Constraints on methane emissions in North America from future geostationary remote-sensing measurements

The success of future geostationary (GEO) satellite observation missions depends on our ability to design instruments that address their key scientific objectives. In this study, an Observation System Simulation Experiment (OSSE) is performed to quantify the constraints on methane (CH4) emissions in North America obtained from shortwave infrared (SWIR), thermal infrared (TIR), and multi-spectral (SWIR+TIR) measurements in geostationary orbit and from future SWIR low-Earth orbit (LEO) measurements. An efficient stochastic algorithm is used to compute the information content of the inverted emissions at high spatial resolution (0.5°  ×  0.7°) in a variational framework using the GEOS-Chem chemistry-transport model and its adjoint. Our results show that at sub-weekly timescales, SWIR measurements in GEO orbit can constrain about twice as many independent flux patterns than in LEO orbit, with a degree of freedom for signal (DOF) for the inversion of 266 and 115, respectively. Comparisons between TIR GEO and SWIR LEO configurations reveal that poor boundary layer sensitivities for the TIR measurements cannot be compensated for by the high spatiotemporal sampling of a GEO orbit. The benefit of a multi-spectral instrument compared to current SWIR products in a GEO context is shown for sub-weekly timescale constraints, with an increase in the DOF of about 50 % for a 3-day inversion. Our results further suggest that both the SWIR and multi-spectral measurements on GEO orbits could almost fully resolve CH4 fluxes at a spatial resolution of at least 100 km  ×  100 km over source hotspots (emissions  >  4  ×  105 kg day−1). The sensitivity of the optimized emission scaling factors to typical errors in boundary and initial conditions can reach 30 and 50 % for the SWIR GEO or SWIR LEO configurations, respectively, while it is smaller than 5 % in the case of a multi-spectral GEO system. Overall, our results demonstrate that multi-spectral measurements from a geostationary satellite platform would address the need for higher spatiotemporal constraints on CH4 emissions while greatly mitigating the impact of inherent uncertainties in source inversion methods on the inferred fluxes

Evaluation of the MOCAGE Chemistry Transport Model during the ICARTT/ITOP Experiment

We evaluate the Meteo-France global chemistry transport 3D model MOCAGE (MOdele de Chimie Atmospherique a Grande Echelle) using the important set of aircraft measurements collected during the ICARRT/ITOP experiment. This experiment took place between US and Europe during summer 2004 (July 15-August 15). Four aircraft were involved in this experiment providing a wealth of chemical data in a large area including the North East of US and western Europe. The model outputs are compared to the following species of which concentration is measured by the aircraft: OH, H2O2, CO, NO, NO2, PAN, HNO3, isoprene, ethane, HCHO and O3. Moreover, to complete this evaluation at larger scale, we used also satellite data such as SCIAMACHY NO2 and MOPITT CO. Interestingly, the comprehensive dataset allowed us to evaluate separately the model representation of emissions, transport and chemical processes. Using a daily emission source of biomass burning, we obtain a very good agreement for CO while the evaluation of NO2 points out incertainties resulting from inaccurate ratio of emission factors of NOx/CO. Moreover, the chemical behavior of O3 is satisfactory as discussed in the paper

Technical note: The CAMS greenhouse gas reanalysis from 2003 to 2020

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 (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 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.</p

Estimation of mixing in the troposphere from Lagrangian trace gas reconstructions during long-range pollution plume transport

International audienceThe dispersion and mixing of pollutant plumes during long-range transport across the North Atlantic is studied using ensembles of diffusive backward trajectories in order to estimate turbulent diffusivity coefficients in the free troposphere under stratified flow conditions. Values of the order of 0.3-1 m2 s−1 and 1 × 104 m2 s−1 for the vertical and horizontal diffusivity coefficients D v and D h , respectively, are derived. Uncertainties related to the method are discussed, and results are compared with previous estimates of atmospheric mixing rates. These diffusivity estimates also yield an estimate of the vertical/horizontal aspect ratio of tracer structures in the troposphere. Results from this case study are used to estimate grid resolutions needed to accurately simulate the intercontinental transport of pollutants as being of the order of 500 m in the vertical and at least 40 km in the horizontal. This work forms the basis of high-resolution chemical simulations using ensembles of diffusive backward trajectories

Correction to “Estimation of mixing in the troposphere from Lagrangian trace gas reconstructions during long-range pollution plume transport”

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Toward a novel high-resolution modeling approach for the study of chemical evolution of pollutant plumes during long-range transport

