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

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 microphysicalproperties (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 ( r eff ) was also underestimated by the model. Modeled effective radiusprofiles began to saturate around 500 CCN per 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. 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 microphysicalproperties. In addition, we evaluate a parameterization of CDNC at cloud baseusing more readily available cloud microphysicalproperties, aimed at in situ observations and satellite retrievals. Our study casts doubt on the validity of regional scale modeling studies of the cloud albedoeffect in convective situations for polluted situations where the number concentration of CCN is greater than 500 cm −3 .