Concurrent assimilation of methane fluxes and concentrations with a 4D LETKF for Germany in 2021 based on ICON–ART

Abstract. Greenhouse gas (GHG) emission quantification is crucial for assessing and mitigating climate change. We present a data assimilation system that can adjust methane concentrations and fluxes concurrently, by augmenting the state vector. We rely on the high resolution numerical weather prediction model ICON to simulate the atmospheric transport of GHG and the associated uncertainties, and assimilate to GHG observations of the Integrated Carbon Observation System (ICOS) station network with a 4D Local Ensemble Transform Kalman Filter (LETKF) system. We use two different approaches to adjust the emissions, one with a perturbed field, the other with a split into emission categories. The results confirm significantly higher methane emissions in Germany compared to the reported national inventory, as well as higher emissions in the BeNeLux region. The 4D LETKF contributes to a comprehensive system to validate national greenhouse gas emission reporting, adding the advantage of spatial flexibility for flux attribution and paving the way for near real time applications.