Aerosol nucleation occurs frequently in the atmosphere and is an important source of particle number. Observations suggest that nucleated particles are capable of growing to sufficiently large sizes that they act as cloud condensation nuclei (CCN), but some global models have reported that CCN concentrations are only modestly sensitive to large changes in nucleation rates. Here we present a novel approach for using long-term size distribution observations to evaluate a global aerosol model's ability to predict formation rates of CCN from nucleation and growth events. We derive from observations at five locations nucleation-relevant metrics such as nucleation rate of particles at diameter of 3 nm (J3), diameter growth rate (GR), particle survival probability (SP), condensation and coagulation sinks, and CCN formation rate (J100). These quantities are also derived for a global microphysical model, GEOS-Chem-TOMAS, and compared to the observations on a daily basis. Using GEOS-Chem-TOMAS, we simulate nucleation events predicted by ternary (with a 10−5 tuning factor) or activation nucleation over one year and find that the model slightly understates the observed annual-average CCN formation mostly due to bias in the nucleation rate predictions, but by no more than 50% in the ternary simulations. At the two locations expected to be most impacted by large-scale regional nucleation, Hyytiälä and San Pietro Capofiume, predicted annual-average CCN formation rates are within 34 and 2% of the observations, respectively. Model-predicted annual-average growth rates are within 25% across all sites but also show a slight tendency to underestimate the observations, at least in the ternary nucleation simulations. On days that the growing nucleation mode reaches 100 nm, median single-day survival probabilities to 100 nm for the model and measurements range from less than 1–6% across the five locations we considered; however, this does not include particles that may eventually grow to 100 nm after the first day. This detailed exploration of new particle formation and growth dynamics adds support to the use of global models as tools for assessing the contribution of microphysical processes such as nucleation to the total number and CCN budget
Abstract. We implement the TwO-Moment Aerosol Sectional (TOMAS) microphysics module into GEOS-CHEM, a CTM driven by assimilated meteorology. TOMAS has 30 size sections covering 0.01-10 µm diameter with conservation equations for both aerosol mass and number. The implementation enables GEOS-CHEM to simulate aerosol microphysics, size distributions, mass and number concentrations. The model system is developed for sulfate and seasalt aerosols, a year-long simulation has been performed, and results are compared to observations. Additionally model intercomparison was carried out involving global models with sectional microphysics: GISS GCM-II' and GLOMAP. Comparison with marine boundary layer observations of CN10 and CCN(0.2%) shows that all models perform well with average errors of 30-50%. However, all models underpredict CN10 by up to 42% between 15 • S and 45 • S while overpredicting CN10 up to 52% between 45 • N and 60 • N, which could be due to the sea-salt emission parameterization and the assumed size distribution of primary sulfate emission, in each case respectively. Model intercomparison at the surface shows that GISS GCM-II' and GLOMAP, each compared against GEOS-CHEM, both predict 40% higher CN10 and predict 20% and 30% higher CCN(0.2%) on average, respectively. Major discrepancies are due to different emission inventories and transport. Budget comparison shows GEOS-CHEM predicts the lowest global CCN(0.2%) due to microphysical growth being a factor of 2 lower than other modCorrespondence to: W. Trivitayanurak (win@cmu.edu) els because of lower SO 2 availability. These findings stress the need for accurate meteorological inputs, updated emission inventories, and realistic clouds and oxidant fields when evaluating global aerosol microphysics models.
Abstract. The flux of cosmic rays to the atmosphere has been reported to correlate with cloud and aerosol properties. One proposed mechanism for these correlations is the "ionaerosol clear-air" mechanism where the cosmic rays modulate atmospheric ion concentrations, ion-induced nucleation of aerosols and cloud condensation nuclei (CCN) concentrations. We use a global chemical transport model with online aerosol microphysics to explore the dependence of CCN concentrations on the cosmic-ray flux. Expanding upon previous work, we test the sensitivity of the cosmic-ray/CCN connection to several uncertain parameters in the model including primary emissions, Secondary Organic Aerosol (SOA) condensation and charge-enhanced condensational growth. The sensitivity of CCN to cosmic rays increases when simulations are run with decreased primary emissions, but show location-dependent behavior from increased amounts of secondary organic aerosol and charge-enhanced growth. For all test cases, the change in the concentration of particles larger than 80 nm between solar minimum (high cosmic ray flux) and solar maximum (low cosmic ray flux) simulations is less than 0.2 %. The change in the total number of particles larger than 10 nm was larger, but always less than 1 %. The simulated change in the column-integratedÅngström exponent was negligible for all test cases. Additionally, we test the predicted aerosol sensitivity to week-long Forbush decreases of cosmic rays and find that the maximum change in aerosol properties for these cases is similar to steady-state aerosol differences between the solar maximum and solar minimum. These results provide evidence that the effect of cosmic rays on CCN and clouds through the ion-aerosol clear-sky mechanism is limited by dampening from aerosol processes.
