Steps towards improved inverse modelling of GHG fluxes: recent work within ITMS

Within the Integrated Greenhouse Gas Monitoring System for Germany (ITMS), the main aim is to provide regular, accurate, observation-based emission estimates that will enhance the transparency in GHG emission reporting needed to build the necessary trust on the path to net zero emissions. Reliable inverse atmospheric transport modelling using atmospheric GHG observations is one of the main ingredients for this. However, multiple studies have shown rather large differences in GHG flux estimates from regional inverse modelling, related to differences in implementation of atmospheric transport processes such as vertical mixing and convective transport. Within the ITMS-M (modelling) project, a number of approaches are taken towards either improving atmospheric transport and mixing, or to reduce the impact of related uncertainties in atmospheric transport. These approaches include the utilization of vertical profiles from ICOS tall towers (using stable layer tracer enhancements during night time, expressed as partial columns as input to the inversion), profile information from IAGOS and mixing height information from ceilometer networks (diagnosing/correcting for uncertainties in daytime vertical mixing), but also multi-tracer inversions using correlated model-data-mismatch errors (utilizing independent knowledge on e.g. Radon surface fluxes in a Rn-CH4 inversion). We will give an overview of these approaches and current status of their developments within ITMS.