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.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
We use a global aerosol microphysics model in combination with an offline radiative transfer model to quantify the radiative effect of biogenic secondary organic aerosol (SOA) in the present-day ...atmosphere. Through its role in particle growth and ageing, the presence of biogenic SOA increases the global annual mean concentration of cloud condensation nuclei (CCN; at 0.2% supersaturation) by 3.6-21.1%, depending upon the yield of SOA production from biogenic volatile organic compounds (BVOCs), and the nature and treatment of concurrent primary carbonaceous emissions. This increase in CCN causes a rise in global annual mean cloud droplet number concentration (CDNC) of 1.9-5.2%, and a global mean first aerosol indirect effect (AIE) of between +0.01 W m-2 and -0.12 W m-2. The radiative impact of biogenic SOA is far greater when biogenic oxidation products also contribute to the very early stages of new particle formation; using two organically mediated mechanisms for new particle formation, we simulate global annual mean first AIEs of -0.22 W m-2 and -0.77 W m-2. The inclusion of biogenic SOA substantially improves the simulated seasonal cycle in the concentration of CCN-sized particles observed at three forested sites. The best correlation is found when the organically mediated nucleation mechanisms are applied, suggesting that the first AIE of biogenic SOA could be as large as -0.77 W m-2. The radiative impact of SOA is sensitive to the presence of anthropogenic emissions. Lower background aerosol concentrations simulated with anthropogenic emissions from 1750 give rise to a greater fractional CCN increase and a more substantial first AIE from biogenic SOA. Consequently, the anthropogenic indirect radiative forcing between 1750 and the present day is sensitive to assumptions about the amount and role of biogenic SOA. We also calculate an annual global mean direct radiative effect of between -0.08 W m-2 and -0.78 W m-2 in the present day, with uncertainty in the amount of SOA produced from the oxidation of BVOCs accounting for most of this range.
Cosmic Rays, Clouds, and Climate Carslaw, K. S.; Harrison, R. G.; Kirkby, J.
Science (American Association for the Advancement of Science),
11/2002, Letnik:
298, Številka:
5599
Journal Article
Recenzirano
It has been proposed that Earth's climate could be affected by changes in cloudiness caused by variations in the intensity of galactic cosmic rays in the atmosphere. This proposal stems from an ...observed correlation between cosmic ray intensity and Earth's average cloud cover over the course of one solar cycle. Some scientists question the reliability of the observations, whereas others, who accept them as reliable, suggest that the correlation may be caused by other physical phenomena with decadal periods or by a response to volcanic activity or El Niño. Nevertheless, the observation has raised the intriguing possibility that a cosmic ray-cloud interaction may help explain how a relatively small change in solar output can produce much larger changes in Earth's climate. Physical mechanisms have been proposed to explain how cosmic rays could affect clouds, but they need to be investigated further if the observation is to become more than just another correlation among geophysical variables.
Impact of nucleation on global CCN Merikanto, J.; Spracklen, D. V.; Mann, G. W. ...
Atmospheric chemistry and physics,
11/2009, Letnik:
9, Številka:
21
Journal Article
Recenzirano
Odprti dostop
Cloud condensation nuclei (CCN) are derived from particles emitted directly into the atmosphere (primary emissions) or from the growth of nanometer-sized particles nucleated in the atmosphere. It is ...important to separate these two sources because they respond in different ways to gas and particle emission control strategies and environmental changes. Here, we use a global aerosol microphysics model to quantify the contribution of primary and nucleated particles to global CCN. The model considers primary emissions of sea spray, sulfate and carbonaceous particles, and nucleation processes appropriate for the free troposphere and boundary layer. We estimate that 45% of global low-level cloud CCN at 0.2% supersaturation are secondary aerosol derived from nucleation (ranging between 31–49% taking into account uncertainties in primary emissions and nucleation rates), with the remainder from primary emissions. The model suggests that 35% of CCN (0.2%) in global low-level clouds were created in the free and upper troposphere. In the marine boundary layer 55% of CCN (0.2%) are from nucleation, with 45% entrained from the free troposphere and 10% nucleated directly in the boundary layer. Combinations of model runs show that primary and nucleated CCN are non-linearly coupled. In particular, boundary layer nucleated CCN are strongly suppressed by both primary emissions and entrainment of particles nucleated in the free troposphere. Elimination of all primary emissions reduces global CCN (0.2%) by only 20% and elimination of upper tropospheric nucleation reduces CCN (0.2%) by only 12% because of the increased contribution from boundary layer nucleation.
