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Large contribution of natural aerosols to uncertainty in indirect forcing
Abstract and Figures
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.
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... While many CCNs have natural sources, such as dust and sea spray (e.g., Carslaw et al., 2013), there are also CCNs emitted from anthropogenic activities, including increased emission of carbonaceous aerosols (Hamilton et al., 2018) and sulfur dioxide (Charlson et al., 1992). Changing the number of CCNs in a cloud can change the droplet number concentration (N d ) of the cloud, shifting the cloud's albedo (Twomey, 1974). ...
... We lack observations of PI aerosol spatial distribution, emission, and composition outside of a few regions (Hamilton et al., 2014) that maintain a pristine state in the present day (PD). This lack of observational constraint of the baseline PI atmosphere drives substantial uncertainty in forcing due to ACI (Carslaw et al., 2013;McCoy et al., 2020b). ...
... The other locations are the ARM southern Great Plains (SGP) site centered near Lamont, Oklahoma, and the Layered Atlantic Smoke Interactions with Clouds (LASIC) field campaign that took place on Ascension Island in the central Atlantic. Maritime liquid clouds are a significant contributor to the uncertainty surrounding ERFaci (Bellouin et al., 2020;Carslaw et al., 2013;McCoy et al., 2017;Wall et al., 2022Wall et al., , 2023, and we argue that a marine environment provides more information about the cloud and precipitation processes driving global aerosol-cloud adjustments. This suggests that SGP is less relevant to our current analysis. ...
Aerosol–cloud interactions (ACIs) are the largest source of uncertainty in inferring the magnitude of future warming consistent with the observational record. The effective radiative forcing due to ACI (ERFaci) is dominated by liquid clouds and is composed of two terms: the change in cloud albedo due to redistributing liquid over a larger number of cloud droplets (Nd) and the change in cloud macrophysical properties due to changes in cloud microphysics. These terms are, respectively, referred to as the radiative forcing due to ACI (RFaci) and aerosol–cloud adjustments. While the magnitude of RFaci is uncertain, its sign is confidently negative and results in a cooling in the historical record. In contrast, the adjustment of cloud liquid water path (LWP) to enhanced Nd and associated radiative forcing is uncertain in sign. Increased LWP in response to increased Nd is consistent with precipitation suppression, while decreased LWP in response to increased Nd is consistent with enhanced evaporation from cloud top. Observational constraints of these processes are poor in part because of causal ambiguity in the relationship between Nd and LWP. To better understand this relationship, precipitation (P), Nd, and LWP surface observations from the Eastern North Atlantic (ENA) atmospheric observatory are combined with the output from a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model version 6 (CAM6). This allows for causal interpretation of observed covariability. Observations of precipitation and cloud from ENA constrain the range of possible LWP aerosol–cloud adjustments relative to the prior from the PPE by 15 %, resulting in a global value that is confidently positive (a historical cooling) ranging from 2.1 to 6.9 g m⁻². It is found that observed covariability between Nd and LWP is dominated by coalescence scavenging and that this observed covariability is not strongly related to aerosol–cloud adjustments.
... By doing so, PPEs can explore a wide range of possible outcomes and identify parameter combinations that align best with observed data. This ensemble-based approach allows researchers to quantify the uncertainty in model predictions due to parametric uncertainty and offers a pathway to constrain these uncertainties by integrating observational data, such as satellite and in-situ measurements of aerosols and cloud properties (e.g., Carslaw et al., 2013). The computational cost of generating the hundreds of simulations required to sample the dozens of uncertain parameters however is formidable, even with optimal sampling and emulator accelerated inference. ...
... Namely: natural background aerosol emissions controlled by the dust and seasalt emission factors, which effect pre-industrial CDNC and hence aerosol forcing (cf. Carslaw et al., 2013); high values of the scaling of the liquid and ice updraft velocities are ruled out by the constraint, again effect the aerosol forcing values; various parameters which control shallow and convective precipitation such as club_C8 and zmconv_tied-ke_add are also constrained, and have recently been shown to be important for both aerosol forcing and cloud feedbacks jointly . Conversely, with this approach we also learn that many other parameters are not particularly important for accurately reproducing the historical temperature record as shown by their approximately uniform posterior densities. ...
