The effect of anthropogenic aerosols on cloud droplet concentrations and radiative properties is the source of one of the largest uncertainties in the radiative forcing of climate over the industrial period. This uncertainty affects our ability to estimate how sensitive the climate is to greenhouse gas emissions. Here we perform a sensitivity analysis on a global model to quantify the uncertainty in cloud radiative forcing over the industrial period caused by uncertainties in aerosol emissions and processes. Our results show that 45 per cent of the variance of aerosol forcing since about 1750 arises from uncertainties in natural emissions of volcanic sulphur dioxide, marine dimethylsulphide, biogenic volatile organic carbon, biomass burning and sea spray. Only 34 per cent of the variance is associated with anthropogenic emissions. The results point to the importance of understanding pristine pre-industrial-like environments, with natural aerosols only, and suggest that improved measurements and evaluation of simulated aerosols in polluted present-day conditions will not necessarily result in commensurate reductions in the uncertainty of forcing estimates.

Figure 1a. In experiments with similar dust surface areas, the temperature at which 50% of droplets were frozen was 250.5 K for K-feldspar, followed by 247 K for Na/Ca-feldspar, 242.5 K for quartz, and below 237.5 K for the clay minerals and calcite. These results suggest that it is the minerals of the feldspar group, in particular K-feldspar, that make mineral dust an effective immersion mode IN in the atmosphere. This data contrasts with the prevailing view 1,2 that clay minerals are the most important component of atmospheric mineral dust for ice nucleation.Droplet freezing temperatures are dependent on experimental parameters such as droplet volume and mineral surface area and are therefore of limited value 2 . In order to normalise the efficiency with which a material nucleates ice we determine the nucleation sites per unit surface area 2,11,14 (n s ; Figure 1b; see supplementary online material). This method of quantifying ice nucleation efficiency neglects the role of time dependence in nucleation, on the basis that IN particle-to-particle variability is more important than the time dependence of nucleation 2,11,14,15 . Our derived n s values for 9 -19 μm size droplets are shown in Figure 1b.This data shows that the feldspar minerals, in particular K-feldspar, are the most efficient mineral dust IN per unit surface area.In airborne dusts the abundance of clay minerals tends to be greater than the feldspars, hence it is not clear which minerals dominate ice nucleation in the atmosphere. The n s values presented in Figure 1b were combined with the average mineralogical composition of atmospheric dust to estimate the temperature-dependent IN concentration (shown in Figure 2). We have assumed that all particles are spherical in order to estimate their surface area and have made two limiting calculations, one assuming that dust particles are internally mixed (i.e. each particle contains all eight minerals) and the other assuming they are externally mixed (each particle is composed of an individual mineral). The mixing state of atmospheric dust is poorly constrained but atmospheric dust falls between these two limiting cases 16 .Despite only accounting for 3% of atmospheric dust by mass, K-feldspar dominates the number of IN above 248 K in both the internally and externally mixed cases. One potential caveat to this conclusion is that clay mineral particles may have a smaller particle size than feldspar or quartz 13 , and therefore may have a greater surface area per unit mass which would increase the concentration of clay IN. However, even if the surface area of the clays was 100 times higher (likely an overestimate 7 ), the feldspars remain the dominant ice nucleating minerals (Supplementary Figure 4). contains the most K-feldspar (20 wt%). In general, the more feldspar a sample contains the higher the freezing temperature. We hypothesise that that the feldspar component controlled the nucleation of ice in these experiments, highlighting the need to characterise sample mineralogy in such work.The mineralog...

We document the development of the first version of the U.K. Earth System Model UKESM1.The model represents a major advance on its predecessor HadGEM2-ES, with enhancements to all component models and new feedback mechanisms. These include a new core physical model with a well-resolved stratosphere; terrestrial biogeochemistry with coupled carbon and nitrogen cycles and enhanced land management; tropospheric-stratospheric chemistry allowing the holistic simulation of radiative forcing from ozone, methane, and nitrous oxide; two-moment, five-species, modal aerosol; and ocean biogeochemistry with two-way coupling to the carbon cycle and atmospheric aerosols. The complexity of coupling between the ocean, land, and atmosphere physical climate and biogeochemical cycles in UKESM1 is unprecedented for an Earth system model. We describe in detail the process by which the coupled model was developed and tuned to achieve acceptable performance in key physical and Earth system quantities and discuss the challenges involved in mitigating biases in a model with complex connections between its components. Overall, the model performs well, with a stable pre-industrial state and good agreement with observations in the latter period of its historical simulations. However, global mean surface temperature exhibits stronger-than-observed cooling from 1950 to 1970, followed by rapid warming from 1980 to 2014. Metrics from idealized simulations show a high climate sensitivity relative to previous generations of models: Equilibrium climate sensitivity is 5.4 K, transient climate response ranges from 2.68 to 2.85 K, and transient climate response to cumulative emissions is 2.49 to 2.66 K TtC −1 . Plain Language SummaryWe describe the development and behavior of UKESM1, a novel climate model that includes improved representations of processes in the atmosphere, ocean, and on land. These processes are inter-related: For example, dust is produced on the land and blown up into the atmosphere where it affects the amount of sunlight falling on Earth. Dust can also be dissolved in the ocean, where it affects marine life. This in turn changes both the amount of carbon dioxide absorbed by the ocean and the material emitted from the surface into the atmosphere, which has an affect on the formation of clouds. UKESM1 includes many processes and interactions such as these, giving it a high level of complexity. Ensuring realistic process behavior is a major challenge in the development of our model, and we have carefully tested this. UKESM1 performs well, correctly exhibiting stable results from a continuous pre-industrial simulation (used to provide a reference for future experiments) and showing good agreement