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Satellites have been providing spaceborne observations of the total column of CO2 (denoted XCO2) for over two decades now, and, with the need for independent verification of Paris Agreement objectives, many new satellite concepts are currently planned or being studied to complement or extend the instruments that already exist. Depending on whether they are targeting natural and/or anthropogenic fluxes of CO2 , the designs of these future concepts vary greatly. The characteristics of their shortwave infrared (SWIR) observations notably explore several orders of magnitude in spectral resolution (from λ/Δλ ∼ 400 for Carbon Mapper to λ/Δλ ∼ 25 000 for MicroCarb) and include different selections of spectral bands (from one to four bands, among which there are the CO2 -sensitive 1.6 µm and/or 2.05 µm bands). The very nature of the spaceborne measurements is also explored: for instance, the NanoCarb imaging concept proposes to measure CO2 -sensitive truncated interferograms, instead of infrared spectra like other concepts, in order to significantly reduce the instrument size. This study synthetically explores the impact of three different design parameters on the XCO2 retrieval performance obtained through optimal estimation: (1) the spectral resolution, (2) the signal-to-noise ratio (SNR) and (3) the spectral band selection. Similar performance assessments are completed for the exactly defined OCO-2, MicroCarb, Copernicus CO2 Monitoring (CO2M) and NanoCarb concepts. We show that improving the SNR is more efficient than improving the spectral resolution to increase XCO2 precision when perturbing these parameters across 2 orders of magnitude, and we find that a low SNR and/or a low spectral resolution yield XCO2 with vertical sensitivities that give more weight to atmospheric layers close to the surface. The exploration of various spectral band combinations illustrates, especially for lower spectral resolutions, how including an O2 -sensitive band helps to increase the optical path length information and how the 2.05 µm CO2 -sensitive band contains more geophysical information than the 1.6 µm band. With very different characteristics, MicroCarb shows a CO2 information content that is only slightly higher than that of CO2M , which translates into XCO2 random errors that are lower by a factor ranging from 1.1 to 1.9, depending on the observational situation. The performance of NanoCarb for a single pixel of its imager is comparable to those of concepts that measure spectra at low SNR and low spectral resolution, but, as this novel concept would observe a given target several times during a single overpass, its performance improves when combining all the observations. Overall, the broad range of results obtained through this synthetic XCO2 performance mapping hint at the future intercomparison challenges that the wide variety of upcoming CO2 -observing concepts will pose. [ABSTRACT FROM AUTHOR]

Following the recent Global Carbon Project (GCP) synthesis of the decadal methane (CH4) budget over 2000-2012 (Saunois et al., 2016), we analyse here the same dataset with a focus on quasi-decadal and inter-annual variability in CH4 emissions. The GCP dataset integrates results from top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models (including process-based models for estimating land surface emissions and atmospheric chemistry), inventories of anthropogenic emissions, and data-driven approaches. The annual global methane emissions from top-down studies, which by construction match the observed methane growth rate within their uncertainties, all show an increase in total methane emissions over the period 2000-2012, but this increase is not linear over the 13 years. Despite differences between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total methane emissions over the period 2000-2006, during the plateau of atmospheric methane mole fractions, and also over the period 2008-2012, during the renewed atmospheric methane increase. However, the top-down ensemble mean produces an emission shift between 2006 and 2008, leading to 22 [16-32]Tg CH4yr-1 higher methane emissions over the period 2008-2012 compared to 2002-2006. This emission increase mostly originated from the tropics, with a smaller contribution from mid-latitudes and no significant change from boreal regions. The regional contributions remain uncertain in top-down studies. Tropical South America and South and East Asia seem to contribute the most to the emission increase in the tropics. However, these two regions have only limited atmospheric measurements and remain therefore poorly constrained. The sectorial partitioning of this emission increase between the periods 2002-2006 and 2008-2012 differs from one atmospheric inversion study to another. However, all top-down studies suggest smaller changes in fossil fuel emissions (from oil, gas, and coal industries) compared to the mean of the bottom-up inventories included in this study. This difference is partly driven by a smaller emission change in China from the top-down studies compared to the estimate in the Emission Database for Global Atmospheric Research (EDGARv4.2) inventory, which should be revised to smaller values in a near future. We apply isotopic signatures to the emission changes estimated for individual studies based on five emission sectors and find that for six individual top-down studies (out of eight) the average isotopic signature of the emission changes is not consistent with the observed change in atmospheric 13CH4. However, the partitioning in emission change derived from the ensemble mean is consistent with this isotopic constraint. At the global scale, the top-down ensemble mean suggests that the dominant contribution to the resumed atmospheric CH4 growth after 2006 comes from microbial sources (more from agriculture and waste sectors than from natural wetlands), with an uncertain but smaller contribution from fossil CH4 emissions. In addition, a decrease in biomass burning emissions (in agreement with the biomass burning emission databases) makes the balance of sources consistent with atmospheric 13CH4 observations. In most of the top-down studies included here, OH concentrations are considered constant over the years (seasonal variations but without any inter-annual variability). As a result, the methane loss (in particular through OH oxidation) varies mainly through the change in methane concentrations and not its oxidants. For these reasons, changes in the methane loss could not be properly investigated in this study, although it may play a significant role in the recent atmospheric methane changes as briefly discussed at the end of the paper.

