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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]

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]

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 Copernicus Atmosphere Monitoring Service (CAMS) has recently produced a greenhouse gas reanalysis (version egg4) that covers almost 2 decades from 2003 to 2020 and which will be extended in the future. This reanalysis dataset includes carbon dioxide (CO 2) and methane (CH 4). 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 to point out deficiencies to the user. The greenhouse gas reanalysis can be used to examine the impact of atmospheric greenhouse gas concentrations on climate change (such as global and regional climate radiative forcing), assess intercontinental transport, and serve as boundary conditions for regional simulations, among other applications and scientific uses. The caveats associated with changes in assimilated observations and fixed underlying emissions are highlighted, as is their impact on the estimation of trends and annual growth rates of these long-lived greenhouse gases. [ABSTRACT FROM AUTHOR]

Several single-platform satellite missions have been designed during the past decades in order to retrieve the atmospheric concentrations of anthropogenic greenhouse gases (GHG), initiating worldwide efforts towards better monitoring of their sources and sinks. To set up a future operational system for anthropogenic GHG emission monitoring, both revisit frequency and spatial resolution need to be improved. The Space Carbon Observatory (SCARBO) project aims at significantly increasing the revisit frequency of spaceborne GHG measurements, while reaching state-of-the-art precision requirements, by implementing a concept of small satellite constellation. It would accommodate a miniaturised GHG sensor named NanoCarb coupled with an aerosol instrument, the multi-angle polarimeter SPEXone. More specifically, the NanoCarb sensor is a static Fabry–Pérot imaging interferometer with a 2.3×2.3 km 2 spatial resolution and 200 km swath. It samples a truncated interferogram at optical path differences (OPDs) optimally sensitive to all the geophysical parameters necessary to retrieve column-averaged dry-air mole fractions of CO 2 and CH 4 (hereafter XCO2 and XCH4). In this work, we present the Level 2 performance assessment of the concept proposed in the SCARBO project. We perform inverse radiative transfer to retrieve XCO2 and XCH4 directly from synthetic NanoCarb truncated interferograms and provide their systematic and random errors, column vertical sensitivities, and degrees of freedom as a function of five scattering-error-critical atmospheric and observational parameters. We show that NanoCarb XCO2 and XCH4 systematic retrieval errors can be greatly reduced with SPEXone posterior outputs used as improved prior aerosol constraints. For two-thirds of the soundings, located at the centre of the 200 km NanoCarb swath, XCO2 and XCH4 random errors span 0.5–1 ppm and 4–6 ppb, respectively, compliant with their respective 1 ppm and 6 ppb precision objectives. Finally, these Level 2 performance results are parameterised as a function of the explored scattering-error-critical atmospheric and observational parameters in order to time-efficiently compute extensive L2 error maps for future CO 2 and CH 4 flux estimation performance studies. [ABSTRACT FROM AUTHOR]

The thermal infrared nadir spectra of IASI (Infrared Atmospheric Sounding Interferometer) are successfully used for retrievals of different atmospheric trace gas profiles. However, these retrievals offer generally reduced information about the lowermost tropospheric layer due to the lack of thermal contrast close to the surface. Spectra of scattered solar radiation observed in the near-infrared and/or shortwave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument), offer higher sensitivity near the ground and are used for the retrieval of total-column-averaged mixing ratios of a variety of atmospheric trace gases. Here we present a method for the synergetic use of IASI profile and TROPOMI total-column level 2 retrieval products. Our method uses the output of the individual retrievals and consists of linear algebra a posteriori calculations (i.e. calculation after the individual retrievals). We show that this approach has strong theoretical similarities to applying the spectra of the different sensors together in a single retrieval procedure but with the substantial advantage of being applicable to data generated with different individual retrieval processors, of being very time efficient, and of directly benefiting from the high quality and most recent improvements of the individual retrieval processors. We demonstrate the method exemplarily for atmospheric methane (CH 4). We perform a theoretical evaluation and show that the a posteriori combination method yields a total-column-averaged CH 4 product (XCH 4) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the high-quality upper troposphere–lower stratosphere (UTLS) CH 4 partial-column information of the corresponding IASI product. As a consequence, the combined product offers additional sensitivity for the tropospheric CH 4 partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effect is verified by comparisons to CH 4 reference data obtained from collocated XCH 4 measurements at 14 globally distributed TCCON (Total Carbon Column Observing Network) stations, CH 4 profile measurements made by 36 individual AirCore soundings, and tropospheric CH 4 data derived from continuous ground-based in situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. The comparisons clearly demonstrate that the combined product can reliably detect the actual variations of atmospheric XCH 4 , CH 4 in the UTLS, and CH 4 in the troposphere. A similar good reliability for the latter is not achievable by the individual TROPOMI and IASI products. [ABSTRACT FROM AUTHOR]

