Influence of the parameterised transport in ICON-ART on the simulated methane concentrations over Europe

Targeted climate change mitigation strategies to reduce greenhouse gas emissions benefit from robust and reliable emission quantification. During the first phase of the Integrated Greenhouse Gas Monitoring System for Germany (ITMS), we aim to obtain top-down estimates of German methane emissions with the help of numerical weather prediction models. Accurately representing the effects of convection and turbulent eddies in a numerical weather prediction model is fundamental for simulating the transport of trace gases with emissions located near the surface, as in our case. In the current configuration of our numerical weather prediction model, ICON-ART, convection and turbulence are parameterised. Using a parameterised transport denial approach and obtaining model equivalents for the ICOS European Obspack dataset, we develop a qualitative picture of the parameterised transport errors at each Obspack station. These insights help to identify the potential sources of error in the simulation and thus improve the accuracy of methane emission estimates, which is crucial for concentration data assimilation and top-down observation-based emission estimation, the so-called "inversions".