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.
Aerosols and their effect on the radiative properties of clouds are one of the largest sources of uncertainty in calculations of the Earth's 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 0.028Wm−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.
Key Points
Forcing sensitivity to aerosol parameters is strongly period dependentUnderstanding near‐future climate is limited if a single period is consideredIn recent decades, parametric uncertainty is smaller than model diversity
Simple climate models can be valuable if they are able to
replicate aspects of complex fully coupled earth system models. Larger
ensembles can be produced, enabling a probabilistic view of future ...climate
change. A simple emissions-based climate model, FAIR, is presented, which
calculates atmospheric concentrations of greenhouse gases and effective
radiative forcing (ERF) from greenhouse gases, aerosols, ozone and other
agents. Model runs are constrained to observed temperature change from 1880
to 2016 and produce a range of future projections under the Representative
Concentration Pathway (RCP) scenarios. The constrained estimates of
equilibrium climate sensitivity (ECS), transient climate response (TCR) and
transient climate response to cumulative CO2 emissions (TCRE) are 2.86
(2.01 to 4.22) K, 1.53 (1.05 to 2.41) K and 1.40 (0.96 to
2.23) K (1000 GtC)−1 (median and 5–95 % credible intervals). These are
in good agreement with the
likely Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5)
range, noting that AR5 estimates were derived from a combination of climate
models, observations and expert judgement. The ranges of future projections
of temperature and ranges of estimates of ECS, TCR and TCRE are somewhat
sensitive to the prior distributions of ECS∕TCR parameters but less
sensitive to the ERF from a doubling of CO2 or the observational
temperature dataset used to constrain the ensemble. Taking these
sensitivities into account, there is no evidence to suggest that the median
and credible range of observationally constrained TCR or ECS differ from
climate model-derived estimates. The range of temperature projections under
RCP8.5 for 2081–2100 in the constrained FAIR model ensemble is lower than
the emissions-based estimate reported in AR5 by half a degree, owing to
differences in forcing assumptions and ECS∕TCR distributions.
Anthropogenic aerosol emissions are predicted to decline sharply throughout the 21st century, in line with climate change and air quality mitigation policies, causing a near-term warming of climate ...that will impact our trajectory towards 1.5 °C above pre-industrial temperatures. However, the persistent uncertainty in aerosol radiative forcing limits our understanding of how much the global mean temperature will respond to near-term reductions in anthropogenic aerosol emissions. We quantify the model and scenario uncertainty in global mean aerosol radiative forcing up to 2050 using statistical emulation of a perturbed parameter ensemble for emission reduction scenarios consistent with three Shared Socioeconomic Pathways. We then use a simple climate model to translate the uncertainty in aerosol radiative forcing into uncertainty in global mean temperature projections, accounting additionally for the potential correlation of aerosol radiative forcing and climate sensitivity. Near-term aerosol radiative forcing uncertainty alone causes an uncertainty window of around 5 years (2034-2039) on the projected year of exceeding a global temperature rise of 1.5 °C above pre-industrial temperatures for a middle of the road emissions scenario (SSP2-RCP4.5). A correlation between aerosol radiative forcing and climate sensitivity would increase the 1.5 °C exceedance window by many years. The results highlight the importance of quantifying aerosol radiative forcing and any relationship with climate sensitivity in climate models in order to reduce uncertainty in temperature projections.
Abstract
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, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop 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 modelers and nonspecialist users. Available measurements are extensive, but they are 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 uncertainty in present‐day anthropogenic forcing is dominated by uncertainty in the strength of the contribution from aerosol. Much of the uncertainty in the direct aerosol forcing can be ...attributed to uncertainty in the anthropogenic fraction of aerosol in the present‐day atmosphere, due to a lack of historical observations. Here, we present a robust relationship between total present‐day aerosol optical depth and the anthropogenic contribution across three multimodel ensembles and a large single‐model perturbed parameter ensemble. Using observations of aerosol optical depth, we determine a reduced likely range of the anthropogenic component and hence a reduced uncertainty in the direct forcing of aerosol.
Plain Language Summary
Despite the impacts of global warming already being felt around the world, it is still unclear how much of the effect of greenhouse gasses is being offset by the cooling effect of atmospheric aerosol through the scattering of incoming sunlight and the modification of clouds. A large part of the difficulty in determining the effect of aerosol is in understanding the proportion of present‐day aerosol that is due to human activity. In this work, we demonstrate a strong relationship between the total amount of aerosol in the present‐day atmosphere (something we can measure) and the amount due to human activity (something we cannot). We further show that this allows us to reduce the uncertainty in the cooling effect of aerosols.
Key Points
A strong relationship is demonstrated between total present‐day aerosol loading and the anthropogenic contribution, across a variety of models
Observations of the total present‐day aerosol loading are thus used to constrain uncertainty in anthropogenic aerosol and aerosol direct forcing
Applying these constraints to one million samples of a 26‐parameter perturbed parameter ensemble leads to a clear‐sky RFari estimate of −0.69 ± 0.14 Wm−2
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