. For this test we use the a priori constraint equivalent to clean pacific air at approximately 30 degrees latitude and -180 degrees longitude. Ozone values are about ppbv in the lower troposphere and ppbv in the upper troposphere. Note that this linear operation is equivalent to calculating a different estimate by swapping in a fixed a priori constraint [Rodgers and Connor, 2003]. ˆx 2 = ˆx 1 + (I! A)(x 2 a! x 1 a ) (0.3) where ˆx 1 is the original TES (log) ozone estimate and ˆx 2 is the new TES (log) ozone 257 estimate, x a 1 is the constraint used for the original TES ozone retrieval and x a 2 is the fixed constraint used to change the TES estimate. The expression (I! A)(x 2 a! x 1 a ) is now equivalent to the right hand side of Equation (0.2) if we replace the true distribution of the logarithm of ozone with this new constraint in order to estimate an upper bound on the bias from the constraint vector. Therefore, instead of showing the difference as seen in Equation (0.2), we instead re-calculate the ozone estimate assuming a fixed a priori constraint vector [Kulawik, et al., 2008]. This new estimate is shown in Figure 2c (bottom panel) for the July 2006 monthly mean. Comparison between the middle panel of Figure 1 and Figure 2c shows differences on the order of 5 ppbv with little change in the spatial variability in the region of enhanced ozone over Northeast Africa, the Eastern Mediterranean, and North of the Tibetan plateau. We can therefore conclude that the a priori constraint does not affect our 12

13 conclusions about the spatial variability of ozone. However, the a priori constraint could be introducing a bias as high as 5 ppbv into the ozone estimates for these regions. Note that a bias from the a priori constraint is removed when comparing to ozonesondes or model profiles because these profiles are first transformed using Equation (0.1) before comparing to TES observations [Worden, et al., 2007a] Vertical Distribution of Ozone over India, the Tibetan Plateau, and Central Asia Having established the spatial extent of the summertime ozone distribution across North Africa and Asia, we now show the vertical ozone distributions over this expansive region between 30 and 90 degrees longitude using observations from the Aura TES and MLS instruments. The objective is to characterize the vertical distribution of ozone over this expansive region. Characterizing the vertical distribution of ozone is needed for understanding how surface emissions, deep convection, long range transport, and lightning transport or produce ozone in the troposphere during this time period. Figure 3 shows the vertical distribution of ozone from TES for longitudes between 70 and 90 degrees and between 20 and 50 degrees latitude; this is the region covering India, the Tibetan Plateau, and Central Asia. Pressures shown are between 100 and 1000 hpa on the TES pressure grid. However, all data are interpolated to a latitudinal grid of 0.5 degrees; we choose a finer latitudinal spacing then shown in Figure 1 because the coarser longitudinal spacing allow for more data to be used in this figure. The average surface pressure over this 20 degree longitudinal swath is shown as a white line on the bottom. The surface pressure changes in each plot because of the different 13

14 sampling in each month of observations. A dashed line in the middle of each figure represents the pressure at 464 hpa for comparison of these vertical distributions with Figure 1. Only profiles where the DOFS in the upper troposphere is larger then 0.3 are selected to ensure sensitivity of the TES estimates to variations in upper tropospheric ozone. The vertical distribution of ozone shown in Figure 3 is characterized by an enhanced layer of ozone, with values that can exceed 100 ppbv, at approximately 300 hpa between 25 and 40 degrees latitude. This enhanced layer of ozone is present in June and July and begins to dissipate by August. The enhanced layer is not apparent in Figure 1 because it is at higher altitudes than the 464 hpa pressure level shown in Figure 1. The lower ozone amounts of approximately ppbvat 200 hpa, between 20 and 30 N, during July and August (or 360 K potential temperature) are consistent with AIRS ozone observations shown by [Randel and Park, 2006]. An additional test to determine the altitude location of the enhanced ozone in this region is to swap in a fixed a priori constrain using the approach discussed in Section 3.2. Vertical ozone distributions from TES using a fixed a priori constraint vector are shown in Figure 4. The vertical distributions for June show slight changes. However, the differences in the vertical distributions of ozone using a fixed a priori constraint do not change our conclusion about ozone enhancements near 350 hpa for latitudes between 20 and 30 0 N for the July and August time period. Another feature shown in the TES data is high ozone past 40 degrees longitude and pressures less then 300 hpa that appears to be a mix of stratospheric and tropospheric air as indicated by the lines of potential temperature in the TES data; however the coarse 14

