L. A. Lee

Large contribution of natural aerosols to uncertainty in indirect forcing.

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.

The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei

Abstract. 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 concentrations of cloud condensation nuclei (CCN). 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 model grid cell. The standard deviation around the mean CCN varies globally between about ±30% over some marine regions to ±40–100% over most land areas and high latitudes, implying that aerosol processes and emissions are likely to be a significant source of uncertainty in model simulations of aerosol–cloud effects on climate. 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 sulfate particles formed on sub-grid scales. Emissions of carbonaceous combustion particles affect CCN uncertainty more than sulfur 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 sulfate formation during cloud-processing. The results lead to several recommendations for research that would result in improved modelling of cloud–active aerosol on a global scale.

Occurrence of pristine aerosol environments on a polluted planet.

Significance Uncertainty in aerosol forcing of climate since the preindustrial era hampers efforts to quantify the sensitivity of global temperature to radiative perturbations caused by human activity. Because forcings are referenced to preindustrial conditions, a large part of the uncertainty will be reduced only by accurately defining pristine aerosol conditions before air pollution. We show that pristine conditions should still be observable on a few days per month in many regions of the Earth. However, pristine cloudy regions, which are of most importance for forcing uncertainty, occur almost entirely in the Southern Hemisphere. Reduction in uncertainty of predominantly Northern Hemisphere forcing may therefore have to rely on measurements from a different hemisphere, which will limit the extent to which uncertainties can be reduced. Natural aerosols define a preindustrial baseline state from which the magnitude of anthropogenic aerosol effects on climate are calculated and are a major component of the large uncertainty in anthropogenic aerosol−cloud radiative forcing. This uncertainty would be reduced if aerosol environments unperturbed by air pollution could be studied in the present-day atmosphere, but the pervasiveness of air pollution makes identification of unperturbed regions difficult. Here, we use global model simulations to define unperturbed aerosol regions in terms of two measures that compare 1750 and 2000 conditions—the number of days with similar aerosol concentrations and the similarity of the aerosol response to perturbations in model processes and emissions. The analysis shows that the aerosol system in many present-day environments looks and behaves like it did in the preindustrial era. On a global annual mean, unperturbed aerosol regions cover 12% of the Earth (16% of the ocean surface and 2% of the land surface). There is a strong seasonal variation in unperturbed regions of between 4% in August and 27% in January, with the most persistent conditions occurring over the equatorial Pacific. About 90% of unperturbed regions occur in the Southern Hemisphere, but in the Northern Hemisphere, unperturbed conditions are transient and spatially patchy. In cloudy regions with a radiative forcing relative to 1750, model results suggest that unperturbed aerosol conditions could still occur on a small number of days per month. However, these environments are mostly in the Southern Hemisphere, potentially limiting the usefulness in reducing Northern Hemisphere forcing uncertainty.

Uncertainty in the magnitude of aerosol-cloud radiative forcing over recent decades

Aerosols and their effect on the radiative properties of clouds are one of the largest sources of uncertainty in calculations of the Earths energy budget. Here the sensitivity of aerosol-cloud albedo effect forcing to 31 aerosol parameters is quantified. Sensitivities are compared over three periods; 1850-2008, 1978-2008, and 1998-2008. Despite declining global anthropogenic SO2 emissions during 1978-2008, a cancelation of regional positive and negative forcings leads to a near-zero global mean cloud albedo effect forcing. In contrast to existing negative estimates, our results suggest that the aerosol-cloud albedo effect was likely positive (0.006 to 0.028 W m −2 ) in the recent decade, making it harder to explain the temperature hiatus as a forced response. Proportional contributions to forcing variance from aerosol processes and natural and anthropogenic emissions are found to be period dependent. To better constrain forcing estimates, the processes that dominate uncertainty on the timescale of interest must be better understood.

Evaluating uncertainty in convective cloud microphysics using statistical emulation

The microphysical properties of convective clouds determine their radiative effects on climate, the amount and intensity of precipitation as well as dynamical features. Realistic simulation of these cloud properties presents a major challenge. In particular, because models are complex and slow to run, we have little understanding of how the considerable uncertainties in parameterized processes feed through to uncertainty in the cloud responses. Here we use statistical emulation to enable a Monte Carlo sampling of a convective cloud model to quantify the sensitivity of 12 cloud properties to aerosol concentrations and nine model parameters representing the main microphysical processes. We examine the response of liquid and ice-phase hydrometeor concentrations, precipitation, and cloud dynamics for a deep convective cloud in a continental environment. Across all cloud responses, the concentration of the Aitken and accumulation aerosol modes and the collection efficiency of droplets by graupel particles have the most influence on the uncertainty. However, except at very high aerosol concentrations, uncertainties in precipitation intensity and amount are affected more by interactions between drops and graupel than by large variations in aerosol. The uncertainties in ice crystal mass and number are controlled primarily by the shape of the crystals, ice nucleation rates, and aerosol concentrations. Overall, although aerosol particle concentrations are an important factor in deep convective clouds, uncertainties in several processes significantly affect the reliability of complex microphysical models. The results suggest that our understanding of aerosol-cloud interaction could be greatly advanced by extending the emulator approach to models of cloud systems.

