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We derive free-tropospheric NO2 volume mixing ratios (VMRs) and stratospheric column amounts of NO2 by applying a cloud slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top-of-the-atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. Estimates of stratospheric column NO2 are obtained by extrapolating the linear fits to the tropopause. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud slicing data indicates signatures of uplifted and transported anthropogenic NO2 in the middle troposphere as well as lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the Global Modeling Initiative (GMI) for cloudy conditions (cloud optical thicknesses > 10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx. Stratospheric column NO2 obtained from cloud slicing agrees well with other independently-generated estimates, providing further confidence in the free-tropospheric results.

Convective transport is one of the dominant factors in determining the composition of the troposphere. It is the main mechanism for lofting constituents from near-surface source regions to the middle and upper troposphere, where they can subsequently be advected over large distances. Gases reaching the upper troposphere can also be injected through the tropopause and play a subsequent role in the lower stratospheric ozone balance. Convection codes in climate models remain a great source of uncertainty for both the energy balance of the general circulation and the transport of constituents. This study uses the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM) to perform a controlled experiment that isolates the impact of convective transport of constituents from the direct changes on the atmospheric energy balance. Two multi-year simulations are conducted. In the first, the thermodynamic variable, moisture, and all trace gases are transported using the multi-plume Relaxed-Arakawa-Schubert (RAS) convective parameterization. In the second simulation, RAS impacts the thermodynamic energy and moisture in this standard manner, but all other constituents are transported differently. The accumulated convective mass fluxes (including entrainment and detrainment) computed at each time step of the GCM are used with a diffusive (bulk) algorithm for the vertical transport, which above all is less efficient at transporting constituents from the lower to the upper troposphere. Initial results show the expected differences in vertical structure of trace gases such as carbon monoxide, but also show differences in lower stratospheric ozone, in a region where it can potentially impact the climate state of the model. This work will investigate in more detail the impact of convective transport changes by comparing the two simulations over many years (1996-2010), focusing on comparisons with observed constituent distributions and similarities and differences of patterns of inter-annual variability caused by the convective transport algorithm. In particular, the impact on lower stratospheric composition will be isolated and the subsequent feedbacks of ozone on the climate forcing and tropopause structure will be assessed.

We present simulations of the tropospheric composition for the years 2004 and 2005, carried out by the GMI Combined Stratosphere-Troposphere (Combo) model, at a resolution of 2degx2.5deg. The model includes a new parameterization of lightning sources of NO(x) which is coupled to the cloud mass fluxes in the adopted meteorological fields. These simulations use two different sets of input meteorological fields: a)late-look assimilated fields from the Global Modeling and Assimilation Office (GMAO), GEOS-4 system and b) 12-hour forecast fields initialized with the assimilated data. Comparison of the forecast to the assimilated fields indicates that the forecast fields exhibit less vigorous convection, and yield tropical precipitation fields in better agreement with observations. Since these simulations include a complete representation of the stratosphere, they provide realistic stratosphere-tropospheric fluxes of O3 and NO(y). Furthermore, the stratospheric contribution to total columns of different troposheric species can be subtracted in a consistent fashion, and the lightning production of NO(y) will depend on the adopted meteorological field. We concentrate here on the simulated tropospheric columns of NO2, and compare them to observations by the OM1 instrument for the years 2004 and 2005. The comparison is used to address these questions: a) is there a significant difference in the agreement/disagreement between simulations for these two different meteorological fields, and if so, what causes these differences?; b) how do the simulations compare to OMI observations, and does this comparison indicate an improvement in simulations with the forecast fields? c) what are the implications of these simulations for our understanding of the NO2 emissions over continental polluted regions?

The approach to create a comprehensive emission inventory for the time period 1980 to 2000 is described in this paper. We have recently compiled an emission database, which we will use for a 21 year simulation of tropospheric aerosols with the GOCART model. Particular attention was paid to the time-dependent SO2, black carbon and organic carbon aerosol emissions. For the emission of SO2 from sporadically erupting volcanoes, we assembled emission data from the Global Volcanism Program of the Smithsonian Institution, using the VEI to derive the volcanic cloud height and the SO2 amount, and amended this dataset by the SO2 emission data from the TOMS instrument when available. 3-dimensional aircraft emission data was obtained for a number of years from the AEAP project, converted from burned fuel to SO2 and interpolated to each year, taking the sparsity of the flight patterns into account. Other anthopogenic SO2 emissions are based on gridded emissions from the EDGAR 2000 database (excluding sources from aircraft, biomass burning and international ship traffic), which were scaled to individual years with country/regional based emission inventories. Gridded SO2 emissions from international ship traffic for 2000 and the scaling factors for other years are from [Eyring et al., 2005]. We used gridded anthropogenic black and organic carbon emissions for 1996 [Bond et al., 2005], again excluding aircraft, biomass burning and ship sources. These emissions were scaled with regional based emission inventories from 1980 to 2000 to derive gridded emissions for each year. The biomass burning emissions are based on a climatology, which is scaled with regional scaling factors derived from the TOMS aerosol index and the AVHRR/ATSR fire counts to each year [Duncan et al., 2003]. Details on the integration of the information from the various sources will be provided and the distribution patterns and total emissions in the final product will be discussed.

Ozone measurements from the OMI and MLS instruments on board the Aura satellite are used for deriving global distributions of tropospheric column ozone (TCO). TCO is determined using the tropospheric ozone residual method which involves subtracting measurements of MLS stratospheric column ozone (SCO) from OMI total column ozone after adjusting for intercalibration differences of the two instruments using the convective-cloud differential method. The derived TCO field, which covers one complete year of mostly continuous daily measurements from late August 2004 through August 2005, is used for studying the regional and global pollution on a timescale of a few days to months. The seasonal and zonal characteristics of the observed TCO fields are also compared with TCO fields derived from the Global Modeling Initiative's Chemical Transport Model. The model and observations show interesting similarities with respect to zonal and seasonal variations. However, there are notable differences, particularly over the vast region of the Saharan desert.