C. Gerbig1*, S. Baum1, F. Boschetti1, S. Verma1, J. Marshall1

Potential of the upcoming IAGOS GHG data stream from passenger aircraft measurements

Introduction and Motivation Efforts to reduce the increase of atmospheric GHGs requires a better understanding of their sources and sinks, including the interaction of a changing climate with natural fluxes, but also the anthropogenic emissions at national scales. Within the European research infrastructure IAGOS, the In-service aircraft for a global observing system, globally distributed measurements of the greenhouse gases CO2, CH4 and H2O as well as CO will start in fall 2017. A supplemental type certificate for installation of the cavity ring-down spectroscopy (CRDS) based measurement system in the avionics bay of Airbus A340 and A330 has been issued by EASA in late 2016. Near-real time data transmission is foreseen for utilization of observations by the Copernicus Atmosphere Monitoring Service (CAMS) and by other users. Within the next years, five aircraft from various airlines operating out of different parts of the world will be equipped, providing about 5000 vertical profiles per year with near-global distribution. The potential of regular vertical GHG profile observations within inverse modeling to constrain GHG fluxes are presented here using synthetic data experiments.

Affiliation: [1] Max Planck Institute for Biogeochemistry, Jena, Germany *Email: cgerbig@bgc-jena.mpg.de

More information on IAGOS: www.iagos.org

References: Filges, A., Gerbig, C., Chen, H., Franke, H., Klaus, C. and Jordan, A.: The IAGOS-core greenhouse gas package: a measurement system for continuous airborne observations of CO2, CH4, H2O and CO, Tellus B, 67(0), doi:10.1007/s00340-008-3135-y, 2015. Verma, S., Marshall, J., Gerbig, C., Rödenbeck, C. and Totsche, K. U.: The constraint of CO2 measurements made onboard passenger aircraft on surface–atmosphere fluxes: the impact of transport model errors in vertical mixing, Atmos. Chem. Phys., 17(9), 5665–5675, doi:10.1029/2003JD004164, 2017. Boschetti, F., Thouret, V., Maenhout, G. J., Totsche, K. U., Marshall, J. and Gerbig, C.: Multi-species inversion and IAGOS airborne data for a better constraint of continental scale fluxes, Atmos. Chem. Phys. Discuss., 1–37, doi:10.5194/acp-2017-69, 2017.

Top: Nine different airlines currently carry IAGOS instruments

Middle right: IAGOS-GHG will be installed in the avionics bay, it includes calibration gases (Filges et al., 2015)

Far right: IAGOS-GHG measurements made onboard the HALO research aircraft on May 11, 2015, near Oberpfaffenhofen

The IAGOS GHG data stream

Reduced impact from mixing height errors The height of the mixed layer, into which surface-atmosphere fluxes are diluted within an hour or less, is not well represented in transport models used for inverse modeling. To investigate the impact of errors in mixing heights when using IAGOS profile data rather then near-surface data, a synthetic data experiment has been set up.

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b.Reshuffleddata(WrongBLH)

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Using locations and times of 9 years of profile measurements from MOZAIC (the IAGOS predecessor) in the CarboScope global inversion we compute the uncertainty reduction for monthly fluxes aggregated to the Transcom regions. Results show that the regions tropical Africa and temperate Eurasia, that are under-constrained by the existing surface based network, will benefit the most from these measurements.

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For regional inverse modeling, the gradient in GHG abundance between mixed-layer air and free tropospheric air is used for constraining surface-atmosphere exchange fluxes. We use a regional modeling framework consisting of the Lagrangian particle dispersion model STILT, combined with the high resolution (10 km x 10 km) EDGARv4.3 emission inventory, differentiated by emission sector and fuel type for CO2, CO, and CH4, and combined with the VPRM (Vegetation Photosynthesis and Respiration Model) for biospheric fluxes of CO2 (Boschetti et al., 2017).

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Benefit for global CO2 inversions: Uncertainty reduction

We use two biospheric models to generate “true” fluxes (Biome-BGC) and a-priori fluxes (LPJ). Two sets of synthetic observations resulting from the “true” fluxes are generated, one of which uses the standard boundary layer height (BLH from ECMWF), while the other has all vertical profiles reshuffled corresponding to NCEP BLH. Six different inversions are then performed (see scheme left) using observations from the surface network (S), aircraft (A) or combined surface network and aircraft (C), either using synthetic data with known BLH as control (a), or using synthetic data corresponding to a different BLH (b). The resulting posterior fluxes from the inversions are then compared to the true fluxes at monthly scales for all Transcom regions for the year (2000) using a Taylor diagram (right). We find that posterior fluxes retrieved using aircraft profiles are much less susceptible to errors in mixing heights as compared to the ground-based network. Using the combined data from the surface network and the aircraft profiles, the impact from errors in mixing heights is still large, indicating that the ground-based network dominates due to the larger number of observations. Further details can be found in Verma et al. (2017).

Benefit for regional inversions

Different species such as CO2 and CO have partially overlapping emission pat-terns for given fuel-combustion related sectors, and thus share part of the uncertainties, both related to the a priori knowledge of emissions (see top right figure), and to model-data mismatch error. Applying the modeling framework to synthetic IAGOS profile observations from in- and outbound flights at Frankfurt air-port, also the benefit of using correlations between different species’ uncertainties on the performance of the atmospheric inversion is evaluated. The inversion solves for 2604 scaling factors for monthly fluxes from specific emission sectors and fuel types as well as gross biospheric fluxes from 5 different vegetation types.

For the area seen most strongly by the IAGOS profile observations over Frankfurt (top figure, outlined by white line) prior and posterior flux

Prior error correlation

FT-PBL gradients

flux budget uncertainties are assessed. Uncertainty reduction for emissions and gross biospheric fluxes is typically in 50-70% range for monthly fluxes (top right). Note that also the separation of anthropogenic emissions from biospheric fluxes for CO2 seems possible. The benefit of a multi-species inversion using correlated uncertainties over three individual single species inversions are about 15% reduced posterior uncertainties in CO2 fossil fuel emissions.

post. unc. (multi) post. unc. (single)

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