Desert dust simulations generated by the National Center for Atmospheric Research's Community Climate System Model for the current climate are shown to be consistent with present day satellite and deposition data. The response of the dust cycle to last glacial maximum, preindustrial, modern, and doubled‐carbon dioxide climates is analyzed. Only natural (non‐land use related) dust sources are included in this simulation. Similar to some previous studies, dust production mainly responds to changes in the source areas from vegetation changes, not from winds or soil moisture changes alone. This model simulates a +92%, +33%, and −60% change in dust loading for the last glacial maximum, preindustrial, and doubled‐carbon dioxide climate, respectively, when impacts of carbon dioxide fertilization on vegetation are included in the model. Terrestrial sediment records from the last glacial maximum compiled here indicate a large underestimate of deposition in continental regions, probably due to the lack of simulation of glaciogenic dust sources. In order to include the glaciogenic dust sources as a first approximation, we designate the location of these sources, and infer the size of the sources using an inversion method that best matches the available data. The inclusion of these inferred glaciogenic dust sources increases our dust flux in the last glacial maximum from 2.1 to 3.3 times current deposition.

Abstract. The scientific understanding of the Earth's climate system, including the central question of how the climate system is likely to respond to human-induced perturbations, is comprehensively captured in GCMs and Earth System Models (ESM). Diagnosing the simulated climate response, and comparing responses across different models, is crucially dependent on transparent assumptions of how the GCM/ESM has been driven -especially because the implementation can involve subjective decisions and may differ between modelling groups performing the same experiment. This paper outlines the climate forcings and setup ofCorrespondence to: C. D. Jones (chris.d.jones@metoffice.gov.uk) the Met Office Hadley Centre ESM, HadGEM2-ES for the CMIP5 set of centennial experiments. We document the prescribed greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the HadGEM2-ES historical and future experiments following the Representative Concentration Pathways. In addition, we provide details of how HadGEM2-ES ensemble members were initialised from the control run and how the palaeoclimate and AMIP experiments, as well as the "emissiondriven" RCP experiments were performed.

The role of direct radiative forcing of desert dust aerosol in the change from wet to dry climate observed in the African Sahel region in the last half of the twentieth century is investigated using simulations with an atmospheric general circulation model. The model simulations are conducted either forced by the observed sea surface temperature (SST) or coupled with the interactive SST using the Slab Ocean Model (SOM). The simulation model uses dust that is less absorbing in the solar wavelengths and has larger particle sizes than other simulation studies. As a result, simulations show less shortwave absorption within the atmosphere and larger longwave radiative forcing by dust. Simulations using SOM show reduced precipitation over the intertropical convergence zone (ITCZ) including the Sahel region and increased precipitation south of the ITCZ when dust radiative forcing is included. In SST-forced simulations, on the other hand, significant precipitation changes are restricted to over North Africa. These changes are considered to be due to the cooling of global tropical oceans as well as the cooling of the troposphere over North Africa in response to dust radiative forcing. The model simulation of dust cannot capture the magnitude of the observed increase of desert dust when allowing dust to respond to changes in simulated climate, even including changes in vegetation, similar to previous studies. If the model is forced to capture observed changes in desert dust, the direct radiative forcing by the increase of North African dust can explain up to 30% of the observed precipitation reduction in the Sahel between wet and dry periods. A large part of this effect comes through atmospheric forcing of dust, and dust forcing on the Atlantic Ocean SST appears to have a smaller impact. The changes in the North and South Atlantic SSTs may account for up to 50% of the Sahel precipitation reduction. Vegetation loss in the Sahel region may explain about 10% of the observed drying, but this effect is statistically insignificant because of the small number of years in the simulation. Greenhouse gas warming * The National Center for Atmospheric Research is sponsored by the National Science Foundation.

The scientific understanding of the Earth's climate system, including the central question of how the climate system is likely to respond to human-induced perturbations, is comprehensively captured in GCMs and Earth System Models(ESM). Diagnosing the simulated climate response, and comparing responses across different models, is crucially dependent on transparent assumptions of how the GCM/ESM has been driven – especially because the implementation can involve subjective decisions and may differ between modelling groups performing the same experiment. This paper outlines the climate forcings and setup of the Met Office Hadley Centre ESM, HadGEM2-ES for the CMIP5 set of centennial experiments. We document the prescribed greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the HadGEM2-ES historical and future experiments following the Representative Concentration Pathways. In addition, we provide details of how HadGEM2-ES ensemble members were initialised from the control run and how the palaeoclimate and AMIP experiments, as well as the "emission-driven" RCP experiments were performed

