Estimation of methane surface fluxes from satellite measurements

Abstract

Methane is a powerful greenhouse gas with direct and indirect effect on global warming but its recent trend is misunderstood and still debated. My PhD aims at evaluating the ability of new satellite methane measurements to quantify the methane annual fluxes and their interannual variability. I assimilate the measurements of three satellite observing systems and the traditional observing surface network in a bayesian variational inversion system over long temporal windows consistent with the methane lifetime.First, I show that the tuning of input error statistics of each observing system allows a good agreement between the annual regional methane budgets inferred from TANSO-FTS, IASI and the surface network. This result opens the possibility to combine these measurements to better constrain the methane emission estimates. However, the results inferred from SCIAMACHY measurements acquired at the end of the life of the instrument, remain inconsistent, probably because of an error structure that is difficult to model.Secondly, I show that the surface network and IASI detect the main methane flux anomalies in South Africa and in East Asia whereas TANSO-FTS detects almost all the anomalies in North Africa. Moreover, negatively correlated with soil moisture, the recent anomalies observed in North Africa and in East Asia suggest, respectively, an increase of fire emissions and a change in rice culture practices. I also show that the lands over the Northern Hemisphere low latitudes have a major contribution to the recent methane trend.