15 degree longitudinal gridding used to create these figures makes the determination of the ozone source difficult. Consequently, we show a special-observation from TES in Figure 5 that has a 35 km spacing between observations taken over a couple of minutes as opposed to the 160 km spacing from the TES global survey; this special observation is part of a yearly set of observations used to study boreal fires and Asian pollution. As with the vertical distributions shown in Figure 3, enhanced ozone at 300 hpa is observed near 30 degrees latitude. However, significantly high ozone greater than 150 ppbv is observed North of 35 degrees also at 300 hpa. This high ozone is co-located with regions of low upper tropospheric water and the Westerly jet as shown in [Randel and Park, 2006] indicate subsiding air. The high ozone and low water suggest a stratospheric origin which is consistent with of the analysis of Moore and Semple, [2005] who found that ozone at the surface in this region can originate from the stratosphere. They are also consistent with the analysis of Sprenger and Wernli [2003] who examined 15 years of ERA15 meteorological data from the European Center for Medium-Range Weather Forecasting and found that stratosphere to troposphere exchange is at a maximum over central Asia in summer. More recently, Ding and Wang [2006] suggested that stratosphere intrusions were primarily responsible for enhanced surface ozone abundances observed in over the Tibetan Plateau. Other TES step and stares taken during the summer of this same region show similar behavior but are not shown because they had significant data gaps due to clouds and increased retrieval failure rate over the mountain regions Vertical Distribution of Ozone over the Middle East 15

16 We next show the vertical distribution of ozone ranging between 30 to 70 degrees longitude and between 20 to 50 degrees latitude. These distributions are shown in Figures 6 and 7 for longitudes between degrees and 30 to 50 degrees respectively. Both figures again show enhanced ozone amounts of 100 ppbv in the middle or upper troposphere. A difference between the ozone distributions in Figures 7 and 8 and those over India and Tibet (Figure 3) are that the peak ozone amounts for latitudes less then 30 degrees appear at lower altitudes as indicated by the dashed line at 450 hpa shown in each figure. For latitudes above 30 degrees, peak ozone values appear to shift to higher altitudes near 200 hpa although an ozone minima can appear at these altitudes during August for longitudes between 50 and 70 degrees. For brevity, we do not show ozone amounts using a fixed a priori constraint although we note that our conclusions about the vertical distribution of ozone would not change using a fixed prior Comparison to MOZAIC and MLS Monthly mean ozone profiles over Delhi, Tehran, and Dubai from the MOZAIC program are shown in Figure 8 for June, July, and August. We use here monthly mean ozone climatologies generated from MOZAIC data between 1996 and 2005 because there is no overlap between these measurements and the TES and MLS data. However, the climatology provides sufficient statistics to capture the vertical distribution of ozone for comparison of the seasonal variations in the vertical structure of ozone. The precision of 16

17 the MOZAIC ozone data is 2 ppbv and the sensors are calibrated every 500 flights hours [Thouret et al., 1998a]. They number of profiles used to calculated the monthly means range from 47 to 110. The constructed climatologies from these profiles are consistent with those based on ozonesondes [Thouret et al., 1998b]. As shown in Figure 8, the profiles are characterized by low ozone amounts in the lower troposphere with higher amounts of up to 80 ppbv between 200 to 400 hpa. The ozone in the free troposphere also decreases from June to August. This seasonal variability is consistent with TES data in that ozone is typically highest in the middle troposphere in June and lowest in August. The MOZAIC climatology over Delhi, Tehran, and Dubai are compared directly with TES and MLS observations for July in Figure 9. Since there are no overlapping TES or MLS data available to compare with the MOZAIC profile, we average both TES and MLS across a 5 degree by 5 degree bin in which each of the cities is a midpoint. Shown in Figure 9 is the mean value of all TES ozone profiles for July 2005, 2006, and 2007 for the grid points centered over Delhi, Tehra, and Dubai. The dotted lines represent the rootmean-square (RMS) about the mean of the TES ozone. A major challenge in comparing the TES and MOZAIC profiles is that accounting for the TES vertical resolution and bias introduced by the a priori constraint is not accurate (e.g., Worden et al., 2006) because of the error introduced by truncating the TES profile at approximately 200 hpa, the upper limit of the MOZAIC profiles. This truncation introduced a cross-state error [Worden et al., 2004] that is due to uncertainties in the TES estimated ozone in the upper troposphere and lower stratosphere. This cross-state error is largest at 200 hpa and becomes smaller at higher pressures. Taking into account the lower sensitivity to ozone of the TES estimates for pressures above 800 hpa, the best overall comparison between 17

18 the TES and MOZAIC data will be between 400 and 800 hpa. As can be seen in Figure 9, in this region the MOZAIC data agree well with TES, within the mean and RMS, with the exception of Dubai at approximately 550 hpa. Previous comparison of TES data with sondes suggest that TES is biased high in the middle troposphere by approximately 5% to 15% [Worden et al., 2006; Nassarr et al. 2008]. This bias is consistent with the TES comparison to MOZAIC. The comparison between TES and MLS in Figure 9 reveals that there is significantly more variability in the MLS data than in TES in the upper troposphere and lower stratosphere for these regions. The variability of MLS data is much less than the expected precision (about 4%) or bias which could be 0 15% [Livesey et al. 2008]. Averaged between hpa, the observed MLS ozone amounts are within the range of variability observed by TES. For example, the average mean ozone between 100 and 215 hpa over Delhi is approximately 91 ppbv for the MLS data versus approximately 83 ppbv for the TES data. However, the TES sensitivity to ozone variability is lowest at the tropopause and highly correlated above and below the tropopause because the temperature above and below the tropopause will have matching values. Consequently, we would not expect the observed TES variability to match that observed by MLS, but, on average, the two instruments should observe similar ozone amounts Discussion and Conclusions