Abstract. A 1200×1200 km2 area of the tropical South Atlantic Ocean near Ascension Island is studied with the HadGEM climate model at convection-permitting and global resolutions for a 10-day case study period in August 2016. During the simulation period, a plume of biomass burning smoke from Africa moves into the area and mixes into the clouds. At Ascension Island, this smoke episode was the strongest of the 2016 fire season.The region of interest is simulated at 4 km resolution, with no parameterised convection scheme. The simulations are driven by, and compared to, the global model. For the first time, the UK Chemistry and Aerosol model (UKCA) is included in a regional model with prognostic aerosol number concentrations advecting in from the global model at the boundaries of the region.Fire emissions increase the total aerosol burden by a factor of 3.7 and cloud droplet number concentrations by a factor of 3, which is consistent with MODIS observations. In the regional model, the inversion height is reduced by up to 200 m when smoke is included. The smoke also affects precipitation, to an extent which depends on the model microphysics. The microphysical and dynamical changes lead to an increase in liquid water path of 60 g m−2 relative to a simulation without smoke aerosol, when averaged over the polluted period. This increase is uncertain, and smaller in the global model. It is mostly due to radiatively driven dynamical changes rather than precipitation suppression by aerosol.Over the 5-day polluted period, the smoke has substantial direct radiative effects of +11.4 W m−2 in the regional model, a semi-direct effect of −30.5 W m−2 and an indirect effect of −10.1 W m−2. Our results show that the radiative effects are sensitive to the structure of the model (global versus regional) and the parameterization of rain autoconversion. Furthermore, we simulate a liquid water path that is biased high compared to satellite observations by 22 % on average, and this leads to high estimates of the domain-averaged aerosol direct effect and the effect of the aerosol on cloud albedo. With these caveats, we simulate a large net cooling across the region, of −27.6 W m−2.

Mineral aerosol impacts on climate through radiative forcing by natural dust sources are examined in the current, last glacial maximum, pre‐industrial and doubled‐carbon dioxide climate. Modeled globally averaged dust loadings change by +88%, +31% and −60% in the last glacial maximum, pre‐industrial and future climates, respectively, relative to the current climate. Model results show globally averaged dust radiative forcing at the top of atmosphere is −1.0, −0.4 and +0.14 W/m2 for the last glacial maximum, pre‐industrial and doubled‐carbon dioxide climates, respectively, relative to the current climate. Globally averaged surface temperature changed by −0.85, −0.22, and +0.06 °C relative to the current climate in the last glacial maximum, pre‐industrial and doubled carbon dioxide climates, respectively, due solely to the dust radiative forcing changes simulated here. These simulations only include natural dust source response to climate change, and neglect possible impacts by human land and water use.

Purpose of Review We assess the current understanding of the state and behaviour of aerosols under pre-industrial conditions and the importance for climate. Recent Findings Studies show that the magnitude of anthropogenic aerosol radiative forcing over the industrial period calculated by climate models is strongly affected by the abundance and properties of aerosols in the preindustrial atmosphere. The low concentration of aerosol particles under relatively pristine conditions means that global mean cloud albedo may have been twice as sensitive to changes in natural aerosol emissions under preindustrial conditions compared to present-day conditions. Consequently, the discovery of new aerosol formation processes and revisions to aerosol emissions have large effects on simulated historical aerosol radiative forcing.Summary We review what is known about the microphysical, chemical, and radiative properties of aerosols in the pre-industrial atmosphere and the processes that control them. Aerosol properties were controlled by a combination of natural emissions, modification of the natural emissions by human activities such as land-use change, and anthropogenic emissions from biofuel combustion and early industrial processes. Although aerosol concentrations were lower in the pre-industrial atmosphere than today, model simulations show that relatively high aerosol concentrations could have been maintained over continental regions due to biogenically controlled new particle formation and wildfires. Despite the importance of preindustrial aerosols for historical climate change, the relevant processes and emissions are given relatively little consideration in climate models, and there have been very few attempts to evaluate them. Consequently, we have very low confidence in the ability of models to simulate the aerosol conditions that form the baseline for historical climate simulations. Nevertheless, it is clear that the 1850s should be regarded as an early industrial reference period, and the aerosol forcing calculated from this period is smaller than the forcing since 1750. Improvements in historical reconstructions of natural and early anthropogenic emissions, exploitation of new Earth system models, and a deeper understanding and evaluation of the controlling processes are key aspects to reducing uncertainties in future.

Changes in aerosols cause a change in net topof-the-atmosphere (ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds, water vapour and temperature; and an effective radiative forcing (ERF) of the planetary energy budget. The diverse sources of model uncertainty and the computational cost of running climate models make it difficult to isolate the main causes of aerosol ERF uncertainty and to understand how observations can be used to constrain it. We explore the aerosol ERF uncertainty by using fast model emulators to generate a very large set of aerosolclimate model variants that span the model uncertainty due to 27 parameters related to atmospheric and aerosol processes. Sensitivity analyses shows that the uncertainty in the ToA flux is dominated (around 80 %) by uncertainties in the physical atmosphere model, particularly parameters that affect cloud reflectivity. However, uncertainty in the change in ToA flux caused by aerosol emissions over the industrial period (the aerosol ERF) is controlled by a combination of uncertainties in aerosol (around 60 %) and physical atmosphere (around 40 %) parameters. Four atmospheric and aerosol parameters account for around 80 % of the uncertainty in short-wave ToA flux (mostly parameters that directly scale cloud reflectivity, cloud water content or cloud droplet concentrations), and these parameters also account for around 60 % of the aerosol ERF uncertainty. The common causes of uncertainty mean that constraining the modelled planetary brightness to tightly match satellite observations changes the lower 95 % credible aerosol ERF value from −2.65 to −2.37 W m −2 . This suggests the strongest forcings (below around −2.4 W m −2 ) are inconsistent with observations. These results show that, regardless of the fact that the ToA flux is 2 orders of magnitude larger than the aerosol ERF, the observed flux can constrain the uncertainty in ERF because their values are connected by constrainable process parameters. The key to reducing the aerosol ERF uncertainty further will be to identify observations that can additionally constrain individual parameter ranges and/or combined parameter effects, which can be achieved through sensitivity analysis of perturbed parameter ensembles.