The Tropospheric Ozone Assessment Report (TOAR) is an activity of the International Global Atmospheric Chemistry Project. This paper is a component of the report, focusing on the present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation. Utilizing the TOAR surface ozone database, several figures present the global distribution and trends of daytime average ozone at 2702 non-urban monitoring sites, highlighting the regions and seasons of the world with the greatest ozone levels. Similarly, ozonesonde and commercial aircraft observations reveal ozone’s distribution throughout the depth of the free troposphere. Long-term surface observations are limited in their global spatial coverage, but data from remote locations indicate that ozone in the 21st century is greater than during the 1970s and 1980s. While some remote sites and many sites in the heavily polluted regions of East Asia show ozone increases since 2000, many others show decreases and there is no clear global pattern for surface ozone changes since 2000. Two new satellite products provide detailed views of ozone in the lower troposphere across East Asia and Europe, revealing the full spatial extent of the spring and summer ozone enhancements across eastern China that cannot be assessed from limited surface observations. Sufficient data are now available (ozonesondes, satellite, aircraft) across the tropics from South America eastwards to the western Pacific Ocean, to indicate a likely tropospheric column ozone increase since the 1990s. The 2014–2016 mean tropospheric ozone burden (TOB) between 60˚N–60˚S from five satellite products is 300 Tg ± 4%. While this agreement is excellent, the products differ in their quantification of TOB trends and further work is required to reconcile the differences. Satellites can now estimate ozone’s global long-wave radiative effect, but evaluation is difficult due to limited in situ observations where the radiative effect is greatest.

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[1] We present global, vertical profile estimates of the HDO/H 2 O ratio from the Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite. We emphasize in this paper the estimation approach and error characterization, which are critical to determining the very small absolute concentration of HDO relative to H 2 O and its uncertainty. These estimates were made from TES nadir-viewing (downlooking) thermal infrared spectral radiances observed on 20 September 2004. Profiles of HDO and H 2 O are simultaneously estimated from the observed radiances and a profile of the ratio is then calculated. This simultaneous, or ''joint,'' estimate is regularized with an a priori covariance matrix that includes expected correlations between HDO and H 2 O. This approach minimizes errors in the profile of the HDO/H 2 O ratio that are due to overlapping HDO and H 2 O spectroscopic lines. Under clear-sky conditions in the tropics, TES estimates of the HDO/H 2 O ratio are sensitive to the distribution of the actual ratio between the surface and about 300 hPa with peak sensitivity at 700 hPa. The sensitivity decreases with latitude through its dependence on temperature and water amount. We estimate a precision of approximately 1% to 2% for the ratio of the HDO/H 2 O tropospheric densities; however, there is possibly a bias of approximately 5% in the ratio due to the HDO spectroscopic line strengths. These global observations clearly show increased isotopic depletion of water vapor at higher latitudes as well as increased depletion in the upper troposphere versus the lower troposphere.

[1] Error covariances and vertical resolutions are reported for Tropospheric Emission Spectrometer (TES) nadir-view retrievals of surface temperature, atmospheric temperature, H 2 O, O 3 , CO, and CH 4 . These error covariances are computed as a result of selecting spectral windows that maximize the information content of simulated, TES nadir-view atmospheric retrievals of four regions representative of northern midlatitude, southern midlatitude, tropical, and polar climates. The information content of a retrieval is a function of an a priori and an a posteriori covariance matrix where the a posteriori covariance depends on an estimated smoothing error, measurement error, and systematic errors from interfering species, surface emissivity, atmospheric and surface temperature, and line parameter uncertainties. For conditions representative of northern midlatitudes, we can expect about 3 degrees of freedom (DOF) for retrievals of H 2 O, 5 DOF for O 3 with about 2.4 DOF in the troposphere, and 0.8 DOF for CO. These measures for the vertical resolution and the predicted errors can be used to assess which atmospheric science questions can be addressed with TES atmospheric retrievals. Proper characterization of TES retrievals is also critical for applications such as atmospheric data assimilation and inverse modeling.

The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS)‐Aura spacecraft measures global profiles of atmospheric ozone with vertical resolution of 6–7 km in the troposphere for the nadir view. For a first validation of TES ozone measurements we have compared TES‐retrieved ozone profiles to ozonesondes from fall, 2004. In some cases the ozonesonde data are from dedicated launches timed to match the Aura overpass, while other comparisons are performed with routine data available from the Southern Hemisphere Additional Ozonesonde (SHADOZ) archive and World Ozone and Ultraviolet Data Center (WOUDC) data archives. We account for TES measurement sensitivity and vertical resolution by applying the TES‐averaging kernel and constraint to the ozonesonde data before differencing the profiles. Overall, for V001 data, TES ozone profiles are systematically higher than sondes in the upper troposphere but compare well in the lower troposphere, with respect to estimated errors. These comparisons show that TES is able to detect relative variations in the coarse vertical structure of tropospheric ozone.

