[1] A primary component of the observed recent climate change is the radiative forcing from increased concentrations of long-lived greenhouse gases (LLGHGs). Effective simulation of anthropogenic climate change by general circulation models (GCMs) is strongly dependent on the accurate representation of radiative processes associated with water vapor, ozone, and LLGHGs. In the context of the increasing application of the Atmospheric and Environmental Research, Inc. (AER), radiation models within the GCM community, their capability to calculate longwave and shortwave radiative forcing for clear sky scenarios previously examined by the radiative transfer model intercomparison project (RTMIP) is presented. Forcing calculations with the AER line-by-line (LBL) models are very consistent with the RTMIP line-by-line results in the longwave and shortwave. The AER broadband models, in all but one case, calculate longwave forcings within a range of À0.20 to 0.23 W m À2 of LBL calculations and shortwave forcings within a range of À0.16 to 0.38 W m À2 of LBL results. These models also perform well at the surface, which RTMIP identified as a level at which GCM radiation models have particular difficulty reproducing LBL fluxes. Heating profile perturbations calculated by the broadband models generally reproduce high-resolution calculations within a few hundredths K d À1 in the troposphere and within 0.15 K d À1 in the peak stratospheric heating near 1 hPa. In most cases, the AER broadband models provide radiative forcing results that are in closer agreement with high-resolution calculations than the GCM radiation codes examined by RTMIP, which supports the application of the AER models to climate change research.

• Retrievals of far infrared surface emissivity are reported for the first time, exploiting aircraft observations taken over Greenland. • The retrieved emissivity reaches values as low as 0.89 over the range 360-535 cm-1 , where the associated uncertainties are smallest. • Simulations of the surface emissivity are unable to simultaneously match retrievals in the far and mid infrared.

International audienceThe collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint ESA-JAXA EarthCARE satellite mission, scheduled for launch in 2017, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, CALIPSO, and Aqua. Specifically, EarthCARE's Cloud Profling Radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle and raindrop fall speeds. EarthCARE's 355-nm High Spectral Resolution Lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The Multi-Spectral Imager will provide a context for, and the ability to construct the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross-section. The consistency of the retrievals will be assessed to within a target of ±10 W m⁻² on the (10 km²) scale by comparing the multi-view Broad-Band Radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains

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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.

[1] Ammonia (NH 3 ) has significant impacts on biodiversity, eutrophication, and acidification. Widespread uncertainty in the magnitude and seasonality of NH 3 emissions hinders efforts to address these issues. In this work, we constrain U.S. NH 3 sources using observations from the TES satellite instrument with the GEOS-Chem model and its adjoint. The inversion framework is first validated using simulated observations. We then assimilate TES observations for April, July, and October of 2006 through 2009. The adjoint-based inversion allows emissions to be adjusted heterogeneously; they are found to increase in California throughout the year, increase in different regions of the West depending upon season, and exhibit smaller increases and occasional decreases in the Eastern U.S. Evaluations of the inversion using independent surface measurements show reduced model underestimates of surface NH 3 and wet deposited NH x in April and October; however, the constrained simulation in July leads to overestimates of these quantities, while TES observations are still under predicted. Modeled sulfate and nitrate aerosols concentrations do not change significantly, and persistent nitrate overestimation is noted, consistent with previous studies. Overall, while satellite-based constraints on NH 3 emissions improve model simulations in several aspects, additional assessment at higher horizontal resolution of spatial sampling bias, nitric acid formation, and diurnal variability and bi-directionality of NH 3 sources may be necessary to enhance year-round model performance across the full range of gas and aerosol evaluations.