LAUSR

Abstract. Understanding the vertical distribution of aerosol helps to reduce the uncertainty in the aerosol lifecycle and therefore in the estimation of the direct and indirect aerosol forcing. To improve our understanding, we use measurements from four deployments of the Atmospheric Tomography (ATom) field campaign (ATom1-4) which systematically sampled data over the Pacific and Atlantic Oceans with near pole-to-pole coverage. We evaluate the UK Earth system model (UKESM1) against ATom observations in terms of joint biases in the vertical profile of three variables related to new particle formation: total particle number concentration (NTotal), sulphur dioxide (SO2) mixing ratio and the condensation sink. The NTotal, SO2 and condensation sink are interdependent quantities and have a controlling influence on the vertical profile of each other. Improving only one of these quantities in comparison with observations can lead to a misleading impression that overall model performance has improved. Analysing NTotal, SO2 and condensation sink simultaneously helps reduce the probability of getting the right answer for the wrong reasons. The model's condensation sink is within a factor of 2 of observations, but the NTotal and SO2 shows larger biases mainly in the tropics and high latitudes. Algorithmic improvements to the model and perturbations to key atmospheric processes help reduce tropospheric model biases consistently. We performed a series of model sensitivity tests to identify atmospheric processes that have the strongest influence on overall model performance (NTotal, SO2 and condensation sink simultaneously). In the boundary layer (which we define in this study as below 1 km altitude) and lower troposphere (1–4 km) inclusion of a boundary layer nucleation scheme (Metzger et al., 2010), which is switched off in the default version of UKESM, is critical to obtaining better agreement with observations. However, in the mid (4–8 km) and upper troposphere (> 8 km), sub-3 nm particle growth, pH of cloud droplets, DMS emissions, upper tropospheric nucleation rate, SO2 gas scavenging rate and cloud erosion rate are found to play a more dominant role. Analysing the data with altitude, we find that perturbations to boundary layer nucleation, sub 3 nm growth, cloud droplet pH and DMS emissions reduces the boundary layer and upper tropospheric model bias. We performed a combined simulation with all 4 perturbations included and found that the model's NTotal, SO2 and condensation sink biases were reduced in most cases (up to a 50 % reduction) in both the boundary layer and upper troposphere simultaneously. These perturbations are well-motivated in that they improve the physical basis of the model and are suitable for implementation in future versions of UKESM.