[1] The causes of renewed growth in the atmospheric CH 4 burden since 2007 are still poorly understood and subject of intensive scientific discussion. We present a reanalysis of global CH 4 emissions during the 2000s, based on the TM5-4DVAR inverse modeling system. The model is optimized using high-accuracy surface observations from NOAA ESRL's global air sampling network for 2000-2010 combined with retrievals of column-averaged CH 4 mole fractions from SCIAMACHY onboard ENVISAT (starting 2003). Using climatological OH fields, derived global total emissions for 2007-2010 are 16-20 Tg CH 4 /yr higher compared to [2003][2004][2005]. Most of the inferred emission increase was located in the tropics (9-14 Tg CH 4 /yr) and mid-latitudes of the northern hemisphere (6-8 Tg CH 4 /yr), while no significant trend was derived for Arctic latitudes. The atmospheric increase can be attributed mainly to increased anthropogenic emissions, but the derived trend is significantly smaller than estimated in the EDGARv4.2 emission inventory. Superimposed on the increasing trend in anthropogenic CH 4 emissions are significant inter-annual variations (IAV) of emissions from wetlands (up to AE10 Tg CH 4 /yr), and biomass burning (up to AE7 Tg CH 4 /yr). Sensitivity experiments, which investigated the impact of the SCIAMACHY observations (versus inversions using only surface observations), of the OH fields used, and of a priori emission inventories, resulted in differences in the detailed latitudinal attribution of CH 4 emissions, but the IAV and trends aggregated over larger latitude bands were reasonably robust. All sensitivity experiments show similar performance against independent shipboard and airborne observations used for validation, except over Amazonia where satellite retrievals improved agreement with observations in the free troposphere. Citation: Bergamaschi, P., et al. (2013), Atmospheric CH 4 in the first decade of the 21st century: Inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements,

Abstract. At the beginning of 2009 new space-borne observations of dry-air column-averaged mole fractions of atmospheric methane (XCH 4

Context. Size measurements of young star clusters are valuable tools to put constraints on the formation and early dynamical evolution of star clusters. Aims. We use HST/ACS observations of the spiral galaxy M 51 in F435W, F555W and F814W to select a large sample of star clusters with accurate effective radius measurements in an area covering the complete disc of M 51. We present the dataset and study the radius distribution and relations between radius, colour, arm/interarm region, galactocentric distance, mass and age. Methods. We select a sample of 7698 (F435W), 6846 (F555W) and 5024 (F814W) slightly resolved clusters and derive their effective radii (R eff ) by fitting the spatial profiles with analytical models convolved with the point spread function. The radii of 1284 clusters are studied in detail. Results. We find cluster radii between 0.5 and ∼10 pc, and one exceptionally large cluster candidate with R eff = 21.6 pc. The median R eff is 2.1 pc. We find 70 clusters in our sample which have colours consistent with being old GC candidates and we find 6 new "faint fuzzy" clusters in, or projected onto, the disc of M 51. The radius distribution can not be fitted with a power law similar to the one for star-forming clouds. We find an increase in R eff with colour as well as a higher fraction of clusters with B−V > ∼ 0.05 in the interarm regions. We find a correlation between R eff and galactocentric distance (R G ) of the form R eff ∝ R 0.12±0.02 G , which is considerably weaker than the observed correlation for old Milky Way GCs. We find weak relations between cluster luminosity and radius: R eff ∝ L 0.15±0.02 for the interarm regions and R eff ∝ L −0.11±0.01 for the spiral arm regions, but we do not observe a correlation between cluster mass and radius. Conclusions. The observed radius distribution indicates that shortly after the formation of the clusters from a fractal gas, the radii of the clusters have changed in a non-uniform way. We find tentative evidence suggesting that clusters in spiral arms are more compact.

Abstract. The Tropospheric Monitoring Instrument (TROPOMI) spectrometer is the single payload of the Copernicus Sentinel 5 Precursor (S5P) mission. It measures Earth radiance spectra in the shortwave infrared spectral range around 2.3 µm with a dedicated instrument module. These measurements provide carbon monoxide (CO) total column densities over land, which for clear sky conditions are highly sensitive to the tropospheric boundary layer. For cloudy atmospheres over land and ocean, the column sensitivity changes according to the light path through the atmosphere. In this study, we present the physics-based operational S5P algorithm to infer atmospheric CO columns satisfying the envisaged accuracy (< 15 %) and precision (< 10 %) both for clear sky and cloudy observations with low cloud height. Here, methane absorption in the 2.3 µm range is combined with methane abundances from a global chemical transport model to infer information on atmospheric scattering. For efficient processing, we deploy a linearized two-stream radiative transfer model as forward model and a profile scaling approach to adjust the CO abundance in the inversion. Based on generic measurement ensembles, including clear sky and cloudy observations, we estimated the CO retrieval precision to be ≤ 11 % for surface albedo ≥ 0.03 and solar zenith angle ≤ 70 • . CO biases of ≤ 3 % are introduced by inaccuracies in the methane a priori knowledge. For strongly enhanced CO concentrations in the tropospheric boundary layer and for cloudy conditions, CO errors in the order of 8 % can be introduced by the retrieval of cloud parameters of our algorithm. Moreover, we estimated the effect of a distorted spectral instrument response due to the inhomogeneous illumination of the instrument entrance slit in the flight direction to be < 2 % with pseudo-random characteristics when averaging over space and time. Finally, the CO data exploitation is demonstrated for a TROPOMI orbit of simulated shortwave infrared measurements. Overall, the study demonstrates that for an instrument that performs in compliance with the pre-flight specifications, the CO product will meet the required product performance well.

[1] Over the past decade the development of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) retrievals has increased the interest in the use of satellite measurements for studying the global sources and sinks of methane. Meanwhile, measurements are becoming available from the more advanced Greenhouse Gases Observing Satellite (GOSAT). The aim of this study is to investigate the application of GOSAT retrievals to inverse modeling, for which we make use of the TM5-4DVAR inverse modeling framework. Inverse modeling calculations are performed using data from two different retrieval approaches: a full physics and a lightpath proxy ratio method. The performance of these inversions is analyzed in comparison with inversions using SCIAMACHY retrievals and measurements from the National Oceanic and Atmospheric Administration-Earth System Research Laboratory flask-sampling network. In addition, we compare the inversion results against independent surface, aircraft, and total-column measurements. Inversions with GOSAT data show good agreement with surface measurements, whereas for SCIAMACHY a similar performance can only be achieved after significant bias corrections. Some inconsistencies between surface and total-column methane remain in the Southern Hemisphere. However, comparisons with measurements from the Total Column Carbon Observing Network in situ Fourier transform spectrometer network indicate that those may be caused by systematic model errors rather than by shortcomings in the GOSAT retrievals. The global patterns of methane emissions derived from SCIAMACHY (with bias correction) and GOSAT retrievals are in remarkable agreement and allow an increased resolution of tropical emissions. The satellite inversions increase tropical methane emission by 30 to 60 Tg CH 4 /yr compared to initial a priori estimates, partly counterbalanced by reductions in emissions at midlatitudes to high latitudes.