Influence of pollutants on activity of aerosol cloud condensation nuclei (CCN) during pollution and post-rain periods in Guangzhou, southern China

Abstract. One of the greatest sources of uncertainty in the science of anthropogenic climate change is from aerosol–cloud interactions. The activation of aerosols into cloud droplets is a direct microphysical linkage between aerosols and clouds; parameterizations of this process link aerosol with cloud condensation nuclei (CCN) and the resulting indirect effects. Small differences between parameterizations can have a large impact on the spatiotemporal distributions of activated aerosols and the resulting cloud properties. In this work, we incorporate a series of aerosol activation schemes into the Community Atmosphere Model version 5.1.1 within the Community Earth System Model version 1.0.5 (CESM/CAM5) which include factors such as insoluble aerosol adsorption and giant cloud condensation nuclei (CCN) activation kinetics to understand their individual impacts on global-scale cloud droplet number concentration (CDNC). Compared to the existing activation scheme in CESM/CAM5, this series of activation schemes increase the computation time by ~10% but leads to predicted CDNC in better agreement with satellite-derived/in situ values in many regions with high CDNC but in worse agreement for some regions with low CDNC. Large percentage changes in predicted CDNC occur over desert and oceanic regions, owing to the enhanced activation of dust from insoluble aerosol adsorption and reduced activation of sea spray aerosol after accounting for giant CCN activation kinetics. Comparison of CESM/CAM5 predictions against satellite-derived cloud optical thickness and liquid water path shows that the updated activation schemes generally improve the low biases. Globally, the incorporation of all updated schemes leads to an average increase in column CDNC of 150% and an increase (more negative) in shortwave cloud forcing of 12%. With the improvement of model-predicted CDNCs and better agreement with most satellite-derived cloud properties in many regions, the inclusion of these aerosol activation processes should result in better predictions of radiative forcing from aerosol–cloud interactions.

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Supplementary material to "The important roles of surface tension and growth rate in the contribution of new particle formation (NPF) to cloud condensation nuclei (CCN) number concentration: evidence from field measurements in southern China"

10.5194/acp-2020-1203-supplement ◽

2020 ◽

Author(s):

Mingfu Cai ◽

Baoling Liang ◽

Qibin Sun ◽

Li Liu ◽

Bin Yuan ◽

...

Keyword(s):

Surface Tension ◽

Growth Rate ◽

Southern China ◽

Cloud Condensation Nuclei ◽

Field Measurements ◽

Particle Formation ◽

Number Concentration ◽

New Particle Formation ◽

Condensation Nuclei ◽

Supplementary Material

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The challenge of simulating the sensitivity of the Amazonian clouds microstructure to cloud condensation nuclei number concentrations

10.5194/acp-2019-474 ◽

2019 ◽

Author(s):

Pascal Polonik ◽

Christoph Knote ◽

Tobias Zinner ◽

Florian Ewald ◽

Tobias Kölling ◽

...

Keyword(s):

Cloud Condensation Nuclei ◽

Regional Scale ◽

Cloud Droplet ◽

Number Concentration ◽

Effective Radius ◽

Cloud Base ◽

Condensation Nuclei ◽

Aerosol Cloud ◽

Microphysical Properties

Abstract. The realistic representation of cloud-aerosol interactions is of primary importance for accurate climate model projections. The investigation of these interactions in strongly contrasting clean and polluted atmospheric conditions in the Amazon area has been one of the motivations for several field observations, including the airborne Aerosol, Cloud, Precipitation, and Radiation Interactions and DynamIcs of CONvective cloud systems – Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON-CHUVA) campaign based in Manaus, Brazil in September 2014. In this work we combine in situ and remotely sensed aerosol, cloud, and atmospheric radiation data collected during ACRIDICON-CHUVA with regional, online-coupled chemistry-transport simulations to evaluate the model’s ability to represent the indirect effects of biomass burning aerosol on cloud microphysical properties (droplet number concentration and effective radius). We found agreement between modeled and observed median cloud droplet number concentrations (CDNC) for low values of CDNC, i.e., low levels of pollution. In general, a linear relationship between modeled and observed CDNC with a slope of two was found, which means a systematic underestimation of modeled CDNC as compared to measurements. Variability in cloud condensation nuclei (CCN) number concentrations and cloud droplet effective radii (reff) was also underestimated by the model. Modeled effective radius profiles began to saturate around 500 CCN per cm3 at cloud base, indicating an upper limit for the model sensitivity well below CCN concentrations reached during the burning season in the Amazon Basin. Regional background aerosol concentrations were sufficiently high such that the additional CCN emitted from local fires did not cause a notable change in modelled cloud microphysical properties. In addition, we evaluate a parameterization of CDNC at cloud base using more readily available cloud microphysical properties, aimed at in situ observations and satellite retrievals. Our study casts doubt on the validity of regional scale modeling studies of the cloud albedo effect in convective situations for polluted situations where the number concentration of CCN is greater than 500 cm−3.

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