Based on advanced spectroscopic databases, line-by-line and layer-by-layer radiative transfer codes numerically solve the radiative transfer equation with very high accuracy. Taking advantage of its pre-calculated optical depth lookup table, the fast and accurate radiative transfer model Automatized Atmospheric Absorption Atlas OPerational (4A/OP) calculates the transmission and radiance spectra for a user-defined layered atmospheric model. Here, we present a module called 4A-Flux, which is developed and implemented into 4A/OP in order to include the calculation of the clear-sky longwave radiative flux profiles and heating rate profiles at a very high spectral resolution. Calculations are performed under the assumption of local thermodynamic equilibrium, a plane-parallel atmosphere, and specular reflection on the surface. The computation takes advantage of pre-tabulated exponential integral functions that are used instead of a classic angular quadrature. Furthermore, the sub-layer variation of the Planck function is implemented to better represent the emission of layers with a high optical depth. Thanks to the implementation of 4A-Flux, 4A/OP models have participated in the Radiative Forcing Model Intercomparison Project (RFMIP-IRF) along with other state-of-the-art radiative transfer models. 4A/OP hemispheric flux profiles are compared to other models over the 1800 representative atmospheric situations of RFMIP, yielding an outgoing longwave radiation (OLR) mean difference between 4A/OP and other models of -0.148 Wm-2 and a standard deviation of 0.218 Wm-2 , showing a good agreement between 4A/OP and other models. 4A/OP is applied to the Thermodynamic Initial Guess Retrieval (TIGR) atmospheric database to analyze the response of the OLR and vertical heating rate to several perturbations of temperature or gas concentration. This work shows that 4A/OP with 4A-Flux module can successfully be used to simulate accurate flux and heating rate profiles and provide useful sensitivity studies including sensitivities to minor trace gases such as HFC134a, HCFC22, and CFC113. We also highlight the interest for the modeling community to extend intercomparison between models to comparisons between spectroscopic databases and modeling to improve the confidence in model simulations. [ABSTRACT FROM AUTHOR]

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]

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]

MERLIN (MEthane Remote sensing LIdar missioN) is a Franco-German space mission designed to provide weighted columns of atmospheric methane through an inversion of the lidar signal using a priori information on the atmospheric state. Uncertainties about the meteorological parameters of the observed scene used in the ground segment contribute to the error budget on the retrieved methane column. With the LIDSIM (LIDar SIMulator) data simulator and the PROLID (PROcessor LIDar) inversion processor developed for MERLIN, we perform an impact experiment using ECMWF (European Centre for Medium Weather Range Forecast) ensemble forecast data. In addition, we estimate the standard deviation of the error in the methane column due to the meteorological uncertainties to be about 0.6 ppb. In addition, we innovate by discussing the impact of interpolations both in time and space, focusing on vertical extrapolations under the topography by using state-of-the-art methods to determine from the scatter between these methods the range in which the actual profile should be. We conclude that, in areas where the topography variations exceed 10 m over 10 km, an additional random error of 0.1 ppb is due to our lack of knowledge of the adjustment of atmospheric profiles to terrain. Finally, we point out that further work needs to be performed on temporal interpolation. Indeed, the 3 h time interpolation of atmospheric tides can create regional biases of up to 2 ppm (which is a major problem for models trying to identify methane sinks and sources). [ABSTRACT FROM AUTHOR]

Based on advanced spectroscopic databases, line-by-line and layer-by-layer radiative transfer codes numerically solve the radiative transfer equation with a very high accuracy. Taking advantage of its pre-calculated optical depth look-up table, the fast and accurate radiative transfer model Automatized Atmospheric Absorption Atlas OPerational (4A/OP) calculates the transmission and radiance spectra for a user defined layered atmospheric model. Here we present a module, called 4A-Flux, developed and implemented into 4A/OP in order to include the calculation of the clear-sky longwave radiative flux profiles and heating rate profiles at a very high spectral resolution. Calculations are performed under the assumption of local thermodynamic equilibrium, plane-parallel atmosphere and specular reflection on the surface. The computation takes advantage of pre-tabulated exponential integral functions that are used instead of a classic angular quadrature. Furthermore, the sublayer variation of the Planck function is implemented to better represent the emission of layers with a high optical depth. Thanks to the implementation of 4A-Flux, 4A/OP model have participated in the Radiative Forcing Model Intercomparison Project (RFMIP-IRF) along with other state-of-the-art radiative transfer models. 4A/OP hemispheric flux profiles are compared to other models over the 1800 representative atmospheric situations of RFMIP, yielding an Outgoing Longwave Radiation (OLR) mean difference between 4A/OP and other models of -0.148 W .m-2 and a mean standard deviation of 0.218 W .m-2, showing a good agreement between 4A/OP and other models. 4A/OP is applied to the Thermodynamic Initial Guess Retrieval (TIGR) atmospheric database to analyze the response of the OLR and vertical heating rate to several perturbations of temperature or gas concentration. This work shows that 4A/OP with 4A-Flux module can successfully be used to simulate accurate flux and heating rate profiles and provide useful sensitivity studies including sensitivities to minor trace gases such as HFC134a, HCFC22 and CFC113. We also highlight the interest for the modeling community to extend intercomparison between models to comparisons between spectroscopic databases and modelling to improve the confidence in model simulations. [ABSTRACT FROM AUTHOR]