19 Previous observations of tropospheric and stratospheric trace gasses in the Asian Monsoon region reveal a complex system involving deep convection of boundary layer air followed by entrainment into strong westerly and easterly winds as well as recirculation of air along the summertime upper tropospheric / lower stratospheric anticyclones. These dynamical processes are indicated by low ozone, high water, and significant surface emissions such as CO and HCN in the upper troposphere and lower stratosphere during summertime [Fu, et al., 2006; Gettelman, et al., 2004; Kar, et al., 2004; Park, et al., 2007; Randel and Park, 2006]. Deep convection of surface emissions, lightning, as well as long range transport of European and Asian emissions and re-circulation in middle tropospheric anticyclones, are expected by the GEOS-CHEM model to significantly enhance ozone in the middle troposphere [Li, et al., 2001] over the Middle East. These model predictions are corroborated by satellite observations showing significant ozone enhancements over Northeast Africa and Northwest Saudi Arabia [Kar, et al., 2002; Liu, et al., 2006] as well as MOZAIC observations over Middle-Eastern cities [Li, et al., 2001]. TES observations of the vertical and horizontal distribution of tropospheric ozone enhance this picture of how tropospheric ozone responds to the dynamics of the Asian monsoon and subsequent chemical processes by showing a highly stratified vertical ozone distribution stretching from North East Africa through India for latitudes less then 30 0 N. Peak ozone amounts over India appear near 300 hpa whereas over the Middle East they appear near 450 hpa with values that can exceed 100 ppbv. Lower ozone values of about 50 ppbv are present above and below this enhanced layer as discussed by [Fu, et al., 2006; Gettelman, et al., 2004; Kar, et al., 2004; Park, et al., 2007; Randel and Park, 19

20 ]. An enhanced ozone layer over the middle East near 450 hpa is consistent with the results from [Li, et al., 2001]. This stratified distribution is corroborated by MLS observations of ozone for pressures less than 200 hpa and by MOZAIC summertime ozone climatologies for pressures above 200 hpa in Tehran, Dubai, and Delhi. As also observed by the MOZAIC climatologies, TES observed ozone values in the middle troposphere peak in June and begin to dissipate in August. After accounting for the TES upper tropospheric bias of 15%, we find that ozone in this enhanced layer can exceed 100 PPBV. We are currently studying whether this bias is instrumental or due to increased surface emissions since the MOZAIC climatology was generated. In addition to these layers of ozone, enhanced upper tropospheric ozone with values exceeding 150 PPBV is observed for latitudes above 40 degrees; initial analysis suggests a significant stratospheric influence, likely due to subsidence along the Westerly Jet. A companion paper by J. Liu et al. [this journal] as well as a subsequent work by Verma et al. [In Preperation] will relate these vertical distributions of ozone to the complex dynamics over this expansive region as well as the horizontal and vertical distribution of ozone pre-cursors and ozone production Acknowledgement The work described here is performed at the Jet Propulsion Laboratory, California Institute of Technology under contracts from the National Aeronautics and Space Administration. D. Jones and J. Liu were funded by the Natural Sciences and Engineering Council of Canada and the Canadian Foundation for Climate and Atmospheric Sciences. We thank Jay Kar for helpful discussions. The views, opinions, and findings contained in this report are those of the author(s) and should not be construed as an official National 20

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25 Figure 1: TES monthly averaged ozone at 464 hpa. Data are gridded on a 6x6 degree bin. There are no data for June 2005 as TES was undergoing operational difficulties during that time period.

26 Figure 2 (Top Panel) Error on the Mean for the July 2006 Ozone values at the 464 hpa level. (Middle Panel) The DOFS for the region between 300 and 600 hpa. (Bottom Panel) The TES estimate of ozone at 464 hpa if we use a fixed a priori constraint vector.

27 Figure 3: TES vertical ozone distributions during the Summers of 2005, 2006, and 2007 for longitudes between degrees East. The vertical scale is the log of pressure. The dashed line indicates the 464 hpa level for comparison with Figure 1. The bottom white line shows the average surface pressure for the set of observations during the specified time period and latitude / longitude range.

28 Figure 4: Same as in Figure 3 except the ozone profiles have been re-calculated using a fixed a priori constraint.

29 Figure 5: TES ozone profiles from the step-and-stare mode. There is approximately 1 observation every 35 km. The white line is the average surface pressure.

30 Figure 6: TES observed vertical ozone distributions for longitudes between 50 and 70 degrees East. The white line indicates the average surface pressure.

31 Figure 7: TES observed vertical ozone distributions for longitudes between 30 and 50 degrees East. The white line indicates the average surface pressure.

32 Figure 8. Monthly mean values averaged over 10 years of ozone measurements from the MOZAIC program.

33 Figure 9: TES, MLS, and MOZAIC ozone over Delhi, Teheran, and Dubai. The TES and MLS data (purple and orange respectively) are averages of all available profiles within a 5x5 degree grid box over the respective cities for July of 2005, 2006, and The ten year ( ) MOZAIC climatology is shown as the black line. Dotted lines are the RMS of the TES ozone profiles within the 5x5 degree grid.