A new estimation of the recent tropospheric molecular hydrogen budget using atmospheric observations and variational inversion

Yver, C.; Pison, Isabelle; Fortems-Cheiney, Audrey; Schmidt, Martina; Chevallier, F.; Ramonet, Michel; Jordan, Andrew; Søvde, O. A.; Engel, Andreas; Fisher, Rebecca E.; Lowry, David; Nisbet, E. G.; Levin, Ingeborg; Hammer, Samuel; Necki, Jaroslaw; Bartyzel, Jakub; Reimann, Stefan; Vollmer, Martin K.; Steinbacher, Martin; Aalto, Tuula; Maione, Michela; Arduini, Jgor; O’Doherty, Simon; Grant, Aoife; Sturges, William T.; Forster, G.; Lunder, Chris Rene; Privalov, V. I.; Paramonova, N. N.; Werner, Anja; Bousquet, Philippe

doi:10.5194/acp-11-3375-2011

Cited by 32 publications

(26 citation statements)

References 54 publications

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“…continental sites) are more difficult to model, especially for coarse global models (Geels et al, 2007). This simple approach has been used previously in atmospheric inversions Yver et al, 2011;Röden-beck et al, 2003). Errors at stations where Globalview-CH 4 data were not available have been interpolated from stations presenting the same characteristics (background/polluted, Northern/Southern Hemisphere, coastal/continental).…”

Section: Set-up Of the Pyvar-lmdz-sacs Inversion Systemmentioning

confidence: 99%

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

et al. 2013

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Abstract.A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model outputs from the international TransCom-CH 4 model inter-comparison exercise, are combined with a prior scenario of methane emissions and sinks, and integrated into the three-component PYVAR-LMDZ-SACS (PYthon VARiational-Laboratoire de Météorologie Dynamique model with Zooming capability-Simplified Atmospheric Chemistry System) inversion system to produce 10 different methane emission estimates at the global scale for the year 2005. The same methane sinks, emissions and initial conditions have been applied to produce the 10 synthetic observation datasets. The same inversion set-up (statistical errors, prior emissions, inverse procedure) is then applied to derive flux estimates by inverse modelling. Consequently, only differences in the modelling of atmospheric transport may cause differences in the estimated fluxes.In our framework, we show that transport model errors lead to a discrepancy of 27 Tg yr −1 at the global scale, representing 5 % of total methane emissions. At continental and annual scales, transport model errors are proportionally larger than at the global scale, with errors ranging from 36 Tg yr −1 in North America to 7 Tg yr −1 in Boreal Eurasia (from 23 to 48 %, respectively). At the model grid-scale, the spread of inverse estimates can reach 150 % of the prior flux. Therefore, transport model errors contribute significantly to overall uncertainties in emission estimates by inverse modelling, especially when small spatial scales are examined. Sensitivity tests have been carried out to estimate the impact of the measurement network and the advantage of higher horizontal resolution in transport models. The large differences found between methane flux estimates inferred in these different configurations highly question the consistency of transport model errors in current inverse systems.Future inversions should include more accurately prescribed observation covariances matrices in order to limit Published by Copernicus Publications on behalf of the European Geosciences Union. R. Locatelli et al.: Transport model errors in methane inversionsthe impact of transport model errors on estimated methane fluxes.

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Section: Set-up Of the Pyvar-lmdz-sacs Inversion Systemmentioning

confidence: 99%

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

et al. 2013

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“…The RSD at each site is considered a proxy of the transport model errors. Previous studies using PYVAR-LMDz-SACS have used this approach (Bousquet et al, 2006;Yver et al, 2011;Locatelli et al, 2013). In satellite-based inversions, GOSAT retrieval random errors are estimated to be about 0.6 % of satellite measurements (Cressot et al, 2014) and a transport model error of 1 % of the observation values is added according to the results of Cressot et al (2014) on tuning of error statistics.…”

Section: Pyvar-lmdz-sacsmentioning

confidence: 99%

Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

Locatelli¹,

Bousquet²,

Saunois³

et al. 2015

Atmos. Chem. Phys.