Several single-platform satellite missions have been designed during the past decades in order to retrieve the atmospheric concentrations of anthropogenic greenhouse gases (GHG), initiating worldwide efforts towards better monitoring of their sources and sinks. To set up a future operational system for anthropogenic GHG emission monitoring, both revisit frequency and spatial resolution need to be improved. The Space CARBon Observatory (SCARBO) project aims at significantly increasing the revisit frequency of spaceborne GHG measurements, while reaching state-of-the-art precision requirements, by implementing a concept of small satellite constellation. It would accommodate a miniaturized GHG sensor named NanoCarb coupled with an aerosol instrument, the multi-angle polarimeter SPEXone. More specifically, the NanoCarb sensor is a static Fabry-Perot imaging interferometer with a 2.3 x 2.3 km² spatial resolution and 200 km swath. It samples a truncated interferogram at optical path differences (OPDs) optimally sensitive to all the geophysical parameters necessary to retrieve column-averaged dry-air mole fractions of CO2 and CH4 (hereafter XCO2 and XCH4). In this work, we present the Level 2 performance assessment of the concept proposed in the SCARBO project. We perform inverse radiative transfer to retrieve XCO2 and XCH4 directly from synthetic NanoCarb truncated interferograms, and provide their systematic and random errors, column vertical sensitivities and degrees of freedom as a function of five scattering error-critical atmospheric and observational parameters. We show that NanoCarb XCO2 and XCH4 systematic retrieval errors can be greatly reduced with SPEXone posterior outputs used as improved prior aerosol constraints. For two thirds of the soundings, located at the centre of the 200 km NanoCarb swath, XCO2 and XCH4 random errors span 0.5 – 1 ppm and 4 – 6 ppb, respectively, compliant with their respective 1-ppm and 6-ppb precision objectives. Finally, these Level 2 performance results are parameterized as a function of the explored scattering error-critical atmospheric and observational parameters in order to time-efficiently compute extensive L2 error maps for future CO2 and CH4 flux estimation performance studies. [ABSTRACT FROM AUTHOR]

A better understanding of greenhouse gas surface sources and sinks is required in order to address the global challenge of climate change. Space-borne remote estimations of greenhouse gas atmospheric concentrations can offer the global coverage that is necessary to improve the constraint on their fluxes, thus enabling a better monitoring of anthropogenic emissions. In this work, we introduce the Adaptable 4A Inversion (5AI) inverse scheme that aims to retrieve geophysical parameters from any remote sensing observation. The algorithm is based on the Optimal Estimation algorithm, relying on the Operational version of the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer forward model along with the Gestion et Étude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information (GEISA) spectroscopic database. Here, the 5AI scheme is applied to retrieve the column-averaged dry air mole fraction of carbon dioxide (XCO2) from a sample of measurements performed by the Orbiting Carbon Observatory-2 (OCO-2) mission. Those have been selected as a compromise between coverage and the lowest aerosol content possible, so that the impact of scattering particles can be neglected, for computational time purposes. For air masses below 3.0, 5AI XCO2 retrievals successfully capture the latitudinal variations of CO2 and its seasonal cycle and long-term increasing trend. Comparison with ground-based observations from the Total Carbon Column Observing Network (TCCON) yields a bias of 1.30±1.32 ppm (parts per million), which is comparable to the standard deviation of the Atmospheric CO2 Observations from Space (ACOS) official products over the same set of soundings. These nonscattering 5AI results, however, exhibit an average difference of about 3 ppm compared to ACOS results. We show that neglecting scattering particles for computational time purposes can explain most of this difference that can be fully corrected by adding to OCO-2 measurements an average calculated–observed spectral residual correction, which encompasses all the inverse setup and forward differences between 5AI and ACOS. These comparisons show the reliability of 5AI as an optimal estimation implementation that is easily adaptable to any instrument designed to retrieve column-averaged dry air mole fractions of greenhouse gases. [ABSTRACT FROM AUTHOR]

The thermal infrared nadir spectra of IASI (Infrared Atmospheric Sounding Interferometer) are successfully used for retrievals of different atmospheric trace gas profiles. However, these retrievals offer generally reduced information about the lowermost tropospheric layer due to the lack of thermal contrast close to the surface. Spectra of scattered solar radiation observed in the near and/or short wave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument) offer higher sensitivity near ground and are used for the retrieval of total column averaged mixing ratios of a variety of atmospheric trace gases. Here we present a method for the synergetic use of IASI profile and TROPOMI total column data. Our method uses the output of the individual retrievals and consists of linear algebra a posteriori calculations (i.e. calculation after the individual retrievals). We show that this approach is largely equivalent to applying the spectra of the different sensors together in a single retrieval procedure, but with the substantial advantage of being applicable to data generated with different individual retrieval processors, of being very time efficient, and of directly benefiting from the high quality and most recent improvements of the individual retrieval processors. We demonstrate the method exemplarily for atmospheric methane (CH4). We perform a theoretical evaluation and show that the a posteriori combination method yields a total column averaged CH4 product (XCH4) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the upper tropospheric and lower stratospheric (UTLS) CH4 partial column information of the corresponding IASI product. As consequence, the combined product offers in addition sensitivity for the tropospheric CH4 partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effects are verified by comparisons to CH4 reference data obtained from collocated XCH4 measurements at six globally distributed TCCON (Total Carbon Column Observing Network) stations, CH4 profile measurements made by 24 individual AirCore soundings, and lower tropospheric CH4 data derived from continuous ground-based in-situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. The comparisons clearly demonstrate that the combined product can reliably detect XCH4 signals and allows to distinguish between tropospheric and UTLS CH4 partial column averaged mixing ratios, which is not possible by the individual TROPOMI and IASI products. We find indications of a weak positive bias of about +1% of the combined lower tropospheric data product with respect to the references. For the UTLS CH4 partial columns we find no significant bias. [ABSTRACT FROM AUTHOR]