Aerosol nucleation occurs frequently in the atmosphere and is an important source of particle number. Observations suggest that nucleated particles are capable of growing to sufficiently large sizes that they act as cloud condensation nuclei (CCN), but some global models have reported that CCN concentrations are only modestly sensitive to large changes in nucleation rates. Here we present a novel approach for using long-term size distribution observations to evaluate a global aerosol model's ability to predict formation rates of CCN from nucleation and growth events. We derive from observations at five locations nucleation-relevant metrics such as nucleation rate of particles at diameter of 3 nm (J3), diameter growth rate (GR), particle survival probability (SP), condensation and coagulation sinks, and CCN formation rate (J100). These quantities are also derived for a global microphysical model, GEOS-Chem-TOMAS, and compared to the observations on a daily basis. Using GEOS-Chem-TOMAS, we simulate nucleation events predicted by ternary (with a 10−5 tuning factor) or activation nucleation over one year and find that the model slightly understates the observed annual-average CCN formation, but by no more than 50% in the ternary simulations. At the two locations expected to be most impacted by large-scale regional nucleation, Hyytiälä and San Pietro Capofiume, predicted annual-average CCN formation rates are within 34% and 2% of the observations, respectively. Model-predicted annual-average growth rates are within 25% across all sites but also show a slight tendency to underestimate the observations, at least in the ternary nucleation simulations. On days that the growing nucleation mode reaches 100 nm, median single-day survival probabilities to 100 nm for the model and measurements range from less than 1% to 6% across the five locations we considered; however, this does not include particles that may eventually grow to 100 nm after the first day. This detailed exploration of new particle formation and growth dynamics adds support to the use of global models as tools for assessing the contribution of microphysical processes such as nucleation to the total number and CCN budget
Abstract.A model of carbonaceous aerosols has been implemented in the TwO-Moment Aerosol Sectional (TOMAS) microphysics module in the GEOS-Chem chemical transport model (CTM), a model driven by assimilated meteorology. Inclusion of carbonaceous emissions alongside pre-existing treatments of sulfate and sea-salt aerosols increases the number of emitted primary aerosol particles by a factor of 2.5 and raises annual-average global cloud condensation nuclei at 0.2 % supersaturation (CCN(0.2 %)) concentrations by a factor of two. Compared to the prior model without carbonaceous aerosols, this development improves the model prediction of condensation nuclei with dry diameter larger than 10 nm (CN10) number concentrations significantly from −45 % to −7 % bias when compared to long-term observations. Inclusion of carbonaceous particles also largely eliminates a tendency for the model to underpredict higher cloud condensation nuclei (CCN) concentrations. Similar to other carbonaceous models, the model underpredicts organic carbon (OC) and elemental carbon (EC) mass concentrations by a factor of 2 when compared to EMEP and IMPROVE observations. Because primary organic aerosol (POA) and secondary organic aerosol (SOA) affect aerosol number size distributions via different microphysical processes, we assess the sensitivity of CCN production, for a fixed source of organic aerosol (OA) mass, to the assumed POA-SOA split in the model. For a fixed OA budget, we found that CCN(0.2 %) decreases nearly everywhere as the model changes from a world dominated by POA emissions to one dominated by SOA condensation. POA is about twice as effective per unit mass at CCN production compared to SOA. Changing from a 100 % POA scenario to a 100 % SOA scenario, CCN(0.2 %) concentrations in the lowest model layer decrease by about 20 %. In any scenario, carbonaceous aerosols contribute significantly to global CCN. The SOA-POA split has a significant effect on global CCN, and the microphysical implications of POA emissions versus SOA condensation appear to be at least as important as differences in chemical composition as expressed by the hygroscopicity of OA. These findings stress the need to better understand carbonaceous aerosols loadings, the global SOA budget, microphysical pathways of OA formation (emissions versus condensation) as well as chemical composition to improve climate modeling.
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