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Abstract:

<jats:p>Abstract. The global distribution of cloud condensation nuclei (CCN) is the fundamental quantity that determines how changes in aerosols affect climate through changes in cloud drop concentrations, cloud albedo and precipitation. Aerosol-cloud interaction effects are a major source of uncertainty in climate models so it is important to quantify the sources of uncertainty and thereby direct research efforts. However, the computational expense of global aerosol models has prevented a full statistical analysis of their outputs. Here we perform a variance-based analysis of a global 3-D aerosol microphysics model to quantify the magnitude and leading causes of parametric uncertainty in model-estimated present-day CCN concentrations. Twenty-eight model parameters covering essentially all important aerosol processes, emissions and representation of aerosol size distributions were defined based on expert elicitation. An uncertainty analysis was then performed based on a Monte Carlo-type sampling of an emulator built for each monthly-mean model grid cell from an ensemble of 168 one-year model simulations covering the uncertainty space of the 28 parameters. The standard deviation around the mean CCN varies globally between about ±30% of the mean over some marine regions to ±40–100% over most land areas and high latitudes. The results imply that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol-cloud effects on climate. Variance decomposition enables the importance of the parameters for CCN uncertainty to be quantified and ranked from local to global scales. Among the most important contributors to CCN uncertainty are the sizes of emitted primary particles, including carbonaceous combustion particles from wildfires, biomass burning and fossil fuel use, as well as sulphate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulphur emissions. Aerosol emission-related parameters dominate the uncertainty close to sources, while uncertainty in aerosol microphysical processes becomes increasingly important in remote regions, being dominated by deposition and aerosol sulphate formation during cloud-processing. Most of the 28 parameters are important for CCN uncertainty somewhere on the globe. The results lead to several recommendations for research that would result in improved modelling of cloud-active aerosol on a global scale. </jats:p>

Abstract:

This study uses the UK Chemistry and Aerosols community model (UKCA) within the Hadley Centre Global Environmental Model (HadGEM3), coupled for the first time to an explicit aerosol activation parameterisation, and hence known as UKCA-Activate. We explore the range of uncertainty in estimates of the indirect aerosol effects attributable to the choice of parameterisation of the subgrid-scale variability of vertical velocity in HadGEM-UKCA. Results of simulations demonstrate that the use of a characteristic vertical velocity cannot replicate results derived with a distribution of vertical velocities, and is to be discouraged in GCMs. This study focuses on the effect of the variance (σw2) of a Gaussian pdf (probability density function) of vertical velocity. Fixed values of σw (spanning the range measured in situ by nine flight campaigns found in the literature) and a configuration in which σw depends on turbulent kinetic energy are tested. Results from the mid-range fixed σw and TKE-based configurations both compare well with observed vertical velocity distributions and cloud droplet number concentrations. The radiative flux perturbation due to the total effects of anthropogenic aerosol is estimated at −1.9 W m−2 with σw = 0.1 m s−1, −2.1 W m−2 with σw derived from TKE, −2.25 W m−2 with σw = 0.4 m s−1, and −2.3 W m−2 with σw = 0.7 m s−1. The breadth of this range is 0.4 W m−2, which is comparable to a substantial fraction of the total diversity of current aerosol forcing estimates. Reducing the uncertainty in the parameterisation of σw would therefore be an important step towards reducing the uncertainty in estimates of the indirect aerosol effects. Detailed examination of regional radiative flux perturbations reveals that aerosol microphysics can be responsible for some climate-relevant radiative effects, highlighting the importance of including microphysical aerosol processes in GCMs.

Abstract:

Abstract. Evaluation of the aerosol schemes in current climate models is dependent upon the available observational data. In-situ observations from flight campaigns can provide valuable data about the vertical distribution of aerosol that is difficult to obtain from satellite or ground-based platforms, although they are localised in space and time. Using single-particle soot-photometer (SP2) measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign, which consists of many vertical profiles over a large region of the Pacific, we evaluate the meridional and vertical distribution of black carbon (BC) aerosol simulated by the HadGEM3–UKCA and ECHAM5–HAM2 models. Both models show a similar pattern of overestimating the BC column burden compared to that derived from the observations, in many areas by an order of magnitude. However, by sampling the simulated BC mass mixing ratio along the flight track and comparing to the observations, we show that this discrepancy has a rather different vertical structure in the two models: in HadGEM3–UKCA the discrepancy is dominated by excess aerosol in the tropical upper troposphere, while in ECHAM5–HAM2 areas of discrepancy are spread across many different latitudes and altitudes. Using this methodology, we conduct sensitivity tests on two specific elements of the models: biomass-burning emissions and scavenging by convective precipitation. We show that, by coupling the convective scavenging more tightly with convective transport, both the column burden and vertical distribution of BC in HadGEM3–UKCA are much improved with respect to the observations, with a substantial and statistically significant increase in correlation – this demonstrates the importance of a realistic representation of this process. In contrast, updating from GFED2 to GFED3.1 biomass-burning emissions makes a more modest improvement in both models, which is not statistically significant. By comparing our results with a more traditional approach using regional- and monthly-mean vertical profile curves, we show that the point-by-point analysis allows the model improvements to be demonstrated more clearly. We also demonstrate the important role that nudged simulations (where the large-scale model dynamics are continuously relaxed towards a reanalysis) can play in this type of evaluation, allowing statistically significant differences between configurations of the aerosol scheme to be seen where the differences between the corresponding free-running simulations would not be significant.