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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]

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. 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]

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]

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]

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]

Carbon dioxide (CO2) and methane (CH4) are the two main greenhouse gases (GHG)emitted by human activities. To better understand their concentration and vertical distributionin several key regions and to prepare future space missions dedicated to GHG, the MAGICinitiative has been put in place. MAGIC stands for: Monitoring of Atmospheric compositionand Greenhouse gases through multi-Instruments Campaigns. Gathering about 40 scientistsall together, the campaigns have two main goals: (i) to better understand the vertical exchangeof GHG along the atmospheric column, in connection with atmospheric transport, sourcesand sinks of the gases at the surface and in the atmosphere; (ii) to contribute to thepreparation and validation of space missions dedicated to the monitoring of greenhousegases. To address these objectives, various instruments are deployed on various platforms:aircraft, balloons, ground. They perform simultaneous observations of GHG concentration:direct in-situ observations at the surface or along the vertical, total and partial weightedcolumns. The MAGIC campaigns rely on SAFIRE Falcon20 measurements of gasconcentrations, temperature/humidity/wind/particles and GHG (CO2/CH4/CO/H2O)between 0 and 11 km altitude. The Falcon20 allows flying under any satellite tracksand making 0-11 km profiles at specific locations, such as ICOS/TCCON sites.They are complemented by balloon-borne instruments making 0-30 km profileswith AirCore atmospheric samplers and Amulse light laser-diode spectrometerslaunched at Aire-sur-l&#x2019;Adour and Trainou, as well as by measurements of total columnswith portable Fourier Transform Spectrometers from the ground (EM27sun andCHRIS). The 2 first MAGIC campaigns have been organized in January and May 2018, the latter inthe framework of the CoMet (Carbon dioxide and Methane) campaign lead by DLR. Inparticular, on May 24th, a coordinated flight between SAFIRE/Falcon20 and DLR/HALO hasbeen performed to compare the column of CH4 measured by the lidar CHARM-F on boardHALO to the column computed from simultaneous Falcon20 and AirCore profiles.Altogether, 2 research aircrafts, 23 launches of meteorological balloons, four ICOSinstrumented sites and a dozen instruments for measuring the concentration of gases havebeen deployed for the 2018 campaign. This talk will present the results obtained during the MAGIC2018 campaign and highlightthe strong benefit of having simultaneous measurements by aircraft, balloons andground-based FTS to validate space missions. Plans for next MAGIC campaigns that will beorganized in July 2019 in France and in summer 2020 tentatively in Sweden will begiven. [ABSTRACT FROM AUTHOR]

A better understanding of greenhouse gas surface sources and sinks is required in order to adress the global challenge of climate change. Spaceborne remote estimations of their atmospheric concentration can offer the global coverage that is necessary to improve the constraints on those fluxes, thus enabling a better monitoring of anthropogenic emissions. Consequently, striving for this goal, several satellite missions have been designed during the past decade, and the TCCON ground-based network provides an essential validation resource for their estimations. Most of these results are obtained thanks to Bayesian optimal estimation, an inverse method that is well-know for its sensitivity to the a priori choice. This work proposes to quantify the influence of a priori CO2 concentration profile covariance choice in term of total column retrieval bias. Several a priori covariance matrices will be compared and used in a Bayesian optimal estimation inversion scheme based on 4A/OP radiative transfer model and GEISA spectroscopic database, evaluated thanks to calc-obs spectral residuals computed for hundreds of observations for which atmospheric situations are known. The matrices will be taken from regular TCCON a priori profile databases, CAMS analyses or derived from a profile climatology of profiles measured by balloon-borne AirCores. The performance of the retrieval procedure will then be assessed against atmospheric profiles of CO2 acquired at several stations as well as during the 2018 Monitoring of Atmospheric composition and Greenhouse gases through multi-Instruments Campaign (MAGIC). [ABSTRACT FROM AUTHOR]

