[1] Properly handling satellite data to constrain the inversion of CO 2 sources and sinks at the Earth surface is a challenge motivated by the limitations of the current surface observation network. In this paper we present a Bayesian inference scheme to tackle this issue. It is based on the same theoretical principles as most inversions of the flask network but uses a variational formulation rather than a pure matrix-based one in order to cope with the large amount of satellite data. The minimization algorithm iteratively computes the optimum solution to the inference problem as well as an estimation of its error characteristics and some quantitative measures of the observation information content. A global climate model, guided by analyzed winds, provides information about the atmospheric transport to the inversion scheme. A surface flux climatology regularizes the inference problem. This new system has been applied to 1 year's worth of retrievals of vertically integrated CO 2 concentrations from the Television Infrared Observation Satellite Operational Vertical Sounder (TOVS). Consistent with a recent study that identified regional biases in the TOVS retrievals, the inferred fluxes are not useful for biogeochemical analyses. In addition to the detrimental impact of these biases, we find a sensitivity of the results to the formulation of the prior uncertainty and to the accuracy of the transport model. Notwithstanding these difficulties, four-dimensional inversion schemes of the type presented here could form the basis of multisensor data assimilation systems for the estimation of the surface fluxes of key atmospheric compounds.Citation: Chevallier, F., M. Fisher, P. Peylin, S. Serrar, P. Bousquet, F.-M. Bréon, A. Chédin, and P. Ciais (2005), Inferring CO 2 sources and sinks from satellite observations: Method and application to TOVS data,

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The GEISA database (Gestion et Etude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information) has been developed and maintained by the ARA/ABC(t) group at LMD since 1974. GEISA is constantly evolving, taking into account the best available spectroscopic data. This paper presents the 2015 release of GEISA (GEISA-2015), which updates the last edition of 2011 and celebrates the 40th anniversary of the database. Significant updates and additions have been implemented in the three following independent databases of GEISA. The “line parameters database” contains 52 molecular species (118 isotopologues) and transitions in the spectral range from 10−6 to 35,877.031 cm−1, representing 5,067,351 entries, against 3,794,297 in GEISA-2011. Among the previously existing molecules, 20 molecular species have been updated. A new molecule (SO3) has been added. HDO, isotopologue of H2O, is now identified as an independent molecular species. Seven new isotopologues have been added to the GEISA-2015 database. The “cross section sub-database” has been enriched by the addition of 43 new molecular species in its infrared part, 4 molecules (ethane, propane, acetone, acetonitrile) are also updated; they represent 3% of the update. A new section is added, in the near-infrared spectral region, involving 7 molecular species: CH3CN, CH3I, CH3O2, H2CO, HO2, HONO, NH3. The “microphysical and optical properties of atmospheric aerosols sub-database” has been updated for the first time since 2003. It contains more than 40 species originating from NCAR and 20 from the ARIA archive of Oxford University. As for the previous versions, this new release of GEISA and associated management software facilities are implemented and freely accessible on the AERIS/ESPRI atmospheric chemistry data center website

The Brewer-Dobson mean circulation and its variability are investigated in the ERA-Interim over the period 1989-2010 by using an off-line Lagrangian transport model driven by analysed winds and heating rates. <br><br> At low and mid-latitudes, the mean age of air in the lower stratosphere is in good agreement with ages derived from aircraft, high altitude balloon and satellite observations of long-lived tracers. At high latitude and in the upper stratosphere, we find, however that the ERA-Interim ages exhibit an old bias, typically of one to two years. <br><br> The age spectrum exhibits a long tail except in the low tropical stratosphere which is modulated by the annual cycle of the tropical upwelling. The distribution of ages and its variability is consistent with the existence of two separate branches, shallow and deep, of the Brewer-Dobson circulation. Both branches are modulated by the tropical upwelling and the shallow branch is also modulated by the subtropical barrier. <br><br> The variability of the mean age is analysed through a decomposition in terms of annual cycle, QBO, ENSO and trend. The annual modulation is the dominating signal in the lower stratosphere and is maximum at latitudes greater than 50° in both hemispheres with oldest ages at the end of the winter. The phase of the annual modulation is also reversed between below and above 25 km. The maximum amplitude of the QBO modulation is of about 0.5 yr and is mostly concentrated within the tropics between 25 and 35 km. It lags the QBO wind at 30 unit{hPa} by about 8 months. The ENSO signal is small and limited to the lower northen stratosphere. <br><br> The age trend over the 1989–2010 period, according to this ERA-Interim dataset, is significant and negative, of the order of −0.3 to −0.5 yr dec⁻¹, within the lower stratosphere in the Southern Hemisphere and south of 40° N in the Northern Hemisphere below 25 km. The age trend is positive (of the order of 0.3 yr dec⁻¹) in the mid stratosphere but there is no region of consistent significance. This suggests that the shallow and deep Brewer-Dobson circulations may evolve in opposite directions. <br><br> Finally, we find that the long lasting influence of the Pinatubo eruption can be seen on the age of air from June 1991 until the end of 1993 and can bias the statistics encompassing this period

This study evaluates model-simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the Aerosol Comparison between Observations and Models phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-viewing Wide Field-of-view Sensor, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based Aerosol Robotic Network Sun photometer measurements, and dust vertical distributions/centroid height from Cloud Aerosol Lidar with Orthogonal Polarization and Atmospheric Infrared Sounder satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects; however, the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model-simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best known dust environment, and stresses the need for observable quantities to constrain the model processes.

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Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information

The updated 2009 edition of the spectroscopic database GEISA (Gestion et Etude des Informations Spectroscopiques Atmosphé riques; Management and Study of Atmospheric Spectroscopic Information) is described in this paper. GEISA is a computer-accessible system comprising three independent sub-databases devoted, respectively, to: line parameters, infrared and ultraviolet/visible absorption cross-sections, microphysical and optical properties of atmospheric aerosols. In this edition, 50 molecules are involved in the line parameters sub-database, including 111 isotopologues, for a total of 3,807,997 entries, in the spectral range from 10 À 6 to 35,877.031 cm À 1. The successful performances of the new generation of hyperspectral sounders depend ultimately on the accuracy to which the spectroscopic parameters of the optically active atmospheric gases are known, since they constitute an essential input to the forward radiative transfer models that are used to interpret their observations. Currently, GEISA is involved in activities related to the assessment of the capabilities of IASI (Infrared Atmospheric Sounding Interferometer; http://smsc.cnes.fr/IASI/index.htm) on board the METOP European satellite through the GEISA/IASI database derived from GEISA. Since the Metop-A (http://www.eumetsat.int) launch (19 October 2006), GEISA is the reference spectroscopic database for the validation of the level-1 IASI data. Also, GEISA is involved in planetary research, i.e., modeling of Titan's atmosphere, in the comparison with observations performed by Voyager, or by ground-based telescopes, and by the instruments on board the Cassini-Huygens mission. GEISA, continuously developed and maintained at LMD (Laboratoire de Mé té orologie Dynamique, France) since 1976, is implemented on the IPSL/CNRS (France) ''Ether'' Products and Services Centre WEB site (http://ether.ipsl.jussieu.fr), where all archived spectroscopic data can be handled through general and user friendly associated management software facilities. More than 350 researchers are registered for on line use of GEISA.