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| Titel |
Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations |
| VerfasserIn |
R. Locatelli, P. Bousquet, M. Saunois, F. Chevallier, C. Cressot |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 17 ; Nr. 15, no. 17 (2015-09-01), S.9765-9780 |
| Datensatznummer |
250120006
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| Publikation (Nr.) |
 copernicus.org/acp-15-9765-2015.pdf |
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| Zusammenfassung |
With the densification of surface observing networks and the development of
remote sensing of greenhouse gases from space, estimations of methane
(CH4) 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 CH4 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 CH4 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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