The natural environment is a major source of atmospheric aerosols, including dust, secondary organic material from terrestrial biogenic emissions, carbonaceous particles from wildfires, and sulphate ...from marine phytoplankton dimethyl sulphide emissions. These aerosols also have a significant effect on many components of the Earth system such as the atmospheric radiative balance and photosynthetically available radiation entering the biosphere, the supply of nutrients to the ocean, and the albedo of snow and ice. The physical and biological systems that produce these aerosols can be highly susceptible to modification due to climate change so there is the potential for important climate feedbacks. We review the impact of these natural systems on atmospheric aerosol based on observations and models, including the potential for long term changes in emissions and the feedbacks on climate. The number of drivers of change is very large and the various systems are strongly coupled. There have therefore been very few studies that integrate the various effects to estimate climate feedback factors. Nevertheless, available observations and model studies suggest that the regional radiative perturbations are potentially several Watts per square metre due to changes in these natural aerosol emissions in a future climate. Taking into account only the direct radiative effect of changes in the atmospheric burden of natural aerosols, and neglecting potentially large effects on other parts of the Earth system, a global mean radiative perturbation approaching 1 W m−2 is possible by the end of the century. The level of scientific understanding of the climate drivers, interactions and impacts is very low.
The Hadley Centre Global Environmental Model (HadGEM) includes two aerosol schemes: the Coupled Large-scale Aerosol Simulator for Studies in Climate (CLASSIC), and the new Global Model of Aerosol ...Processes (GLOMAP-mode). GLOMAP-mode is a modal aerosol microphysics scheme that simulates not only aerosol mass but also aerosol number, represents internally-mixed particles, and includes aerosol microphysical processes such as nucleation. In this study, both schemes provide hindcast simulations of natural and anthropogenic aerosol species for the period 2000–2006. HadGEM simulations of the aerosol optical depth using GLOMAP-mode compare better than CLASSIC against a data-assimilated aerosol re-analysis and aerosol ground-based observations. Because of differences in wet deposition rates, GLOMAP-mode sulphate aerosol residence time is two days longer than CLASSIC sulphate aerosols, whereas black carbon residence time is much shorter. As a result, CLASSIC underestimates aerosol optical depths in continental regions of the Northern Hemisphere and likely overestimates absorption in remote regions. Aerosol direct and first indirect radiative forcings are computed from simulations of aerosols with emissions for the year 1850 and 2000. In 1850, GLOMAP-mode predicts lower aerosol optical depths and higher cloud droplet number concentrations than CLASSIC. Consequently, simulated clouds are much less susceptible to natural and anthropogenic aerosol changes when the microphysical scheme is used. In particular, the response of cloud condensation nuclei to an increase in dimethyl sulphide emissions becomes a factor of four smaller. The combined effect of different 1850 baselines, residence times, and abilities to affect cloud droplet number, leads to substantial differences in the aerosol forcings simulated by the two schemes. GLOMAP-mode finds a present-day direct aerosol forcing of −0.49 W m−2 on a global average, 72% stronger than the corresponding forcing from CLASSIC. This difference is compensated by changes in first indirect aerosol forcing: the forcing of −1.17 W m−2 obtained with GLOMAP-mode is 20% weaker than with CLASSIC. Results suggest that mass-based schemes such as CLASSIC lack the necessary sophistication to provide realistic input to aerosol-cloud interaction schemes. Furthermore, the importance of the 1850 baseline highlights how model skill in predicting present-day aerosol does not guarantee reliable forcing estimates. Those findings suggest that the more complex representation of aerosol processes in microphysical schemes improves the fidelity of simulated aerosol forcings.
