[1] Precision requirements are determined for space-based column-averaged CO 2 dry air mole fraction (X CO 2 ) data. These requirements result from an assessment of spatial and temporal gradients in X CO 2 , the relationship between X CO 2 precision and surface CO 2 flux uncertainties inferred from inversions of the X CO 2 data, and the effects of X CO 2 biases on the fidelity of CO 2 flux inversions. Observational system simulation experiments and synthesis inversion modeling demonstrate that the Orbiting Carbon Observatory mission design and sampling strategy provide the means to achieve these X CO 2 data precision requirements.

[1] The objective, design, and implementation of the OCO inverse method are presented. The inverse method is the algorithm which finds the profile-weighted mean mixing ratio, X CO2 , which best fits the measured spectrum, given a ''forward model'' which calculates the spectrum for a given atmospheric state, surface, and instrument properties. Minimizing bias among comparative values of X CO2 is a critical objective. The algorithm uses an ''optimal,'' maximum a posteriori inverse method, with weak a priori constraint, and employs a state vector containing atmospheric and surface properties expected to vary significantly between soundings. An extensive operational characterization and error analysis will be employed, producing quantities designed to aid atmospheric modelers in use of the OCO data. In particular, comparison to inverse models of surface CO 2 flux will require use of the OCO column averaging kernel and a priori state vector. An off-line error analysis has also been developed for more detailed error studies, and its use is illustrated by prospective application to case studies of nadir observations in summer and winter at three sites. Uncertainties due to noise, geophysical variability, and spectroscopic parameters are considered in detail. At low and midlatitudes, the single-sounding errors due to these sources are expected to be $0.7-0.8 ppm for high-sun conditions and $1.5-2.5 ppm for low sun (winter). Errors from the same sources in semimonthly regional averages are predicted to be <1 ppm for all conditions.

We report new short‐wave infrared (SWIR) column retrievals of atmospheric methane (XCH4) from the Japanese Greenhouse Gases Observing SATellite (GOSAT) and compare observed spatial and temporal variations with correlative ground‐based measurements from the Total Carbon Column Observing Network (TCCON) and with the global 3‐D GEOS‐Chem chemistry transport model. GOSAT XCH4 retrievals are compared with daily TCCON observations at six sites between April 2009 and July 2010 (Bialystok, Park Falls, Lamont, Orleans, Darwin and Wollongong). GOSAT reproduces the site‐dependent seasonal cycles as observed by TCCON with correlations typically between 0.5 and 0.7 with an estimated single‐sounding precision between 0.4–0.8%. We find a latitudinal‐dependent difference between the XCH4 retrievals from GOSAT and TCCON which ranges from 17.9 ppb at the most northerly site (Bialystok) to −14.6 ppb at the site with the lowest latitude (Darwin). We estimate that the mean smoothing error difference included in the GOSAT to TCCON comparisons can account for 15.7 to 17.4 ppb for the northerly sites and for 1.1 ppb at the lowest latitude site. The GOSAT XCH4 retrievals agree well with the GEOS‐Chem model on annual (August 2009 – July 2010) and monthly timescales, capturing over 80% of the zonal variability. Differences between model and observed XCH4 are found over key source regions such as Southeast Asia and central Africa which will be further investigated using a formal inverse model analysis.

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

Abstract. We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4 • × 5 • and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a −1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a −1 , as compared to 24.9-27.0 Tg a −1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a −1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern-central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29-44 % of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, Published by Copernicus Publications on behalf of the European Geosciences Union.