Cloud droplet number closure for tropical convective clouds during the ACRIDICON–CHUVA campaign
crossref(2021)
Abstract
Abstract. The main objective of the ACRIDICON-CHUVA (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 Global Precipitation measurements) campaign in September 2014 was the investigation of aerosol-cloud-interactions in the Amazon Basin. Cloud properties near cloud base of growing convective cumuli were characterized by cloud droplet size distribution measurements using a cloud combination probe (CCP) and a cloud and aerosol spectrometer (CAS-DPOL). In the current study, an adiabatic parcel model was used to perform cloud droplet number (Nd) closure studies for several flights in differently polluted air masses. Model input parameters included aerosol size distributions, measured with an ultra-high sensitive aerosol spectrometer (UHSAS), in combination with a condensation particle counter (CPC). Updraft speeds (w) were measured near cloud base using a boom-mounted Rosemount model 858 AJ probe. To compare to model predictions, measured Nd and w were statistically matched based on equal percentiles of occurrence. Reasonable agreement between measured and predicted Nd was achieved when a particle hygroscopicity of κ ~ 0.1 is assumed. Similar closure results were obtained when the variability in the particle number concentration was taken into account. We conclude that Nd can be predicted using a single κ, and measured aerosol particle number concentration below cloud base when w is constrained based on measurements. In accordance with previous adiabatic air parcel model studies, the largest disagreements between predicted and measured Nd were found when updraft speeds were high (w > 2.5 m s−1) or in the presence of a bimodal aerosol size distribution. We show that simplifying assumptions on κ might not be appropriate when the aerosol size distribution is comprised of both distinct Aitken and accumulation modes, as predicted Nd clearly deviate from measured ones at w ≥ 1 m s−1 which points to a contribution of Aitken mode particles to Nd.
MoreTranslated text
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined