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  • 1
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    Online Resource
    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
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 2
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    Exploring How Eruption Source Parameters Affect Volcanic Radiative Forcing Using Statistical Emulation
    American Geophysical Union (AGU) ; 2019
    In:  Journal of Geophysical Research: Atmospheres Vol. 124, No. 2 ( 2019-01-27), p. 964-985
    Details
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 124, No. 2 ( 2019-01-27), p. 964-985
    Abstract: We demonstrate the feasibility and value of using statistical emulation to quantify the radiative impact of volcanic eruptions Emulated response surfaces illustrate the dependencies of model output such as net radiative forcing on eruption source parameters Emulated response surfaces can also be used to constrain the eruption source parameters for a particular volcanic response
    Type of Medium: Online Resource
    ISSN: 2169-897X , 2169-8996
    URL: Article
    DOI: 10.1029/2018JD028675
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2019
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
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  • 3
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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
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 4
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    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
    detail.hit.zdb_id: 2092549-9
    detail.hit.zdb_id: 2069847-1
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  • 5
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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
    detail.hit.zdb_id: 2069847-1
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