16 research outputs found

    Exploring How Eruption Source Parameters Affect Volcanic Radiative Forcing Using Statistical Emulation

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    The radiative forcing caused by a volcanic eruption is dependent on several eruption source parameters such as the mass of sulfur dioxide (SO2) emitted, the eruption column height, and the eruption latitude. General circulation models with prognostic aerosol and chemistry schemes can be used to investigate how each parameter influences the volcanic forcing. However, the range of multidimensional parameter space that can be explored is restricted because such simulations are computationally expensive. Here we use statistical emulation to explore the radiative impact of eruptions over a wide covarying range of SO2 emission magnitudes, injection heights, and eruption latitudes based on only 30 simulations. We use the emulators to build response surfaces to visualize and predict the sulfate aerosol e-folding decay time, the stratospheric aerosol optical depth, and net radiative forcing of thousands of different eruptions. We find that the volcanic stratospheric aerosol optical depth and net radiative forcing are primarily determined by the mass of SO2 emitted, but eruption latitude is the most important parameter in determining the sulfate aerosol e-folding decay time. The response surfaces reveal joint effects of the eruption source parameters in influencing the net radiative forcing, such as a stronger influence of injection height for tropical eruptions than high-latitude eruptions. We also demonstrate how the emulated response surfaces can be used to find all combinations of eruption source parameters that produce a particular volcanic response, often revealing multiple solutions

    Global and regional trends in particulate air pollution and attributable health burden over the past 50 years

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    Long-term exposure to ambient particulate matter (PM2.5, mass of particles with an aerodynamic dry diameter of < 2.5 μm) is a major risk factor to the global burden of disease. Previous studies have focussed on present day or future health burdens attributed to ambient PM2.5. Few studies have estimated changes in PM2.5 and attributable health burdens over the last few decades, a period where air quality has changed rapidly. Here we used the HadGEM3-UKCA coupled chemistry-climate model, integrated exposure-response relationships, demographic and background disease data to provide the first estimate of the changes in global and regional ambient PM2.5 concentrations and attributable health burdens over the period 1960 to 2009. Over this period, global mean population-weighted PM2.5 concentrations increased by 38%, dominated by increases in China and India. Global attributable deaths increased by 89% to 124% over the period 1960 to 2009, dominated by large increases in China and India. Population growth and ageing contributed mostly to the increases in attributable deaths in China and India, highlighting the importance of demographic trends. In contrast, decreasing PM2.5 concentrations and background disease dominated the reduction in attributable health burden in Europe and the United States. Our results shed light on how future projected trends in demographics and uncertainty in the exposure–response relationship may provide challenges for future air quality policy in Asia

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

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    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 diversit

    The hemispheric contrast in cloud microphysical properties constrains aerosol forcing

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    The change in planetary albedo due to aerosol−cloud interactions during the industrial era is the leading source of uncertainty in inferring Earth’s climate sensitivity to increased greenhouse gases from the historical record. The variable that controls aerosol−cloud interactions in warm clouds is droplet number concentration. Global climate models demonstrate that the present-day hemispheric contrast in cloud droplet number concentration between the pristine Southern Hemisphere and the polluted Northern Hemisphere oceans can be used as a proxy for anthropogenically driven change in cloud droplet number concentration. Remotely sensed estimates constrain this change in droplet number concentration to be between 8 cm−3 and 24 cm−3. By extension, the radiative forcing since 1850 from aerosol−cloud interactions is constrained to be −1.2 W⋅m−2 to −0.6 W⋅m−2. The robustness of this constraint depends upon the assumption that pristine Southern Ocean droplet number concentration is a suitable proxy for preindustrial concentrations. Droplet number concentrations calculated from satellite data over the Southern Ocean are high in austral summer. Near Antarctica, they reach values typical of Northern Hemisphere polluted outflows. These concentrations are found to agree with several in situ datasets. In contrast, climate models show systematic underpredictions of cloud droplet number concentration across the Southern Ocean. Near Antarctica, where precipitation sinks of aerosol are small, the underestimation by climate models is particularly large. This motivates the need for detailed process studies of aerosol production and aerosol−cloud interactions in pristine environments. The hemispheric difference in satellite estimated cloud droplet number concentration implies preindustrial aerosol concentrations were higher than estimated by most models

    Reassessment of pre-industrial fire emissions strongly affects anthropogenic aerosol forcing

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    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

    On the relationship between aerosol model uncertainty and radiative forcing uncertainty

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    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
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