TransCom N2O model inter-comparison - Part 2:Atmospheric inversion estimates of N2O emissions

This study examines N2O emission estimates from five different atmospheric inversion frameworks based on chemistry transport models (CTMs). The five frameworks differ in the choice of CTM, meteorological data, prior uncertainties and inversion method but use the same prior emissions and observation data set. The posterior modelled atmospheric N2O mole fractions are compared to observations to assess the performance of the inversions and to help diagnose problems in the modelled transport. Additionally, the mean emissions for 2006 to 2008 are compared in terms of the spatial distribution and seasonality. Overall, there is a good agreement among the inversions for the mean global total emission, which ranges from 16.1 to 18.7 TgN yr(-1) and is consistent with previous estimates. Ocean emissions represent between 31 and 38% of the global total compared to widely varying previous estimates of 24 to 38%. Emissions from the northern mid- to high latitudes are likely to be more important, with a consistent shift in emissions from the tropics and subtropics to the mid- to high latitudes in the Northern Hemisphere; the emission ratio for 0-30A degrees N to 30-90A degrees N ranges from 1.5 to 1.9 compared with 2.9 to 3.0 in previous estimates. The largest discrepancies across inversions are seen for the regions of South and East Asia and for tropical and South America owing to the poor observational constraint for these areas and to considerable differences in the modelled transport, especially inter-hemispheric exchange rates and tropical convective mixing. Estimates of the seasonal cycle in N2O emissions are also sensitive to errors in modelled stratosphere-to-troposphere transport in the tropics and southern extratropics. Overall, the results show a convergence in the global and regional emissions compared to previous independent studies

Inverse modelling of European CH4 emissions during 2006-2012 using different inverse models and reassessed atmospheric observations

We present inverse modelling (top down) estimates of European methane (CH4) emissions for 2006-2012 based on a new quality-controlled and harmonised in situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions.The inverse models infer total CH4 emissions of 26.8 (20.2-29.7) TgCH(4) yr(-1) (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006-2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom up, based on statistical data and emissions factors) amount to only 21.3 TgCH(4) yr(-1) (2006) to 18.8 TgCH(4) yr(-1) (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP), total wetland emissions of 4.3 (2.3-8.2) TgCH(4) yr(-1) from the EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability. Taking into account the wetland emissions from the WETCHIMP ensemble, the top-down estimates are broadly consistent with the sum of anthropogenic and natural bottom-up inventories. However, the contribution of natural sources and their regional distribution remain rather uncertain.Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. The estimated average regional biases range between -40 and 20% at the aircraft profile sites in France, Hungary and Poland.</p

Identification of potential methane source regions in Europe using δ13 CCH4 measurements and trajectory modeling

The methane emissions from the Hungarian Pannonian Basin are not well qualified, due to a lack of measurements of CH4 mole fraction and δ13CCH4 in the air. This study reports methane measurements in air samples from Hungary, placing them in the context of regional and global background data, to investigate the inputs to the methane burden in Central Europe. CH4 mole fraction and δ13CCH4 from the Hungarian tall tower station, Hegyhátsál, and additional data from Mace Head (Ireland) and Zeppelin (Svalbard) are used with back-trajectory modeling to identify central European source areas and their seasonal variation between the summer vegetation and winter heating periods. Methane measurements in air masses sampled in the European interior, have significantly higher maxima and seasonal amplitudes than at the Mace Head and Zeppelin European background sites. The mean CH4 mole fraction value is about 80 ppb higher than the comparable marine background, and values above 2000 ppb were frequently observed between February 2013 and December 2015. The mean δ13CCH4 value -47.5±0.3 ‰ (2σ) was comparable to values at all three monitoring sites, but specific pollution events were detected at Hegyhátsál. Concentration weighted trajectory modeling, meteorological parameters, stable carbon isotopic composition (δ13CCH4), and Miller-Tans analysis show that the main factors influencing CH4 at the Hegyhátsál, apart from diurnal and seasonal changes in the Planetary Boundary Layer, are emissions from residential heating and industrial CH4 emissions during the winter

Global CO2 fluxes inferred from surface air-sample measurements and from TCCON retrievals of the CO2 total column

We present the first estimate of the global distribution of CO2surface fluxes from 14 stations of the Total Carbon Column Observing Network (TCCON). The evaluation of this inversion is based on 1) comparison with the fluxes from a classical inversion of surface air-sample-measurements, and 2) comparison of CO2mixing ratios calculated from the inverted fluxes with independent aircraft measurements made during the two years analyzed here, 2009 and 2010. The former test shows similar seasonal cycles in the northern hemisphere and consistent regional carbon budgets between inversions from the two datasets, even though the TCCON inversion appears to be less precise than the classical inversion. The latter test confirms that the TCCON inversion has improved the quality (i.e., reduced the uncertainty) of the surface fluxes compared to the assumed or prior fluxes. The consistency between the surface-air-sample-based and the TCCON-based inversions despite remaining flaws in transport models opens the possibility of increased accuracy and robustness of flux inversions based on the combination of both data sources and confirms the usefulness of space-borne monitoring of the CO2 column.It was co-funded by the European Commission under the EU Seventh Research Framework Programme (grants agreements 218793, MACC, and 212196, COCOS