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Abstract. With the densification of surface observing networks and the development of remote sensing of greenhouse gases from space, estimations of methane (CH 4 ) sources and sinks by inverse modeling are gaining additional constraining data but facing new challenges. The chemical transport model (CTM) linking the flux space to methane mixing ratio space must be able to represent these different types of atmospheric constraints for providing consistent flux estimations.Here we quantify the impact of sub-grid-scale physical parameterization errors on the global methane budget inferred by inverse modeling. We use the same inversion setup but different physical parameterizations within one CTM. Two different schemes for vertical diffusion, two others for deep convection, and one additional for thermals in the planetary boundary layer (PBL) are tested. Different atmospheric methane data sets are used as constraints (surface observations or satellite retrievals).At the global scale, methane emissions differ, on average, from 4.1 Tg CH 4 per year due to the use of different sub-grid-scale parameterizations. Inversions using satellite total-column mixing ratios retrieved by GOSAT are less impacted, at the global scale, by errors in physical parameterizations. Focusing on large-scale atmospheric transport, we show that inversions using the deep convection scheme of Emanuel (1991) derive smaller interhemispheric gradients in methane emissions, indicating a slower interhemispheric exchange. At regional scale, the use of different sub-grid-scale parameterizations induces uncertainties ranging from 1.2 % (2.7 %) to 9.4 % (14.2 %) of methane emissions when using only surface measurements from a background (or an extended) surface network. Moreover, spatial distribution of methane emissions at regional scale can be very different, depending on both the physical parameterizations used for the modeling of the atmospheric transport and the observation data sets used to constrain the inverse system. When using only satellite data from GOSAT, we show that the small biases found in inversions using a coarser version of the transport model are actually masking a poor representation of the stratosphere-troposphere methane gradient in the model. Improving the stratosphere-troposphere gradient reveals a larger bias in GOSAT CH 4 satellite data, which largely amplifies inconsistencies between the surface and satellite inversions. A simple bias correction is proposed. The results of this work provide the level of confidence one can have for recent methane inversions relative to physical parameterizations included in CTMs.

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“…The different components of the H 2 budget have been estimated based on various approaches, initially using up-scaling from emission studies or related trace gases (e.g. CO), but recently also chemistry transport models, inverse modeling, or the use of deuterium component of H 2 Ehhalt and Rohrer, 2009;Hauglustaine and Ehhalt, 2002;Novelli et al, 1999;Pieterse et al, 2011;Pison et al, 2009;Price et al, 2007;Rhee et al, 2006;Sanderson et al, 2003;Xiao et al, 2007;Yver et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

H<sub>2</sub> vertical profiles in the continental boundary layer: measurements at the Cabauw tall tower in The Netherlands

et al. 2011

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Abstract. In-situ, quasi-continuous measurements of atmospheric hydrogen (H 2 ) have been performed since October 2007 at the Cabauw tall tower station in the Netherlands. Mole fractions of H 2 , CO and several greenhouse gases are determined simultaneously in air sampled successively at four heights, between 20 and 200 m above ground level. 222 Rn measurements are performed in air sampled at 20 and 200 m.This H 2 dataset represents the first in-situ, quasicontinuous long-term measurement series of vertical profiles of H 2 in the lower continental boundary layer. Seasonal cycles are present at all heights in both H 2 and CO, and their amplitude varies with the sampling height. The seasonality is evident in both the "baseline" values and in the short term (diurnal to synoptic time scales) variability, the latter being significantly larger during winter.The observed H 2 short term signals and vertical gradients are in many cases well correlated to other species, especially to CO. On the other hand, H 2 has at times a unique behaviour, due to its particular distribution of sources and sinks. Our estimation for the regional H 2 soil uptake flux, using the radon tracer method, is (−1.89 ± 0.26) × 10 −5 g/(m 2 h), significantly smaller than other recent results from Europe.H 2 /CO ratios of the traffic emissions computed from our data, with an average of 0.54 ± 0.07 mol:mol, are larger and more variable than estimated in some of the previous studies in Europe. This difference can be explained by a different driving regime, due to the frequent traffic jams in the influence area of Cabauw. The H 2 /CO ratios of the large scale pollution events have an average of 0.36 ± 0.05 mol:mol;Correspondence to: M. E. Popa (epopa2@yahoo.com) these ratios were observed to slightly increase with sampling height, possibly due to a stronger influence of soil uptake at the lower sampling heights.

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A new estimation of the recent tropospheric molecular hydrogen budget using atmospheric observations and variational inversion

Cited by 32 publications

References 54 publications

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

H<sub>2</sub> vertical profiles in the continental boundary layer: measurements at the Cabauw tall tower in The Netherlands

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A new estimation of the recent tropospheric molecular hydrogen budget using atmospheric observations and variational inversion

Cited by 32 publications

References 54 publications

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

Impact of transport model errors on the global and regional methane emissions estimated by inverse modelling

Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations

H&lt;sub&gt;2&lt;/sub&gt; vertical profiles in the continental boundary layer: measurements at the Cabauw tall tower in The Netherlands

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H<sub>2</sub> vertical profiles in the continental boundary layer: measurements at the Cabauw tall tower in The Netherlands