Sensitivity analysis of methane emissions derived from SCIAMACHY observations through inverse modelling

[摘要] Satellite observations of trace gases in the atmosphere offer a promisingmethod for global verification of emissions and improvement of globalemission inventories. Here, an inverse modelling approach based onfour-dimensional variational (4D-var) data assimilation is presented andapplied to synthetic measurements of atmospheric methane. In this approach,emissions and initial concentrations are optimised simultaneously, thusallowing inversions to be carried out on time scales of weeks to months,short compared with the lifetime of methane. Observing System SimulationExperiments (OSSEs) have been performed to demonstrate the feasibility of themethod and to investigate the utility of SCIAMACHY observations for methanesource estimation. The impact of a number of parameters on the error in themethane emission field retrieved has been analysed. These parameters includethe measurement error, the error introduced by the presence of clouds, andthe spatial resolution of the emission field. It is shown that 4D-var is anefficient method to deal with large amounts of satellite data and to retrieveemissions at high resolution. Some important conclusions regarding theSCIAMACHY measurements can be drawn. (i) The observations at their estimatedprecision of 1.5 to 2% will contribute considerably to uncertainty reductionin monthly, subcontinental (~500 km) methane source strengths. (ii)Systematic measurement errors well below 1% have a dramatic impact on thequality of the derived emission fields. Hence, every effort should be made toidentify and remove such systematic errors. (iii) Itis essential to take partly cloudy pixels into account in order to achievesufficient spatial coverage. (iv) The uncertainty in measured cloudparameters may at some point become the limiting factor for methane emissionretrieval, rather than the uncertainty in measured methane itself.

[学科分类] 大气科学