Changes in concentrations of greenhouse gases lead to changes in radiative fluxes throughout the atmosphere. The value of this change, the instantaneous radiative forcing, varies across climate models, due partly to differences in the distribution of clouds, humidity, and temperature across models and partly due to errors introduced by approximate treatments of radiative transfer. This paper describes an experiment within the Radiative Forcing Model Intercomparision Project that uses benchmark calculations made with line‐by‐line models to identify parameterization error in the representation of absorption and emission by greenhouse gases. Clear‐sky instantaneous forcing by greenhouse gases is computed using a set of 100 profiles, selected from a reanalysis of present‐day conditions, that represent the global annual mean forcing from preindustrial times to the present day with sampling errors of less than 0.01 W m−2. Six contributing line‐by‐line models agree in their estimate of this forcing to within 0.025 W m−2 while even recently developed parameterizations have typical errors 4 or more times larger, suggesting both that the samples reveal true differences among line‐by‐line models and that parameterization error will be readily identifiable. Agreement among line‐by‐line models is better in the longwave than in the shortwave where differing treatments of the water vapor continuum affect estimates of forcing by carbon dioxide and methane. The impacts of clouds on instantaneous radiative forcing are estimated from climate model simulations, and the adjustment due to stratospheric temperature changes estimated by assuming fixed dynamical heating. Adjustments are large only for ozone and for carbon dioxide, for which stratospheric cooling introduces modest nonlinearity. Key Points: Mean clear‐sky instantaneous radiative forcing by greenhouse gases is computed with six benchmark models using 100 atmospheric profilesSampling error is several times smaller than the level of disagreement among models, which is itself smaller than parameterization errorThe impacts of clouds and stratospheric adjustment are roughly estimated; adjustments are large only for carbon dioxide and ozone [ABSTRACT FROM AUTHOR]

A better understanding of greenhouse gas surface sources and sinks is required in order to address the global challenge of climate change. Spaceborne remote estimations of greenhouse gas atmospheric concentrations can offer the global coverage that is necessary to improve the constraint on their fluxes, thus enabling a better monitoring of anthropogenic emissions. In this work, we introduce the Adaptable 4A Inversion (5AI) inverse scheme that aims to retrieve geophysical parameters from any remote sensing observation. The algorithm is based on Bayesian optimal estimation relying on the Operational version of the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer forward model along with the Gestion et Étude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information (GEISA) spectroscopic database. Here, the 5AI scheme is applied to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from measurements performed by the Orbiting Carbon Observatory-2 (OCO-2) mission, and uses an empirically corrected absorption continuum in the O2 A-band. For airmasses below 3.0, XCO2 retrievals successfully capture the latitudinal variations of CO2, as well as its seasonal cycle and long-term increasing trend. Comparison with ground-based observations from the Total Carbon Column Observing Network (TCCON) yields a difference of 1.33 ± 1.29 ppm, which is similar to the standard deviation of the Atmospheric CO2 Observations from Space (ACOS) official products. We show that the systematic differences between 5AI and ACOS results can be fully removed by adding an average calculated - observed spectral residual correction to OCO-2 measurements, thus underlying the critical sensitivity of retrieval results to forward modelling. These comparisons show the reliability of 5AI as a Bayesian optimal estimation implementation that is easily adaptable to any instrument designed to retrieve column-averaged dry-air mole fractions of greenhouse gases. [ABSTRACT FROM AUTHOR]

Since the 1970s, results from radiative transfer models unambiguously show that an increase in the carbon dioxide (CO2) concentration leads to an increase of the greenhouse effect. However, this robust result is often misunderstood and often questioned. A common argument is that the CO2 greenhouse effect is saturated (i.e., does not increase) as CO2 absorption of an entire atmospheric column, named absorptivity, is saturated. This argument is erroneous first because absorptivity by CO2 is currently not fully saturated and still increases with CO2 concentration and second because a change in emission height explains why the greenhouse effect may increase even if the absorptivity is saturated. However, these explanations are only qualitative. In this article, we first propose a way of quantifying the effects of both the emission height and absorptivity and we illustrate which one of the two dominates for a suite of simple idealized atmospheres. Then, using a line-by-line model and a representative standard atmospheric profile, we show that the increase of the greenhouse effect resulting from an increase of CO2 from its current value is primarily due (about 90%) to the change in emission height. For an increase of water vapor, the change in absorptivity plays a more important role (about 40%) but the change in emission height still has the largest contribution (about 60%). [ABSTRACT FROM AUTHOR]

