globalchange  > 气候变化与战略
DOI: 10.5194/acp-20-1591-2020
论文题名:
The challenge of simulating the sensitivity of the Amazonian cloud microstructure to cloud condensation nuclei number concentrations
作者: Polonik P.; Knote C.; Zinner T.; Ewald F.; Kölling T.; Mayer B.; Andreae M.O.; Jurkat-Witschas T.; Klimach T.; Mahnke C.; Molleker S.; Pöhlker C.; Pöhlker M.L.; Pöschl U.; Rosenfeld D.; Voigt C.; Weigel R.; Wendisch M.
刊名: Atmospheric Chemistry and Physics
ISSN: 16807316
出版年: 2020
卷: 20, 期:3
语种: 英语
Scopus关键词: aerosol ; biomass burning ; cloud condensation nucleus ; cloud microphysics ; cloud radiative forcing ; computer simulation ; concentration (composition) ; optical property ; remote sensing ; Amazonia
英文摘要: The realistic representation of aerosol-cloud 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 region has been one of the motivations for several field campaigns, 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 ACRIDICONCHUVA 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 and optical properties (droplet number concentration and effective radius). We found agreement between the modeled and observed median cloud droplet number concentration (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 0.3 was found, which implies a systematic underestimation of modeled CDNC when compared to measurements. Variability in cloud condensation nuclei (CCN) number concentrations was also underestimated, and cloud droplet effective radii (reff) were overestimated by the model. Modeled effective radius profiles began to saturate around 500 CCN cm-3 at cloud base, indicating an upper limit for the model sensitivity well below CCN concentrations reached during the burning season in the Amazon Basin. Additional CCN emitted from local fires did not cause a notable change in modeled cloud droplet effective radii. Finally, we also evaluate a parameterization of CDNC at cloud base using more readily available cloud microphysical properties, showing that we are able to derive CDNC at cloud base from cloud-side remote-sensing observations. © 2020 Author(s).
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159352
Appears in Collections:气候变化与战略

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作者单位: Meteorologisches Institut, Ludwig-Maximilians-Universität München, Munich, Germany; Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft-und Raumfahrt (DLR), Oberpfaffenhofen, Germany; Scripps Institution of Oceanography, University of California San Diego, San Diego, CA, United States; Multiphase Chemistry and Biogeochemistry Departments, Max Planck Institute for Chemistry, Mainz, Germany; Particle Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany; Institut für Physik der Atmosphäre, Johannes Gutenberg-Universität, Mainz, Germany; Institute of Earth Sciences, Hebrew University of Jerusalem, Jerusalem, Israel; Leipziger Institut für Meteorologie, Universität Leipzig, Leipzig, Germany; Scripps Institution of Oceanography, University of California San Diego, San Diego, CA, United States

Recommended Citation:
Polonik P.,Knote C.,Zinner T.,et al. The challenge of simulating the sensitivity of the Amazonian cloud microstructure to cloud condensation nuclei number concentrations[J]. Atmospheric Chemistry and Physics,2020-01-01,20(3)
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