Abstract. We present a method to derive atmospheric-observation-based estimates of carbon dioxide (CO2) fluxes at the national scale, demonstrated using data from a network of surface tall tower sites across the UK and Ireland over the period 2013–2014. The inversion is carried out using simulations from a Lagrangian chemical transport model and an innovative hierarchical Bayesian Markov chain Monte Carlo (MCMC) framework, which addresses some of the traditional problems faced by inverse modelling studies, such as subjectivity in the specification of model and prior uncertainties. Biospheric fluxes related to gross primary productivity and terrestrial ecosystem respiration are solved separately in the inversion and then combined a posteriori to determine net primary productivity. Two different models, CARDAMOM and JULES, provide prior estimates for these fluxes. We carry out separate inversions to assess the impact of these different priors on the posterior flux estimates and evaluate the differences between the prior and posterior estimates in terms of missing model components. The Numerical Atmospheric dispersion Modelling Environment (NAME) is used to relate fluxes to the measurements taken across the regional network. Posterior CO2 estimates from the two inversions agree within estimated uncertainties, despite large differences in the prior fluxes from the different models. With our method, averaging results from 2013 and 2014, we find a total annual net biospheric flux for the UK of −8 ± 79 Tg CO2 yr−1 (CARDAMOM prior) and −64 ± 85 Tg CO2 yr−1 (JULES prior), where -ve values represent an uptake of CO2. These biospheric CO2 estimates show that annual UK biospheric sources and sinks are roughly in balance. These annual mean estimates are consistently higher than the prior estimates, which show much more pronounced uptake in the summer months.
Supplementary material to "Quantifying the UK’s Carbon Dioxide Flux: An atmospheric inverse
modelling approach using a regional measurement network"