Methane (CH4) is the second strongest anthropogenic greenhouse gas after carbon dioxide (CO2) and is responsible for about 20 % of the warming induced by long-lived greenhouse gases since pre-industrial times. Oxidation by the hydroxyl radical (OH) is the dominant atmospheric sink for methane, contributing to approximately 90 % of the total methane loss. Chemical losses by reaction with atomic oxygen (O1D) and chlorine radicals (Cl) in the stratosphere are other sinks, contributing about 3 % to the total methane destruction. Moreover, the reaction with Cl is very fractionating, thus it has a much larger impact on δ13C-CH4 than the reaction with OH. In this paper, we assess the impact of atomic Cl on atmospheric methane mixing ratios, methane atmospheric loss and atmospheric δ13C-CH4. The offline version of the Global Circulation Model (GCM) LMDz, coupled to a chemistry module including the major methane chemical reactions, is run to simulate CH4 concentrations and δ13C-CH4 at the global scale. Atmospheric methane sink by Cl atoms in the stratosphere is found to be 7.32 ± 0.16 Tg/yr. Methane observations from vertical profiles obtained using AirCore samplers above 11 different locations across the globe and balloon measurements of δ13C-CH4 and methane are used to assess the impact of the Cl sink in the chemistry transport model. Above 10 km, the presence of Cl in the model is found to have only a small impact on the vertical profile of total methane but a major influence on δ13C-CH4 values, significantly improving the agreement between simulations and available observations. Stratospheric Cl is also found to have a substantial impact on surface δ13C-CH4 values, leading to a difference of +0.27 ‰ (less negative values) after a 19-year run. As a result, this study suggests that the Cl sink needs to be properly taken into account (magnitude and trends) in order to better understand trends in the atmospheric δ13C-CH4 signal when using atmospheric chemistry transport models for forward or inverse calculations. [ABSTRACT FROM AUTHOR]

The highly accurate measurements of the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) are used in numerical weather prediction (NWP), atmospheric chemistry and climate monitoring. As the second generation of the European Polar System (EPS-SG) is being developed, a new generation of IASI instruments has been designed to fly on board the MetOp-SG constellation: IASI New Generation (IASI-NG). In order to prepare the arrival of this new instrument, and to evaluate its impact on NWP and atmospheric chemistry applications, a set of IASI and IASING simulated data was built and made available to the public to set a common framework for future impact studies. This paper describes the information available in this database and the procedure followed to run the IASI and IASI-NG simulations. These simulated data were evaluated by comparing IASI-NG to IASI observations. The result is also presented here. Additionally, preliminary impact studies of the benefit of IASI-NG compared to IASI on the retrieval of temperature and humidity in a NWP framework are also shown in the present work. With a channel dataset located in the same wave numbers for both instruments, we showed an improvement of the temperature retrievals throughout the atmosphere, with a maximum in the troposphere with IASI-NG and a lower benefit for the tropospheric humidity. [ABSTRACT FROM AUTHOR]

In situ, airborne and satellite measurements are used to characterize the structure of water vapor in the lower tropical troposphere-below the height, $$z_*,$$ of the triple-point isotherm, $$T_*.$$ The measurements are evaluated in light of understanding of how lower-tropospheric water vapor influences clouds, convection and circulation, through both radiative and thermodynamic effects. Lower-tropospheric water vapor, which concentrates in the first few kilometers above the boundary layer, controls the radiative cooling profile of the boundary layer and lower troposphere. Elevated moist layers originating from a preferred level of convective detrainment induce a profile of radiative cooling that drives circulations which reinforce such features. A theory for this preferred level of cumulus termination is advanced, whereby the difference between $$T_*$$ and the temperature at which primary ice forms gives a 'first-mover advantage' to glaciating cumulus convection, thereby concentrating the regions of the deepest convection and leading to more clouds and moisture near the triple point. A preferred level of convective detrainment near $$T_*$$ implies relative humidity reversals below $$z*$$ which are difficult to identify using retrievals from satellite-borne microwave and infrared sounders. Isotopologues retrievals provide a hint of such features and their ability to constrain the structure of the vertical humidity profile merits further study. Nonetheless, it will likely remain challenging to resolve dynamically important aspects of the vertical structure of water vapor from space using only passive sensors. [ABSTRACT FROM AUTHOR]

The MEthane Remote sensing Lidar missioN (MERLIN) aims at demonstrating the spaceborne active measurement of atmospheric methane, a potent greenhouse gas, based on an Integrated Path Differential Absorption (IPDA) nadir-viewing LIght Detecting and Ranging (Lidar) instrument. MERLIN is a joint French and German space mission, with a launch currently scheduled for the timeframe 2021/22. The German Space Agency (DLR) is responsible for the payload, while the platform (MYRIADE Evolutions product line) is developed by the French Space Agency (CNES). The main scientific objective of MERLIN is the delivery of weighted atmospheric columns of methane dry-air mole fractions for all latitudes throughout the year with systematic errors small enough (<3.7 ppb) to significantly improve our knowledge of methane sources from global to regional scales, with emphasis on poorly accessible regions in the tropics and at high latitudes. This paper presents the MERLIN objectives, describes the methodology and the main characteristics of the payload and of the platform, and proposes a first assessment of the error budget and its translation into expected uncertainty reduction of methane surface emissions. [ABSTRACT FROM AUTHOR]

The highly accurate measurements of the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) are used in Numerical Weather Prediction (NWP), atmospheric chemistry and climate monitoring. As the second generation of the European Polar System (EPS-SG) is being developed, a new generation of IASI instruments has been designed to fly on board the MetOp-SG constellation: IASI New Generation (IASI-NG). In order to prepare the arrival of this new instrument, and to evaluate its impact on NWP and atmospheric chemistry applications, a set of IASI and IASI-NG simulated data was built and made available to the public to set a common framework for future impact studies. This paper describes the information available in this database and the procedure followed to run the IASI and IASI-NG simulations. These simulated data were evaluated by comparing IASI-NG to IASI observations. The result is also presented here. Additionally, preliminary impact studies of the benefit of IASI-NG compared to IASI on the retrieval of temperature and humidity in a NWP framework are also shown in the present work. With a channel dataset located in the same wave numbers for both instruments, we showed an improvement of the temperature retrievals along all the atmosphere with a maximum in the troposphere with IASI-NG and a lower benefit for the tropospheric humidity. [ABSTRACT FROM AUTHOR]

