Assessing aerosol-cloud relationships from dual-field-of-view-polarization lidar: Results and perspectives

• Main Authors: Jiménez, C., Ansmann, A., Engelmann, R., Seifert, P., Radenz, M., Hofer, J., Griesche, H., Althausen, D., Baars, H.
• Format: Conference Object
• Language: English
• Published: 2023
• Subjects: Arctic
• Online Access: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021351

Cloud-droplet, -ice as well as CCN and INP concentrations, stand as key parameters to improve our knowledge of cloud microphysics and dynamics and to approach a better understanding of aerosol impacts on Earth's radiative and precipitation budgets. This contribution will focus on the relationship between aerosol- and liquid-cloud properties by means of long-term observations with dual-field-of-view polarization lidars, which allow the spatiotemporal sampling of aerosol-microphysical properties, relevant for CCN and INP estimates from the ground-up to the Stratosphere, and of the droplet-number concentration and effective radius at liquid-cloud layers, only possible with the new dual-field-of-view feature. We performed measurements since 2019 at three strategic locations: in the pristine Punta Arenas (south tip of Chile), in the dry and often-polluted city of Dushanbe (in Central Asia), and in the Arctic on board of Polarstern. This lidar-based dataset of collocated aerosol and cloud properties was used to investigate the cloud response to local conditions, in which we found similar cloud-droplet numbers for Punta Arenas and the Arctic (in the order of 100 cm-3), but much larger concentrations for Central Asia reaching values in the order of 500 cm-3 in Dushanbe. Preliminary results on the co-variability of cloud-droplet and CCN number (aerosol-cloud-interaction index) show the highest correlations at Punta Arenas, close to 0.85 on the monthly scale. The potential of these aerosol-cloud scenes to learn about the aerosol-cloud radiative effect, as well as to look into cloud processes will be discussed, giving focus to the observational scale.