The quantification of aerosol‐induced radiative forcing and cloud feedbacks remains a significant challenge in climate modeling, primarily due to the complex interplay of aerosol and clouds in a warming world. Traditional approaches often rely on either bottom‐up process‐based models, difficult to constrain against present‐day observations, or top‐down methods that lack the ability to capture the underlying processes accurately. Here, we present an approach that combines both bottom‐up process‐based constraints and top‐down energetic constraints of aerosol forcing and cloud feedbacks simultaneously to achieve a more comprehensive understanding of aerosol impacts on clouds and the climate. Applying the new method to the Community Atmosphere Model v6, we infer narrower parameter ranges for key process parameters, a reduced effective radiative forcing of −1.08 [−1.29–−0.77] Wm⁻², and hence 66% more precise future projections.
... We examine airborne observations taken from SOCRATES as our observational constraint (McFarquhar et al., 2021). The importance of the Southern Ocean (SO) to understanding the global anthropogenic contribution to N d has been shown in 115 several previous studies (Carslaw et al., 2013;McCoy et al., 2020). The National Science Foundation Gulfstream-V (GV) aircraft was deployed during January-March 2018 for SOCRATES. ...
Aerosol-cloud interactions (ACI) in warm clouds alter reflected shortwave radiation by influencing cloud microphysical and macrophysical properties. The variable of state controlling ACI is the cloud droplet number concentration (Nd). Here, we examine the perturbations in Nd due to anthropogenic aerosols (∆Nd, PD–PI) using a perturbed parameter ensemble (PPE) hosted in the sixth Community Atmosphere Model (CAM6). Surrogate models are created for the CAM6 PPE outputs and are used to generate 1 million model variants of CAM6 by sampling 45 sources of parameter uncertainty. The range of uncertain physical parameters related to ACI are constrained with observations of aerosol and cloud properties from SOCRATES. The likely range of uncertain parameters and the associated range of ∆Nd, PD–PI are more strongly constrained with observations of Nd relative to observations of cloud condensation nuclei. We conduct sensitivity tests of how constraints on ∆Nd, PD–PI are affected by systematic uncertainties in observations and our limitations in our surrogate models created for CAM6 PPE outputs. Based on this, we provide guidance on the impact of reducing systematic uncertainty in airborne microphysical observations and in surrogate models.
... Dimethyl sulfide (DMS: CH 3 SCH 3 ) is the most abundant biogenic volatile sulfur compound in the atmosphere and plays a crucial role in climate regulation (Bates et al., 1992;Carslaw et al., 2013;Charlson et al., 1987;Ghahreman et al., 2019;Quinn and Bates, 2011). Global oceanic DMS emissions account for >50% of natural gas-phase sulfur emissions and about 70% of natural sulfur emissions in the atmosphere (Andreae, 1990;Galí et al., 2018;Levasseur, 2013). ...
Ship‐borne high time‐resolution in situ measurements of dimethyl sulfide (DMS) in the marine air of the Arabian Sea reveal large spatiotemporal variations (20−709 ppt) during the post‐monsoon season. The DMS mixing ratios in the southeast (98 ± 87 ppt) and northeast (116 ± 120 ppt) coastal regions were higher than in the oligotrophic central Arabian Sea (62 ± 53 ppt). The frequent DMS peaks over the coastal regions were associated with calm winds, lower salinity, higher SST, and elevated chlorophyll concentrations. The time series of DMS along the coastal regions exhibits stronger diurnal variability with higher values during early morning and evening hours compared to the open ocean. The lower daytime DMS throughout the campaign is attributed to the predominance of OH‐oxidation loss, while nighttime radical chemistry was modulated by polluted air masses in coastal regions. The DMS levels showed a noticeable response to changes in meteorological and oceanic physiochemical parameters, including salinity gradients (−0.3 to 0.2 psu hr⁻¹), mostly associated with localized upwelling events. A weak negative correlation between DMS and seawater nitrate concentrations indicates the role of nitrogen availability in seawater DMS production. Despite relatively low phytoplankton biomass in the post‐monsoon, the estimated DMS fluxes of ∼11 μmol m⁻² d⁻¹ were ∼3‐times higher than the values determined two decades ago. Strong spatiotemporal variations and high levels of DMS could have significant implications for regional atmospheric chemistry, including the formation of sulfate aerosols and cloud condensation nuclei in the marine boundary layer over the Arabian Sea.
Organosulfate (OS) surfactants can influence cloud condensation nuclei (CCN) activation and hygroscopic growth by reducing the surface tension of aerosol particles. We investigate the surface tension and hygroscopicity of aerosols containing short- and long-chain OSs under supersaturated conditions using an electrodeformation method coupled with Raman spectroscopy. For short-chain OSs, the surface tension continues to decrease even under dry, viscous conditions. Sodium ethyl sulfate (SES) lowered surface tension to approximately 30 mN m-1, a value lower than that of sodium dodecyl sulfate (SDS) at its critical micelle concentration. We also studied ternary systems containing OSs with citric acid (CA) or sodium chloride (NaCl). Even small amounts of SDS, with a molar ratio of 10-3 relative to CA, reduce surface tension by up to 40 % at low relative humidity (RH) compared to CA alone. Despite strong surface tension reduction, ternary OS–CA–water systems show hygroscopicity nearly identical to binary CA–water systems, suggesting that surface tension does not influence water uptake under subsaturated conditions. Ternary systems containing NaCl and OS undergo efflorescence at 47 % RH, but the crystallized NaCl becomes partially engulfed. If the RH is subsequently increased, the coating takes up water. At the deliquescence point (72 % RH), the particle becomes homogeneous again. These findings improve our understanding of particle growth and cloud drop formation processes, which influence cloud properties like albedo and lifetime.
Plain Language Summary
Understanding how much Earth's temperature may change in response to increasing atmospheric CO2 concentrations is essential for understanding outputs of earth system models. A key component of this process is equilibrium climate sensitivity (ECS), which estimates how temperature changes respond to a doubling of atmospheric CO2 levels. Recent earth system models have shown a wider range of ECS values than before, increasing uncertainty about the future. In this study, we used a simple climate model to investigate how different constraints on ECS uncertainty shapes the uncertainty in end‐of‐century temperature projections. Our findings show that excluding certain lines of evidence (process and paleoclimate evidence) results in more uncertain temperature projections. This occurs because leaving out critical lines of evidence increases the likelihood of ECS values falling at either ends of the distribution. Therefore, including this evidence is critical for constraining ECS distributions and reducing the uncertainty of temperature projections. Our results also show by how much inducing all information at our disposal to constrain ECS can narrow the uncertainty of future temperature projections. Simple climate models with a probabilistic framework offer a fast, interpretable way to test how ECS distributions impact climate projections.
The accurate representation of cloud droplet number concentration (Nd) is crucial for predicting future climate. However, models often underestimate Nd over the Southern Ocean (SO), where natural sources dominate, and aerosols are composed primarily of marine biogenic sulfate and sea spray. This study uses a range of diverse data sets to evaluate and untangle biases in Energy Exascale Earth System Model version 2 (E3SMv2) simulated clouds, aerosols, and sulfur species. The default E3SMv2 underestimates Nd over SO by a factor of 2 when compared with observations in 3 km‐resolution simulations. Updating the dimethyl sulfide (DMS) emission and chemistry leads to a better agreement between the model and the observations in Nd and boundary layer aerosols, but low biases persist in the free tropospheric aerosol concentrations larger than 70 nm, possibly attributable to insufficient particle growth. Furthermore, updates to DMS emissions and chemistry resulted in reduced vertical DMS concentrations and improved the overall agreement between simulated and observed DMS vertical profiles. Preliminary evaluation also reveals remaining biases in simulated sulfur species, including overestimation in DMS at high latitudes, and in simulated sulfate mass concentration, highlighting the necessity for further efforts to improve the model treatment of relevant processes.
We synthesised observations of total particle number (CN) concentration from 36 sites around the world. We found that annual mean CN concentrations are typically 300–2000 cm−3 in the marine boundary layer and free troposphere (FT) and 1000–10 000 cm−3 in the continental boundary layer (BL). Many sites exhibit pronounced seasonality with summer time concentrations a factor of 2–10 greater than wintertime concentrations. We used these CN observations to evaluate primary and secondary sources of particle number in a global aerosol microphysics model. We found that emissions of primary particles can reasonably reproduce the spatial pattern of observed CN concentration ( R 2=0.46) but fail to explain the observed seasonal cycle ( R 2=0.1). The modeled CN concentration in the FT was biased low (normalised mean bias, NMB=−88%) unless a secondary source of particles was included, for example from binary homogeneous nucleation of sulfuric acid and water (NMB=−25%). Simulated CN concentrations in the continental BL were also biased low (NMB=−74%) unless the number emission of anthropogenic primary particles was increased or a mechanism that results in particle formation in the BL was included. We ran a number of simulations where we included an empirical BL nucleation mechanism either using the activation-type mechanism (nucleation rate, J , proportional to gas-phase sulfuric acid concentration to the power one) or kinetic-type mechanism ( J proportional to sulfuric acid to the power two) with a range of nucleation coefficients. We found that the seasonal CN cycle observed at continental BL sites was better simulated by BL particle formation ( R 2=0.3) than by increasing the number emission from primary anthropogenic sources ( R 2=0.18). The nucleation constants that resulted in best overall match between model and observed CN concentrations were consistent with values derived in previous studies from detailed case studies at individual sites. In our model, kinetic and activation-type nucleation parameterizations gave similar agreement with observed monthly mean CN concentrations.
New-particle formation in the plumes of coal-fired power plants and other anthropogenic sulfur sources may be an important source of particles in the atmosphere. It remains unclear, however, how best to reproduce this formation in global and regional aerosol models with grid-box lengths that are 10s of kilometers and larger. The predictive power of these models is thus limited by the resultant uncertainties in aerosol size distributions. In this paper, we focus on sub-grid sulfate aerosol processes within coal-fired power plant plumes: the sub-grid oxidation of SO2 with condensation of H2SO4 onto newly-formed and pre-existing particles. We have developed a modeling framework with aerosol microphysics in the System for Atmospheric Modelling (SAM), a Large-Eddy Simulation/Cloud-Resolving Model (LES/CRM). The model is evaluated against aircraft observations of new-particle formation in two different power-plant plumes and reproduces the major features of the observations. We show how the downwind plume aerosols can be greatly modified by both meteorological and background aerosol conditions. In general, new-particle formation and growth is greatly reduced during polluted conditions due to the large pre-existing aerosol surface area for H2SO4 condensation and particle coagulation. The new-particle formation and growth rates are also a strong function of the amount of sunlight and NOx since both control OH concentrations. The results of this study highlight the importance for improved sub-grid particle formation schemes in regional and global aerosol models.
A new version of the Global Model of Aerosol Processes (GLOMAP) is described, which uses a two-moment modal aerosol scheme rather than the original two-moment bin scheme. GLOMAP-mode simulates the multi-component global aerosol, resolving sulphate, sea-salt, dust, black carbon (BC) and particulate organic matter (POM), the latter including primary and biogenic secondary POM. Aerosol processes are simulated in a size-resolved manner including primary emissions, secondary particle formation by binary homogeneous nucleation of sulphuric acid and water, particle growth by coagulation, condensation and cloud-processing and removal by dry deposition, in-cloud and below-cloud scavenging. A series of benchmark observational datasets are assembled against which the skill of the model is assessed in terms of normalised mean bias ( b ) and correlation coefficient ( R ). Overall, the model performs well against the datasets in simulating concentrations of aerosol precursor gases, chemically speciated particle mass, condensation nuclei (CN) and cloud condensation nuclei (CCN). Surface sulphate, sea-salt and dust mass concentrations are all captured well, while BC and POM are biased low (but correlate well). Surface CN concentrations compare reasonably well in free troposphere and marine sites, but are underestimated at continental and coastal sites related to underestimation of either primary particle emissions or new particle formation. The model compares well against a compilation of CCN observations covering a range of environments and against vertical profiles of size-resolved particle concentrations over Europe. The simulated global burden, lifetime and wet removal of each of the simulated aerosol components is also examined and each lies close to multi-model medians from the AEROCOM model intercomparison exercise.
It is important to understand the relative contribution of primary and secondary particles to regional and global aerosol so that models can attribute aerosol radiative forcing to different sources. In large-scale models, there is considerable uncertainty associated with treatments of particle formation (nucleation) in the boundary layer (BL) and in the size distribution of emitted primary particles, leading to uncertainties in predicted cloud condensation nuclei (CCN) concentrations. Here we quantify how primary particle emissions and secondary particle formation influence size-resolved particle number concentrations in the BL using a global aerosol microphysics model and aircraft and ground site observations made during the May 2008 campaign of the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). We tested four different parameterisations for BL nucleation and two assumptions for the emission size distribution of anthropogenic and wildfire carbonaceous particles. When we emit carbonaceous particles at small sizes (as recommended by the Aerosol Intercomparison project, AEROCOM), the spatial distributions of campaign-mean number concentrations of particles with diameter >50 nm ( N 50) and >100 nm ( N 100) were well captured by the model ( R 2≥0.8) and the normalised mean bias (NMB) was also small (−18% for N 50 and −1% for N 100). Emission of carbonaceous particles at larger sizes, which we consider to be more realistic for low spatial resolution global models, results in equally good correlation but larger bias ( R 2≥0.8, NMB = −52% and −29%), which could be partly but not entirely compensated by BL nucleation. Within the uncertainty of the observations and accounting for the uncertainty in the size of emitted primary particles, BL nucleation makes a statistically significant contribution to CCN-sized particles at less than a quarter of the ground sites. Our results show that a major source of uncertainty in CCN-sized particles in polluted European air is the emitted size of primary carbonaceous particles. New information is required not just from direct observations, but also to determine the "effective emission size" and composition of primary particles appropriate for different resolution models.
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.
Clouds constitute a large uncertainty in global
climate modeling and climate change projections as many clouds are
smaller than the size of a model grid box. Some processes, such as the
rates of rain and snow formation that have a large impact on climate,
cannot be observed. The uncertain parameters in the representation of
these processes are therefore adjusted in order to achieve radiation
balance. Here we systematically investigate the impact of key
tunable parameters within the convective and stratiform cloud schemes
and of the ice cloud optical properties on the present-day climate in
terms of clouds, radiation and precipitation. The total anthropogenic
aerosol effect between pre-industrial and present-day times amounts to
−1.00 W m−2 obtained as an average over all simulations as
compared to −1.02 W m−2 from those simulations where the
global annual mean top-of-the atmosphere radiation balance is within
±1 W m−2. Thus tuning of the present-day climate does not
seem to have an influence on the total anthropogenic aerosol effect.
The parametric uncertainty regarding the above mentioned cloud
parameters has an uncertainty range of 25% between the minimum and
maximum value when taking all simulations into account. It is reduced
to 11% when only the simulations with a balanced top-of-the
atmosphere radiation are considered.
The budget of atmospheric secondary organic aerosol (SOA) is very uncertain, with recent estimates suggesting a global source of between 12 and 1820 Tg (SOA) a−1. We used a dataset of aerosol mass spectrometer (AMS) observations from 34 different surface locations to evaluate the GLOMAP global chemical transport model. The standard model simulation (which included SOA from monoterpenes only) underpredicted organic aerosol (OA) observed by the AMS and had little skill reproducing the variability in the dataset. We simulated SOA formation from biogenic (monoterpenes and isoprene), lumped anthropogenic and lumped biomass burning volatile organic compounds (VOCs) and varied the SOA yield from each precursor source to produce the best overall match between model and observations. We assumed that SOA is essentially non-volatile and condenses irreversibly onto existing aerosol. Our best estimate of the SOA source is 140 Tg (SOA) a−1 but with a large uncertainty range which we estimate to be 50–380 Tg (SOA) a−1. We found the minimum in normalised mean error (NME) between model and the AMS dataset when we assumed a large SOA source (100 Tg (SOA) a−1) from sources that spatially matched anthropogenic pollution (which we term antropogenically controlled SOA). We used organic carbon observations compiled by Bahadur et al. (2009) to evaluate our estimated SOA sources. We found that the model with a large anthropogenic SOA source was the most consistent with these observations, however improvement over the model with a large biogenic SOA source (250 Tg (SOA) a−1) was small. We used a dataset of 14C observations from rural locations to evaluate our estimated SOA sources. We estimated a maximum of 10 Tg (SOA) a−1 (10 %) of the anthropogenically controlled SOA source could be from fossil (urban/industrial) sources. We suggest that an additional anthropogenic source is most likely due to an anthropogenic pollution enhancement of SOA formation from biogenic VOCs. Such an anthropogenically controlled SOA source would result in substantial climate forcing. We estimated a global mean aerosol direct effect of −0.26 ± 0.15 Wm−2 and indirect (cloud albedo) effect of −0.6+0.24−0.14 Wm−2 from anthropogenically controlled SOA. The biogenic and biomass SOA sources are not well constrained with this analysis due to the limited number of OA observations in regions and periods strongly impacted by these sources. To further improve the constraints by this method, additional OA observations are needed in the tropics and the Southern Hemisphere.
The European Centre for Medium-range Weather Forecast (ECMWF) provides an aerosol re-analysis starting from year 2003 for the Monitoring Atmospheric Composition and Climate (MACC) project. The re-analysis assimilates total aerosol optical depth retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) to correct for model departures from observed aerosols. The re-analysis therefore combines satellite retrievals with the full spatial coverage of a numerical model. Re-analysed products are used here to estimate the shortwave direct and first indirect radiative forcing of anthropogenic aerosols over the period 2003–2010, using methods previously applied to satellite retrievals of aerosols and clouds. The best estimate of globally-averaged, all-sky direct radiative forcing is −0.7 ± 0.3 Wm−2. The standard deviation is obtained by a Monte-Carlo analysis of uncertainties, which accounts for uncertainties in the aerosol anthropogenic fraction, aerosol absorption, and cloudy-sky effects. Further accounting for differences between the present-day natural and pre-industrial aerosols provides a direct radiative forcing estimate of −0.4 ± 0.3 Wm−2. The best estimate of globally-averaged, all-sky first indirect radiative forcing is −0.6 ± 0.4 Wm−2. Its standard deviation accounts for uncertainties in the aerosol anthropogenic fraction, and in cloud albedo and cloud droplet number concentration susceptibilities to aerosol changes. The distribution of first indirect radiative forcing is asymmetric and is bounded by −0.1 and −2.0 Wm−2. In order to decrease uncertainty ranges, better observational constraints on aerosol absorption and sensitivity of cloud droplet number concentrations to aerosol changes are required.
The impact of primary sulfate emissions on cloud condensation nuclei (CCN)
concentrations, one of the major uncertainties in global CCN predictions,
depends on the fraction of sulfur mass emitted as primary sulfate particles
(fsulfate), the fraction of primary sulfate mass distributed into the
nucleation mode particles (fnucl), and the nucleation and growth
processes in the ambient atmosphere. Here, we use a global size-resolved
aerosol microphysics model recently developed to study how the different
parameterizations of primary sulfate emission affect particle properties and
CCN abundance. Different from previous studies, we use the ion-mediated
nucleation scheme to simulate tropospheric particle formation. The kinetic
condensation of low volatile secondary organic gas (SOG) (in addition to
H2SO4 gas) on nucleated particles is calculated based on our new
scheme that considers the SOG volatility changes arising from the oxidation
aging. Our simulations show a compensation effect of nucleation to primary
sulfate emission. We find that the change of fnucl from 5% to 15%
has a more significant impact on the simulated particle number budget than
that of fsulfate within the range of 2.5–5%. Based on our model
configurations, an increase of fsulfate from 0% to 2.5% (with
fnucl = 5%) does not improve the agreement between simulated and
observed annual mean number concentrations of particles >10 nm at 21
stations but further increase of either fsulfate from 2.5% to 5%
(with fnucl = 5%) or fnucl from 5% to 15% (with
fsulfate = 2.5%) substantially deteriorates the agreement. For
fsulfate of 2.5%–5% and fnucl of 5%, our simulations
indicate that the global CCN at supersaturation of 0.2% increases by
8–11% in the boundary layer and 3–5% in the whole troposphere
(compared to the case with fsulfate=0).