The magnitude and sources of uncertainty in global aerosol

Aerosol radiative forcing over the industrial period has remained the largest forcing uncertainty through all IPCC assessments since 1996. Despite the importance of this uncertainty for our understanding of past and future climate change, very little attention is given to the problem of uncertainty reduction in its own right, mainly because most uncertainty analysis approaches are not appropriate to computationally expensive global models. Here we show how a comprehensive understanding of global aerosol model parametric uncertainty can be obtained by using emulators. The approach enables a Monte Carlo sampling of the model uncertainty space based on a manageable number of simulations. This allows full probability density functions of model outputs to be generated from which the uncertainty and its causes can be diagnosed using variance decomposition. We apply this approach to global concentrations of particles larger than 3 and 50 nm diameter (N3 and N50) to produce a ranked list of twenty-eight processes and emissions that control the uncertainty. The results show that the uncertainty in N50 is much more strongly affected by emissions and processes that control the availability of gas phase H2SO4 than by uncertainties in the nucleation rate itself, which cause generally less than 10% uncertainty in N50 in July. Secondary organic aerosol production is assumed to be very uncertain (5-360 Tg a(-1) for biogenic emissions) but the effect on global N3 uncertainty is < 3% except in a few hotspots, and generally < 2% for N50. A complete understanding of the model uncertainty combined with global observations can be used to determine plausible and implausible parts of parameter space as well as to identify model structural weaknesses. In this direction, a preliminary comparison of the model ensemble with observations at Hyytiala, Finland, suggests that an organic-mediated boundary layer nucleation mechanism would help to optimise the behaviour of the model.

On the relationship between aerosol model uncertainty and radiative forcing uncertainty

The largest uncertainty in the historical radiative forcing of climate is caused by the interaction of aerosols with clouds. Historical forcing is not a directly measurable quantity, so reliable assessments depend on the development of global models of aerosols and clouds that are well constrained by observations. However, there has been no systematic assessment of how reduction in the uncertainty of global aerosol models will feed through to the uncertainty in the predicted forcing. We use a global model perturbed parameter ensemble to show that tight observational constraint of aerosol concentrations in the model has a relatively small effect on the aerosol-related uncertainty in the calculated forcing between preindustrial and present-day periods. One factor is the low sensitivity of present-day aerosol to natural emissions that determine the preindustrial aerosol state. However, the major cause of the weak constraint is that the full uncertainty space of the model generates a large number of model variants that are equally acceptable compared to present-day aerosol observations. The narrow range of aerosol concentrations in the observationally constrained model gives the impression of low aerosol model uncertainty. However, these multiple “equifinal” models predict a wide range of forcings. To make progress, we need to develop a much deeper understanding of model uncertainty and ways to use observations to constrain it. Equifinality in the aerosol model means that tuning of a small number of model processes to achieve model−observation agreement could give a misleading impression of model robustness.

The global aerosol synthesis and science project (GASSP): Measurements and modeling to reduce uncertainty

The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in-situ measurements of the particle size distribution, number concentration and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, an extensive global dataset of aerosol in-situ microphysical and chemical measurements, and new ways to assess the uncertainty associated with comparing sparse point measurements with low resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modellers and non-specialist users. Available measurements are extensive, but they biased to polluted regions of the northern hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model-data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.

The Climatic Importance of Uncertainties in Regional Aerosol–Cloud Radiative Forcings over Recent Decades

AbstractRegional patterns of aerosol radiative forcing are important for understanding climate change on decadal time scales. Uncertainty in aerosol forcing is likely to vary regionally and seasonally because of the short aerosol lifetime and heterogeneous emissions. Here the sensitivity of regional aerosol cloud albedo effect (CAE) forcing to 31 aerosol process parameters and emission fluxes is quantified between 1978 and 2008. The effects of parametric uncertainties on calculations of the balance of incoming and outgoing radiation are found to be spatially and temporally dependent. Regional uncertainty contributions of opposite sign cancel in global-mean forcing calculations, masking the regional importance of some parameters. Parameters that contribute little to uncertainty in Earth’s global energy balance during recent decades make significant contributions to regional forcing variance. Aerosol forcing sensitivities are quantified within 11 climatically important regions, where surface temperatures ar...

The Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP): Motivation and experimental design

The Stratospheric Sulfur and its Role in Climate (SSiRC) Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP) explores uncertainties in the processes that connect volcanic emission of sulfur gas species and the radiative forcing associated with the resulting enhancement of the stratospheric aerosol layer. The central aim of ISA-MIP is to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardized model experiments with a range of observations. In this paper we present four co-ordinated inter-model experiments designed to investigate key processes which influence the formation and temporal development of stratospheric aerosol in different time periods of the observational record. The Background (BG) experiment will focus on microphysics and transport processes under volcanically quiescent conditions, when the stratospheric aerosol is controlled by the transport of aerosols and their precursors from the troposphere to the stratosphere. The Transient Aerosol Record (TAR) experiment will explore the role of smallto moderate-magnitude volcanic eruptions, anthropogenic sulfur emissions, and transport processes over the period 1998– 2012 and their role in the warming hiatus. Two further experiments will investigate the stratospheric sulfate aerosol evolution after major volcanic eruptions. The Historical Eruptions SO2 Emission Assessment (HErSEA) experiment will focus on the uncertainty in the initial emission of recent large-magnitude volcanic eruptions, while the Pinatubo EmPublished by Copernicus Publications on behalf of the European Geosciences Union. 2582 C. Timmreck et al.: ISA-MIP: motivation and experimental design ulation in Multiple models (PoEMS) experiment will provide a comprehensive uncertainty analysis of the radiative forcing from the 1991 Mt Pinatubo eruption.