Towards a greenhouse gas emission monitoring and Verification system for Belgium (VERBE): Evaluation of WRF-GHG simulations with observational data

Belgium’s national greenhouse gas (GHG) inventory currently relies on a bottom-up approach, but incorporating top-down methods using atmospheric observations and inverse modeling offers significant potential to improve the understanding of CO₂ and CH₄ emissions. The VERBE project aims to develop such a system tailored for Belgium by combining satellite, ground-based remote sensing, and in situ observations from the Integrated Carbon Observation System (ICOS) network with inverse modeling techniques. As part of this effort, we start by assessing the ability of the atmospheric transport model to accurately reproduce the spatiotemporal distribution of GHGs in this region.  

We employed the Weather Research and Forecast model coupled with chemistry in its Greenhouse Gas configuration (WRF-GHG) to simulate the Western Europe region, with a focus over Belgium, from June to August 2018. Simulations were conducted at horizontal resolutions of 9 km and 3 km over two domains. In comparison with meteorological data from Automatic Weather Stations in Belgium and ICOS sites, our results indicate that the WRF-GHG simulation is capable to capture the variations of the near surface meteorological fields (temperature, wind speed and wind direction) very well, especially for temperature.

The simulated CO₂ and CH₄ are compared with near-surface concentrations at different heights from four ICOS sites around Belgium and with column-averaged dry-air concentrations from the Total Carbon Column Observing Network (TCCON) site in Orléans, France. While WRF-GHG successfully reproduces most observed variations, discrepancies were identified. These include an overestimation of the CO₂ peak values at most ICOS sites and an overall underestimation of near-surface CH₄ concentrations by 20-30 ppb at three of the four ICOS sites. Additionally, the TCCON comparison revealed a significant deviation in XCO₂ in early June, likely due to inaccuracies in biogenic fluxes which are calculated based on the Vegetation Photosynthesis and Respiration Model (VPRM). For XCH₄, we find an increasing bias towards the end of summer, possibly related to the background signal.

We will present the latest results of our analysis, including additional observational data and updates to the model configuration aimed at improving model-data agreement such as the integration of the TNO high-resolution fossil fuel inventory and refinements to the VPRM fluxes.