German methane fluxes in 2021 estimated with an ensemble-enhanced scaling inversion based on the ICON–ART model

Abstract. A reliable quantification of greenhouse gas emissions is important for climate change mitigation strategies. Inverse methods based on observations and atmospheric transport simulations can support emission quantification down to the national scale, yet, they are often limited by the observing systems, transport model uncertainties, and inversion methodologies. Here, we present a system for observation-based, regional methane flux estimation, which has the potential for long-term operational support of national emission reporting. We apply this to Central Europe in 2021 with focus on Germany, where we distinguish emissions from different anthropogenic sectors. The atmospheric transport is calculated with the numerical weather prediction model ICON–ART at 6.5 km resolution, sampling the meteorological uncertainty with a 12-member transport ensemble. We use a priori fluxes from national reporting to facilitate the validation of reported fluxes. Posterior fluxes are estimated with a modified synthesis inversion method, relying on observations from the Integrated Carbon Observation System (ICOS). Compared to the a priori, we find a significant increase in methane emissions in Germany and in the Benelux. We estimate German methane emissions (32 ± 19)  % higher than the anthropogenic emissions in the national inventory, and attribute this difference mainly to the agricultural sector, although separation from Land Use, Land Use Change and Forestry (LULUCF) as well as natural fluxes requires further research. The combination of an ensemble-enhanced numerical weather prediction model for atmospheric transport and good observation coverage paves the way to sector-specific, observation-based national emission estimates.