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  • 1
    Online Resource
    Online Resource
    The value of remote marine aerosol measurements for constraining radiative forcing uncertainty
    Copernicus GmbH ; 2020
    In:  Atmospheric Chemistry and Physics Vol. 20, No. 16 ( 2020-08-28), p. 10063-10072
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 20, No. 16 ( 2020-08-28), p. 10063-10072
    Abstract: Abstract. Aerosol measurements over the Southern Ocean are used to constrain aerosol–cloud interaction radiative forcing (RFaci) uncertainty in a global climate model. Forcing uncertainty is quantified using 1 million climate model variants that sample the uncertainty in nearly 30 model parameters. Measurements of cloud condensation nuclei and other aerosol properties from an Antarctic circumnavigation expedition strongly constrain natural aerosol emissions: default sea spray emissions need to be increased by around a factor of 3 to be consistent with measurements. Forcing uncertainty is reduced by around 7 % using this set of several hundred measurements, which is comparable to the 8 % reduction achieved using a diverse and extensive set of over 9000 predominantly Northern Hemisphere measurements. When Southern Ocean and Northern Hemisphere measurements are combined, uncertainty in RFaci is reduced by 21 %, and the strongest 20 % of forcing values are ruled out as implausible. In this combined constraint, observationally plausible RFaci is around 0.17 W m−2 weaker (less negative) with 95 % credible values ranging from −2.51 to −1.17 W m−2 (standard deviation of −2.18 to −1.46 W m−2). 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.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.5194/acp-20-10063-2020
    DOI: 10.5194/acp-20-10063-2020-supplement
    DOI: 10.5194/acp-20-10063-2020-editorial-note
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
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  • 2
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    Large simulated radiative effects of smoke in the south-east Atlantic
    Copernicus GmbH ; 2018
    In:  Atmospheric Chemistry and Physics Vol. 18, No. 20 ( 2018-10-24), p. 15261-15289
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 18, No. 20 ( 2018-10-24), p. 15261-15289
    Abstract: Abstract. A 1200×1200 km2 area of the tropical South Atlantic Ocean near Ascension Island is studied with the HadGEM climate model at convection-permitting and global resolutions for a 10-day case study period in August 2016. During the simulation period, a plume of biomass burning smoke from Africa moves into the area and mixes into the clouds. At Ascension Island, this smoke episode was the strongest of the 2016 fire season.The region of interest is simulated at 4 km resolution, with no parameterised convection scheme. The simulations are driven by, and compared to, the global model. For the first time, the UK Chemistry and Aerosol model (UKCA) is included in a regional model with prognostic aerosol number concentrations advecting in from the global model at the boundaries of the region.Fire emissions increase the total aerosol burden by a factor of 3.7 and cloud droplet number concentrations by a factor of 3, which is consistent with MODIS observations. In the regional model, the inversion height is reduced by up to 200 m when smoke is included. The smoke also affects precipitation, to an extent which depends on the model microphysics. The microphysical and dynamical changes lead to an increase in liquid water path of 60 g m−2 relative to a simulation without smoke aerosol, when averaged over the polluted period. This increase is uncertain, and smaller in the global model. It is mostly due to radiatively driven dynamical changes rather than precipitation suppression by aerosol.Over the 5-day polluted period, the smoke has substantial direct radiative effects of +11.4 W m−2 in the regional model, a semi-direct effect of −30.5 W m−2 and an indirect effect of −10.1 W m−2. Our results show that the radiative effects are sensitive to the structure of the model (global versus regional) and the parameterization of rain autoconversion. Furthermore, we simulate a liquid water path that is biased high compared to satellite observations by 22 % on average, and this leads to high estimates of the domain-averaged aerosol direct effect and the effect of the aerosol on cloud albedo. With these caveats, we simulate a large net cooling across the region, of −27.6 W m−2.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.5194/acp-18-15261-2018
    DOI: 10.5194/acp-18-15261-2018-supplement
    DOI: 10.5194/acp-18-15261-2018-corrigendum
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
    detail.hit.zdb_id: 2092549-9
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  • 3
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    Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation
    Copernicus GmbH ; 2019