Within the EU-funded Readiness of Integrated carbon observation system (ICOS) for Necessities of integrated Global Observations (RINGO) project, vertical profile measurements have been explored using both AirCores and the ground-based Total Carbon Column Observing Network (TCCON) Fourier-transform infrared spectrometers (FTIRs) to enhance the link between ICOS ground-based stations, TCCON, and satellite measurements. AirCore is a long coiled stainless steel tube used for atmospheric sampling up to heights of around 30 km, which is launched on a weather balloon with one end open and the other end closed, and collects continuously ambient air samples during descent. The analysis results of the air samples for greenhouse and other trace gases mole fractions combined with the recorded in-flight information, e.g. coil temperatures, ambient pressure and altitude, allow for the retrieval of the vertical profiles. As for TCCON FTIRs, two-layer vertical profiles will be derived either by optimal estimation profile retrieval or by the use of a different gas (HF, N2O). In June 2018, an intensive AirCore comparison campaign took place at the TCCON site in Sodankylä, Finland. A total of 10 balloon flights were made, with combinations of different AirCores and/or the LIghtweight Stratospheric Air (LISA) sampler per balloon flight. The measured species include CO2, CH4, CO, O2, H2O by continuous cavity ring-down spectrometers (CRDS) at Sodankylä, and subsequent isotopic compositions of CO2 and CH4 and halogenated trace gases by delayed analyses of collected stratospheric air samples conducted later in several individual home laboratories. Here we present the first results from this campaign and compare the different AirCore/LISA profiles. The analyses are focused on 1) the accuracy of AirCore measurements of CO2, CH4 and CO mole fractions; 2) the accuracy of the altitude registration of AirCore profiles; 3) a comparison of AirCore observations with and without drying the air sample. Furthermore, we will evaluate the TCCON FTIR profile retrievals with collocated AirCore profiles. [ABSTRACT FROM AUTHOR]

Atmospheric profiles of greenhouse gases (GHG) are of special interest for studies modeling the current and future climate of the Earth and for studies determining atmospheric GHG budgets. Several techniques are currently available: beside tall tower measurements or aircraft flights, upward-looking ground-based Fourier-transform infrared spectrometers (FTIR) can be used, for example within the Total Column Carbon Observing Network (TCCON) or Collaborative Carbon Column Observing Network (COCCON). Furthermore, the promising AirCore technique allows column air sampling up to 30 km using a sampling tube attached to a stratospheric balloon. One challenge is to compare the results of these different techniques on the same site.Traînou is located approximately 100 km south of Paris/France. The Traînou site benefits from a tall tower setup for in-situ GHG measurements at 5, 50, 100 and 180 m height, and is equipped with a ground-based FTIR (TCCON-Orléans) for total column measurements. Since October 2016, lightweight AirCores specifically designed for weather balloons at LMD are operated by LSCE at Trainou. In addition, in May 2018, a multi-instruments campaign (MAGIC/COMET) was conducted to demonstrate the feasibility of combining surface, airborne, balloon-based and remote sensing total column measurements of GHG at several locations in France, including Trainou. During the campaign, aircraft flights were done to measure GHGs between 100 and 6000 m above the tall tower and AirCores were launched to sample and derive GHG vertical profiles. In addition, a compact FTIR instrument (EM27/SUN) measuring total column was also deployed at the estimated landing sites of the launched AirCores.The proposed contribution will describe the AirCore measurement technique used by LSCE and LMD. It will also present the data acquired during the MAGIC/COMET measurement campaign and discuss the similarities and differences between surface, aircraft, AirCore and remote-sensing measurements at the Traînou supersite. AIRCORE profiles will be integrated over the vertical and compared to partial and total column measurements from FTIR instruments. The sensitivity to the scenarios used to extrapolate the measurements in the upper atmosphere (>30km) will be investigated. [ABSTRACT FROM AUTHOR]