An original and innovative sampling system called AirCore was presented by NOAA in 2010 (Karion et al., 2010). It consists of a long ( >100 m) and narrow (<1 cm) stainless steel tube that can retain a profile of atmospheric air. The captured air sample has then to be analyzed with a gas analyzer for trace mole fraction. In this study, we introduce a new AirCore aiming to improve resolution along the vertical with the objectives to (i) better capture the vertical distribution of CO2 and CH4, (ii) provide a tool to compare Air- Cores and validate the estimated vertical resolution achieved by AirCores. This (high-resolution) AirCore-HR consists of a 300m tube, combining 200m of 0.125 in. (3.175 mm) tube and a 100m of 0.25 in. (6.35 mm) tube. This new configuration allows us to achieve a vertical resolution of 300m up to 15 km and better than 500m up to 22 km (if analysis of the retained sample is performed within 3 h). The AirCore-HR was flown for the first time during the annual StratoScience campaign from CNES in August 2014 from Timmins (Ontario, Canada). High-resolution vertical profiles of CO2 and CH4 up to 25 km were successfully retrieved. These profiles revealed well-defined transport structures in the troposphere (also seen in CAMS-ECMWF high-resolution forecasts of CO2 and CH4 profiles) and captured the decrease of CO2 and CH4 in the stratosphere. The multi-instrument gondola also carried two other low-resolution AirCore-GUF that allowed us to perform direct comparisons and study the underlying processing method used to convert the sample of air to greenhouse gases vertical profiles. In particular, degrading the AirCore-HR derived profiles to the low resolution of AirCore-GUF yields an excellent match between both sets of CH4 profiles and shows a good consistency in terms of vertical structures. This fully validates the theoretical vertical resolution achievable by AirCores. Concerning CO2 although a good agreement is found in terms of vertical structure, the comparison between the various AirCores yields a large and variable bias (up to almost 3 ppm in some parts of the profiles). The reasons of this bias, possibly related to the drying agent used to dry the air, are still being investigated. Finally, the uncertainties associated with the measurements are assessed, yielding an average uncertainty below 3 ppb for CH4 and 0.25 ppm for CO2 with the major source of uncertainty coming from the potential loss of air sample on the ground and the choice of the starting and ending point of the collected air sample inside the tube. In an ideal case where the sample would be fully retained, it would be possible to know precisely the pressure at which air was sampled last and thus to improve the overall uncertainty to about 0.1 ppm for CO2 and 2 ppb for CH4. [ABSTRACT FROM AUTHOR]

Mean age of stratospheric air can be derived from observations of sufficiently long-lived trace gases with approximately linear trends in the troposphere. Mean age can serve as a tracer to investigate stratospheric transport and long-term changes in the strength of the overturning Brewer- Dobson circulation of the stratosphere. For this purpose, a low-cost method is required in order to allow for regular observations up to altitudes of about 30 km. Despite the desired low costs, high precision and accuracy are required in order to determine mean age. We present balloonborne AirCore observations from two midlatitude sites: Timmins in Ontario/Canada and Lindenberg in Germany. During the Timmins campaign, five AirCores sampled air in parallel with a large stratospheric balloon and were analysed for CO2, CH4 and partly CO. We show that there is good agreement between the different AirCores (better than 0.1%), especially when vertical gradients are small. The measurements from Lindenberg were performed using small low-cost balloons and yielded very comparable results. We have used the observations to extend our long-term data set of mean age observations at Northern Hemisphere midlatitudes. The time series now covers more than 40 years and shows a small, statistically non-significant positive trend of 0.15±0.18 years decade-1. This trend is slightly smaller than the previous estimate of 0.24±0.22 years decade-1 which was based on observations up to the year 2006. These observations are still in contrast to strong negative trends of mean age as derived from some model calculations. [ABSTRACT FROM AUTHOR]

Mean age of stratospheric air can be derived from observations of sufficiently long lived trace gases with approximately linear trends in the troposphere. Mean age can serve as a tracer to investigate stratospheric transport and long term changes in the strength of the overturning Brewer-Dobson circulation of the stratosphere. For this purpose, a low-cost method is required in order to allow for regular observations up to altitudes of about 30 km. Despite the desired low costs, high precision and accuracy are required in order to allow determination of mean age. We present balloon borne AirCore observations from two mid latitude sites: Timmins in Ontario/Canada and Lindenberg in Germany. During the Timmins campaign five AirCores sampled air in parallel from a large stratospheric balloon and were analysed for CO2, CH4 and partly CO. We show that there is good agreement between the different AirCores (better than 0.1 %) especially when vertical gradients are small. The measurements from Lindenberg were performed using small low-cost balloons and yielded very comparable results. We have used the observations to extend our long term data set of mean age observations at Northern Hemi-sphere mid latitudes. The time series now covers more than 40 years and shows a small, statis-tically not significant positive trend of 0.15 ± 0.18 years/decade. This trend is slightly smaller than the previous estimate of 0.24 ± 0.22 years/decade which was based on observations up to the year 2006. These observations are still in contrast to strong negative trends of mean age as derived from some model calculations. [ABSTRACT FROM AUTHOR]