International audienceThis paper presents results from a new method, ZooM-CiTTy, that aims to accurately reproduce filamentation observed in profiles of chemically active species in the free troposphere. Lagrangian tracer reconstructions of aircraft measurements across pollutant plumes including a stochastic representation of mixing are coupled with photochemical trajectory simulations, initialized with global model fields. The results provide a high-resolution simulation of trace gases along the flight track together with a detailed picture about the multiple air mass origins influencing chemical composition in the region where plume measurements were taken. This paper builds on results from Pisso et al. (2009) for the dynamic part of the model (the stochastic tracer reconstructions) and focuses on reconstruction of reactive species like O3. The model is evaluated for a case of long-range transport of a forest fire plume from Alaska to Europe. Simulated trace species are compared with measurements made in the plume by the DLR Falcon aircraft flying over Europe, and the role of photochemistry in governing the chemical composition across the plume is evaluated. It is shown that the model reproduces well O3 and NOy concentrations and O3 production per CO in the plumes as well as gradients at plume edges. In particular, because ZooM-CiTTy represents the contribution of several air masses to a measurement at a particular location, the model can reproduce so-called mixing lines between air masses. Results show that photochemistry and mixing contributions vary in different parts of the plume and that resulting trace gas correlations are a combination of these different mixtures. One limitation of the method is the fact that mixing between air masses is only performed at the end of the trajectories. Errors on simulated O3 reconstruction from this formulation are evaluated. These errors seems to be negligible in this case (in the free troposphere, far from emission region) because strong gradients are maintained by large-scale winds. Results from ZooM-CiTTy are also used to evaluate errors due to nonlinearities in O3 photochemistry in coarse-grid models. It is shown that in cases where strong gradients are maintained, errors in net O3 production can be as high as 50% at plumes edges. This new method is interesting to simulate relatively small layering structures observed in the free troposphere, but a more realistic treatment of mixing “en route” is needed if the model has to be used more extensively

Constraints on methane emissions in North America from future geostationary remote-sensing measurements

The success of future geostationary (GEO) satellite observation missions depends on our ability to design instruments that address their key scientific objectives. In this study, an Observation System Simulation Experiment (OSSE) is performed to quantify the constraints on methane (CH₄) emissions in North America obtained from shortwave infrared (SWIR), thermal infrared (TIR), and multi-spectral (SWIR+TIR) measurements in geostationary orbit and from future SWIR low-Earth orbit (LEO) measurements. An efficient stochastic algorithm is used to compute the information content of the inverted emissions at high spatial resolution (0.5°  ×  0.7°) in a variational framework using the GEOS-Chem chemistry-transport model and its adjoint. Our results show that at sub-weekly timescales, SWIR measurements in GEO orbit can constrain about twice as many independent flux patterns than in LEO orbit, with a degree of freedom for signal (DOF) for the inversion of 266 and 115, respectively. Comparisons between TIR GEO and SWIR LEO configurations reveal that poor boundary layer sensitivities for the TIR measurements cannot be compensated for by the high spatiotemporal sampling of a GEO orbit. The benefit of a multi-spectral instrument compared to current SWIR products in a GEO context is shown for sub-weekly timescale constraints, with an increase in the DOF of about 50 % for a 3-day inversion. Our results further suggest that both the SWIR and multi-spectral measurements on GEO orbits could almost fully resolve CH₄ fluxes at a spatial resolution of at least 100 km  ×  100 km over source hotspots (emissions  &gt;  4  ×  10⁵ kg day⁻¹). The sensitivity of the optimized emission scaling factors to typical errors in boundary and initial conditions can reach 30 and 50 % for the SWIR GEO or SWIR LEO configurations, respectively, while it is smaller than 5 % in the case of a multi-spectral GEO system. Overall, our results demonstrate that multi-spectral measurements from a geostationary satellite platform would address the need for higher spatiotemporal constraints on CH₄ emissions while greatly mitigating the impact of inherent uncertainties in source inversion methods on the inferred fluxes

Inferring regional sources and sinks of atmospheric CO2 from GOSAT XCO2 data

We have examined the utility of retrieved column-averaged, dry-air mole fractions of CO2 (XCO2) from the Greenhouse Gases Observing Satellite (GOSAT) for quantifying monthly, regional flux estimates of CO2, using the GEOS-Chem four-dimensional variational (4D-Var) data assimilation system. We focused on assessing the potential impact of biases in the GOSAT CO2 data on the regional flux estimates. Using different screening and bias correction approaches, we selected three different subsets of the GOSAT XCO2 data for the 4D-Var inversion analyses, and found that the inferred global fluxes were consistent across the three XCO2 inversions. However, the GOSAT observational coverage was a challenge for the regional flux estimates. In the northern extratropics, the inversions were more sensitive to North American fluxes than to European and Asian fluxes due to the lack of observations over Eurasia in winter and over eastern and southern Asia in summer. The regional flux estimates were also sensitive to the treatment of the residual bias in the GOSAT XCO2 data. The largest differences obtained were for temperate North America and temperate South America, for which the largest spread between the inversions was 1.02 and 0.96 Pg C, respectively. In the case of temperate North America, one inversion suggested a strong source, whereas the second and third XCO2 inversions produced a weak and strong sink, respectively. Despite the discrepancies in the regional flux estimates between the three XCO2 inversions, the a posteriori CO2 distributions were in good agreement (with a mean difference between the three inversions of typically less than 0.5 ppm) with independent data from the Total Carbon Column Observing Network (TCCON), the surface flask network, and from the HIAPER Pole-to-Pole Observations (HIPPO) aircraft campaign. The discrepancy in the regional flux estimates from the different inversions, despite the agreement of the global flux estimates suggests the need for additional work to determine the minimum spatial scales at which we can reliably quantify the fluxes using GOSAT XCO2. The fact that the a posteriori CO2 from the different inversions were in good agreement with the independent data although the regional flux estimates differed significantly, suggests that innovative ways of exploiting existing data sets, and possibly additional observations, are needed to better evaluate the inferred regional flux estimates