Evaluating the UK's carbon budget using a dense network of tall-tower observations

The UK has committed to reducing greenhouse gas (GHG) emissions to 80% of 1990 levels by 2050. Evaluating the UK's GHG emissions, and in particular those of carbon dioxide, is imperative to the UK's ability to track progress towards these goals. Making top-down estimates of regional carbon dioxide emissions is challenging due to the rapid temporal variability in the biogenic flux, and the co-location of anthropogenic and biogenic sources and sinks. We present a hierarchical Bayesian inverse modelling framework, which is able to estimate a yearly total (anthropogenic and biogenic) carbon dioxide budget for the UK. Using observations from a high-density GHG monitoring network, combined with high temporal resolution prior information and a Lagrangian atmospheric transport model (NAME, developed by the UK Met Office), we derive a net positive flux for the UK of 0.39 Pg/yr in 2014. We will compare the outcome of inversions that used prior information from two different biosphere models, CARDAMOM and JULES. This comparison helps to understand more about the biogenic processes contributing to the UK's carbon dioxide budget, limitations with different modelling approaches and the sensitivity of the inversion framework to the choice of prior. A better understanding of how the biogenic flux changes throughout the year can, in turn, help to improve the UK's anthropogenic carbon dioxide inventory by identifying times in the year when the anthropogenic signal may be possible to detect.