An original and innovative sampling system called AirCore was presented by NOAA in 2010 (Karion et al., 2010). It consists of a long (> 100 m) and narrow (< 1 cm) stainless steel tube that can retain a profile of atmospheric air. The captured air sample has then to be analyzed with a gas analyzer for trace mole fraction. In this study, we introduce a new AirCore aiming at improved resolution along the vertical with the objectives to: (i) better capture the vertical distribution of CO2 and CH4, (ii) provide a tool to compare AirCores and validate the estimated vertical resolution achieved by AirCores. This AirCore-HR (high resolution) consists of a 300 m tube, combining 200 m of 1/8 in. (3.175 mm) tube and a 100 m of 1/4 in. (6.35 mm) tube. This new configuration allows to achieve a vertical resolution of 300 m up to 15 km and better than 500 m up to 22 km (if analysis of the retained sample is performed within 3 hours). The AirCore-HR was flown for the first time during the annual StratoScience campaign from CNES in August 2014 from Timmins (Ontario, Canada). High-resolution vertical profiles of CO2 and CH4 up to 25 km were successfully retrieved. These profiles revealed well defined transport structures in the troposphere (also seen in CAMS-ECMWF high resolution forecasts of CO2 and CH4 profiles) and captured the decrease of CO2 and CH4 in the stratosphere. The multi-instruments gondola from the flight carried two other low-resolution AirCore-GUF that allowed to perform direct comparisons and study the underlying processing method used to convert the sample of air to greenhouse gases vertical profiles. In particular, degrading the AirCore-HR derived profiles to the low resolution of AirCore-GUF yields an excellent match between both sets of CH4 profiles, and shows a good consistency between vertical structures of CO2 and CH4. These results fully validate the theoretical vertical resolution achievable by AirCores. Finally, the uncertainties associated with the measurements are assessed, yielding an average uncertainty below 3 ppb for CH4 and 0.25 ppm for CO2 with the major source of uncertainty coming from the potential loss of air sample on the ground and the choice of the starting and ending point of the collected air sample inside the tube. In an ideal case where the sample would be fully retained, it would be possible to know precisely the pressure at which air was sampled last and thus to improve the overall uncertainty to about 0.1 ppm for CO2 and 2 ppb for CH4. [ABSTRACT FROM AUTHOR]

The Infrared Atmospheric Sounding Interferometer (IASI) forms the main infrared sounding component of the European Organisation for the Exploitation of Meteorological Satellites's (EUMETSAT's) Meteorological Operation (MetOp)-A satellite (Klaes et al. 2007), which was launched in October 2006. This article presents the results of the first 4 yr of the operational IASI mission. The performance of the instrument is shown to be exceptional in terms of calibration and stability. The quality of the data has allowed the rapid use of the observations in operational numerical weather prediction (NWP) and the development of new products for atmospheric chemistry and climate studies, some of which were unexpected before launch. The assimilation of IASI observations in NWP models provides a significant forecast impact; in most cases the impact has been shown to be at least as large as for any previous instrument. In atmospheric chemistry, global distributions of gases, such as ozone and carbon monoxide, can be produced in near-real time, and short-lived species, such as ammonia or methanol, can be mapped, allowing the identification of new sources. The data have also shown the ability to track the location and chemistry of gaseous plumes and particles associated with volcanic eruptions and fires, providing valuable data for air quality monitoring and aircraft safety. IASI also contributes to the establishment of robust long-term data records of several essential climate variables. The suite of products being developed from IASI continues to expand as the data are investigated, and further impacts are expected from increased use of the data in NWP and climate studies in the coming years. The instrument has set a high standard for future operational hyperspectral infrared sounders and has demonstrated that such instruments have a vital role in the global observing system. [ABSTRACT FROM AUTHOR]

We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V is specifically designed to address the consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700-2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures' carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process-based mode! suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO2 concentration, nutrients availability, and climate. [ABSTRACT FROM AUTHOR]

An ocean model has been forced with NCEP reanalysis fluxes over 1948-2003 to evaluate the pathways and timescales associated with the uptake of anthropogenic CO2 over the North Pacific. The model reveals that there are two principal regions of uptake, the first in the region bounded by 35-45°N and 140-180°E, and the second along a band between 10-20°N and between 120°W and 180°E. For both of these regions, the dominant timescale of variability in uptake is seasonal, with maximum uptake occurring during winter and uptake being close to zero or slightly negative during summer when integrated over the basin. A decadal trend toward increased uptake of anthropogenic CO2 consists largely of modulations of the uptake maximum in winter. For detection of anthropogenic changes, this implies that in situ measurements will need to resolve the seasonal cycle in order to capture decadal trends in ΔpCO2. As uptake of anthropogenic CO2 occurs preferentially during winter, observationally based estimates which do not resolve the full seasonal cycle may result in underestimates of the rate of uptake of anthropogenic CO2. There is also a sizable circulation-driven decadal trend in the seasonal cycle of sea surface ΔpCO2 for the North Pacific, with maximum changes found near the boundary separating the subtropical and subpolar gyres in western and central regions of the basin. These changes are due to a trend in the large-scale circulation of the gyres, which itself is driven by a trend in the wind stress over the basin scale. This trend in the three-dimensional circulation is more important than the local trend in mixed layer depth (MLD) in contributing to the decadal trend in ΔpCO2. [ABSTRACT FROM AUTHOR]

