 |
| Titel |
Understanding atmospheric methane variability between 2000 and 2008 using inverse modelling and a global Lagrangian transport model |
| VerfasserIn |
Christina Schnadt Poberaj, Stephan Henne, Dominik Brunner, Renato Spahni |
| Konferenz |
EGU General Assembly 2013
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250075380
|
|
|
|
|
|
| Zusammenfassung |
| Methane (CH4) is the second most important well-mixed greenhouse gas in terms of radiative
forcing after carbon dioxide. To improve our understanding of recent CH4 growth rate
variability, focusing particularly on the latest increase since 2007 after a period of stagnation,
we performed a global model simulation in combination with an emission inversion. This
allowed us to quantify the temporal evolution of different methane sources during this period.
In contrast to previous studies relying on Eulerian models, our simulations were performed
with an enhanced version of the Lagrangian Particle Dispersion Model FLEXPART in
a global domain filling mode and extended with a simple CH4 chemistry. 3 mio
particles (air parcels) were permanently transported in the model over the years
2000-2008 each carrying a set of 44 tracers representing 11 different CH4 sources in 4
emission age classes each. A priori CH4 emissions were taken from state-of-the-art
inventories and a wetland emission model. In FLEXPART, these are picked up by the
particles residing in the atmospheric boundary layer. CH4 is subsequently lost by
reactions with prescribed fields of OH and stratospheric Cl and O(1D) and deposition
at the surface. Simulated concentrations are mostly in very good agreement with
continuous in situ measurements and flask samples of the networks of NOAA, GAW and
AGAGE. Finally, a posteriori emissions were inversely estimated using a fixed-lag
Kalman smoother by analyzing modeled CH4 concentrations against the in-situ
measurements. Our results indicate that the renewed growth of CH4 in 2007 and
2008 was mainly attributable to positive anomalies in CH4 emissions from tropical
biomass burning in 2006/2007, a positive anomaly in wet mineral soil and large rice
agriculture emissions in 2007/08. Additionally, non-negligible contributions also
arose from Siberian peatland emissions in these last two years of the simulation. |
|
|
|
|
|
|