| abstract | Satellite observations of trace gases in the atmosphere
offer a promising method for global verification
of emissions and improvement of global emission inventories.
Here, an inverse modelling approach based on fourdimensional
variational (4D-var) data assimilation is presented
and applied to synthetic measurements of atmospheric
methane. In this approach, emissions and initial concentrations
are optimised simultaneously, thus allowing inversions
to be carried out on time scales of weeks to months, short
compared with the lifetime of methane. Observing System
Simulation Experiments (OSSEs) have been performed to
demonstrate the feasibility of the method and to investigate
the utility of SCIAMACHY observations for methane source
estimation. The impact of a number of parameters on the
error in the methane emission field retrieved has been analysed.
These parameters include the measurement error, the
error introduced by the presence of clouds, and the spatial
resolution of the emission field. It is shown that 4D-var is an
efficient method to deal with large amounts of satellite data
and to retrieve emissions at high resolution. Some important
conclusions regarding the SCIAMACHY measurements can
be drawn. (i) The observations at their estimated precision of
1.5 to 2% will contribute considerably to uncertainty reduction
in monthly, subcontinental ( 500 km) methane source
strengths. (ii) Systematic measurement errors well below 1%
have a dramatic impact on the quality of the derived emission
fields. Hence, every effort should be made to identify
and remove such systematic errors. (iii) It is essential
to take partly cloudy pixels into account in order to achieve
sufficient spatial coverage. (iv) The uncertainty in measured
cloud parameters may at some point become the limiting factor
for methane emission retrieval, rather than the uncertainty
in measured methane itself. |