    In:  Atmospheric Chemistry and Physics Vol. 19, No. 13 ( 2019-07-08), p. 8591-8617
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 19, No. 13 ( 2019-07-08), p. 8591-8617
    Abstract: Abstract. A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters 〉50 and 〉120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (〈0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂Nd/∂Na and ∂Nd/∂w; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-19-8591-2019
    DOI: 10.5194/acp-19-8591-2019-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
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  • 4
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    Aerosol and physical atmosphere model parameters are both important sources of uncertainty in aerosol ERF
    Copernicus GmbH ; 2018
    In:  Atmospheric Chemistry and Physics Vol. 18, No. 13 ( 2018-07-13), p. 9975-10006
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 18, No. 13 ( 2018-07-13), p. 9975-10006
    Abstract: Abstract. Changes in aerosols cause a change in net top-of-the-atmosphere (ToA) short-wave and long-wave radiative fluxes; rapid adjustments in clouds, water vapour and temperature; and an effective radiative forcing (ERF) of the planetary energy budget. The diverse sources of model uncertainty and the computational cost of running climate models make it difficult to isolate the main causes of aerosol ERF uncertainty and to understand how observations can be used to constrain it. We explore the aerosol ERF uncertainty by using fast model emulators to generate a very large set of aerosol–climate model variants that span the model uncertainty due to 27 parameters related to atmospheric and aerosol processes. Sensitivity analyses shows that the uncertainty in the ToA flux is dominated (around 80 %) by uncertainties in the physical atmosphere model, particularly parameters that affect cloud reflectivity. However, uncertainty in the change in ToA flux caused by aerosol emissions over the industrial period (the aerosol ERF) is controlled by a combination of uncertainties in aerosol (around 60 %) and physical atmosphere (around 40 %) parameters. Four atmospheric and aerosol parameters account for around 80 % of the uncertainty in short-wave ToA flux (mostly parameters that directly scale cloud reflectivity, cloud water content or cloud droplet concentrations), and these parameters also account for around 60 % of the aerosol ERF uncertainty. The common causes of uncertainty mean that constraining the modelled planetary brightness to tightly match satellite observations changes the lower 95 % credible aerosol ERF value from −2.65 to −2.37 W m−2. This suggests the strongest forcings (below around −2.4 W m−2) are inconsistent with observations. These results show that, regardless of the fact that the ToA flux is 2 orders of magnitude larger than the aerosol ERF, the observed flux can constrain the uncertainty in ERF because their values are connected by constrainable process parameters. The key to reducing the aerosol ERF uncertainty further will be to identify observations that can additionally constrain individual parameter ranges and/or combined parameter effects, which can be achieved through sensitivity analysis of perturbed parameter ensembles.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-18-9975-2018
    DOI: 10.5194/acp-18-9975-2018-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
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  • 5
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    Robust observational constraint of uncertain aerosol processes and emissions in a climate model and the effect on aerosol radiative forcing
    Copernicus GmbH ; 2020
    In:  Atmospheric Chemistry and Physics Vol. 20, No. 15 ( 2020-08-13), p. 9491-9524
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 20, No. 15 ( 2020-08-13), p. 9491-9524
    Abstract: Abstract. 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 Hadley Centre General Environment Model version 3 (HadGEM3) that sample 26 sources of uncertainty, together with over 9000 monthly aggregated grid-box measurements of aerosol optical depth, PM2.5, particle number concentrations, sulfate 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 sulfate 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 overconfident.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-20-9491-2020
    DOI: 10.5194/acp-20-9491-2020-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
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  • 6
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    The importance of comprehensive parameter sampling and multiple observations for robust constraint of aerosol radiative forcing
    Copernicus GmbH ; 2018
    In:  Atmospheric Chemistry and Physics Vol. 18, No. 17 ( 2018-09-11), p. 13031-13053
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 18, No. 17 ( 2018-09-11), p. 13031-13053