In order to exploit the upcoming regular measurements of vertical carbon dioxide (CO2) profiles over North America implemented in the framework of the North American Carbon Program (NACP), we design a direct carbon budgeting approach to infer carbon sources and sinks over the continent using model simulations. Direct budgeting puts a control volume on top of North America, balances air mass in- and outflows into the volume and solves for the surface fluxes. The flows are derived from the observations through a geostatistical interpolation technique called Kriging combined with transport fields from weather analysis. The use of CO2 vertical profiles simulated by the atmospheric transport model MOZART-2 at the planned 19 stations of the NACP network has given an estimation of the error of 0.39 GtC yr−1 within the model world. Reducing this error may be achieved through a better estimation of mass fluxes associated with convective processes affecting North America. Complementary stations in the north-west and the north-east are also needed to resolve the variability of CO2 in these regions. For instance, the addition of a single station near 52°N; 110°W is shown to decrease the estimation error to 0.34 GtC yr−1. [ABSTRACT FROM AUTHOR]

In the context of MERLIN (MEthane Remote LIdar missioN), a French–German spatial lidar mission dedicated to monitoring the atmospheric methane content, two software programs have been developed: LIDSIM (LIDar SIMulator) and PROLID (PROcessor LIDar). The objectives are to assess whether the instrument design meets the performance requirements and to study the sensitivity of this performance to geophysical parameters. LIDSIM is an end-to-end mission simulator and PROLID is a retrieval processor that provides mole fractions of methane in dry air, averaged over an atmospheric column. These two tools are described in this paper. Results of the validation tests and the first full orbit simulations are reported. Merlin target performance does not seem to be reachable but breakthrough performance is reached. [ABSTRACT FROM AUTHOR]

In the context of the FrenchGerman space lidar mission MERLIN (MEthane Remote LIdar missioN) dedicated to the determination of the atmospheric methane content, an end-to-end mission simulator is being developed. In order to check whether the instrument design meets the performance requirements, simulations have to count all the sources of noise on the measurements like the optical energy variability induced by speckle. Speckle is due to interference as the lidar beam is quasi monochromatic. Speckle contribution to the error budget has to be estimated but also simulated. In this paper, the speckle theory is revisited and applied to MERLIN lidar and also to the DLR (Deutsches Zentrum für Luft und Raumfahrt) demonstrator lidar CHARM-F. Results show: on the signal path, speckle noise depends mainly on the size of the illuminated area on ground; on the solar flux, speckle is fully negligible both because of the pixel size and the optical filter spectral width; on the energy monitoring path a decorrelation mechanism is needed to reduce speckle noise on averaged data. Speckle noises for MERLIN and CHARM-F can be simulated by Gaussian noises with only one random draw by shot separately for energy monitoring and signal paths. [ABSTRACT FROM AUTHOR]

MEthane Remote LIdar missioN (MERLIN) is a German‐French space mission, scheduled for launch in 2024 and built around an innovative light detecting and ranging instrument that will retrieve methane atmospheric weighted columns. MERLIN products will be assimilated into chemistry transport models to infer methane emissions and sinks. Here the expected performance of MERLIN to reduce uncertainties on methane emissions is estimated. A first complete error budget of the mission is proposed based on an analysis of the plausible causes of random and systematic errors. Systematic errors are spatially and temporally distributed on geophysical variables and then aggregated into an ensemble of 32 scenarios. Observing System Simulation Experiments are conducted, originally carrying both random and systematic errors. Although relatively small (±2.9 ppb), systematic errors are found to have a larger influence on MERLIN performances than random errors. The expected global mean uncertainty reduction on methane emissions compared to the prior knowledge is found to be 32%, limited by the impact of systematic errors. The uncertainty reduction over land reaches 60% when the largest desert regions are removed. At the latitudinal scale, the largest uncertainty reductions are achieved for temperate regions (84%) and then tropics (56%) and high latitudes (53%). Similar Observing System Simulation Experiments based on error scenarios for Greenhouse Gases Observing SATellite reveal that MERLIN should perform better than Greenhouse Gases Observing SATellite for most continental regions. The integration of error scenarios for MERLIN in another inversion system suggests similar results, albeit more optimistic in terms of uncertainty reduction. Plain Language Summary: Atmospheric methane is the second most important anthropogenic greenhouse gas. Its evolution in the atmosphere reflects the balance between its emissions and its sinks, both being still very uncertain. Observations and models are necessary to improve this situation and reduce the uncertainties associated to the global methane cycle, which is critical considering climate change. In this context, the MEthane Remote LIdar missioN (MERLIN) German‐French space satellite mission, scheduled for launch in 2023, will retrieve methane atmospheric columns. MERLIN products will be integrated into atmospheric models to improve estimates of methane emissions and sinks. In this paper, we establish the first complete error budget of the future MERLIN instrument and use it to estimate the reduction of uncertainties on methane emissions that can be expected once the satellite is launched. The two main findings are that the uncertainties should be reduced on average by 60% over land, where most methane emissions are located, and that MERLIN should perform better than the main methane sounder currently on orbit for most continental regions. Key Points: MERLIN is a German‐French space mission, scheduled for launch in 2023 that will retrieve methane atmospheric weighted columnsThe expected performances of MERLIN products to improve the estimation of methane emissions is assessedMERLIN should improve estimates of continental‐scale methane emissions by 60%, performing better than GOSAT for most regions [ABSTRACT FROM AUTHOR]