Abstract. Thermal infrared (IR) radiances measured near 8 microns contain information about the vertical distribution of water vapor (H 2 O), the water isotopologue HDO, and methane (CH 4 ), key gases in the water and carbon cycles. Previous versions (Version 4 or less) of the TES profile retrieval algorithm used a "spectral-window" approach to minimize uncertainty from interfering species at the expense of reduced vertical resolution and sensitivity. In this manuscript we document changes to the vertical resolution and uncertainties of the TES version 5 retrieval algorithm. In this version (Version 5), joint estimates of H 2 O, HDO, CH 4 and nitrous oxide (N 2 O) are made using radiances from almost the entire spectral region between 1100 cm −1 and 1330 cm −1 . The TES retrieval constraints are also modified in order to better use this information. The new H 2 O estimates show improved vertical resolution in the lower troposphere and boundary layer, while the new HDO/H 2 O estimates can now profile the HDO/H 2 O ratio between 925 hPa and 450 hPa in the tropics and during summertime at high latitudes. The new retrievals are now sensitive to methane in the free troposphere between 800 and 150 mb with peak sensitivity near 500 hPa; whereas in previous versions the sensitivity peaked at 200 hPa. However, the upper troposphere methane concentrations are biased high relative to the lower troposphere by approximately 4 % on average. This bias is likely related to temperature, calibration, and/or methane spectroscopy errors. This bias can be mitigated by normalizing the CH 4 estimate by the ratio of the N 2 O estimate relative to the N 2 O prior, under the assumption that the same systematic error affects both the N 2 O and CH 4 estimates. We demonstrate that applying this ratio theoretically reduces the CH 4 estimate for non-retrieved parameters that jointly affect both the N 2 O and CH 4 estimates. The relative upper troposphere to lower troposphere bias is approximately 2.8 % after this bias correction. Quality flags based upon the vertical variability of the methane and N 2 O estimates can be used to reduce this bias further. While these new CH 4 , HDO/H 2 O, and H 2 O estimates are consistent with previous TES retrievals in the altitude regions where the sensitivities overlap, future comparisons with independent profile measurement will be required to characterize the biases of these new retrievals and determine if the calculated uncertainties using the new constraints are consistent with actual uncertainties.

Abstract. The use of global three-dimensional (3-D) models with satellite observations of CO 2 in inverse modeling studies is an area of growing importance for understanding Earth's carbon cycle. Here we use the GEOS-Chem model (version 8-02-01) CO 2 mode with multiple modifications in order to assess their impact on CO 2 forward simulations. Modifications include CO 2 surface emissions from shipping (∼ 0.19 Pg C yr −1 ), 3-D spatially-distributed emissions from aviation (∼0.16 Pg C yr −1 ), and 3-D chemical production of CO 2 (∼1.05 Pg C yr −1 ). Although CO 2 chemical production from the oxidation of CO, CH 4 and other carbon gases is recognized as an important contribution to global CO 2 , it is typically accounted for by conversion from its precursors at the surface rather than in the free troposphere. We base our model 3-D spatial distribution of CO 2 chemical production on monthly-averaged loss rates of CO (a key precursor and intermediate in the oxidation of organic carbon) and apply an associated surface correction for inventories that have counted emissions of CO 2 precursors as CO 2 . We also explore the benefit of assimilating satellite observations of CO into GEOS-Chem to obtain an observation-based estimate of the CO 2 chemical source. The CO assimilationCorrespondence to: R. Nassar (ray.nassar@ec.gc.ca) corrects for an underestimate of atmospheric CO abundances in the model, resulting in increases of as much as 24% in the chemical source during May-June 2006, and increasing the global annual estimate of CO 2 chemical production from 1.05 to 1.18 Pg C. Comparisons of model CO 2 with measurements are carried out in order to investigate the spatial and temporal distributions that result when these new sources are added. Inclusion of CO 2 emissions from shipping and aviation are shown to increase the global CO 2 latitudinal gradient by just over 0.10 ppm (∼3%), while the inclusion of CO 2 chemical production (and the surface correction) is shown to decrease the latitudinal gradient by about 0.40 ppm (∼10%) with a complex spatial structure generally resulting in decreased CO 2 over land and increased CO 2 over the oceans. Since these CO 2 emissions are omitted or misrepresented in most inverse modeling work to date, their implementation in forward simulations should lead to improved inverse modeling estimates of terrestrial biospheric fluxes.

[1] Comparisons of tropospheric carbon monoxide (CO) volume mixing ratio profiles and total columns are presented from nadir-viewing measurements made by the Tropospheric Emission Spectrometer (TES) on the NASA Aura satellite and by the Measurements of Pollution in the Troposphere (MOPITT) instrument on the NASA Terra satellite. In this paper, we first explore the factors that relate the retrieved and the true species profiles. We demonstrate that at a given location and time the retrieved species profiles reported by different satellite instrument teams can be very different from each other. We demonstrate the influence of the a priori data and instrument characteristics on the CO products from TES and MOPITT and on their comparisons. Direct comparison of TES and MOPITT retrieved CO profiles and columns show significant differences in the lower and upper troposphere. To perform a more proper and rigorous comparison between the two instrument observations we allow for different a priori profiles and averaging kernels. We compare (1) TES retrieved CO profiles adjusted to the MOPITT a priori with the MOPITT retrievals and (2) the above adjusted TES CO profiles with the MOPITT profiles vertically smoothed by the TES averaging kernels. These two steps greatly improve the agreement between the CO profiles and the columns from the two instruments. No systematic differences are found as a function of latitude in the final comparisons. These results show that knowledge of the a priori profiles, the averaging kernels, and the error covariance matrices in the standard data products provided by the instrument teams and understanding their roles in the retrieval products are essential in quantitatively interpreting both retrieved profiles and the derived total or partial columns for scientific applications.