Uncertainty in pre-industrial natural aerosol emissions is a major component of the overall uncertainty in the radiative forcing of climate. Improved characterisation of natural emissions and their ...radiative effects can therefore increase the accuracy of global climate model projections. Here we show that revised assumptions about pre-industrial fire activity result in significantly increased aerosol concentrations in the pre-industrial atmosphere. Revised global model simulations predict a 35% reduction in the calculated global mean cloud albedo forcing over the Industrial Era (1750-2000 CE) compared to estimates using emissions data from the Sixth Coupled Model Intercomparison Project. An estimated upper limit to pre-industrial fire emissions results in a much greater (91%) reduction in forcing. When compared to 26 other uncertain parameters or inputs in our model, pre-industrial fire emissions are by far the single largest source of uncertainty in pre-industrial aerosol concentrations, and hence in our understanding of the magnitude of the historical radiative forcing due to anthropogenic aerosol emissions.
Black carbon in carbonaceous combustion aerosol warms the climate by absorbing solar radiation, meaning reductions in black carbon emissions are often perceived as an attractive global warming ...mitigation option. However, carbonaceous combustion aerosol can also act as cloud condensation nuclei (CCN) so they also cool the climate by increasing cloud albedo. The net radiative effect of carbonaceous combustion aerosol is uncertain because their contribution to CCN has not been evaluated on the global scale. By combining extensive observations of CCN concentrations with the GLOMAP global aerosol model, we find that the model is biased low (normalised mean bias = −77 %) unless carbonaceous combustion aerosol act as CCN. We show that carbonaceous combustion aerosol accounts for more than half (52–64 %) of global CCN with the range due to uncertainty in the emitted size distribution of carbonaceous combustion particles. The model predicts that wildfire and pollution (fossil fuel and biofuel) carbonaceous combustion aerosol causes a global mean cloud albedo aerosol indirect effect of −0.34 W m−2, with stronger cooling if we assume smaller particle emission size. We calculate that carbonaceous combustion aerosol from pollution sources cause a global mean aerosol indirect effect of −0.23 W m−2. The small size of carbonaceous combustion particles from fossil fuel sources means that whilst pollution sources account for only one-third of the emitted mass they cause two-thirds of the cloud albedo aerosol indirect effect that is due to carbonaceous combustion aerosol. This cooling effect must be accounted for, along with other cloud effects not studied here, to ensure that black carbon emissions controls that reduce the high number concentrations of fossil fuel particles have the desired net effect on climate.
In the last two IPCC assessments aerosol radiative forcings have been given the largest uncertainty range of all forcing agents assessed. This forcing range is really a diversity of simulated ...forcings in different models. An essential step towards reducing model uncertainty is to quantify and attribute the sources of uncertainty at the process level. Here, we use statistical emulation techniques to quantify uncertainty in simulated concentrations of July-mean cloud condensation nuclei (CCN) from a complex global aerosol microphysics model. CCN was chosen because it is the aerosol property that controls cloud drop concentrations, and therefore the aerosol indirect radiative forcing effect. We use Gaussian process emulation to perform a full variance-based sensitivity analysis and quantify, for each model grid box, the uncertainty in simulated CCN that results from 8 uncertain model parameters. We produce global maps of absolute and relative CCN sensitivities to the 8 model parameter ranges and derive probability density functions for simulated CCN. The approach also allows us to include the uncertainty from interactions between these parameters, which cannot be quantified in traditional one-at-a-time sensitivity tests. The key findings from our analysis are that model CCN in polluted regions and the Southern Ocean are mostly only sensitive to uncertainties in emissions parameters but in all other regions CCN uncertainty is driven almost exclusively by uncertainties in parameters associated with model processes. For example, in marine regions between 30° S and 30° N model CCN uncertainty is driven mainly by parameters associated with cloud-processing of Aitken-sized particles whereas in polar regions uncertainties in scavenging parameters dominate. In these two regions a single parameter dominates but in other regions up to 50% of the variance can be due to interaction effects between different parameters. Our analysis provides direct quantification of the reduction in variance that would result if a parameter could be specified precisely. When extended to all process parameters the approach presented here will therefore provide a clear global picture of how improved knowledge of aerosol processes would translate into reduced model uncertainty.
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