    Abstract: Abstract. Observational constraint of simulated aerosol and cloud properties is an essential part of building trustworthy climate models for calculating aerosol radiative forcing. Models are usually tuned to achieve good agreement with observations, but tuning produces just one of many potential variants of a model, so the model uncertainty cannot be determined. Here we estimate the uncertainty in aerosol effective radiative forcing (ERF) in a tuned climate model by constraining 4 million variants of the HadGEM3-UKCA aerosol–climate model to match nine common observations (top-of-atmosphere shortwave flux, aerosol optical depth, PM2.5, cloud condensation nuclei at 0.2 % supersaturation (CCN0.2), and concentrations of sulfate, black carbon and organic carbon, as well as decadal trends in aerosol optical depth and surface shortwave radiation.) The model uncertainty is calculated by using a perturbed parameter ensemble that samples 27 uncertainties in both the aerosol model and the physical climate model, and we use synthetic observations generated from the model itself to determine the potential of each observational type to constrain this uncertainty. Focusing over Europe in July, we show that the aerosol ERF uncertainty can be reduced by about 30 % by constraining it to the nine observations, demonstrating that producing climate models with an observationally plausible “base state” can contribute to narrowing the uncertainty in aerosol ERF. However, the uncertainty in the aerosol ERF after observational constraint is large compared to the typical spread of a multi-model ensemble. Our results therefore raise questions about whether the underlying multi-model uncertainty would be larger if similar approaches as adopted here were applied more widely. The approach presented in this study could be used to identify the most effective observations for model constraint. It is hoped that aerosol ERF uncertainty can be further reduced by introducing process-related constraints; however, any such results will be robust only if the enormous number of potential model variants is explored.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    DOI: 10.5194/acp-18-13031-2018
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 7
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    Online Resource
    Impacts of aviation fuel sulfur content on climate and human health
    Copernicus GmbH ; 2016
    In:  Atmospheric Chemistry and Physics Vol. 16, No. 16 ( 2016-08-24), p. 10521-10541
    Details
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 16, No. 16 ( 2016-08-24), p. 10521-10541
    Abstract: Abstract. Aviation emissions impact both air quality and climate. Using a coupled tropospheric chemistry-aerosol microphysics model we investigate the effects of varying aviation fuel sulfur content (FSC) on premature mortality from long-term exposure to aviation-sourced PM2.5 (particulate matter with a dry diameter of  〈  2.5 µm) and on the global radiation budget due to changes in aerosol and tropospheric ozone. We estimate that present-day non-CO2 aviation emissions with a typical FSC of 600 ppm result in  ∼  3600 [95 % CI: 1310–5890] annual premature mortalities globally due to increases in cases of cardiopulmonary disease and lung cancer, resulting from increased surface PM2.5 concentrations. We quantify the global annual mean combined radiative effect (REcomb) of non-CO2 aviation emissions as −13.3 mW m−2; from increases in aerosols (direct radiative effect and cloud albedo effect) and tropospheric ozone. Ultra-low sulfur jet fuel (ULSJ; FSC  =  15 ppm) has been proposed as an option to reduce the adverse health impacts of aviation-induced PM2.5. We calculate that swapping the global aviation fleet to ULSJ fuel would reduce the global aviation-induced mortality rate by  ∼  620 [95 % CI: 230–1020] mortalities a−1 and increase REcomb by +7.0 mW m−2. We explore the impact of varying aviation FSC between 0 and 6000 ppm. Increasing FSC increases aviation-induced mortality, while enhancing climate cooling through increasing the aerosol cloud albedo effect (CAE). We explore the relationship between the injection altitude of aviation emissions and the resulting climate and air quality impacts. Compared to the standard aviation emissions distribution, releasing aviation emissions at the ground increases global aviation-induced mortality and produces a net warming effect, primarily through a reduced CAE. Aviation emissions injected at the surface are 5 times less effective at forming cloud condensation nuclei, reducing the aviation-induced CAE by a factor of 10. Applying high FSCs at aviation cruise altitudes combined with ULSJ fuel at lower altitudes results in reduced aviation-induced mortality and increased negative RE compared to the baseline aviation scenario.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    URL: Article
    URL: Article
    DOI: 10.5194/acp-16-10521-2016
    DOI: 10.5194/acp-16-10521-2016-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2016
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