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New particle formation (NPF) involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Laboratory studies have shown that highly oxygenated organic molecules (HOMs) can make a substantial contribution to NPF, but there is a lack of global model studies of NPF with detailed HOMs chemistry. Here, we add a state-of-art biogenic HOMs chemistry scheme with 96 chemical reactions to a global chemistry-climate model and quantify the contribution to global aerosols through HOMs-driven NPF. The updated model captures the frequency of NPF events observed at continental surface sites (normalized mean bias changes from -96 % to -15 %) and shows reasonable agreement with measured rates of NPF and sub-20 nm particle growth. Sensitivity simulations show that the effect of HOMs on particle growth is more important for particle number than the effect on particle formation. Globally, organics contribute around 45 % of the annual mean vertically-integrated nucleation rate (at 1 nm) and 25 % of the vertically-averaged growth rate. The inclusion of HOMs-related processes leads to a 39 % increase in the global annual mean aerosol number burden and a 33 % increase in cloud condensation nuclei (CCN) burden at 0.5 % supersaturation compared to a simulation with only inorganic nucleation. Our work predicts a greater contribution of organic nucleation to NPF than previous studies due to the explicit HOMs mechanism and an updated inorganic NPF scheme. The large contribution of biogenic HOMs to NPF on a global scale could make global aerosol sensitive to changes in biogenic emissions. [ABSTRACT FROM AUTHOR]

New particle formation (NPF) involving organic compounds has been identified as an important process affecting aerosol particle number concentrations in the global atmosphere. Laboratory studies have shown that highly oxygenated organic molecules (HOMs) can make a substantial contribution to NPF, but there is a lack of global model studies of NPF with detailed HOMs chemistry. Here, we add a state-of-art biogenic HOMs chemistry scheme with 96 chemical reactions to a global chemistry-climate model and quantify the contribution to global aerosols through HOMs-driven NPF. The updated model captures the frequency of NPF events observed at continental surface sites (normalized mean bias changes from -96 % to -15 %) and shows reasonable agreement with measured rates of NPF and sub-20 nm particle growth. Sensitivity simulations show that the effect of HOMs on particle growth is more important for particle number than the effect on particle formation. Globally, organics contribute around 45 % of the annual mean vertically-integrated nucleation rate (at 1 nm) and 25 % of the vertically-averaged growth rate. The inclusion of HOMs-related processes leads to a 39 % increase in the global annual mean aerosol number burden and a 33 % increase in cloud condensation nuclei (CCN) burden at 0.5 % supersaturation compared to a simulation with only inorganic nucleation. Our work predicts a greater contribution of organic nucleation to NPF than previous studies due to the explicit HOMs mechanism and an updated inorganic NPF scheme. The large contribution of biogenic HOMs to NPF on a global scale could make global aerosol sensitive to changes in biogenic emissions. [ABSTRACT FROM AUTHOR]

Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth-atmosphere system, alter the formation of clouds and precipitation, and have substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO2 injection, seasonality of SO2 and BC emissions, and the assumed fraction of SO2 emissions that is injected into the atmosphere as SO4 in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find a large variation in atmospheric lifetime across models for SO2, SO4, and BC, with a particularly large relative variation for SO2, which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of -0.35 W m-2), SO2 lifetime over northern hemisphere land (maximum difference of 0.8 days), surface SO2 concentration (up to 59 % decrease), and surface sulfate concentration (up to 23 % increase). Emitting SO2 at height consistently increased SO2 and SO4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to assure that anthropogenic emission injection height and SO4 emission fraction are accurately and consistently represented in global models. [ABSTRACT FROM AUTHOR]

Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill at making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy-balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample uncertainty in 37 model parameters related to aerosols, clouds and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian Process emulators) against satellite-derived observations over several cloudy regions. We show that it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range in close agreement with energy-balance constraints (around −1.3 to −0.1 W m−2). However, our analysis of a very large set of model variants exposes model internal inconsistencies that would not be apparent in a small set of model simulations. Incorporating observations associated with these inconsistencies weakens the forcing constraint because they require a wider range of parameter values to accommodate conflicting information. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then narrow the uncertainty further. Such an approach provides a rigorous pathway to improved model realism and reduced uncertainty that has so far not been achieved through the normal model development approach. [ABSTRACT FROM AUTHOR]

Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill at making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy-balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties, limit the effectiveness of observational constraint of the uncertain physical processes. We sample uncertainty in 37 model parameters related to aerosols, clouds and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate one million model variants (different parameter settings from Gaussian Process emulators) against satellite-derived observations over several cloudy regions. We show it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 % to a range in close agreement with energy-balance constraints (around -1.3 to -0.1 W m-2). However, incorporating observations associated with model inconsistencies weakens the constraint because the inconsistencies introduce conflicting information about relationships between model parameter values and aerosol forcing. Our estimated aerosol forcing range is the maximum feasible constraint using these observations and our structurally imperfect model. Structural model developments, targeted at the inconsistencies identified here, would enable a larger set of observations to be used for constraint, which would then narrow the uncertainty further. [ABSTRACT FROM AUTHOR]

Aerosol measurements over the Southern Ocean are used to constrain aerosol-cloud interaction radiative forcing uncertainty in a global climate model. Aerosol forcing uncertainty is quantified using one million climate model variants that sample the uncertainty in nearly 30 model parameters. Ship-based measurements of cloud condensation nuclei, particle number concentrations and sulfate mass concentrations from the Antarctic Circumnavigation Expedition: Study of Preindustrial-like Aerosols and Their Climate Effects (ACE-SPACE) are used to identify observationally implausible variants and thereby reduce the spread in the simulated forcing. Southern Ocean measurements strongly constrain natural aerosol emissions: default sea spray emissions in the model need to be increased by around a factor of 3 to be consistent with measurements. Aerosol forcing uncertainty is reduced by around 7 % using these measurements, which is comparable to the 8 % reduction achieved using an extensive set of over 9000 predominantly Northern Hemisphere measurements. The radiative forcing due to aerosol–cloud interactions (RFaci) is constrained to −2.61 to −1.10 W m−2 (95 % confidence) and the effective radiative forcing from aerosol-cloud interactions (ERFaci) is constrained to −2.43 to −0.54 W m−2. When Southern Ocean and Northern Hemisphere measurements are combined, the uncertainty in RFaci is reduced by 21 % and the strongest 20 % of forcing values are ruled out as implausible. In this combined constraint the observationally plausible RFaci is around 0.17 W m−2 weaker (less negative) with credible values ranging from −2.51 to −1.17 W m−2 and from −2.18 to −1.46 W m−2 when using one standard deviation to quantify the uncertainty. The Southern Ocean and Northern Hemisphere measurement datasets are complementary because they constrain different processes. These results highlight the value of remote marine aerosol measurements. [ABSTRACT FROM AUTHOR]

The effect of observational constraint on the ranges of uncertain physical and chemical process parameters was explored in a global aerosol-climate model. The study uses 1 million variants of the HadGEM3-UKCA climate model that sample 26 sources of uncertainty, together with over 9000 monthly aggregated grid-box measurements of aerosol optical depth, PM2.5, particle number concentrations, sulphate and organic mass concentrations. Despite many compensating effects in the model, the procedure constrains the probability distributions of parameters related to secondary organic aerosol, anthropogenic SO2 emissions, residential emissions, sea spray emissions, dry deposition rates of SO2 and aerosols, new particle formation, cloud droplet pH and the diameter of primary combustion particles. Observational constraint rules out nearly 98 % of the model variants. On constraint, the ± 1σ (standard deviation) range of global annual mean direct radiative forcing, RFari, is reduced by 33 % to -0.14 to -0.26 W m-2, and the 95 % credible interval (CI) is reduced by 34 % to -0.1 to -0.32 W m-2. For the global annual mean aerosol-cloud radiative forcing, RFaci, the ± 1σ range is reduced by 7 % to -1.66 to -2.48 W m-2, and the 95 % CI by 6 % to -1.28 to -2.88 W m-2. The tightness of the constraint is limited by parameter cancellation effects (model equifinality) as well as the large and poorly defined representativeness error associated with comparing point measurements with a global model. The constraint could also be narrowed if model structural errors that prevent simultaneous agreement with different measurement types in multiple locations and seasons could be improved. For example, constraints using either sulphate or PM2.5 measurements individually result in RFari ± 1σ ranges that only just overlap, which shows that emergent constraints based on one measurement type may be over-confident. [ABSTRACT FROM AUTHOR]