CO2 surface fluxes at grid point scale estimated from a global 21 year reanalysis of atmospheric measurements

This paper documents a global Bayesian variational inversion of CO2 surface fluxes during the period 1988–2008. Weekly fluxes are estimated on a 3.75° × 2.5° (longitude-latitude) grid throughout the 21 years. The assimilated observations include 128 station records from three large data sets of surface CO2 mixing ratio measurements. A Monte Carlo approach rigorously quantifies the theoretical uncertainty of the inverted fluxes at various space and time scales, which is particularly important for proper interpretation of the inverted fluxes. Fluxes are evaluated indirectly against two independent CO2 vertical profile data sets constructed from aircraft measurements in the boundary layer and in the free troposphere. The skill of the inversion is evaluated by the improvement brought over a simple benchmark flux estimation based on the observed atmospheric growth rate. Our error analysis indicates that the carbon budget from the inversion should be more accurate than the a priori carbon budget by 20% to 60% for terrestrial fluxes aggregated at the scale of subcontinental regions in the Northern Hemisphere and over a year, but the inversion cannot clearly distinguish between the regional carbon budgets within a continent. On the basis of the independent observations, the inversion is seen to improve the fluxes compared to the benchmark: the atmospheric simulation of CO2 with the Bayesian inversion method is better by about 1 ppm than the benchmark in the free troposphere, despite possible systematic transport errors. The inversion achieves this improvement by changing the regional fluxes over land at the seasonal and at the interannual time scales.This work was performed using HPC resources from GENCI‐ (CCRT/CINES/IDRIS; grant 2009‐ t2009012201). It was cofunded by the European Commission under the EU Seventh Research Framework Programme (grant agreements 212196, COCOS, and 218793, MACC)

Inverse modelling of European N2O emissions: assimilating observations from different networks

We describe the setup and first results of an inverse modelling system for atmospheric N₂O, based on a four-dimensional variational (4DVAR) technique and the atmospheric transport zoom model TM5. We focus in this study on the European domain, utilizing a comprehensive set of quasi-continuous measurements over Europe, complemented by N₂O measurements from the Earth System Research Laboratory of the National Oceanic and Atmospheric Administration (NOAA/ESRL) cooperative global air sampling network. Despite ongoing measurement comparisons among networks parallel measurements at a limited number of stations show that significant offsets exist among the different laboratories. Since the spatial gradients of N₂O mixing ratios are of the same order of magnitude as these biases, the direct use of these biased datasets would lead to significant errors in the derived emissions. Therefore, in order to also use measurements with unknown offsets, a new bias correction scheme has been implemented within the TM5-4DVAR inverse modelling system, thus allowing the simultaneous assimilation of observations from different networks. The N₂O bias corrections determined in the TM5-4DVAR system agree within ~0.1 ppb (dry-air mole fraction) with the bias derived from the measurements at monitoring stations where parallel NOAA discrete air samples are available. The N₂O emissions derived for the northwest European and east European countries for 2006 show good agreement with the bottom-up emission inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Moreover, the inverse model can significantly narrow the uncertainty range reported in N₂O emission inventories for these countries, while the lack of measurements does not allow to reduce the uncertainties of emission estimates in southern Europe. <br><br> Several sensitivity experiments were performed to test the robustness of the results. It is shown that also inversions without detailed a priori spatio-temporal emission distributions are capable to reproduce major regional emission patterns within the footprint of the existing atmospheric network, demonstrating the strong constraints of the atmospheric observations on the derived emissions

Precision requirements for space-based XCO2 data

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): D10314, doi:10.1029/2006JD007659.Precision requirements are determined for space-based column-averaged CO2 dry air mole fraction (XCO2) data. These requirements result from an assessment of spatial and temporal gradients in XCO2, the relationship between XCO2 precision and surface CO2 flux uncertainties inferred from inversions of the XCO2 data, and the effects of XCO2 biases on the fidelity of CO2 flux inversions. Observational system simulation experiments and synthesis inversion modeling demonstrate that the Orbiting Carbon Observatory mission design and sampling strategy provide the means to achieve these XCO2 data precision requirements.This work was supported by the Orbiting Carbon Observatory (OCO) project through NASA’s Earth System Science Pathfinder (ESSP) program. SCO and JTR were supported by a NASA IDS grant (NAG5-9462) to JTR