To assess the accuracy of satellite monitoring of anthropogenic CO 2 emissions, inversions of satellite data in SWIR are usually combined with the assimilation of the total CO 2 column into a Kalman filter that reconstructs the sources and sinks of atmospheric CO 2 . To provide error estimates of the total CO 2 column for multi-month assimilation experiments of simulated satellite data, we parametrise these errors using linear regressions. These regression are obtained from a database that links meteorological situations, albedos, and aerosols to the errors in the inversion of the total CO 2 column based on simulated satellite data for those conditions. The errors in this database are explicitly computed using the Bayesian estimation formalism, and the linear regressions are optimised by selecting appropriate predictors and predictants. For different levels of measurement noise, error simulations are performed over a period of several months using the albedo and aerosol data from MODIS. [ABSTRACT FROM AUTHOR]

Abstract. The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (~biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (T-D, exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories, and data-driven approaches (B-U, including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by T-D inversions at 558 Tg CH4 yr−1 (range [540–568]). About 60 % of global emissions are anthropogenic (range [50–65 %]). B-U approaches suggest larger global emissions (736 Tg CH4 yr−1 [596–884]) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the T-D budget, it is likely that some of the individual emissions reported by the B-U approaches are overestimated, leading to too large global emissions. Latitudinal data from T-D emissions indicate a predominance of tropical emissions (~64 % of the global budget,

Satellites have been providing spaceborne observations of the total column of CO2 (noted xco2) for over two decades now and, with the need for independent verification of Paris Agreement objectives, many new satellite concepts are currently planned or being studied to complement or extend the already existing instruments. Depending on whether they are targeting natural and/or anthropogenic fluxes of CO2, the design of these future concepts vary greatly. The characteristics of their shortwave infrared (SWIR) observations notably explore several orders of magnitude in spectral resolution (from λ/Δλ~400 for Carbon Mapper to λ/Δλ~25000 for MicroCarb) and include different selections of spectral bands (from one to four bands, among which the CO2-sensitive 1.6 µm and/or 2.05 µm bands). Besides, the very nature of the spaceborne measurements is also explored: for instance, the NanoCarb imaging concept proposes to measure CO2-sensitive truncated interferograms, instead of infrared spectra as other concepts, in order to significantly reduce the instrument size. This study synthetically explores the impact of three different design parameters on xco2 retrieval performance, as obtained through Optimal Estimation: (1) the spectral resolution; (2) the signal-to-noise ratio (SNR) and (3) the spectral band selection. Similar performance assessments are completed for the exactly-defined MicroCarb, Copernicus CO2 Monitoring (CO2M) and NanoCarb concepts. We show that improving SNR is more efficient than improving spectral resolution to increase xco2 precision when perturbating these parameters across two orders of magnitude, and that low-SNR and/or low spectral resolution yield xco2 with vertical sensitivities giving more weight to atmospheric layers close to the surface. The exploration of various spectral band combinations illustrates, especially for lower spectral resolutions, how including an O2- sensitive band helps to increase optical path length information, and how the 2.05 µm CO2-sensitive band contains more geophysical information than the 1.6 µm band. With very different characteristics, MicroCarb shows a CO2 information content only slightly higher than CO2M, which translates into lower xco2 random errors, by a factor ranging from 1.1 to 1.9 depending on the observational situation. The NanoCarb performance for a single pixel of its imager compares to concepts that measure spectra at low-SNR and low-spectral resolution but, as this novel concept would observe a given target several times during a single overpass, its performance improves when combining all the observations. Overall, the broad range of results obtained through this synthetic xco2 performance mapping hints at the future intercomparison challenges that the wide variety of upcoming CO2-observing concepts will pose. [ABSTRACT FROM AUTHOR]

The MEthane Remote sensing Lidar missioN (MERLIN), currently in phase C, is a joint cooperation between France and Germany on the development of a spatial Integrated Path Differential Absorption (IPDA) LIDAR (LIght Detecting And Ranging) to conduct global observations of atmospheric methane. This presentation will focus on the status of a LIDAR mission data simulator and processor developed at LMD (Laboratoire de Météorologie Dynamique), Ecole Polytechnique, France, for MERLIN to assess the performances in realistic observational situations.

The Copernicus Atmosphere Monitoring Service has recently produced a greenhouse gases reanalysis (version egg4) that covers almost two decades from 2003 to 2020 and will be extended in the future. This reanalysis dataset includes carbon dioxide (CO2) and methane (CH4). The reanalysis procedure combines model data with satellite data into a globally complete and consistent dataset using the European Centre for Medium-range Weather Forecasts' Integrated Forecasting System (IFS). This dataset has been carefully evaluated against independent observations to ensure validity and point out deficiencies to the user. The greenhouse gas reanalysis can be used to examine the impact of atmospheric greenhouse gases concentrations on climate change, such as global and regional climate radiative forcing, assess intercontinental transport, and also serve as boundary conditions for regional simulations, among other applications and scientific studies. The caveats associated with changes in assimilated observations and fixed underlying emissions are highlighted, as well as their impact on the estimation of trends and annual growth rates of these long-lived greenhouse gases. [ABSTRACT FROM AUTHOR]